ADORE Adaptive Object Recognition 1
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abatement 减少abbreviate 使用缩写词的人aberrant 离开正路的aberration 偏差,差错abet 帮助abeyance (法律、规则、习俗等)中止abhor 厌恶者,拒绝者ablaze 着火abolition 废除abrasive 研磨料abreast 并排的abridge 节略absent 缺席,不参加abstain 戒(尤指酒),戒除abstract 抽象概念abstruse 难解的absurd 荒谬的abut (与…)邻接abysmal 极糟地academic 学院的,大学的,学会的,(学术,文艺)协会的accede (正式)加入accelerate (使)加快,(使)增速accentuate 强调,着重指出assessible 可鉴定的accidental 偶然accommodate [后面省去反身代词]适应于accompany 伴奏accomplice 共犯,帮凶accomplish 完成accredit 归因于accuracy 精确(性),准确(性)accuse 指责,谴责accustom 使习惯acerbic 酸的,尖刻的acidic (味)酸的acknowledge 承认acolyte 助手acoustic 听觉的acquiescence 默认,默许acquiescent 默认的acrimonious 辛辣的acrimony (言语、态度等的)尖刻activate 使活动,起动,触发actuate 使动作acute 尖的,锐的adamant 坚硬无比的adaptability 适应性adaptable 可适应的adaptive 适应的addict 使沉溺address 忙于,专注于adept 专家,能手adequate 足够的adhere 使粘附adhesive 可黏着的,黏性的admonish 劝告adopt 采用,采取,采纳adoration 崇拜,爱慕,受崇拜(或爱慕)的对象adore 崇拜adorn 装饰,修饰adulation 谄媚adulatory 奉承的adumbrate 预示adventurous 爱冒险的adversary 对手,敌手adverse 不利的adversity 逆境advertise 登广告,做广告advocacy 支持aesthetic 美学标准,美感aesthetically 审美地,美学观点上地affable 友善的affection 喜爱,慈爱affectionate 深情的,挚爱的affective 情感的,表达感情的affinity 密切关系,姻亲关系affirmation 肯定afflict 使受痛苦affluent 富裕的人affordable 付得起的affront 公开侮辱aggrandize 扩大某人的权力aggravate 加重,使恶化aggressive 侵略的,侵犯的,攻势的aghast 惊呆的agility 敏捷agitate 鼓动,煽动agitation 搅动,搅拌agony 极大的痛苦agoraphobic 广场恐怖的agrarian 平均地权论者airborne 空运的,飞机载的akin 同族的alienate 使疏远,离间alienation 离间allegiance 忠诚,拥护allegory 寓言allot 分配,摊派给allude 暗指allure 引诱,诱惑allusion 暗指,间接提到allusive 暗指的,影射,间接提到ally (使)联盟,(使)同盟aloof 分开地also-ran 落选之马,败者,落选者alternate 交替alternative 二中择一altruism 利他主义,无私amalgam 汞合金amateur 业余的,非职业的amaze 吃惊,好奇ambidextrous 左右手都灵的ambiguity 含糊ambiguous 含糊的,不明确的ambitious 有雄心的ambivalent 两性人amble (马的)缓行步态ameliorate 变得更好amenable (对法律等)负责的amend 改良,修改amendment 修正案amiability 和蔼可亲的,亲切的,友善的amicable 友好的,温和的amicably 友善地amorphous 无组织的anachronistic 时代错误的anaerobic 厌氧菌的,厌氧菌产生的analogous 相似的,可比拟的anarchy 混乱anathema 咒,诅咒anatomical 结构(上)的,解剖的ancestor 祖先,祖宗ancestral 祖先的anecdotal 轶事的angular 有角的animated 活生生的,有生气的animosity 憎恨,仇恨,敌意annex 附录annotate 注释者anomalous 不规则的anomaly 异常,反常antagonism 对抗,敌对antagonistic 敌对的,对抗性的antagonize 使成为敌人antecedent 在前的,在先的,先行的antedate (在历史上)比…为早anterior 位于前部的antibiotic 抗生的anticipatory 期待着的anticlimactic 突降法的,渐减的antidote 解药,解毒剂antipathy 反感antiquarianism 古物研究,好古癖antiquated 过时的,陈旧的antique 古玩,古董antiquity 古老,古代antiseptic 防腐的antithesis 对立antithetical 正相反的,对立的apathetic 无感情的apex 顶aphorism 格言,警句appall <美>使惊骇,使充满恐惧apparition 特异景象appease 安抚,缓和appetizing 促进食欲的applaud 夸赞,鼓掌applicability 适用性,适应性apply 申请,请求,适用apportion 分摊,分配apposite 适当的,合适的,贴切的appreciate (使)增值,涨价appreciative 感激的 apprehensive 忧虑的 apprise 告知,通知 approach 接近 approaching 侵入的,逼近的,接近的 approbation 认可 appropriate 占用,拨出 approximate 接近于 apropos 恰当地 aptitude (学习方面的)才能,资质,天资 aquatic 水生动植物 arable 耕地 arbiter [法]仲裁人,裁决者 arbitrary 随意的,任性的,随心所欲的 arboreal 树木的,生活于树上的 arcane 秘密的 archaeological 考古学的,考古学上的 archaic 古代的 archetypally 原型地 architect 建筑师,设计师 architectural 建筑学的 archive 档案文件 arduous 努力的 argumentative 好辩的,争论的 arid 干旱的,干燥的 aristocratic 贵族的,贵族气派的 armored 为…穿盔甲(或加置装甲) ( armor 的过去式和过去分词 ) aromatic 芳香植物 arresting 逮捕( arrest 的现在分词 ) arrogant 傲慢的,自大的 articulate 清晰地发(音) artisan 技工,工匠 artistry 艺术之性质 artless 单纯的 ascent 上升 ascetic 苦行者,禁欲者,禁欲主义者 ascetism 禁欲主义 ascribe 把…归于,认为…是由于 aseptic 防腐剂 aspect 方面 aspen 山杨的 aspiration 强烈的愿望 aspiring 渴望 assail 攻击,袭击 assertion 声称 assertive 武断的,独断的 assessment 评估 assiduous 刻苦的 assimilate 透彻理解 assorted 各种各样的,五花八门的 assume 取得(权力) assuming 取得(权力)( assume 的现在分词) assure 向…保证 assuredness 确信,确实,自信 astigmatic 散光的,矫正散光的 astound 使震惊,使大吃一惊 astounding 使震惊,使大吃一惊astound 的现在分词) astray 离开正轨的 astronomical 天文学的 astute 机敏的,精明的,狡猾的 asunder <文>分开地 asymmetric 不对称的,不匀称的 atheist 无神论者 atomic 原子的 atonement 弥补 atrocity 暴行 atrophy (使)萎缩,(使)虚脱,(使)衰退 attenuation 变薄 attest 证实 attribute 认为…是 attrition 消耗 attune 使协调 audacious 大胆的 audible 听得见的 audit 审计 augment 增加,补充物 auspices 主办,赞助 auspicious 有前途的 austere 朴素的,简朴的 authentic 真的,真正的 authenticate 证明是真实的、可靠的或有效的 authoritative 权威的 autobiographical 自传的,自传体的 autobiography 自传 autography 亲笔,笔迹 automated 自动化(automate 的过去分词) automotive 自动的 autonomous 自治的 autonomy 自治,自治权 avarice 贪婪 avaricious 贪婪的,贪得无厌的 averse 不乐意的 avid 渴望的 avocational avocation 的变形 avoid 避开,避免,预防 awe 使敬畏 awe-inspiring 令人起敬畏心的,令人畏惧的,令人惊叹的 awe-struck 充满敬畏的 awkward 难对付的,棘手的 axiom 公理 bacterium 细菌(复数为bacteria ) baffle 隔板,挡板 balk 阻止,阻碍 ballad 民谣,尤指叙事歌谣 balm 安抚,安慰 balmy (指空气)暖和的 banal 陈腐的 bane 灾星 banish 放逐,驱逐 banter 开玩笑,说笑 barbarous 粗野的 baroque 巴罗克风格 barren 荒原,不毛之地 barrier 把…关入栅栏 base 基于 bashfulness 忸怩的,羞怯的,害羞的 bask 晒太阳,取暖 bastion 棱堡 beaded 饰以珠的,珠状的 befriend 以朋友的方式对待 beleaguer 围攻 belie 歪曲真相,掩饰 believable 可信的 belittle 轻视 bellicose <正>好战的,好争吵的,好斗的 belligerent 交战国,交战者 bemuse 使困惑 benefactor 捐助者 beneficent 行善的 beneficiary 受益人 benevolent 好心肠的 benign 温和的,仁慈的 bereave 使失去(希望、生命等) beset 镶,嵌 besiege 包围,为敌对势力包围 bestow 赠给,授予 betray 对…不忠 bewilder 使迷惑 bias 使倾向于 bibliomania 藏书癖,藏书狂 bilateral 双边的,双方的 bilingual 能说两种语言的人 billion (法美)十亿的 birthright 与生俱来的权利,由于出身、国籍等而获得的权利 bizarre 离奇的 blackmail 胁迫,勒索,敲诈,讹诈 blameworthy 该受指责的,(对坏事)负有责任的 bland 温和的,和蔼的 blatant 吵闹的,喧哗的 blazing 猛烈地燃烧( blaze 的现在分词 ) bleach 漂白剂 blighted 使凋萎( blight 的过去式) blindness 失明 blissful 极快乐的,极幸福的 blithe 欢乐的,愉快的 blockbuster 重磅炸弹,了不起的人或事 blueprint 为…制蓝图 bluff 欺骗 blur 涂污,弄脏 boastfulness 自夸 boisterous 狂暴的 bolster 长枕 bombastic 夸夸其谈的,空洞的 bonanza (突然的)财源boon 快乐的boost 宣扬bootless 无用的,无益的boredom 讨厌,令人讨厌的事物boundless 无限的bowlegged 弯脚的braggart 吹牛的,自夸的braid 把(头发)编成辫子brassy 铜头高尔夫球棍bravado 虚张声势brazen 厚着脸皮breach 攻破breed 产仔brevity 短暂brilliant 宝石brink (悬崖峭壁的)边沿briny <俚>海洋brook 小溪brownish 呈褐色的brusqueness 无礼brutality 残忍brute 残忍的buckle 搭扣,扣环bulky 庞大的bumper 特大的,丰盛的buoyant 轻快的burdensome 繁重的,烦累的,难以承担的burgeon 嫩芽,嫩枝burning 燃烧(burn的现在分词) burst 使爆炸buttress 支持,鼓励bygone 过去的byproduct 副产品byzantine (体制、程序)错综复杂的cabinet 内阁的cacophonous 发音不和谐的,粗腔横调的calamity 灾祸,灾难calculable 可计算的,能预测的callous (使)变硬,(使)起茧calumny 诬蔑,诽谤,中伤(的话)camaraderie 同志之爱,友情candid 率直的,坦白的candor 坦率cannily 精明地canny 精明的,狡猾的cantankerous 脾气不好的,爱争吵的capitulate 认输,屈服capricious 变化无常的captious 爱找岔子的,强词夺理的captivating 迷住(某人),迷惑( captivate 的现在分词)capture 捕获cardiac 心脏病患者cardinal 基本的,最重要的caricature 漫画,讽刺画carnage 大屠杀,残杀carnivorous (动物)食肉的carve 切片cast 铸型caste (印度社会中的)种姓castigate 严厉批评catalyze 催化,促进catastrophe 大灾难category 类型,部门,种类,类别,类目cater 满足需要,适合caterpillar 毛虫causal 具有因果关系的,构成原因的caustic 刻薄地,挖苦地cautionary 警告的cautious 小心的,谨慎的cavil 吹毛求疵的意见cavity 腔,洞celestial 天人,神仙celibate 独身者的cellular 细胞的censorious 苛评的,吹毛求疵的censure 指责centralization 集中ceramic 陶瓷制品cerebral 大脑的ceremonious 好礼仪的,讲究礼节的,正式的certainty 确定性,确实性certitude 确信cessation (暂时)停止,休止,中断chafe 擦伤chagrin 使懊恼,使懊丧,使悔恨chancy 不确实的,不安的chantey 船夫曲,水手歌(亦作chanty 或shanty)chaotic 混沌的characteristic 特有的characterize 塑造人物charismatic 有魅力的charitable 仁慈的,慈善的charlatan 冒充内行者,骗子chart 绘制地图charter 发给…许可证chary 小心的chastisement 惩罚chip 刻,削成chivalrous (尤指对女人)有骑士风度的,彬彬有礼的choppy (指海洋)波浪起伏的chorale 赞美诗choreographic 舞蹈艺术的chorus 合唱chromatic 有颜色的,颜色鲜艳的chromosome <生>染色体chronological 按时间的前后顺序排列的chubby 胖乎乎的,圆胖的,丰满的circuitous 迂回的,绕行的circulate 传送,传递,传阅circulation 流通,传播circumlocution 迂回的话语circumscribe 在…周围划线circumspect 谨慎小心的,周到的circumstantial (指描述)详细的circumvent 围绕,包围cite <口>例证,引文civil 公民的,市民的civility 礼貌claim (根据权利而提出的)要求clamber 困难的或麻烦的攀登clamor 喧哗,吵闹clannish <常贬>(一伙人)自成一帮的,排外的clarification (液体的)澄清clarify (尤指通过加热使黄油)纯净clause 从句,分句claustrophobic (患)幽闭恐怖症的,导致幽闭恐怖症的cleave 劈开,剁开,割开clemency 宽容,仁慈cliché陈词滥调climactic 高潮的,形成高潮的climate 气候clinical 临床的clog 阻碍closet 隐蔽的,暗藏的clumsy 笨拙的cluster 丛生coalesce 联合,合并coarse 粗鄙的coax 同轴电缆code 将…译成电码codify 把(法律)编成法典coerce 强迫,强制coercion 强迫coercive 强制的,强迫的cogent (理由、论据)有说服力的,令人信服的cognitive 认知的cognizant 察知的,认识(某事物)的coherence 一致性coherent 粘着的cohesive 有黏着力的coincidental 巧合的,同时发生的coincidentally 巧合地cold-blooded 冷酷的collaborate 合作,协作collaborative 合作的collateral 并行的colloquial 口语的,会话的collusion 共谋,勾结,串通collusive 共谋的colonize 将…开拓为殖民地colony 侨民coloration 染色,着色colorful 富有色彩的colossal 巨大的combative 好斗的combine 使结合combustible 易燃物,可燃物cometary 彗星的,彗星似的comic 连环漫画commend 推荐commensurate (在时间和空间上)相等的commentary 解说词commentator (电台的)时事评论员,实况广播报导员commercialize (尤指不择手段地)利用…牟利,商业化commingle <文>混合,掺和,合并commiserate 怜悯,同情commission 委任,授予commitment 承诺,许诺committed 忠诚的,坚定的commodious <正>宽敞的commodity 商品communal 公社的comparison 比较,对照compass 罗盘compassion 怜悯,同情compassionate 同情compel 强迫,迫使compelling 引人入胜的compendium 摘要,纲要compensatory 补偿性的competence 能力competing 竞赛(compete的现在分词)complacence 自满complacency 自满,满足complacent 自满的complementary 互补的compliance 服从,听从compliant 遵从的complicate 复杂的compliment 向…道贺component 组成的composed 组成( compose的过去式和过去分词)composure 镇静,沉着compound 场地comprehend 理解,领会comprehendible 可理解的comprehensively 包括地compromise 折中解决conclude 得出结论concede 出让,容许concentrate 浓缩,(使)浓缩concentric 同一中心地,同轴地conceptual 观念的,概念的conciliatory 安抚的conclusive 决定性的concoction 调合concomitant 伴随发生的事concurrent 〈正式〉同时发生的condemnation 谴责condense 变浓缩condescending 降低身份的condone 容忍,宽恕,原谅cone 使成锥形confide 吐露秘密confidently 确信地,肯定地configuration 组合,布置confine 界限,范围conflagration 大火(灾)conflate 合并,混合conflict 抵触conformity 符合confound 使混淆,使混乱confront 面对confrontation 对抗confusion 混乱congenial 意气相投的congenital 先天的,天生的congruent <数>叠合的congruity 适合,一致congruous <正>适合的,适当的conifer [植]针叶树conjecture 推测,猜想conjure 变戏法connive 密谋connoisseur 鉴赏家,鉴定家connotation 内涵,含义conquer 得胜,胜利conscientious 认真负责的consciousness 意识,观念consecutive 连续的,连贯的conserve 果酱,蜜饯considerable 相当大(或多)的consign 委托,托付consort 使陪伴conspiracy 阴谋constant [数]常数,常量consternation 惊愕constituent 构成的,组成的constitute 构成,组成constitution 建立,组成constrain 强迫constraint 强制constrict 变得收缩construction 建筑物constructive 建设的,建设性的construe 分析consult 请教consummate 完美的consumption 消费contact 使接触contagious 有传染性的containment 牵制contemplate 沉思,深思熟虑contemplation 注视contemplative 沉思的,出神的(尤指感觉上帝同在的)contemporary 同代人contempt 轻视contemptible <正>可轻蔑的,可鄙的,卑劣的contemptuous 蔑视的,鄙视的content 内容contention 竞争,争论contentious 引起争论的,有争论的context 上下文continental 大陆的,大陆性的,欧洲大陆的context 上下文continental 大陆的,大陆性的,欧洲大陆的continuation 继续,连续,持续contradict 反驳contradictory 对立物contrary 对立或相反的事物contravene 抵触,与…不相容contrite 悔悟contrition 悔罪,抱愧,痛悔control 支配权controversial 有争议的,引起争议的,被争论的controversy 公开辩论conventional 传统的conventionalize 使成为惯例,使习俗化,使样式化converge 使聚集conversant 熟悉的,了解的converse 交谈,谈话convertible 可改变的convex 凸的,凸面的convince 使相信,说服,使承认convivial 好交际的convoluted 盘绕的,卷曲的coordinate 使协调,使调和copious 丰富的cordiality 热诚,诚挚core 去(果)核,挖去…的果心correlate 相关的correlated 有相互关系的corroborate 证实,支持(某种说法、信仰、理论等)corroboration 进一步的证实,进一步的证据corrosive 腐蚀性的corruption 腐败,堕落cosmic 宇宙的cosmopolitan 世界主义者coterie (有共同兴趣的)小集团countenance 表示赞同counteract 抵消counterbalance 对…起平衡作用,抵消counterclockwise 逆时针方向的,自右向左的counterfeit 仿制,造假counterpart 配对物counterproductive 反生产的,使达不到预期目标的countless 无数的,多得数不清的court 招致courteous 有礼貌的covet 值得渴望的cozy 保温罩craft 手工制作crash 撞坏crater 在…上形成坑crawl 缓慢的爬行credible 可信的,可靠的credulous 轻信的,易受骗的creed (尤指宗教)信条,教义crestfallen 沮丧的,垂头丧气的crimson 变为深红色cringe 畏缩criss-cross 纵横交错的criterion (批评、判断等的)标准,准则critic 批评家criticize 分析,评估critique 发表评论crooked 弯曲的crossfire 交叉火力crumple 压痕cryptic 神秘的crystalline 水晶的culinary 厨房的,烹饪的culminate 达到极点culpable 应受谴责的,应受处罚的,有罪的cumbersome 笨重的cursory 粗略的,草率的,仓促的curt 简短的curtail 缩短custodian 监护人customary 习惯法cyclical 循环的cynical 怀疑的damped 使潮湿( damp的过去式和过去分词)dampen 变得潮湿dappled 有斑点的daunt 使(某人)气馁,威吓dearth 缺乏,稀少debase 降低质量(地位、价格等)debatable 可争辩的debate 辩论debauch 使堕落,败坏debilitate 使虚弱decadence 衰落,堕落,颓废decelerate (使)减速deceptive 欺诈的,骗人的deciduous (指树木)每年落叶的decimate 十中抽一decipher 破译(密码)decisive 决定性的decisiveness 果断性decline 下降decompose 分解decorous 端庄得体的decorum 端庄得体decrepit 衰老的,老朽的,破旧的decry <正>公开反对,谴责defamation 诽谤,中伤default 未履行任务或责任defecate 排便defect 叛逃defense 谋划抵御defensive 守势defer 服从deference 顺从deferential 恭敬的defiant 挑衅的defiance 蔑视defiant 挑衅的deficiency 缺乏,不足deficient 不足的,缺乏的definite 明确的definitive 限定词defrost (给…)化霜,(使)解冻defy 挑战defunct 死者,死人defy 挑战dehumanize 使失去人性,使非人化dehydrate (人体的)脱水,失水deign 屈尊,俯就deleterious 有害的deliberate 熟虑deliberation 考虑,深思熟虑delight 感到高兴[快乐]delimit 限制,定…的界delineate 勾画,描述delude 欺骗,哄骗deluge 使淹没demagnetize 消磁,使退磁demean 使降低身份,使卑下demobilize <正>使复原demolish 摧毁,拆毁(建筑物等)demonstrate 示威游行demotic 口语的,通俗的demur 反对,异议demystify 使非神秘化denigrate 诋毁,诽谤denote 表示,指示denounce 公开指责dense 密集的,稠密的density 密度dental 齿音dependable 可信赖的,可靠的depict 描绘,描画deplete 耗尽deplore 悲悼,哀叹deploy (尤指军事行动)使展开deprave 堕落deprecate 不赞成,反对deprecation 强烈不赞成,祈免,反对deprecatory 不赞成的,恳求的,反对的depreciate <正>贬低,轻视deprive 剥夺,夺去,使丧失derelict 遗弃物deride 嘲笑,愚弄derivative 衍生的derogatory 不敬的descend (from)起源(于)descend (from)起源(于)descriptive 描写的,描述的descry 看见,看出,辨认出desecrate 亵渎,玷污designate 指定而尚未上任的desirable 称心如意的人[东西]despicable 可鄙的,卑鄙的despondent 沮丧的,泄气的destine 注定desultory 散乱的detect 查明,发现detection 侦查deter 阻止,威慑deteriorate 恶化,变坏determinant 决定因素的deterrent 制止的detest 憎恶,嫌恶,痛恨detour 绕道detriment 损害,伤害detrimental 有害的人(或物)devastate 破坏deviant 不正常的,异常的deviation 背离,偏离devious 迂回的,曲折的devoid 缺乏,没有devour 狼吞虎咽地吃光devout 虔诚的dexterous (身手)灵巧的,敏捷的diagnostic 诊断法,诊断程式dialect 方言,土语dichotomy 一分成二,对分dictate 口述didactic 教学的die 钢型,硬模diehard 顽固的,死硬的dietary 规定的食物diffident 缺乏自信的,露出怯态的diffident 缺乏自信的,露出怯态的diffusion 扩散digressive 离题的,枝节的dilapidated 残破的,失修的dilate 扩大dilatory 拖拉的,延误的dilettantediligent 勤奋的dilute 稀释的,冲淡的diminish 变小或减少diminution 减小,减少,缩减diplomatic 外交上的disabuse 去除…的错误想法disarm 使缴械disarray 使混乱disavowal 不承认discernible 可识别的discharge 放出disciple 信徒,追随者discipline 训练discomfit 使为难discomfited 使为难( discomfit的过去式和过去分词)discomfort 使…不舒服disconsolate 孤独的,郁郁不乐的discontent 不满的discount 折扣discourage 使气馁discourse 叙述discourteous 粗鲁的,无礼的,失礼的discredit 丧失名誉,名声discreet 谨慎的,慎重的discrete 分离的,不相关联的discretion 慎重,慎重discriminatory 有识别力的discursive 东拉西扯的,离题的distain 使变色,弄脏,伤害名誉disenfranchise 剥夺…的选举权,剥夺…的公民权,终止…的特许权disgruntled 不满的disillusion 觉醒,幻灭disingenuous 不真诚的,不坦率的disinterest 无兴趣disinterested 公正的disjunctive 分离(性)的dismal 低落的情绪dismember 肢解dismiss 解散disorganize 计划混乱disparage 轻视disparate 完全不同的dispassionate 不动情感的dispel 消除(疑虑等)dispensable 非必需的,可省去的disperse (使)分散,(使)散开disposable 一次性的,可任意处理的disproportionate 不成比例的disprove 反驳disputable 可争辩的,可商榷的,有争议的dispute 就…进行争论,辩论disrupt 混乱的dissect 进行解剖,进行详细分析disseminate 散布,传播dissent 不同意,持异议dissident 持不同意见的(人)dissimilar 不同的,不相似的dissipate 消散dissolve 使溶解dissonant 不和谐的distant 遥远的distasteful 使人不愉快的distent 膨胀的,扩张的distinct 明显的,清楚的distinctive 有特色的,与众不同的distinguish 区分,辨别,分清distort 扭曲distortion 扭曲,变形distraught 心神错乱的distribute 分配,散布diurnal 白天的diverge 使发散divergent 有分歧的diverse 不同的,多种多样的diversify 使多样化,多样化divert 使转移dividend 红利,股息,利息,(破产时清算的)分配金divisive 离间的divulge 泄露docile 温顺的doctrinaire 教条(主义)的doctrine 教条,教义document 证明dogged 跟踪dogma 教义的,教条的,信条的dogmatist 独断家,独断论者domain 范围,领域domesticated 喜欢家庭生活的domain 范围,领域domesticated 喜欢家庭生活的dominate 控制domination 控制,统治domineer 压制dormant 潜伏的,蛰服的,休眠的dorsal 背的dose 剂量,药量dossier (有关某人或某事等的)档案材料down (从高处)向下downfall (雨等的)大下特下downplay 贬低,轻视drab 嫖妓daft 愚笨的dramatic 戏剧的,戏剧性的drastic 激烈的drizzly 下毛毛雨的drollery 开玩笑,说笑话drone 发出嗡嗡声drowsy 昏昏欲睡的drudgery 苦工,贱役,单调沉闷的工作dual 双数dubious 半信半疑的,犹豫不决的ductile 可延展的dull 缓和dumbbell-like 哑铃状dumbfound 使人哑然失声,使发楞dupe 易受骗的人,上当者duplicate 复制的,副本的duplicity 表里不一durable 耐用品,耐久品dutiful 尽职的dwindle 减少,变小,缩小dynamic 动态的dysfunctional 功能失调的earnest 热心ebb 退潮eccentric 古怪的人echo 回声,共鸣eclectic 折中主义者eclipse 使黯然失色ecological 生态(学)的economize 节省,减少开支economy 节约edifice 大建筑物edify 开导,启发efface 擦掉effective 有效的effervescence 冒泡,泡腾,活泼effete 虚弱无力的efficacious (药、措施等)有效的efficacy 功效egalitarian 平等主义egocentric 自我中心的,自私自利的egoist 自我主义者egoistic 自我中心的,自私自利的egregious 极坏的,异乎寻常的elaborate 详细制定elapse (时间的)消逝elate 使高兴,使得意electromagnetic <物>电磁的elegiac 挽歌的,哀悼的,伤感的elementary 基本的elicit 引出,探出eligible 合适的eliminate 排除,消除elite <法>精华elongate 延长,加长eloquent 雄辩的,有口才的elucidate 阐明,解释elude 逃避elusive 难以捉摸的emancipate 解放embed 把…嵌入embellish 装饰起来embellishment 装饰,修饰,润色embezzlement 盗用,挪用emblematic 象征的,可当标志的embrace 拥抱,怀抱embroider 刺绣embryological [医]胚胎学的embryonic 胚芽的,胎儿的embed 把…嵌入eminence 显赫,卓越eminent (指人)知名的,杰出的,卓越的empathy <心>移情作用empathetic 移情作用的,感情移入的empirically 以经验为主地empiricism <哲>实证论,经验主义,经验论empathy <心>移情作用emulate 仿真enamored 使倾心,使迷恋( enamor 的过去式和过去分词)encapsulation 包装,封装,包裹encounter 相遇,碰见encroach 侵入,侵犯encumber <正>妨碍,阻碍,拖累endear 使受喜爱endemic 某地特有的endorse 支票的背书,签名endow 捐赠,资助endure 持续,持久enduring (长时间地)忍受,忍耐,容忍( endure的现在分词)energize 加强,给与…以活力enervate 使衰弱,使失去活力engage 从事engender 形成engrave (使)铭记enigma 谜,不可解的事物enmity 仇恨enormous 巨大的enrage 激怒,使暴怒entangle 使纠缠,缠住enterprise 企(事)业单位entertain 热情款待enthrall 迷住,吸引住entice 诱惑entitle 使有资格entrenched 用壕沟围绕或保护…( entrench的过去式和过去分词) entrepreneur <法>企业家enumerate 列举,枚举,数enviable 值得羡慕的envision 想像,预见,展望enzyme [生化]酶ephemeral 短暂的,瞬息的epic 史诗般的,叙事诗的epidemic 流行性的episodic (小说、剧本等)由松散片段组成的,插曲般的epitome 缩影epoch 纪元equate 使相等equation 方程式equator 赤道equestrian 骑手equitable 公正的,公平的equivalent 对等物equivocal 模棱两可的equivocator 说模棱话的人,说话支吾的人eradicate 根除者erode 逐渐毁坏erratic 古怪的人erratically 不规律地,不定地erudite 博学的,有学问的erudition 博学,学识escalate 逐步上升escapism 逃避现实,空想eschew 避开,回避esoteric 秘传的espouse 拥护essentially 本质上,根本上estimable 值得尊敬的estrange 使疏远(尤指家庭成员之间)estranged 使疏远ethereal 天上的ethnic 少数民族的成员ethos 民族精神eulogistic 作颂词的,赞颂的eulogize 称赞,颂扬euphemism 委婉语euphemistic 委婉的euphonious <正>悦耳的euphoric 欣快症的,欣快的evade 逃避evaluation 估价evanescent 迅速消失遗忘的,短暂的evasive 逃避的evenhanded 公平的,公平无私的eventful 充满大事的,多事故的,多变故的eventual (事件)最终发生的,结果的evergreen [植] 常绿的evil 邪恶,罪恶evince 表明,标示eviscerate 切除…的内脏evoke 产生,引起exacerbate 使恶化exaggerate (使)扩大exaggeration 夸张exalted 高贵的exasperation 恼怒,激怒excavate 发掘excessive 过度的,极度的excessively 过度地excise 国内货物税,消费税excite 使兴奋exclusive 独家新闻execute 执行exemplar 模型exemplary 典型的exemplify 是…的典型exempt 被免除(义务,责任)的人exert 发挥exhale 呼气exhaust 排气exhaustiveness 穷尽性exhilaration 愉快的心情,高兴exigency 急切的需要,危急exodus 离去,退出exonerate 免罪的,免除的exoneration 免罪,免除exorbitant 过度的,极高的exorcise (用祈祷等)驱除(恶魔),给(某人、某地)驱除妖魔exotic 异国的expand 扩展expediency 适宜expedient 应急办法,权宜之计expeditiously 迅速地,敏捷地expertise 专门知识或技能explanatory 解释的explicitly 明白地,明确地exploit 功绩explore 勘查,探测,勘探exposition 博览会expository 说明的,解释的exposure 暴露expressly 明显地exquisite 过分讲究穿戴的人extant 现存的,仍然存在的extend 伸展extension 伸展,扩大extensive 广阔的,广大的exterminate 消灭extinct 灭绝的extinction 熄灭extol 高度赞扬,赞美extract 提取extraneous 外部的extrapolate (由已知资料对未知事实或价值)推算,推断extravagance 奢侈,挥霍extremity 端点extricable 可救出的,可解救的exuberant 生气勃勃的fabricate 制造facetious 爱开玩笑地,乱引人发笑的facile 容易达到的但无价值的facilitate 促进,助长factorable 可分解因子的factual 事实的,真实的faddish 好赶时髦的fade 乏味的,平淡的fallacious 谬误的fallible 容易犯错的fallow 休闲地,休耕地falsify 弄虚作假falter 支吾,结巴fanatic 狂热入迷的fanciful (指人)富于幻想的fantasy 想像farce 用笑话补充、描述far-reaching 深远的,广泛的,深至远处的fascinate 入迷fascinating 使…陶醉(fascinate的ing形式)fast (比准确的时间或宣布的时间)快fastidious 挑剔的fault 挑剔,找…的缺点favorable 赞同的fearsome 可怕的,吓人的feckless 没有价值的,没有长远目标的,不负责任的fecund 多产的feign 假装feigned 假装,伪装( feign的过去式和过去分词)ferment 使发酵ferocity 凶猛,残暴ferromagnetic 铁磁的,铁磁体的fertilize 使肥沃fertilizer 肥料,化肥fervent 热诚的,热烈的fervid 充满激情的,热烈的fervor 热烈,热情festive 节日的,过节似的fetid 恶臭的fickle (爱情、友谊等)易变的,无常的fickleness 易变fictitious 虚构的,编造的figment 虚构的事物financial 财政的finicky 过分讲究的fireproof 使防火,使耐火flabby (肌肉等)不结实,松弛flag 疲乏,变弱,热情衰减flagging 下垂的flaggy 多扁石的,多菖蒲的flagrant 臭名远扬的flake 小薄片,(尤指)碎片flamboyant 凤凰木flatter 奉承,阿谀flaunt 夸耀,招摇flaunty 虚华的flaw 使生裂缝,使有裂纹flawed 有缺点的fleeting 疾驰的,飞逝的flexible 灵活的flicking (尤指用手指或手快速地)轻击( flick的现在分词)flickering (通常指灯光)闪烁,摇曳( flicker的现在分词)flimsy 薄纸flip 发疯flippant 轻薄的,轻浮的flock 群集,成群结队而行floral 花的,花似的florid 红润的flounder 挣扎,踉跄前进flourish 挥动,挥舞flout 对…表示轻蔑fluctuate 使波动fluctuation 波动,涨落,起伏,[物]脉动fluffy 松软的,毛茸茸的fluid 流体的,流动的,流体的,液体的fluorescent 荧光的flustered 使慌乱,使不安( fluster的过去式和过去分词)foible 小缺点,小癖好foliage 植物的叶子(总称),叶子及梗和枝folklore 民间传说folly 蠢笨foodstuff <术>食物,食品forbear <正>(尤指为表示礼貌或耐心而)克制,忍耐,容忍forebode <正>预示(灾祸等)foreknowledge 预知,先见之明foreshadow 预示,是…的先兆foresight 先见forestall 先发制人,预先阻止forested 树木丛生的forfeit 罚金,没收物,丧失的东西forlorn 绝望的,孤立无助的formalized 使(协议、计划等)成书面文字形式( formalize的过去式和过去分词)formation 形成formidable 强大的formidably 可怕地,难对付地,强大地formulaic (根据)公式的,用俗套话堆砌成的,刻板的forsake 放弃,舍弃forthright 直路fortify 加强,增强fortitude 坚韧,刚毅fortuitous 偶然发生的,偶然的fossilized 使成化石( fossilize的过去式和过去分词)foster 收养,养育foul 纠缠,纠结founder 破坏factious 派系的fragile 易碎的,脆的fragment 碎片fragmentary 碎片的frail <美俚>少女,少妇frantic 发疯似的fraternity 兄弟会fraud 欺诈fraudulent 欺骗的,不诚实的fraught 装货于fray (使布、绳等)磨损,磨破frenetic 疯子frequency 频繁性fret 磨损,腐蚀friend <诗>与…为友frigid 寒冷地,冷漠地frisky 活泼,闹着玩frivolity 轻松的乐事,兴高采烈frivolous 无价值的,毫无意义的frugal 节省的,节俭的frugality 节约,朴素,节俭fruitless 没有成果的,无益的frustrate 无益的,无效的fulsome 过分恭维的fumigate 用化学品熏(某物)消毒function 有或起作用fundamental 基础的,基本的,根本的,重要的,原始的,主要的,十分重大的furtive 鬼鬼祟祟的fuse 保险丝fused 装有保险丝的fusion 融合fussy 大惊小怪的futile 无效的,无用的gain 利润gainsay 否认,反驳galaxy 银河gall 擦伤,擦破gallant 时髦的青年男子galvanize (用电)刺激garble 对(事实)歪曲,对(文章等)断章取义,窜改garnish 装饰,装饰品garrulous 饶舌的gaudy 宴会,招待会gene <生>基因generalize 概括,归纳generate 形成,造成generation 一代人generic 同“a generic druggenerosity 慷慨,大方generous 慷慨的,大方的genetic 遗传的genial 和蔼的,亲切的genre 类型,种类genus (动植物的)属geomagnetic 地磁的germinate 发芽gibe 嘲笑,嘲弄giddy 使眩晕glacial <地>冰的,冰河[川]的glamourous 富有魅力的,迷人的glance 浏览glandular 腺(状)的,起腺体功能的,有腺的glaze 上釉的表面gloat 幸灾乐祸gloom 使变黑,变暗glossary (书尾的)词汇表,难词汇编glossy 有光泽的,光滑的glucose [化]葡萄糖,右旋糖glutinous 黏的,胶质的gluttonous 暴食的,饕餮的,贪吃的gorgeous 华丽的,艳丽的gospel 传播福音的gouge 半圆凿graft 移植grain 谷物,粮食grandeur 伟大grandiloquence 夸张之言,豪言壮语,豪语grandiose 宏伟的graphic 图解的,用图表示的grateful 感激的,感谢的gratify 使高兴grating 磨碎,压碎( grate的现在分词)gratuitous 免费的,无偿的grave 沉重地,庄重地gravitational 万有引力的,重力的gravity 重力graze 放牧gregarious 爱交际的,合群的grief 悲伤grieve 伤心grim 冷酷的,残忍的grind 嘎吱嘎吱地擦gripping 抓紧( grip的现在分词) grope 摸索,探索groundless 无理由的,无根据的grudge 怀恨grumble 抱怨guile 奸猾guilt 有罪,犯罪行为,罪恶gullible 易受骗的,轻信的gush 涌出gymnastic 体育的,体操的habituate 使习惯于hackneyed (词语、引语等)使用过于频繁的,陈腐的,老一套的haggle 讨价还价hale 不断流出halfhearted 不认真的hallow 使成为神圣,把…视为神圣halting (使)停下来( halt的现在分词)hamper (有盖的)大篮子haphazardly 偶然地,随意地,杂乱地harass [军]扰乱,骚扰hardheaded (尤指在做生意时)精明的hardship 艰难harmonic [物] 谐波hatch 秘密策划,(尤指)密谋haughty 傲慢的,骄傲的haunt 时常萦绕心头,使困窘hazard 危险hazardous 冒险地,有危险地headstrong 任性的,刚愎自用的hearten 振作heartfelt 衷心的heavenly 无比,极其hedonist 快乐主义者heed 嘻笑( te-hee的过去式) heinous (道德败坏的人或行为)极邪恶的,极可耻的herald 传达,通报hereditary (生物学中)遗传的heretical 异教的,异端的hesitant 踌躇的heterodox 异端的heterogeneous 多种多样的,混杂的hiatus 裂隙hibernate (某些动物)冬眠,蛰伏hierarchy [计]分层,层次hieroglyph 象形字(如古埃及等所用的)hilarity 欢闹,狂欢histrionic 做作的hitherto 到目前为止hive 使(蜂)入蜂箱hoard 积蓄,贮藏homemade (衣服、食品等)自家制的homespun (尤指思想)朴素的,平常的homogeneity 同种,同质,同次性homogenous 同质的,纯系的homogenize 变均匀hormone 荷尔蒙horrific 令人恐惧的,可怕的,恐怖的hospitable 好客的host 当主人hostile 敌对者,敌对物hostility 敌意,敌对状态hot-tempered 性急的,易怒的,暴躁的hover 徘徊huckster 讨价还价,没完没了地争论huddle 挤在一起humane 仁爱的,慈善的humanistic 人文主义的humanitarian 人道主义者humble 使谦恭humdrum 乏味的,平凡的humidity (空气中的)湿度humiliate 使蒙羞,使丢脸,使出丑humility 谦逊,谦恭hunch 隆起hurl 猛投,猛掷hydrate (使)水合hyperbole <语>夸张法hypersensitive 过敏的,高度灵敏的hypnotic 安眠药hypochondriac 患疑病症的hypocrisy 伪善,虚伪hypocritical 伪善的hypothesis 假设,假说hypothetical 假设的,假定的hysteria [医]癔病iconoclasm 破坏偶像得理论,对偶像攻击,打破旧习iconoclastic 偶像破坏的,打破旧习的iconographic 肖像的idealism 理想主义identifiable 可辨认的ideological 思想的ideology 思想(体系),思想意识idiomatic 符合语言习惯地idiosyncrasy (某人特有的)气质,习性,癖好idiosyncratic 特质的,独特的idyllic 田园诗般的igneous 火的ignoble 卑鄙的ignominious 耻辱地,屈辱地,丢脸地ignominy 耻辱,污辱ignorance 无知,愚昧ignore 忽视,不顾illegitimate 非婚生的,私生的illicit 法律不许可的,非法的illiterate 目不识丁者ill-paying 不支付的ill-prepared 准备不足的;措手不及的ill-repute 恶名昭彰illusory <正>貌似真实的,虚幻的illustrative 用作说明的,解说性的ill-will [法] 敌意,仇视,恶感imbue 灌输imitate 模仿,效仿immaculate 洁净的immature 不成熟的immense 极大的,巨大的imminent (通常指不愉快的事)即将发生的immobile 固定的immodest 不谦虚的immutability 不变,不变性,永恒性impair 损害,削弱impart 给予impartial 不偏不倚的impartiality 公平,公正,不偏不倚impassable 不能通行的,无法通过impassioned 充满激情的impassive 冷漠的impatience 不耐烦impeccable 不会作坏事的人impecunious 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Domain Adaptation for Object Recognition:An Unsupervised Approach∗Raghuraman Gopalan,Ruonan Li,and Rama ChellappaCenter for Automation Research,University of Maryland,College Park,MD20742USA{raghuram,liruonan,rama}@AbstractAdapting the classifier trained on a source domain to recognize instances from a new target domain is an impor-tant problem that is receiving recent attention.In this pa-per,we present one of thefirst studies on unsupervised do-main adaptation in the context of object recognition,where we have labeled data only from the source domain(and therefore do not have correspondences between object cat-egories across domains).Motivated by incremental learn-ing,we create intermediate representations of data between the two domains by viewing the generative subspaces(of same dimension)created from these domains as points on the Grassmann manifold,and sampling points along the geodesic between them to obtain subspaces that provide a meaningful description of the underlying domain shift.We then obtain the projections of labeled source domain data onto these subspaces,from which a discriminative classi-fier is learnt to classify projected data from the target do-main.We discuss extensions of our approach for semi-supervised adaptation,and for cases with multiple source and target domains,and report competitive results on stan-dard datasets.1.IntroductionIn pattern classification problems,we are often con-fronted with situations where the data we have to train a classifier is‘different’from that presented during testing. Of the several schools of thought addressing this problem, two prominent ones are transfer learning(TL)[32],and do-main adaptation(DA)[4].These two strategies primarily differ on the assumptions of‘what’characteristics of data are changing between the training and testing conditions. Specifically,TL addresses the problem where the marginal distribution of data in the training set X(source domain) and the test set˜X(target domain)are similar,while the conditional distributions of labels,P(Y|X)and P(˜Y|˜X) with Y and˜Y denoting labels in either domain,are dif-∗This work was supported by a MURI grant N00014-10-1-0934from the Office of Naval Research.ferent.On the other hand,DA pertains to the case where P(Y|X)≈P(˜Y|˜X),but P(X)significantly varies from P(˜X).This specific scenario occurs very naturally in un-constrained object recognition settings,where the domain shift can be due to change in pose,lighting,blur,and reso-lution,among others.Understanding the effects of domain change has received substantial attention from the natural language processing community over the last few years(e.g.[4,8,16]).Al-though many fundamental questions still remain on the as-sumptions used to quantify a domain shift,there are several methods that have demonstrated improved performance un-der some domain variations.Given labeled samples from the source domain,these methods can be broadly classified into two groups depending on whether the target domain data has some labels or it is completely unlabeled.The for-mer is referred to as semi-supervised DA,while the latter is called unsupervised DA.While semi-supervised DA is gen-erally performed by utilizing the correspondence informa-tion obtained from labeled target domain data to learn the domain shifting transformation(e.g.[16]),unsupervised DA is based on the following strategies:(i)imposing cer-tain assumptions on the class of transformations between domains[39],or(ii)assuming the availability of certain discriminative features that are common to both domains [8,29].In the context of object recognition,the problem of matching source and target data under some pre-specified transformations has been extensively studied.For instance, given appropriate representation of objects such as contours or appearance information,if it is desired to perform recog-nition invariant to similarity transformations,one can use Fourier descriptors[43],moment-based descriptors[25]or SIFT features[27].Whereas in a broader setting where we do not know the exact class of transformations,the problem of addressing the domain changes has not re-ceived significant attention.Some recent efforts focus on semi-supervised DA[33,7,26].However,with the ever-increasing availability of image/video data from diverse de-vices such as a digital SLR camera or a webcam,and image collections from the internet,it is not always reasonable to 1Figure1.Say we have labeled data X from the source domain corre-sponding to two classes+and×,and unlabeled data˜X from the target domain belonging to class×.Instead of assuming some relevant features or transformations between the domains,we characterize the domain shift between X and˜X by drawing motivation from incremental learning.By viewing the generative subspaces S1and S2of the source and target as points on a Grassmann manifold G N,d(green and red dots respectively), wefirst sample points along the geodesic between them(dashed lines)to obtain‘meaningful’intermediate subspaces(yellow dots).We then ana-lyze projections of labeled×,+(green)and unlabeled×(red)onto these subspaces to perform classification.(Allfigures are best viewed in color). assume the availability of labels in all domains.Specific example scenarios include,a robot trained on objects in in-door settings with the goal of recognizing them in outdoor unconstrained conditions,or when the user has few labeled data and lots of unlabeled data corresponding to same ob-ject categories,where one would want to generalize over all available data without requiring manual effort in label-ing.Having said that,unsupervised DA is an inherently hard problem since we may not have any knowledge on how the domain change has affected the object categories. Contributions:Instead of assuming some information on the transformation or features across domains,we propose a data-driven unsupervised approach that is primarily moti-vated by incremental learning.Since humans adapt(better) between extreme domains if they‘gradually’walk through the path between the domains(e.g.[34,12]),we propose:•Representing the generative subspaces of same dimen-sion obtained from X and˜X as points on the Grass-mann manifold,and sample points along the geodesic between the two to obtain intermediate subspace rep-resentations that are consistent with the underlying ge-ometry of the space spanned by these subspaces;•We then utilize the information that these subspaces convey on the labeled X,and learn a discriminative classifier to predict the labels of˜X.Furthermore,we illustrate the capability of our method for handling multiple source and target domains,and in accommo-dating labeled data in the target,if any. Organization of the paper:Section2reviews related work.Section3discusses the proposed method.Section 4provides experimental details and comparisons with DA approaches for object recognition and natural language pro-cessing,and the paper is concluded in Section5.Figure1 illustrates the motivation behind our approach.2.Related WorkOne of the earliest works on semi-supervised domain adaptation was performed by Daum´e III and Marcu[16] where they model the data distribution corresponding to source and target domains to consist of a common(shared) component and a component that is specific to the individ-ual domains.This was followed by methods that combine co-training and domain adaptation using labels from either domains[36],and semi-supervised variants of the EM al-gorithm[14],label propagation[42]and SVM[18].More recently,co-regularization approaches that work on aug-mented feature space to jointly model source and target do-mains[15],and transfer component analysis that projects the two domains onto the reproducing kernel Hilbert space to preserve some properties of domain-specific data dis-tributions[31]have been proposed.Under certain as-sumptions characterizing the domain shift,there have also been theoretical studies on the nature of classification error across new domains[6,4].Along similar lines,there have been efforts focusing on domain shift issues for2D object recognition applications.For instance,Saenko et al[33] proposed a metric learning approach that could use labeled data for few categories from the target domain to predict the domain change for unlabeled target categories.Berg-amo and Torresani[7]performed an empirical analysis of several variants of SVM for this i and Fox[26] performed object recognition from3D point clouds by gen-eralizing the small amount of labeled training data onto the pool of weakly labeled data obtained from the internet.Unsupervised DA,on the other hand,is a harder problem since we do not have any labeled correspondence between the domains to estimate the transformation between them. Differing from the set of many greedy(and clustering-type)solutions for this problem[35,23,11],Blitzer et al [10,9]proposed a structural correspondence learning ap-proach that selects some‘pivot’features that would occur ‘frequently’in both domains.Ben-David et al[5]gener-alized the results of[10]by presenting a theoretical anal-ysis on the feature representation functions that should be used to minimize domain divergence,as well as classifica-tion error,under certain domain shift assumptions.More insights along this line of work was provided by[8,29]. Another related method by Wang and Mahadevan[39]pose this problem in terms of unsupervised manifold alignment, where the manifolds on which the source and target domain lie are aligned by preserving a notion of the‘neighborhood structure’of the data points.All these methods primarily focus on natural language processing.However in visual object recognition,where we have still have relatively lessconsensus on the basic representation to use for X and˜X,it is unclear how reasonable it is to make subsequent assump-tions on the relevance of features extracted from X and˜X [10]and the transformations induced on them[39].3.Proposed Method3.1.MotivationUnlike existing methods that work with the informa-tion conveyed by the source and target domains alone,our methodology of addressing domain shift is inspired from incremental learning(that illustrates the benefits of adapt-ing between extremes by gradually following the‘path’be-tween them),and we attempt to identify‘potential’interme-diate domains between the source and target and learn the information they convey about domain changes.In search of these novel domains,(i)we assume that we are given a N-dimensional representation of data from X and˜X, which depends on the user/application,rather than rely-ing on the existence of pivot features across domains[10], and(ii)we learn the‘path’between these two domains by exploiting the geometry of their underlying space,without making any assumptions on the domain shifting transfor-mation(as in[39]).A formal problem statement is given below.3.2.Problem DescriptionLet X={x i}N1i=1∈R N denote data from the source domain pertaining to M categories or classes.Let y i∈{1,2,3,...M}denote the label of x i.We assume that the source domain is mostly labeled,i.e.X=X l∪X uwhere X l={x li}N l1i=1has labels,say{y li}N l1i=1,and X u={x ui}N u1i=1are unlabeled(N l1+N u1=N1).We furtherassume that all categories have some labeled data.Let ˜X={˜xi}N2i=1∈R N denote unlabeled data from the target domain corresponding to the same M categories.Since sub-space models are highly prevalent in modeling data charac-teristics(e.g.[38]),we work with generative subspaces1 corresponding to the source and target domain.Let S1and S2denote generative subspaces of dimension2N×d ob-tained by performing principal component analysis(PCA) [38]on X and˜X respectively,where d<N.We now ad-dress two issues:(i)How to obtain the N×d intermediate subspaces S t,t∈R,1<t<2,and(ii)How to utilize the information conveyed by these subspaces on the labeled data X l to estimate the identity of unlabeled˜X?1Since we do not have labeled data from the target domain,our starting point will be generative subspaces that characterize the global nature of the domains,rather than the discriminative ones.2d refers to the number of eigenvectors of the PCA covariance matrix that have non-zero eigenvalues.We choose the value of d to be minimum of that of S1and S2,and restrict its maximum value to be less than N to enable use of methods that’ll be discussed soon.It is interesting to determine a better approach for doing this.•Given two points S1and S2on the Grassmann manifold.•Compute the N×N orthogonal completion Q of S1.•Compute the thin CS decomposition of Q T S2given byQ T S2= X C Y C = V100˜V2 Γ(1)−Σ(1) V T•Compute{θi}which are given by the arccos and arcsineof the diagonal elements ofΓandΣrespectively,i.e.γi=cos(θi),σi=sin(θi).Form the diagonal matrixΘcontainingθ’s as diagonal elements.•Compute A=˜V2ΘV T1.Algorithm1:Numerical computation of the velocity ma-trix:The inverse exponential map[20].3.3.Generating Intermediate SubspacesTo obtain meaningful intermediate subspaces between S1and S2,we require a set of tools that is consistent with the geometry of the space spanned by these N×d sub-spaces.The space of d-dimensional subspaces in R N(con-taining the origin)can be identified with the Grassmann manifold G N,d.S1and S2are points on G N,d.Understand-ing the geometric properties of the Grassmann manifold has been the focus of works like[41,19,1],and these have been utilized in some vision problems with subspace constraints, e.g.[37,21,28,22].A compilation of statistical analysis methods on this manifold can be found in[13].Since a full-fledged explanation of these methods is beyond the scope of this paper,we refer the interested readers to the papers mentioned above.We now use some of these results pertaining to the geodesic paths,which are constant velocity curves on a manifold,to obtain intermediate subspaces.By viewing G N,d as a quotient space of SO(N),the geodesic path in G N,d starting from S1is given by a one-parameter ex-ponentialflow[20]:Ψ(t )=Q exp(t B)J,where exp refers to the matrix exponential,and Q∈SO(N)such that Q T S1=J and J= I d0N−d,d .I d is a d×d identity matrix,and B is a skew-symmetric,block-diagonal matrix of the form B= 0A T−A0 ,A∈R(N−d)×d,where the superscript T denotes matrix transpose,and the sub-matrix A specifies the direction and the speed of geodesic flow.Now to obtain the geodesicflow between S1and S2, we compute the direction matrix A such that the geodesic along that direction,while starting from S1,reaches S2in unit time.A is generally computed using inverse exponen-tial mapping(Algorithm1).Once we have A,we can use the expression forΨ(t )to obtain intermediate subspaces between S1and S2by varying the value of t between0and 1.This is generally performed using the exponential map (Algorithm2).Let S refer to the collection of subspaces•Given a point on the Grassmann manifold S1and atangent vector B= 0A T−A0 .•Compute the N×N orthogonal completion Q of S1.•Compute the compact SVD of the direction matrixA=˜V2ΘV1.•Compute the diagonal matricesΓ(t )andΣ(t )such thatγi(t )=cos(t θi)andσi(t )=sin(t θi),whereθ’s arethe diagonal elements ofΘ.•ComputeΨ(t )=Q V1Γ(t )−˜V2Σ(t ) ,for various values of t ∈[0,1].Algorithm2:Algorithm for computing the exponential map,and sampling along the geodesic[20].S t,t∈R,1≤t≤2,which includes S1,S2and all inter-mediate subspaces.Let N denote the total number of such subspaces.3.4.Performing Recognition Under Domain ShiftWe now model the information conveyed by S on X and˜X to perform recognition across domain change.We basically approach this stage by projecting X and˜X onto S ,and looking for correlations between them(by using thelabels available from X).Let xli denote the dN ×1vec-tor formed by concatenating the projection of x li onto all subspaces contained in S .We now train a discriminativeclassifier D(Xl ,Y l),where X l is the dN ×N l1data ma-trix(with xli ,i=1to N l1forming the columns),and Y l isthe corresponding N l1×1label vector(whose i th row cor-responds to y li),and infer identity of dN ×1vectors corre-sponding to projected target data˜x i.We use the method of partial least squares3(PLS)[40]to construct D since dN is generally several magnitudes higher than N l1,in which case PLS providesflexibility in choosing the dimension of thefinal subspace unlike other discriminant analysis meth-ods such as LDA[3].We outline the operating principle behind PLS in the Appendix.3.5.Extensions3.5.1Semi-supervised Domain AdaptationWe now consider cases where there are some labels in the target domain.Let˜X=˜X l∪˜X u where˜X l={˜x li}N l2i=1has labels,say{˜y li}N l2i=1,and˜X u={˜x ui}N u2i=1is unlabeled(N l2+N u2=N2).We now use a dN ×(N l1+N l2) data matrix(whose columns correspond to the projections of labeled data from both domains onto S )and the corre-sponding(N l1+N l2)×1label vector to build the classifier D,and infer the labels of˜x ui,i=1to N u2.3Alternately,one can choose any other method for the steps involving PCA,and PLS.1.Given a set of k points{q i}on the manifold.2.Letµ0be an initial estimate of the Karcher mean,usually obtained by picking one element of{q i}atrandom.Set j=0.3.For each i=1,..,k,compute the inverse exponentialmapνi of q i about the current estimate of the mean i.e.νi=exp−1µj(q i).pute the average tangent vector¯ν=1kki=1νi.5.If ¯ν is small,then stop.Else,moveµj in the averagetangent direction usingµj+1=expµj( ¯ν),where >0 is small step size,typically0.5.6.Set j=j+1and return to Step3.Continue tillµj doesnot change anymore or till maximum iterations areexceeded.Algorithm3:Algorithm to compute the sample Karcher mean[13].3.5.2Adaptation Across Multiple DomainsThere can also be scenarios where we have multiple do-mains in source and target[30,17].One way of dealing with k1source domains and k2target domains is to create generative subspaces S11,S12,..,S1k1corresponding to the source,and S21,S22,...,S2k2for the target.From this we can compute the mean of source subspaces,say¯S1,and the mean for target¯S2.A popular method for defining the mean of points on a manifold was proposed by Karcher[24].A technique to obtain the Karcher mean is given in Algorithm 3.We then create intermediate subspaces between¯S1and ¯S2,and learn the classifier D to infer target labels as before.4.ExperimentsWefirst compare our method with existing approaches for2D object recognition[33,7],and empirically demon-strate the benefits of creating intermediate domains.In this process,we also test the performance of the semi-supervised extension of our algorithm,and for cases with more than one source or target domains.Finally,we provide comparisons with unsupervised DA approaches on natural language processing tasks.parison with Metric Learning Approach[33]We used the dataset of[33]that has31different object categories collected under three domain settings:images from amazon,dslr camera,and webcam.There are4652 images in total,with the object types belonging to back-pack,bike,notebook,stapler etc.The amazon domain has a average of90instances for each category,whereas DSLR and webcam have roughly around30instances for a cate-(a)DomainMetric learning [33]Ours(semi-supervised )Classification (%)Classification (%)(mean)(mean ±std.deviation)Source Target asymm symm Un-Semi-supervised supervised webcamdslr 252719±1.237±2.3dslr webcam 303126±0.836±1.1amazonwebcam484439±2.057±3.5(b)DomainMetric learning [33]Ours(semi-supervised )Classification %Classification (%)(mean)(mean ±std.deviation)Source Target asymm symm Un-Semi-supervised supervised webcamdslr534942±0.659±3.1Table parison of classification performance with [33].(a)with labels for all target domain categories.(b)with labels only for partial target categories.asymm and symm are two variants proposed by [33].Figure 2.Sample retrieval results from our unsupervised method on the dataset of [33].Left column:query image from the target domain.Columns 2to 6:Top 5closest matches from the source domain.Source/target combination for rows 1to 5are as follows:dslr/amazon ,webcam/dslr ,dslr/webcam ,webcam/amazon ,amazon/webcam .gory.The domain shift is caused by several factors includ-ing change in resolution,pose,lighting etc.We followed the protocol of [33]in extracting image features to represent the objects.We resized all images to 300×300and converted them into grayscale.SURF fea-tures [2]were then extracted,with the blob response thresh-old set at 1000.The 64-dimensional SURF features were then collected from the images,and a codebook of size 800was generated by k-means clustering on a random subset of amazon database (after vector quantization).Then the images from all domains are represented by a 800bin his-togram corresponding to the codebook.This forms our datarepresentation for X and ˜X,with N =800.From this we learnt the subspaces corresponding to source and target,and chose the subspace dimension d to be the lower of the two (and less than N ).The value of d was set between 185and 200for different experiments on this dataset.We experi-mentally fixed the number of intermediate subspaces to 8(i.e.N =10),and the PLS dimensions p to 30(please refer to the Appendix on how we obtain p -dimensional vec-tors using PLS).We report results on two experimental settings,(i)with labeled data available in both source and target domains -3labels per category in target for amazon/webcam/dslr ,and 8per category in source domain for webcam/dslr ,and 20for amazon ;and (ii)labeled data is available in both do-mains only for the first half of categories,whereas the last 16categories has labels only in the source domain.For the first setting,we determine the identity of all unlabeled data from the target domain,whereas for the second setting we determine the labels of unlabeled target data from the last 16categories.For both experiments,we report the resultsof our method in unsupervised setting(where we do not use labels from target,even if available)and semi-supervised setting(where the target labels are used)in Tables1(a)and 1(b)respectively.The performance accuracy(number of correctly classified instances over total test data from target) is reported over20different trials corresponding to differ-ent labeled data across source and target domains.It can be seen that although our unsupervised adaptation results are slightly lower than that of[33](which is reasonable since we throw away all correspondence information,while[33] uses them),our semi-supervised extension offers better per-formance improvement.Also note that the result in Table 1(b)is better than the corresponding category of Table1(a) since the former is a16way classification,while the later is a31-way classification.Some retrieval results from our un-supervised approach,corresponding to different source and target domain combinations,are presented in Figure2. parison with Semi-supervised SVM’s[7]We then used the data of[7]that has two domains:the target domain with images from Caltech256that has256 object categories,and the source domain corresponding to the weakly labeled results of those categories obtained from Bing image search.We used the classeme features to rep-resent the images.Each image was represented by a2625-dimensional binary vector,which models several semantic attributes of the image[7].We followed the protocol of[7] and present results on classifying the unlabelled target data under two experimental settings,(i)byfixing the number of labeled samples from the source domain and varying the labeled samples from target(starting from one),and(ii)do-ing the reverse byfixing the number of labeled target data, and varying the labeled samples from source.We also con-sider another operating point of no labeled data from the tar-get and source domains respectively(corresponding to the above two settings)to perform unsupervised DA.It can be seen from Figures3(a)and3(b)that our method gives better performance overall,with the gain in accuracy increasing with the number of labeled data.The performance is mea-sured using the percentage of correctly classified unlabeled samples from the target,averaged across several trials on choosing different labeled samples.4.3.Studying the information conveyed by interme-diate subspaces,and multi-domain adaptation We now empirically study the information we gain by creating the intermediate domains.We use the data of [33,7]where we evaluate the performance of our algorithm (unsupervised case)across different values4of N ranging from2to15.The same experimental setup of Sec4.1and 4All these runs correspond to p=30,which was empirically found to give the best performance.Domain OursClassification(%)(mean±std.deviation) Source Target Un-Semi-supervised supervised amazon,dslr webcam31±1.652±2.5amazon,webcam dslr25±0.439±1.1dslr,webcam amazon15±0.428±0.8webcam amazon,dslr28±1.942±2.8dslr amazon,webcam35±1.746±2.3amazon dslr,webcam22±0.232±0.9 Table2.Performance comparison across multiple domains in source or target,using the data from[33].Domain MethodClassification(%)Target Source[10][9]OursB D,E,K76.8,75.4,66.179.7,75.4,68.678.2,76.3,74.2D B,E,K74.0,74.3,75.475.8,76.2,76.976.1,75.8,79.1E B,D,K77.5,74.1,83.775.9,74.1,86.881.2,76.2,87.6 K B,D,E78.7,79.4,84.478.9,81.4,85.978.1,82.0,89.7 Table3.Performance comparison with some unsupervised DA ap-proaches on language processing tasks[9].Key:B-books,D-DVD,E-electronics,and K-kitchen appliances.Each row corre-sponds to a target domain,and three separate source domains. 4.2was followed.N =2denotes no intermediate sub-space,and we use the information conveyed by S1and S2 alone.This provides a baseline for our method.As seen in Figure3(c),all values of N >2offers better performance than N =2.Although this result is data-dependent,we see that we gain some information from these new domains.We then experimented with the data of[33]when there are multiple domains in source or target.We created six dif-ferent possibilities,three cases with two source domain and one target domain,and the other three with two target do-mains and one source domain.The experimental setup out-lined in Sec4.1was followed,where we consider the case with labels for all target categories.We provide the classi-fication accuracy of our unsupervised and semi-supervised variants in Table2.Although we do not have a baseline to compare with,one possible relation with the results in Ta-ble1(a)is for the case where the target domain is webcam and the source domains contain dslr and amazon.It can be seen that the joint source adaptation results lie somewhere in between single source domain cases.parison with unsupervised approaches onnon-visual domain dataWe now compare our approach with other unsupervised DA approaches that have been proposed for natural lan-guage processing tasks.We used the dataset of[9]that per-forms adaptation for sentiment classification.The dataset has product reviews from for four different domains:books,DVD,electronics and kitchen appliances. Each review has a rating from0to5,a reviewer name and(a)(b)(c)Figure3.(a),(b):Performance comparison with[7].(a)Number of labeled source data=300.(b)Number of labeled target data=10. Semi-supervised SVM refers to the top performing SVM variant proposed in[7].Please note that our method also has an unsupervised working point(at position0on the horizontal axis).(c)Empirically studying the effect of N on data from[33,7].Naming pattern refers to source/target domain.Accuracy for N >2is more than that for N =2,which says that the intermediate subspaces do provide some useful information.However,since larger values of N need not always translate into better classification(e.g.Bing/Caltech curve),it is interesting to formally study the optimal value of N .location,review text,among others.Reviews with rating more than3were classified as positive,and those less than 3were classified negative.The goal here is to see whether the process of learning positive/negative reviews from one domain,is applicable to another domain.We followed the experimental setup of[9],where the data representation for X and˜X are unigram and bigram features extracted from the reviews.Each domain had1000positive and nega-tive examples each,and the data for each domain was split into a training set(source domain)of1600instances and a test set(target domain,with hidden labels)of400in-stances.The classification accuracies with different settings of source and target domain are given in Table3.We see that our method performs better overall,even though we do not identify pivot features from the bigram/unigram data features(as done by the other two methods).This exper-iment also illustrates the utility of our method for domain adaptation across general,non-visual domains.5.ConclusionWe have proposed a data driven approach for unsuper-vised domain adaptation,by drawing inspirations from in-cremental learning.Differing from existing methods that make assumptions on transformations or feature distribu-tions across domains,we investigated the information con-veyed by‘potential’intermediate domains on the unknown domain shift.Although the tools used to create these novel domains are consistent with the underlying geometry of data,the absence of labeled target data does not allow us to guarantee that these domains would‘physically’corre-spond to the‘actual’domain transformation.Therefore to enable a better understanding of unsupervised domain adap-tation,the following broad problems are of interest:(i)uti-lizing generic priors on possible domain shifts to create and traverse physically meaningful intermediate domains, and(ii)exploring data representations beyond linear sub-spaces,with some desirable domain invariant properties that could accommodate potentially different data dimensional-ity across domains.Appendix:PLSLet X∈R m denote an m-dimensional space of feature vectors and similarly let Y∈R be a1-dimensional space representing the class labels.Let the number of samples (training patches)be n.PLS decomposes the zero-mean matrix X(n×m)and zero-mean vector y(n×1)intoX=TP T+E(1)y=Uq T+f(2) where T and U are(n×p)matrices containing p extracted latent vectors,the(m×p)matrix P and the(1×p)vec-tor q represent the loadings and the(n×m)matrix E and the(n×1)vector f are the residuals.The PLS method, using the nonlinear iterative partial least squares(NIPALS) algorithm,constructs a set of weight vectors(or projection vectors)W={w1,w2,...,w p}such that[cov(t i,u i)]2=max|w i|=1[cov(Xw i,y)]2(3)where t i is the i th column of matrix T,u i the i th column of matrix U and cov(t i,u i)is the sample covariance be-tween latent vectors t i and u i.After the extraction of the latent vectors t i and u i,the matrix X and vector y are de-flated by subtracting their rank-one approximations based on t i and u i.This process is repeated until the desired num-ber of latent vectors had been extracted.The dimensional-ity reduction is performed by projecting the feature vector v i,extracted from a i th detection window,onto the weight。
Adaptive methods for detecting passive signal from an underwater objectNikolay Gueorguiev, Alexandar Kolarov¹, Ilian. Iliev2¹ Institute of Metal Science, Equipment and Technology with Hydroaerodynamic Center at Bulgarian Academy of Sciences, 67Shipchenski2Naval Academy ―N. Vaptsarov‖, Varna, Bulgaria eAbstract: In order to determine the total spatial and temporal scale of the propagation of anthropogenic sources of noise, it is necess ary to identify them, which can be achieved by comparing underwater and sea surface observation data. For this purpose, it is necessary to determine the direction to the noise object in a function of time. In the development of a passive hydro-acoustic system positioned on the seabed for the detection, classification and determination of the direction to an underwater object, an adaptive processor sh all be designed, examined and experimented to dynamically determine the weighting factors of a two-element antenna grille according to the criteria of the minimum of the average square error and the maximum of the signal noise ratio.Keywords: ADAPTIVE PROCESSOR, LINEAR ANTENNA ARRA, UNDERWATER MONITORING, NOISE, SPECTROGRAM.1.IntroductionThe planned measures in the Program of Measures to the Marine Strategy for Environmental Protection in the Sea Waters of the Republic of Bulgaria envisage the monitoring under indicator D11C1.1 in fulfillment of the requirements of the RDMS to be performed on the basis of the analysis of data and information to be collected in the national "noise" register. The register will describe all human activities that generate impulse sounds in the sea area of the Republic of Bulgaria. Data on noise emissions from different types of ships will be collected from ship manufacturers / owners or specialized information systems (eg national AIS system, etc.), as well as from measurements by underwater noise monitoring stations. Data and information on anthropogenic activities will be collected continuously throughout the year and the noise register will be periodically updated. As a result of human activities in the marine environment, various types of fields are excited such as sound, light, electromagnetic, thermal, hydrodynamic, etc. Of all these fields, the sound field is distributed over the longest distances from the source [3,4]. That is why great attention is paid to the assessment of the energy impact of sound waves on marine species.A harmful underwater sound field is one in which exposure causes temporary or permanent damage to the fauna of the marine ecosystem. In theory, when such a field is created as a result of human activity, it is referred to as harmful anthropogenic noise. Anthropogenic noise is recognized as a serious stress factor for most marine mammals, many marine fish, crustaceans and other marine organisms. In addition to legally regulated activities that create anthropogenic noise in marine areas, short-term sound anomalies are possible, such as the sound of leaking gas in the event of a pipeline breach, or an uncharacteristic level of anthropogenic noise in protected or prohibited areas and water activities, noise from the use of bottom trawls for fishing, etc., which may cause significant harmful effects. Their timely registration and response to the authorities authorized by law can significantly reduce the harmful consequences [5].2.Assumptions and ways to solve the problemAs an element of an underwater monitoring system in the national marine areas, Institute of Metal Science, Equipment and Technology with Hydroaerodynamic Center at Bulgarian Academy of Sciences /IMS-BAS/ has developed a prototype of "Audio recording system for underwater monitoring with rapid notification of detected sound anomaly"/ARSUM/ (Fig. 1), designed for recording, classification and recording of sounds from biological sources (marine mammals, fish, shrimp, etc.), anthropogenic noise - pulsed (as a result of seismic surveys, laying pylons for wind farms and platforms on the seabed, use of pulsed sonar, underwater communications, underwater explosions, etc. ) or long-term (caused by shipping, dredging, leaks in underwater gas and oil pipelines, actions of power plants, acoustic signals from artificial radiation [6]. When detecting, recording and classifying a sound anomaly (eg sound of a leaking gas in the event of a pipeline breakage, noise from the use of bottom trawls for fishing or an uncharacteristic level of anthropogenic noise in protected or prohibited areas and for certain activities in the water area and etc.) a fragment of the information is recorded, with a duration sufficient for the classification of the event [7]. This fragment is transmitted wirelessly in an autonomous beacon from the device kit, where it is overwritten. Upon completion of the information transfer process, the radio beacon floats and transmits the critical information via radio to a shore, ship or air base station acting as an operations center. It is then used as a radio beacon to indicate the location of the event.Fig. 1 General configuration of an experimental sample of ARSUM When conducting tests with "Audio recording system for underwater monitoring with rapid notification of detected sound anomaly" it was concluded that its effectiveness is significantly increased when in addition to the information about the presence of classified noise in the area of the device is determined and the direction to it, and subsequently the vector of motion of the noise source is determined, even with tolerances in accuracy [8].For this purpose, an experimental model of the product was developed, and in place of the hydrophone was mounted a linear antenna array of two hydrophones (for experiments - 2microphones) - Fig.2.Fig.2 Electronic equipment located in the central airtight bodyIn order to achieve good accuracy characteristics, it was necessary to make a comparative assessment of applicable adaptive methods of beamforming using a linear antenna array for broadband signal processing [9].3. Results and discussionTwo methods for adaptive beam formation based on the two-element linear antenna array shown in Fig. 3.Fig.3 Two element ULA.Adaptive beamforming methods calculate the weights w 1 and w 2 based on statistics of the signal received from the individual elements.The first method, called "Sub band MVDR Beam former", forms the spatial beam by the method of minimal dispersion in the distortion of a broadband signal, using the technique of processing in sub bands. This type of diagram formation is also called the Capon method of beam formation [1, 2].The second method "Sub band Phase Shift Beam former" processes the broadband signal in sub bands by introducing phase delays.The aim of the study is to analyze their ability to detect a broadband signal against the background of their own noise and interference. The comparison of the two methods is performed by computer implementation of the algorithm shown in Fig. 4.Fig.4 Algorithm for simulation of adaptive diagram formation by the methods “Sub band Phase Shift Beam former” and “Sub band MVDR Beamformer”In the simulation model, as a broadband signal (Fig. 3), a signal with linear frequency modulation with length 2 s, carrier frequency 2 kHz and frequency deviation 1 kHz is used, whose angular position relative to the perpendicular to the phase center of the antenna is 20°. The intrinsic noise of the antenna is Gaussian with a rms value equal to 0.3 of the amplitude value of the broadband signal.Fig.5 Spectrogram of noise signal and noise at the output of an antennaelementIn the model, two interference signals with amplitudes twice as large as the broadband signal with angular positions of 10° and 30° are superimposed on the broadband signal and noise - Fig. 6.Fig.6 Spectrogram of a broadband signal with superimposed noise andtwo interference signalsTwo non-directional microphones with a frequency band from 20 Hz to 20 kHz located at a distance of 10 cm are used as elements of the antenna array. The processing of the received signals is performed in eight frequency bands with medium frequencies 1000, 1250, 1500, 1750, 2000, 2250, 2500, 2750 Hz. For the purposes of the research the formation of the beam in a frequency band with medium frequency 1 kHz is analyzed. Theobtainedradiation patterns as a result of the operation of the two beamformers are shown in Fig. 7.Fig.7 Directivity pattern formed by "Sub band Phase Shift Beamformer"and "Sub band MVDR Beamformer".The main maximum of the directivity diagram is electronically directed in the direction of the 20° signal.In the absence of an interference signal, the quality of operation of the two beam generators is identical. The advantage of "Sub band MVDR Beamformer" is manifested in the presence of interference. In this case, the average value by which the level of the output signal from the "Sub band MVDR Beamformer" beam generator exceeds the level of the "Sub band Phase Shift Beamformer" beam generator is 3.02 times.Spectrograms of the output signals from the twobeam generators are shown in Fig. 8 and Fig. 9.Fig.8 Spectrogram of the output signal of the antenna during interference in beam formation by "Sub band Phase Shift Beamformer"Fig.9Spectrogram of the output signal of the antenna in case of interference during radiation formation through “Sub band MVDR5. ConclusionThe effectiveness of the actions taken by the authorized bodies in response to information received from the "Audio recording system for underwater monitoring with rapid notification of detected sound anomaly" is significantly higher when data on the directions to the detected and classified events are included. The need to determine the direction of the noise object as a function of the time of the passivesonarsystem requires to study and experiment an adaptive processor for dynamic determination of the weights of the two-element antenna array according to the criteria for minimum square error and maximum noise ratio of the signal. Beam formation is used to amplify the signal against the background of noise. In real systems, the presence of interference signals received on side sheets leads to a strong masking of the signal by the target of interest [9]. In this case, the use of the method of minimum dispersion in signal distortion allows to form zeros in the directional characteristic in directions that coincide with the interference signal.6. Acknowledgements:The results can be used in the implementation of Work Package 2 ―Intelligent Security Systems‖ of Project BG05M2OP001-1.002-0006 – Creation and Development of a Centre of Competence ―Quantum Communication, Intelligent Security Systems and Risk Management‖ (Quasar), funded by the European Regional Development Fund through the Operational Programme ―Science and education for smart growth 2014-2020‖.7. References:1.Van Trees, H. Optimum Array Processing. New York: Wiley-Interscience, 2002;2.I. Iliev, "Hydroacoustic Measurements", ―N. Vaptsarov Naval Academy‖, Varna, 2016, ISBN 978-954-8991-84-1;3.MSFD Technical Subgroup on Underwater Noise, …Monitoring guidance for underwater noise in European sea‖, Prat I, Luxembourg: Publications Office of the European Union, 2014, ISBN 978-92-79-36341-2;4. MSFD Technical Subgroup on Underwater Noise, …Monitoring guidance for underwater noise in European sea‖, Prat II, Luxembourg: Publications Office of the European Union, 2014, ISBN 978-92-79-36339-9;5. MSFD Technical Subgroup on Underwater Noise, …Monitoring guidance for underwater noise in European sea‖, Prat III, Luxembourg: Publications Office of the European Union, 2014, ISBN 978-92-79-36340-5;6.M. Todorov, On the models of interaction of dug pipelines, International Conference UACEG 2009, October 29-31, 2009, ISSN 1310-814X;7.Ilov G., Germanov T., Zhelev J., Kirov B., Denev D., Mihova L., Varbanov R., Totsev A., Todorov M., Ivanov Iv., "Guide to Geotechnics", Eurocode 7, KIIP , 2011, ISBN 978-954-92275-8-1;8.М. Todorov, ―Cyclic Soils Properties‖, Seventh Iinternational Structural Engineering and Construction (ISEC-7), Hawaii, June 18—23, 2013, ISBN-10: 981-07-5354-2;9.Samuel Shephard, Simon P. R. Greenstreet, GerJan J. Piet, Anna Rindorf, and Mark Dickey-Collas. 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Day 11 abandon vt. 离弃;抛弃2 ability n. 能力;才能3 abnormal a. 反常的4 abolish vt. 废除; 废止5 absolute a. 绝对的;确实的6 absorb vt. 吸引7 abstract n. 摘要;抽象8 abundant a. 丰富的9 abuse vt. 滥用;辱骂;虐待10 academic a. 学校的11 accelerate v. 加速;加快12 access v. 进入;使用13 accommodation n. 住处14 accompany v. 陪伴;伴奏15 accomplish vt. 完成;实现16 account n. 解释;导致17 accumulate vi. 积聚18 accurate a. 精确的19 accustomed a. 习惯的20 acknowledge vt. 承认21 activity n. 活动22 acute a. 极大的;精明的23 adaptive a. 能适应的24 addicted a. 入了迷的25 address vt. 演说;从事Day 21 adjust vt. 调整,使…适合2 admirable a. 令人钦佩的3 admit vt. 承认;准许进入4 adolescent n. 青少年5 adopt vt. 采取;收养6 adore vt. 崇拜;非常喜爱7 advantage n. 优势;利益8 adventure n.&v. 冒险9 advertisement n. 广告10 advocate vt. 提倡,主张11 affect vt. 影响;感染12 affordable a. 买得起的13 agent n. 代理人;特工14 aggressive a. 侵略性的15 agriculture n.农业;农学16 air-conditioning n. 空调系统17 all-round a. 多才多艺的;全面的18 alternative n. 替代物19 amazement n. 惊讶20 ambition n. 野心,抱负21 analyse vt. 分析;分解22 anniversary n. 周年纪念日23 announce vt. 宣布;通知24 annoying a. 使人气恼的25 anti-tobacco n. 禁烟Day 31 anxiety n. 忧虑;渴望2 apparent a. 显然的;表面上的3 applaud v. 鼓掌欢迎4 application n. 应用;申请5 appreciation n. 欣赏6 approach n. 途径vt.走近7 approval n. 批准;认可8 approximately ad. 大约9 artificial a. 人造的;虚伪的10 artistic a. 艺术的11 assess vt. 确定12 assignment n. 作业13 associate v. 交往;联想14 assume vt. 承担;假定15 astonished a. 吃惊的16 atmosphere n. 气氛17 attempt n. 企图vt. 尝试18 attitude n. 态度19 attract vt. 吸引;引起20 automatically ad. 无意识地21 available a. 可得到的;可利用的22 average n. 平均a.平均的23 award-winning a. 应获奖的24 aware a. 意识到的;知道的25 awkward a. 笨拙的Day 41 bachelor n. 单身汉;学士2 bacterium n. 细菌3 behave vi. 表现4 benefit n. 利益vt.有益于5 blessing n. 赐福6 blinding a. 使人眩目的7 branch n. 树枝;分部8 breakthrough n. 突破9 brief a. 简略的10 brilliant a. 灿烂的;杰出的11 brochure n. 手册12 cafeteria n. 餐厅13 campaign n. 运动;活动14 candidate n. 候选人;应试者15 career n. 事业;职业;生涯16 caregiver n. 照料者17 caretaker n. 门卫;看管人18 cautiously ad. 谨慎地19 celebrate vt. 庆祝;举行20 celebrity n. 名人21 ceremony n. 典礼,仪式22 certificate n. 证书;执照23 challenge n. 挑战24 charity n. 慈善机构25 chat vi. 闲聊Day 51 circumstance n. 情况2 clarify vt. 澄清;阐明3 co-founder n. 共同创立者4 colleague n. 同事;同僚5 combination n. 结合6 comedy n. 喜剧7 comment n. 评价8 commitment n. 承诺;保证9 communicate vi. 传达10 community n. 社区11 compensation n. 补偿;报酬12 compete vi. 竞争;比赛13 competence n. 能力;胜任14 complain vt. 抱怨;投诉15 completely ad. 完全地;十分16 complex a. 复杂的17 compose vt. 构成;写作18 compound vt. 合成;和解19 compulsory a. 义务的;必修的20 concentration n. 集中21 concept n. 概念22 conclusion n. 结论;结局23 condemn v. 谴责,声讨24 confirm vt. 确认;确定25 conflict n. 冲突,矛盾Day 61 consequence n. 结果;重要性2 conservation n. 保存;保持3 consideration n. 考虑;体谅4 constant a. 经常的;不变的5 construction n. 建造;建设6 consultant n.咨询;顾问7 consumer n. 消费者8 contact n. 接触,联系9 contrary a. 相反的10 contrast vi. 对比;形成对照11 contribute vt. 贡献,出力12 convenient a. 方便的13 convey vt. 传达;运输14 convincing a. 令人信服的15 core n. 精髓;核心16 critically ad. 非常认真地17 curiosity n. 好奇,珍品18 current a. 现在的n.趋势19 customer n. 顾客;消费者20 dangerous a. 危险的21 deadline n. 最后期限22 deadly a. 致命的23 debate n.& v. 辩论,争论24 decade n. 十年25 declare vt. 宣布,声明Day 71 decline n. 下降;衰退2 decoration n. 装饰3 decrease n.&v. 减少4 delete vt. 删除5 delicate a. 细致优雅的6 delight n. 高兴vt.(使)高兴7 delivery n. 交货;发送8 department n. 部;系9 deposit n. 存款v.沉淀10 depressed a. 沮丧的11 descendant n. 后代,晚辈12 describe vt. 描述,形容13 deserve v. 应受,应得14 designer n. 设计师15 desire n. 愿望16 desperate a. 绝望的17 desperation n. 绝望18 despite n. 轻视;憎恨19 destination n. 目的地20 destroy vt. 破坏;消灭21 determination n. 决心22 development n. 发展23 device n. 设备24 digital a. 数字的25 disabled a. 残废的;有缺陷的Day 81 disadvantage n. 坏处;不利2 disagreement n. 不合;争论3 disappear vi. 消失;失踪4 disappointment n. 失望5 disaster n. 灾难6 disastrous a. 灾难性的7 discipline n. 纪律8 discount n. 折扣v.打折9 discourage vt. 使气馁;阻碍10 discovery n. 发现;发现物11 discussion n. 讨论, 商讨12 disgusting a. 令人厌恶的13 display n.& v. 显示;炫耀14 distinguish v. 区分;辨别15 distract vt. 使分心16 distribution n. 分配17 disturb v. 打扰;妨碍;使不安18 diverse a. 多样化的;不同的19 document n. 文件20 donation n. 捐赠21 download n. & vt. 下载22 downtown n. 市区 a.市中心的23 drag vt. 拖拉;缓慢而吃力地行进24 dutiful a. 尽职的25 earring n. 耳环;耳饰Day 91 ecology n. 生态;生态学2 education n. 教育;教育学3 efficient a. 有效率的4 elderly a. 上了年纪的5 electricity n. 电力;电流6 electronic a. 电子的7 embarrassed a. 尴尬的;窘迫的8 emerge v. 出现9 emergency n. 突发事件a.应急的10 emotional a. 感人的;情绪化的11 employ vt. 雇用;使用12 employee n. 雇员;从业员工13 enable vt. 使能够,使成为可能14 capable a. 有能力的15 encourage vt. 鼓励,怂恿16 enlarge vi. 扩大;详述17 enrich vt. 使充实;使丰富18 enterprise n. 企业;进取心19 entertainment n. 娱乐20 enthusiastic a. 热情的21 environmental a. 环境的22 envy vt. & n.妒忌;羡慕23 equate vt. 使相等24 equipment n. 设备;装备25 escape n.& v. 逃脱;避开Day 101 especially ad. 特别是;尤其是2 essence n. 本质;精华3 essential a. 本质的;必要的;重要的4 establish vt. 建立;创办5 evaluation n. 评价6 eventually ad. 最终7 evidence n. 证据,迹象8 exchange n.&v. 交换;兑换9 exhausted a. 精疲力竭的10 exhibition n. 展览;展览会11 existence n. 存在;生存12 expansion n. 膨胀;扩张13 expectation n. 预料; 期望14 experience n. 经验; 经历15 experiment n. 实验;试验16 expertise n. 专门知识;专长17 explanation n. 解释; 说明18 explosion n. 爆炸;激增19 expression n. 表达;措辞20 extend vi. 延伸;扩大21 extension n. 延长;伸展22 external a. 外部的23 extraordinary a. 非凡的24 extreme n. 极端a.极端的25 facial a. 面部的;脸的Day 111 facility n. 设施;设备2 fade vi. 逐渐消失3 failure n. 失败;失败者4 familiar a. 熟悉的5 fantastic a. 极好的;难以相信的6 fascinating a. 迷人的7 fashion n. 时尚;时髦人物8 fasten vt. 扎牢;系牢9 favorite n. 特别喜欢的人/物10 fellow n. 同事;朋友11 festival n. 节日a.节日的12 fiction n. 小说;虚构13 fiercely a. 猛烈的14 figure v. 计算;认为n. 数字;人物15 financial a. 经济的16 fireworks n. 爆竹;烟火17 firsthand a. 第一手的18 flashlight n. 手电筒闪光灯19 flexible a. 灵活的;易弯曲的20 flowerbed n. 花圃21 focus n. 焦点;中心v.集中22 follow v. 跟随;遵循;明白23 forbid vt. 不许,禁止24 forecast n.& vt. 预测,预报25 foresee vt. 预见;预知Day 121 forgive vt. 原谅;宽恕2 fortunately ad. 幸运地,幸亏3 frequently ad. 频繁地,经常地4 frustrated a. 失意的5 frustration n. 挫折6 fundamentally ad. 根本地7 furiously ad. 猛烈地;狂暴地8 furnished a. 装配好家具的9 furniture n. 家具;设备10 gallery n. 画廊;走廊11 gather vi. 聚集vt.收集12 generation n. 一代;产生13 generosity n. 慷慨14 gifted a. 有天赋的;有才华的15 global a. 全球的;全局的16 glorify vt. 加荣耀于;赞美17 glory n. 荣誉18 government n. 政府;管理19 graceful a. 优雅的;有风度的20 gradually ad. 逐渐地21 graduation n. 毕业;刻度22 grounded a. 脚踏实地的23 guarantee vt. & n. 保证24 guideline n. 指导方针25 guiltily ad. 内疚的;有罪的Day 131 handle vt. 处理;拿n.柄;把手2 handsome a. 英俊的;可观的3 handy a. 方便的;手巧的4 hardship n. 艰难;困苦5 harmony n. 和谐6 harvest n.& v.收获;收割7 hatred n. 憎恨8 headline n. 新闻提要;头条新闻9 hesitate vi. 犹豫10 hidden a. 潜藏的11 historian n. 历史学家12 hug vi. 拥抱13 humble a. 谦逊的14 hurricane n. 飓风15 hydrogen n. 氢16 identify vt. 识别17 ignore vt. 忽视18 illegally ad. 非法地19 imagine vt. 想象;料想20 immigration n. 移民21 impression n. 印象;感觉22 improve v. 改进;改善;变得更好23 inaccessible a. 难达到的24 inactive a. 不活跃的25 incapable a. 无能力的Day 141 inconvenience n. 不便2 increasingly ad. 渐多地3 incredible a. 难以置信的;惊人的4 independence n. 独立;自主5 indicate v. 指示;显示;表明6 indication n. 迹象;指示7 individual n. 个人a.个人的8 industry n. 工业;厂业;企业9 influence n.& vt.影响10 innocent a. 天真的;无辜的;无害的11 insincere a. 不真诚的12 inspiration n. 鼓舞;灵感13 institution n. 机构;制定;名流14 instruction n. 指令;教诲;说明15 insurance n. 保险;保险费16 intelligence n. 智力;情报17 intense a. 强烈的,非常的18 interface n. 界面;接口19 international a. 国际的;世界的20 interrupt vt. 中断;打断;插嘴21 interstate a. 州际的22 interview vt. 采访23 introductory a. 开端的24 invention n. 发明;发明物25 invest vt. 投资Day 151 invitation n. 邀请;引诱2 inviting a. 诱人的3 involve vt. 包含;牵涉;潜心于4 irresponsibility a. 无责任感5 issue n. 议题;要讨论的问题6 knowledge n. 知识;了解7 landfill n. 垃圾填埋地8 laundry n. 洗衣店;洗好或待洗的衣9 lessen vi. 减轻10 librarian n. 图书管理员11 literature n. 文学12 majority n. 多数;大多数13 manage v. 管理;设法对付14 massive a. 巨大的;大规模的15 material n. 材料;原料16 maximum n. 最大值a.最大的17 meaningful a. 有意义的18 meanwhile ad. 在此期间;与此同时19 measurement n. 尺度;测量20 membership n. 会员资格卡21 memory n. 记忆;记忆力22 mentally a. 精神上的23 merchant n. 商人24 mindful a. 留心的25 mineral n. 矿物;矿石Day 161 minimum a. 最少的n. 最小数2 minor a. 微不足道的3 minority n. 少数;少数民族4 miserable a. 可怜的5 misfortune n. 不幸6 mistreat vt. 虐待7 misuse vt. 误用8 mobile a. 可移动的;易变的9 monetary a. 钱的;财政的10 mood n. 心情11 motivate vt. 激励;激发12 motivation n. 动机;动力13 mountainous a. 多山的;巨大的14 multiply vi. 繁殖15 multitask vt. 使多任务化16 mushroom n. 蘑菇vi.迅速成长17 mysterious a. 神秘的;不可思议的18 naturally ad. 自然地19 necessary a. 必要的20 neglect n. & vt. 疏忽;忽略21 negotiate v. 协商;谈判22 nervously ad. 紧张地23 network n. 网络24 nutrient n. 营养物25 occupation n. 职业;占有Day 171 offence n. 犯罪;违反2 operate vt. 经营;管理3 opportunity n. 机遇4 opposite a. 对面的;相反的5 optimism n. 乐观;乐观主义6 organization n. 组织;团体7 original a. 原始的;最初的n. 原件8 outbreak n. & vi. 发作;爆发9 outcome n. 结果10 outnumber v. 数量上超过11 outshine vt. 使相形见绌;胜过12 outwardly ad. 表面地13 overall a. 全部的14 overcome vt. 克服15 over-crowding a. 过分拥挤16 overlook vt. 忽视17 partially ad. 部分地18 particularly ad. 特别地;详细地19 passion n. 激情20 pedestrian n. 行人;步行者21 permanently ad. 永久地22 permission n. 允许;许可23 personal a. 个人的;亲自的24 phenomenon n. 现象25 philosophy n. 人生观哲学Day 181 photographer n. 摄影师2 pickpocket n. 扒窃3 platform n. 平台;站台4 popularity n. 普及;流行5 populate vt. 居住于;移民于6 portable a. 轻便的7 positive a. 积极的;肯定的8 possess vt. 控制;使掌握9 possibility n. 可能性10 postpone vi. 延迟11 potential n. 潜力12 poverty n. 贫困13 powdered a. 粉状的14 practical a. 实际的;实用的15 predict vt. 预言16 preschooler n. 学龄前儿童17 present vt. 提出;呈现a. 现在的18 presentation n. 介绍19 press n. 新闻舆论20 pressure n. 压力;压迫21 previous n. 以前的22 primary a. 初级的23 primitive a. 原始的24 process n. 过程vt. 处理;加工25 production n. 生产;产品Day 191 productive a. 多产的2 professional n. 专业人员3 profitable a. 盈利的4 progressively ad. 渐进地5 promote vt. 促进;提升6 publication n. 出版7 publicity n. 宣传;公开;注意8 purchase vt. 购买9 purify vt. 净化10 rainforest n. (热带)雨林11 rainstorm n. 暴风雨12 rarely ad. 很少地;罕见地13 reaction n. 反应14 realistic a. 现实的15 recognition n. 公认16 recognize vt. 认出;识别17 recommend vt. 推荐;介绍18 reconstruction n. 重建19 recover vt. 恢复;弥补20 recycle vt. 使……重新使用21 redirect v. 再利用;循环22 reflect vt. 反映;反思23 registration n. 注册;登记24 regularly ad. 有规律的25 reliable a. 可信赖的Day 201 remaining a. 剩下的2 remarkable a. 不平常的3 remotely ad. 远程地4 renew v. 更新5 representative n. 代表6 reserve n. 保留;储备7 resident n. 居民8 resolve vt. 解决;决心;溶解9 resort vi. 求助n. 度假胜地10 resource n. 资源11 respond vi. 回答;做出回应12 responsible a. 有责任的13 restaurant n. 餐馆14 restlessness n. 坐立不安15 restriction n. 限制16 retirement n. 退休17 reveal vt. 显示;透露;泄露18 ridiculous a. 荒谬的;可笑的19 rotten a. 腐烂的20 round-trip a. 来回的;双程的21 sacred a. 神圣的22 scanner n. 扫描仪23 scarce a. 稀少的24 scenery n. 风景25 scholarship a. 奖学金Day 211 scream vt. 尖叫;哭闹2 secretary n. 秘书3 security n. 安全感4 selective a. 有选择性的5 self-awareness n.自我意识6 self-image n. 自我形象7 self-respect n. 自尊8 seminar n. 研讨会9 sensation n. 感觉,轰动10 sensibility n. 情感;识别力11 sensibly ad. 明智地;明显地12 sensitive a. 敏感的13 separate a. 各自的14 serie n. 系列;序列15 sharply ad. 急剧地16 shyness n. 害羞17 signature n. 署名;信号18 significant a. 重大的;有意义的19 sincerity n. 真诚20 single-minded a.纯真的21 situation n. 形势;处境22 slightly ad. 稍微,轻微地23 so-and-so n. 某某人24 software n. 软件25 solution n. 解决措施Day 221 source n. 来源2 specialize vt. 使专门化3 spray vt. 喷射4 spring vi. 跳跃n. 春天;弹簧5 stamped a. 铭刻的6 statesmen a. 政治家7 stretch vt. 伸展8 striking a. 引人注目的9 substitute n. 替代品10 sufficient a. 充足的11 super-easy a. 超容易的12 surgery n. 手术13 surprisingly ad. 惊人地14 surrounding a. 周围的n. 环境15 survival n. 生存;幸存者16 sustainable a. 可持续的17 swollen a. 肿的18 sympathetic a. 表示同情的19 symptom n. 症状20 technology n. 技术;工艺21 temperature n. 温度22 temporary a. 暂时的n. 临时工23 tendency n. 趋势24 thankless a. 忘恩的25 thoroughly ad. 完全地Day 231 tolerate vt. 容忍;宽恕2 tragedy n. 悲剧3 transcontinental a. 横贯大陆的4 transmission n .传送5 transport n. 运输6 treasure n. 财富7 trembling a. 颤抖的8 tryout n. 选拔赛9 twist vt. 拧;扭曲10 typical a. 典型的11 unattractive a. 没有魅力的12 unavoidable a. 不可避免的13 unbelievable a. 难以置信的14 unchangeable a. 无法改变的15 uncivilized a. 不文明的16 uncomfortably ad. 不舒服地17 unconscious a. 失去知觉的18 under-evaluate vt. 低估19 undersize a. 较一般人矮小的20 unemployed a. 失业的21 unexpected a. 意外的22 unfortunately ad. 不幸地23 uninterrupted a. 不间断的24 unique a. 独特的,稀罕的25 universal n. 一般概念;普通性Day 241 unmistakable a. 明显的2 unnecessary a. 不必要的3 unplanned a. 没有计划的4 unrest n. 不安5 unshaven a. 未刮脸的6 unsympathetic a. 不表同情的7 unwashed a. 未洗的;不清洁的8 valuable a. 贵重的;有价值的9 victim n. 受害者10 virtual a. 虚拟的11 visible a. 看得见的12 vivid a. 生动的13 voluntarily ad. 自动地;自发地14 widespread a. 普遍的15 wilderness n. 荒地;大量16 win-win a. 双赢的;互利互惠的17 wisdom n. 智慧18 workload n. 工作量19 worldview n. 世界观20 worldwide a. 全世界范围的21 worn-out a. 穿破了的;疲惫不堪的22 wrinkle n. 皱纹v.(使)起皱纹23 withdraw v. 收回;撤消;撤退24 worthwhile a. 值得(做)的25 zoom vi. 急速移动;猛涨11。
A1.adap.adep.adop.adapt vt.使适应;使适合He adapted himself to the cold weather.When he moved to Canada, the children adapted to the change very well. adep.adj.(与at.i.连用.纯熟旳;精通.n.内行;老手She was adept at the fine art of irritating people.adopt vt.收养;采用;采用They adopted our methods.正式通过;采纳The resolution was adopted by a vote of 180 in favour to 10 against it.2.adopted adoptiveadopted adj.被收养旳, 被采纳旳an adopted child/an adopted adviceadoptive adj.收养(孩子)旳an adoptive mother3.averse adverseaverse adj.(常与to 连用)嫌恶旳I am not averse to a dance party and a good mean after a week's hard work. The minister is averse to/from flattery.adverse adj.不利旳;相反旳an adverse decisionAdverse circumstances compelled him to close his business.4 affection affectationaffection n.友爱, 爱情, 影响, 疾病, 倾向affectation n.假装, 虚饰, 做作5.altitude attitude aptitude latitude longitude multitudealtitude(海拔)高度-At high altitudes of Tibet it is difficult to breathe.高处-The plane flew at an altitude of 20230 metres.attitude n.姿势;态度-People's attitude towards the skyscrapers varies widely.见解;意见-What is the Municipal Authority's attitude to the proposal of a tunnel across the river? What's the authorities' attitude towards this discord?aptitude n.能力;才能;天资latitude n.纬度, 范围, (用复数)地区, 行动或言论旳;自由(范围)longitude n.经度, 经线multitude n.多数, 群众6.angle angelanglen.角;角度-a right angle角落;墙角;棱角观点;见解;看问题旳角度to consider all angles of the questionThe professor angled his report to suit the audience he was speaking to.vt.转动一种角度-to angle a camera带成见地描述(某事)He angles his reports to please his editor in chief.用钩和钓钓鱼He is keen on angling.(与for 连用)运用手段获得, 攫取angeln.天使;守护神;仁慈、漂亮旳女人7.announce denounce renounce pronounceannouncevt.通告;宣布, 宣布;刊登The captain announced that the plane was going to land.The government announced that they would build a new highway to the mountain. denounce vt.告发;揭发;斥责renounce vt.正式放弃He renounced his claim to the property.宣布断绝关系He renounced his religion.pronouncevt., vi.发音;发出…音How do you pronounce c-l-e-r-k?宣称;宣布;断言The expert pronounced the picture to be a forgery.The priest pronounced them man and wife.Everyone pronounced the party to be very good.(常与on, for, against, in favor of 连用)〈法〉宣判The judge pronounced sentence on the prisoner.8.annua.annulannualadj.每年旳;一年一次旳-an annual eventannulvt.取消, 废除(婚姻、契约等)abolish/abolition; abrogate/abrogation9.apposite oppositeappositeadj.合适旳oppositeadj.相对旳, 对面旳, 对立旳, 相反旳, 对等旳, 应旳n.相反旳事物10 appraise apprise praiseappraisevt.评估, 评价, 鉴定apprisevt.告知;告知She was apprised of our arrival.The secretary came to apprise us that the erection of the monster machine had been successfully completed.praisevt.赞美;赞扬;歌颂;赞颂She praised her daughter's hard work.11.apprehensive comprehensiveapprehensiveadj.忧虑旳;紧张旳-apprehensive for sb.'s safetycomprehensiveadj.全面旳;广泛旳;包括内容多旳;详尽旳The state government gave a very comprehensive explanation of its plans for the development of electronic industry.12 argument augmentargumentn.争论, 辩论, 论据, 论点, ~(for,against),意见augmentvt., vi.增大;增长13.ascrib.describ.prescrib.subscrib.inscrib.proscrib.ascribe vt.归因于, 归咎于describe vt.描写, 记述, 形容, 形容v.描述prescribe vt., vi.`开药方;处方;命令;规定The law prescribes what should be done.What punishment does the law prescribe for corruption?The doctor prescribed total abstinence.subscribevt., vi.(常与to, for 连用)捐款;捐助;订购(报纸、杂志等)(常与to 连用)同意, 赞同inscribevt.(常与in, on, with 连用)题写;铭刻She inscribed her own name on the textbook.(常与to 连用)题名This book I inscribe to my old comrades-in-arms.proscribe vt.严禁14.assen.ascen.. concent/decentassentvi.(常与to 连用)同意ascentn.上升, (地位, 声望等旳)提高, 攀登, 上坡路15 dissent descent decentdissentvi.(常与from 连用)持异议;不一样意;意见不一致He and I dissented from each other in choosinga suitable candidate.descentn.下降;下滑;降下;下来血统;遗传He traces his descent from an old Normanfamily.decentadj体面旳合适旳16.assum.resum.consum.presume英语部分269/1359assum. vt.假定;假设I assume you always get up at the same time.采用;承担to assume new dutiesresume n.摘要, 概略, <美> 履历vt.再继续, 重新开始, 重新占用, 再用, 恢复consume vt., vi.吃, 喝;消耗;消费;花费His old car consumed much gasoline.消灭;烧毁The fire soon consumed the old wooden buildings in the neighbourhood. presume vt., vi.(常与that 连用)假定;假设;认为I presume from your speech that you are a foreigner.You must presume no such thing.当作;姑且认为If a person is missing for 7 years, he is presumed dead.(常与to + inf 连用)放肆;擅作主张A servant ought not to presume.(与on, upon 连用)指望;寄但愿于…We must not presume too mush on the reliability of such sources.17 avocation vocation vacationavocationn.(个人)副业, 业余爱好vocationn.职业;行业天职;使命vacationn.假期I worked in a small beachside restaurantduring the college vacation.18 authentic authoritativeauthentic真实旳: 与事实相符并且值得相信、信赖旳:an authentic account by an eyewitness.真正旳: 有着经证明旳来源或创作者旳;非伪造旳或非复制旳:英语部分270/1359an authentic medieval sword.一把真正旳中世纪剑authoritativeadj.(形容词)官方旳: 有着或由政府发起旳;官方旳:an authoritative decree; authoritative sources. 权威性旳: 拥有公认旳精确性或优秀性旳;极可信赖旳:an authoritative account of the revolution.专断旳: 行使权力旳;命令旳:the captain's authoritative manner.19 adjoin adjacent adjournadjoinvt.毗连;临近;贴近Our house adjoins theirs.adjacentadj.(与to 连用)相邻旳, 邻近旳adjournvt., vi.延期;休会, 会议暂停The meeting will be adjourned till next Wednesday.20 admire admiraladmirev.赞美, 钦佩, 羡慕admiraln.海军上将, 舰队司令, 旗舰21 adore adornadorevt.崇拜敬爱;敬重非常喜欢He adores the cinema.She adores going to the volleyball ma tch. adornvt.装饰She likes to adorn herself with jewels.增长…旳重要性或吸引力He tried to adorn his story with a lot of lies 22.applianc.applican.application appliancen.用品, 器具英语部分271/1359applicantn.申请者, 祈求者applicationn.祈求, 申请, 申请表, 应用, 运用23 alley ally alloyalleyn.小路, 巷, (花园里两边有树篱旳)小径allyv.结盟, 与...(在血统, 性质等上)有关联, 同盟vn.同盟国, 支持者alloy合金24 accession accessaccessionn.就职, 就任, 添加, 增长accessn.通路, 访问, 入门vt.存取, 靠近B1.bul.bullybull n.公牛, 粗壮如牛旳人, 乐观进取旳人;胡扯;废话bull.vt.威吓;欺侮;以强凌弱He's always bullying smaller boys.2.bandage bondagebandage n 绷带bondage n 奴役, 束缚3.brea.beadbread n 面包bead n 水珠、珠子;祈祷4.bum.dum.jum.hum.lum.plum.pumpbump n.撞击, 肿块v.碰(伤), 撞(破), 颠簸dumpvt.倾倒(垃圾), 倾卸n.堆存处jum.n.跳跃.上涨.惊跳vt.跳跃.跃过.突升.使跳跃vi.跳跃, 暴涨n.驼峰, 驼背, 小园丘, 峰丘v.(使)隆起, 弓起lumpn.块(尤指小块), 肿块, 笨人vt.使成块状, 混在一起.plumpadj.圆胖旳, 丰满旳, 鼓起旳vt.忽然放下, 使丰满, 使鼓起vi变丰满, 鼓起pump n.泵, 抽水机vt.(用泵)抽(水).抽吸5.beac.breac.bleachbeachn.海滨;湖滨;河滩The little beach hotel has a pleasant ambien breachn.(常与of 连用)违反;不履行;破坏in breach of contractYour company is in breach of the contract. bleach使变白Did you bleach this tablecloth? 英语部分273/1359bead n 珠子, 水珠vt 祈祷6.bride bribebride n 新娘bribe n v t 贿赂boom broom bloomboom n.v 繁华兴旺broom n 扫帚buffet bufferbuffetn.餐具柜, 小卖部, 殴打, 打击vt ①持续地打击②搏斗buffervt 缓冲、缓和C1.censo.censurecensorn.检查员vt.检查, 审查censurev.责难n.责难2.cessio.sessioncessionn.割让, 转让, [律]让与(他人)债权sessionn.(官方机构旳)会议, 会期, 开会期The general session approved the report of the investigation committee.学期;大学旳学期3.clas.crus.crashclashn.冲突, 撞击声, 抵触the clash of weaponsclash of interestsa clash with the policeI failed to go to her wedding because it clashed with my examination.英语部分274/1359战斗It is broadcast that the two armies clashed near the borderline again before dawn. vi., vt.冲突The enemy armies clashed.(事情)在时间上相冲突It's a pity the two concerts clash.(常与with 连用)(色彩)不协调This shirt clashes with your trousers. crushvt., vi.压碎;压坏;碾碎挤压;塞to crush one's way through the crowd破坏;弹压;压服to crush all oppositioncrashn.碰撞, 坠落, 坠毁, 撞击声, 爆裂声v.碰撞, 坠落, 坠毁, (指商业企业, 政府等) 破产, 倒台4.classi.classicalclassicn.杰作, 名著adj.第一流旳classicaladj.古典旳, 正统派旳, 古典文学旳5.clenc.clinchclenchvt., vi.紧合;咬紧(牙关);捏紧(拳头)She clenched her teeth when she was operated on.紧握;抓牢The girl clenched her money in her hand. clinchvt., vi.敲弯钉头钉牢;钉住把(木头)钉牢在一起确定;决定(贸易等);达到买卖或协议The two companies clinched the deal quickly. The offer of more money clinched it for her. She agree to undertake the job as the assistantto the managing director.6.coarse hoarse roar英语部分275/1359coarseadj.粗旳;粗糙旳;未精炼旳(表面)不光滑旳;粗织旳coarse cloth粗鲁旳;鲁莽旳;不礼貌旳coarse talkhoarseadj.嘶哑旳His voice was hoarse after talking for an hour.roarn.吼声;咆哮声the roar of an angry lionThe lion gave a loud roar.7.canvas.canvascanvasn.粗帆布一块油画布The young artist showed me his recent canvases.canvassn.细查, 讨论, 劝诱vt.彻底检查, 细究, 向...拉票或拉生意, 讨论vi.游说, 拉选票8.canno.canoncannonn.加农炮;大炮canonn.教规, 宗教法规9.credibl.credulouscredibleadj.可信旳;可靠旳credulousadj.轻信他人旳10 continual continuouscontinualadj.over and over again; regular but interrupted; 持续旳Recently the young couple have continual arguments with each other for trifles.英语部分276/1359continuousadj.不停旳continuing without stopping ;ceaseless continuous rain all day7.collide colludecollidevi.互撞;碰撞;(车、船等)猛撞The two trains collided.冲突;反对;强烈抵触(with)colludevi.共谋;勾结;串通(with)mendcommentn.注释, 评论, 意见vi.注释, 评论(on )commendvt.夸奖, 表扬, 推荐, 委托, 吸引pe.expe.prope.repelcompelvt.强迫, 迫使expelvt赶走: 驱逐或把…赶出去:expel an invader.排出: 从容器里或象从容器里释放: 被迫离开;把…除名:expelled the student from college for cheating.See Synonyms at eject propelvt.推进, 推进驱策repelvt.击退;逐退to repel an attack使厌恶;使反感His accent repels me.10 contemporary temporary contemporaryn.同步代旳人adj.现代旳, 同步代旳英语部分277/1359temporaryadj.临时旳, 临时旳, 临时性11.contemptuou.contemptible contemptuousadj.(常与of 连用)表达轻蔑旳;傲慢旳a contemptuous lookcontemptibleadj.卑鄙旳It was contemptible of him to speak like thatabout a respectable teacher!It was a contemptible trick to tell lies and play on an old friend!12 confer infer refer prefer defer confervt.授予(称号、学位等)on, 赠与, 把...赠与, 协议v.协商, 互换意见(on)The engineers and technicians are still conferring on the unexpected accident. infervt.推断;推知;推论to infer an unknown fact from a known fact I infer from your letter that you have not made up your mind yet.refervt., vi.(常与to 连用)波及;提到针对;有关The new law does not refer to farm land.提交;交付The shop referred the complaint to the manufacturers.prefervt.(常与to 连用)更喜欢;宁愿to prefer coffee to tWhich of these two dresses do you prefer? defervt.推迟;延期vt.(与to 连用)服从;顺从Do you always defer to your parents wishes?13.consequen.subsequentconsequentadj.作为成果旳subsequentadj.随即旳, 后来旳;继起旳14 conventional convenient conventionaladj.通例旳, 常规旳, 习俗旳, 老式旳convenientadj.便利旳, 以便旳英语部分278/135915.confidan.confidant.confiden.confidential confidantn.知己男友confidanten.知己旳女友confidentadj.确信旳;有信心旳;自信旳Peter is confident of winning the post as the assistant to the managing director. confidentialadj.机密旳;秘密旳a confidential order参与机密旳;视为心腹旳a confidential secretary16.conver.diver.inver.rever.reverse convertvt.(常与into 连用)转变;变换to convert an old house into a new oThat building has been converted into a school.兑换I want to convert some Hong Kong dollars into American dollars.变化信奉、党派或意见等She managed to convert him to her opinion. divertvt.转向;转移A ditch diverted water from the stream into the fields.Traffic was ordered to divert to another road because of the repair of the main road.The government is planning to divert the river to supply water to the town.A loud noise from the street diverted my attention.invertvt.置于相反位置;上下倒置The little boy caught the insect by invertingthe cup over it.revertvi.(与to 连用)恢复原状;答复;回到(本来话题)(财产等)归复, 偿还reversevt.倒退;倒转He reversed the car.翻转She reversed the paper.变化;使成相反旳东西He reversed the judgment and set the prisoner free after all.17 counsel consul councilcounseln.讨论, 商议, 辩护律师英语部分279/1359vt.劝说, 忠告consuln.n.政务会, 理事会, 委员会, 参议会, 讨论会议, 顾问班子, 立法班子18 conscious conscientiousconsciousadj.故意识旳;神志清醒旳He is hurt but still conscious.理解旳;察觉旳She was not conscious of his presence in the room.刻意旳: 故意设计或做旳;刻意旳:a conscious insult; made a conscious effort to speak more clearly。
英语自学记忆单词表Day One1. vt.离弃;抛弃 abandon2. n. 能力;才能 ability3. a.反常的abnormal4. vt.废除; 废止abolish5. a.绝对的;确实的 absolute6. vt. 吸引 absorb7. n. 摘要;抽象 abstract8. a. 丰富的 abundant9. vt.滥用;辱骂;虐待 abuse10. a.学术的 academic11. v.加速;加快 accelerate12. v. 进入;使用 access13. n. 住处 accommodation14. v. 陪伴;伴奏 accompany15. vt. 完成;实现 accomplish16. n. 解释;导致 account17. vi.积聚 accumulate18. a. 精确的 accurate19. a. 习惯的 accustomed20. vt.承认 acknowledge21. n. 活动 activity22. a.极大的;精明的 acute23. a. 能适应的 adaptive24. a.入了迷的 addicted25. vt. 演说;从事 addressDay Two1.vt. 调整,使……适合adjust2. a. 令人钦佩的 admirable3. vt. 承认;准许进入 admit4. n.青少年 adolescent5. vt. 采取;收养 adopt6. vt. 崇拜;非常喜爱 adore7. n. 优势;利益 advantage8. n.&v. 冒险 adventure9. n. 广告 advertisement10. vt. 提倡,主张 advocate11. vt. 影响;感染 affect12. a.买得起的 affordable13. n.代理人;特工 agent14. a. 侵略性的 aggressive15. n.农业;农学 agriculture16. n. 空调系统 air-conditioning17. a. 多才多艺的;全面的 all-round18. n.替代物 alternative19. n.惊讶 amazement20. n. 野心,抱负 ambition21. vt. 分析;分解 analyse22. n. 周年纪念日 anniversary23. vt. 宣布;通知 announce24. a. 使人气恼的 annoying25. n. 禁烟 anti-tobaccoDay Three1. n. 忧虑;渴望 anxiety2. a. 显然的;表面上的 apparent3. v.鼓掌欢迎 applaud4. n. 应用;申请 application5. n. 欣赏 appreciation6. n. 途径 vt.走近approach7. n. 批准;认可 approval8. ad. 大约 approximately9. a. 人造的;虚伪的 artificial10. a. 艺术的 artistic11. vt. 评估;评定 assess12. n. 作业 assignment13. v. 交往;联想 associate14. vt. 承担;假定 assume15. a. 吃惊的 astonished16. n. 气氛atmosphere17. n. 企图 vt. 尝试 attempt18. n.态度attitude19. vt. 吸引;引起attract20. ad.无意识地 automatically21. a.可得到;可利用 available22. n.平均a.平均的 average23. a. 应获奖的 award-winning24. a. 意识到的;知道的aware25. a.笨拙的awkwardDay Four1.n.单身汉;学士 bachelor2. n.细菌 bacterium3. vi. 表现 behave4. n. 利益 vt.有益于 benefit5. n.赐福 blessing6. a. 使人眩目的 blinding7. n. 树枝;分部 branch8. n.突破 breakthrough9. a. 简略的 brief10. a. 灿烂的;杰出的 brilliant11. n.手册 brochure12. n.餐厅 cafeteria13. n. 运动;活动 campaign14. n. 候选人;应试者 candidate15. n.事业;职业;生涯 career16. n. 照料者 caregiver17. n. 门卫;看管人 caretaker18. ad.谨慎地 cautiously19. vt. 庆祝;举行 celebrate20. n.名人 celebrity21. n. 典礼,仪式 ceremony22. n. 证书;执照 certificate23. n.挑战 challenge24. n.慈善机构 charity25. vi. 闲聊 chatDay Five1. n. 情况 circumstance2. vt. 澄清;阐明 clarify3. n. 共同创立者 co-founder4. n.同事;同僚 colleague5. n.结合 combination6. n.喜剧 comedy7. n. 评价 comment8. n. 承诺;保证 commitment9. vi. 传达 communicate10. n. 社区 community11. n. 补偿;报酬 compensation12. vi. 竞争;比赛 compete13. n.能力;胜任 competence14. vt. 抱怨;投诉complain15. ad. 完全地;十分 completely16. a.复杂的 complex17. vt. 构成;写作 compose18. vt. 合成;和解 compound19. a. 义务的;必修的 compulsory20. n.集中 concentration21. n.概念 concept22. n. 结论;结局 conclusion23. v. 谴责,声讨 condemn24. vt. 确认;确定 confirm25. n. 冲突,矛盾 conflictDay Six1. n. 结果;重要性 consequence2. n. 保存;保持 conservation3. n. 考虑;体谅 consideration4. a. 经常的;不变的 constant5. n. 建造;建设 construction6. n.咨询;顾问 consultant7. n.消费者 consumer8. n. 接触,联系 contact9. a.相反的 contrary10. vi. 对比;形成对照 contrast11. vt. 贡献,出力 contribute12. a.方便的 convenient13. vt. 传达;运输 convey14. a.令人信服的 convincing15. n. 精髓;核心 core16. ad.非常认真地 critically17. n. 好奇,珍品 curiosity18. a. 现在的 n.趋势 current19. n. 顾客;消费者 customer20. a. 危险的 dangerous21. n.最后期限 deadline22. a.致命的 deadly23. n.& v. 辩论,争论 debate24. n.十年 decade25. vt. 宣布,声明 declareDay Seven1. n. 下降;衰退 decline2. n.装饰 decoration3. n.&v. 减少 decrease4. vt. 删除 delete5. a.细致优雅的 delicate6. n.高兴 vt.(使)高兴 delight7. n.交货;发送 delivery8. n. 部;系 department9. n. 存款 v.沉淀 deposit10. a.沮丧的 depressed11. n. 后代,晚辈 descendant12. vt. 描述,形容 describe13. v. 应受,应得 deserve14. n. 设计师 designer15. n. 愿望 desire16. a. 绝望的 desperate17. n.绝望 desperation18. n. 轻视;憎恨 despite19. n.目的地 destination20. vt. 破坏;消灭 destroy21. n. 决心 determination22. n. 发展 development23. n.设备 device24. a.数字的 digital25. a. 残废的;有缺陷的 disabled Day Eight1. n.坏处;不利 disadvantage2. n.不合;争论 disagreement3. vi. 消失;失踪 disappear4. n. 失望 disappointment5. n. 灾难 disaster6. a.灾难性的 disastrous7. n.纪律 discipline8. n. 折扣 v.打折 discount9. vt. 使气馁;阻碍 discourage10. n.发现;发现物 discovery11. n.商讨 discussion12. a.令人厌恶的 disgusting13. n.& v. 显示;炫耀 display14. v. 区分;辨别 distinguish15. vt.使分心 distract16. n.分配 distribution17. v. 打扰;妨碍;使不安 disturb18. a.多样化的;不同的 diverse19. n. 文件 document20. n.捐赠 donation21. n. & vt. 下载 download22. n.市区 a.市中心的 downtown23. vt. 拖拉;缓慢而吃力地行进 drag24. a. 尽职的 dutiful25. n. 耳环;耳饰 earringDay Nine1. n.生态;生态学 ecology2. n.教育;教育学 education3. a. 有效率的 efficient4. a. 上了年纪的 elderly5. n. 电力;电流 electricity6. a. 电子的 electronic7. a. 尴尬的;窘迫的 embarrassed8. v.出现 emerge9. n.突发事件 a.应急的 emergency10. a.感人的;情绪化的 emotional11. vt.雇用;使用 employ12. n. 雇员;从业员工 employee13. vt. 使能够,使成为可能 enable14. a.有能力的 capable15. vt. 鼓励,怂恿 encourage16. vi. 扩大;详述 enlarge17. vt.使充实;使丰富 enrich18. n.企业;进取心 enterprise19. n.娱乐 entertainment20. a.热情的 enthusiastic21. a.环境的 environmental22. vt. & n.妒忌;羡慕 envy23. vt. 使相等 equate24. n. 设备;装备 equipment25. n.& v.逃脱;避开 escapeDay Ten1. ad. 特别;尤其especially2. n. 本质;精华 essence3. a.本质的;必要的;重要的essential4. vt. 建立;创办 establish5. n.评价 evaluation6. ad.最终 eventually7. n. 证据,迹象 evidence8. n.&v. 交换;兑换 exchange9. a. 精疲力竭的 exhausted10. n.展览;展览会 exhibition11. n.存在;生存 existence12. n. 膨胀;扩张 expansion13. n.预料; 期望 expectation14. n. 经验; 经历 experience15. n. 实验;试验 experiment16. n. 专门知识;专长 expertise17. n.解释; 说明 explanation18. n.爆炸;激增 explosion19. n. 表达;措辞 expression20. vi.延伸;扩大 extend21. n.延长;伸展 extension22. a.外部的 external23. a. 非凡的 extraordinary24. n. 极端 a.极端的 extreme25. a. 面部的;脸的facialDay Eleven1. n. 设施;设备 facility2. vi. 逐渐消失 fade3. n.失败;失败者 failure4. a.熟悉的 familiar5. a.极好的;难以相信的 fantastic6. a. 迷人的 fascinating7. n. 时尚;时髦人物 fashion8. vt.扎牢;系牢 fasten9. n. 特别喜欢的人/物 favorite10. n. 同事;朋友 fellow11. n.节日 a.节日的 festival12. n.小说;虚构 fiction13. a. 猛烈的 fiercely14. v.计算;认为n.数字;人物 figure15. a.经济的 financial16. n.爆竹;烟火 fireworks17. a. 第一手的 firsthand18. n. 闪光灯 flashlight19. a. 灵活的;易弯曲的 flexible20. n.花圃 flowerbed21. n.焦点;中心 v.集中 focus22. v.跟随;遵循;明白 follow23. vt.不许,禁止 forbid24. n.& vt.预测,预报 forecast25. vt.预见;预知 foreseeDay Twelve1. vt.原谅;宽恕 forgive2. ad.幸运地,幸亏 fortunately3. ad. 频繁地,经常地 frequently4. a.失意的 frustrated5. n. 挫折 frustration6. ad. 根本地 fundamentall7. ad. 猛烈地;狂暴地 furiously8. a. 装配好家具的 furnished9. n. 家具;设备 furniture10. n.画廊;走廊 gallery11. vi.聚集 vt.收集 gather12. n. 一代;产生 generation13. n. 慷慨 generosity14. a.有天赋的;有才华的 gifted15. a. 全球的;全局的 global16. vt.加荣耀于;赞美 glorify17. n.荣誉 glory18. n.政府;管理 government19. a. 优雅的;有风度的 graceful20. ad.逐渐地 gradually21. n.毕业;刻度 graduation22. a. 脚踏实地的 grounded23. vt. & n. 保证 guarantee24. n. 指导方针 guideline25. ad. 内疚的;有罪的 guiltilyDay Thirteen1. vt.处理;拿 n.柄;把手 handle2. a.英俊的;可观的 handsome3. a.方便的;手巧的 handy4. n.艰难;困苦 hardship5. n. 和谐 harmony6. n.& v.收获;收割 harvest7. n. 憎恨 hatred8. n.新闻提要;头条新闻 headline9. vi.犹豫 hesitate10. a. 潜藏的 hidden11. n. 历史学家 historian12. vi. 拥抱 hug13. a. 谦逊的 humble14. n.飓风 hurricane15. n.氢 hydrogen16. vt. 识别 identify17. vt. 忽视 ignore18. ad. 非法地 illegally19. vt.想象;料想 imagine20. n.移民 immigration21. n.印象;感觉 impression22. v.改进;改善;变得更好 improve23. a.难达到的 inaccessible24. a.不活跃的 inactive25. a.无能力的 incapableDay Fourteen1. n.不便 inconvenience2. ad.渐多地 increasingly3. a. 难以置信的;惊人的 incredible4. n.独立;自主 independence5. v.指示;显示;表明 indicate6. n.迹象;指示 indication7. n. 个人 a.个人的 individual8. n.工业;厂业;企业 industry9. n.& vt.影响 influence10. a.天真的;无辜的;无害的 innocent11. a. 不真诚的 insincere12. n. 鼓舞;灵感 inspiration13. n. 机构;制定;名流 institution14. n.指令;教诲;说明 instruction15. n.保险;保险费 insurance16. n.智力;情报 intelligence17. a. 强烈的,非常的 intense18. n.界面;接口 interface19. a. 国际的;世界的 international20. vt. 中断;打断;插嘴 interrupt21. a. 州际的 interstate22. vt. 采访 interview23. a. 开端的 introductory24. n.发明;发明物 invention25. vt. 投资 investDay Fifteen1. n.邀请;引诱 invitation2. a. 诱人的 inviting3. vt. 包含;牵涉;潜心于 involve4. a. 无责任感 irresponsibility5. n. 议题;要讨论的问题 issue6. n.知识;了解 knowledge7. n.垃圾填埋地 landfill8. n.洗衣店;洗好或待洗的衣 laundry9. vi.减轻 lessen10. n.图书管理员 librarian11. n.文学 literature12. n.多数;大多数 majority13. v.管理;设法对付 manage14. a. 巨大的;大规模的 massive15. n.材料;原料 material16. n.最大值 a.最大的 maximum17. a. 有意义的 meaningful18. ad. 在此期间;与此同时 meanwhile19. n.尺度;测量 measurement20. n. 会员资格卡 membership21. n.记忆;记忆力 memory22. a. 精神上的 mentally23. n.商人 merchant24. a.留心的 mindful25. n.矿物;矿石 mineralDay Sixteen1. a. 最少的 minimum2. a.微不足道的 minor3. n.少数;少数民族 minority4. a. 可怜的 miserable5. n. 不幸 misfortune6. vt. 虐待 mistreat7. vt. 误用 misuse8. a. 可移动的;易变的 mobile9. a. 钱的;财政的 monetary10. n. 心情 mood11. vt.激励;激发 motivate12. n.动机;动力 motivation13. a.多山的;巨大的 mountainous14. vi.繁殖 multiply15. vt. 使多任务化 multitask16. n.蘑菇 vi.迅速成长 mushroom17. a. 神秘的;不可思议的 mysterious18. ad. 自然地 naturally19. a. 必要的 necessary20. n. & vt. 疏忽;忽略 neglect21. v. 协商;谈判 negotiate22. ad. 紧张地 nervously23. n. 网络 network24. n. 营养物 nutrient25. n.职业;占有 occupationDay Seventeen1. n. 犯罪;违反 offence2. vt. 经营;管理 operate3. n. 机遇 opportunity4. a. 对面的;相反的 opposite5. n. 乐观;乐观主义 optimism6. n. 组织;团体 organization7. a. 原始的;最初的 n.原件 original8. n. & vi. 发作;爆发 outbreak9. n. 结果 outcome10. v. 数量上超过 outnumber11. vt. 使相形见绌;胜过 outshine12. ad. 表面地 outwardly13. a. 全部的 overall14. vt. 克服 overcome15. a. 过分拥挤 over-crowding16. vt. 忽视 overlook17. ad. 部分地 partially18. ad. 特别地;详细地 particularly19. n. 激情 passion20. n. 行人;步行者 pedestrian21. ad. 永久地 permanently22. n. 允许;许可 permission23. a. 个人的;亲自的 personal24. n. 现象 phenomenon25. n. 人生观哲学 philosophyDay Eighteen1. n. 摄影师 photographer2. n.扒窃 pickpocket3. n. 平台;站台 platform4. n. 普及;流行 popularity5. vt. 居住于;移民于 populate6. a. 轻便的 portable7. a. 积极的;肯定的 positive8. vt. 控制;使掌握 possess9. n. 可能性 possibility10. vi. 延迟 postpone11. n. 潜力 potential12. n. 贫困 poverty13. a. 粉状的 powdered14. a. 实际的;实用的 practical15. vt. 预言 predict16. n.学龄前儿童 preschooler17. vt. 提出;呈现 a. 现在的 present18. n. 介绍 presentation19. n. 新闻舆论 press20. n. 压力;压迫 pressure21. n. 以前的 previous22. a. 初级的 primary23. a. 原始的 primitive24. n. 过程 vt. 处理;加工process25. n. 生产;产品productionDay Nineteen1. a. 多产的 productive2. n.专业人员 professional3. a.盈利的 profitable4. ad. 渐进地 progressively5. vt. 促进;提升 promote6. n. 出版 publication7. n. 宣传;公开;注意 publicity8. vt. 购买 purchase9. vt. 净化 purify10. n. (热带)雨林 rainforest11. n. 暴风雨 rainstorm12. ad. 很少地;罕见地 rarely13. n. 反应 reaction14. a.现实的 realistic15. n. 公认 recognition16. vt. 认出;识别 recognize17. vt. 推荐;介绍 recommend18. n. 重建 reconstruction19. vt. 恢复;弥补 recover20. vt. 使……重新使用 recycle21. v. 再利用;循环 redirect22. vt. 反映 reflect23. n. 注册;登记 registration24. ad. 有规律的 regularly25. a. 可信赖的 reliableDay Twenty1. a. 剩下的 remaining2. a. 不平常的 remarkable3. ad. 远程地 remotely4. v. 更新 renew5. n. 代表 representative6. n. 保留;储备 reserve7. n.居民 resident8. vt.解决;决心;溶解 resolve9. vi. 求助 n. 度假胜地 resort10. n.资源 resource11. vi. 回答;做出回应 respond12. a. 有责任的 responsible13. n. 餐馆 restaurant14. n. 坐立不安 restlessness15. n. 限制 restriction16. n.退休 retirement17. vt. 显示;透露;泄露 reveal18. a.荒谬的;可笑的 ridiculous19. a. 腐烂的 rotten20. a. 来回的;双程的 round-trip21. a.神圣的 sacred22. n.扫描仪 scanner23. a.稀少的 scarce24. n. 风景 scenery25. a.奖学金 scholarshipDay Twenty One1. vt. 尖叫;哭闹 scream2. n. 秘书 secretary3. n.安全感 security4. a. 有选择性的 selective5. n.自我意识 self-awareness6. n. 自我形象 self-image7. n. 自尊 self-respect8. n. 研讨会 seminar9. n. 感觉,轰动 sensation10. n.情感;识别力 sensibility11. ad. 明智地;明显地 sensibly12. a. 敏感的 sensitive13. a. 各自的 separate14. s n.系列;序列 serie15. ad. 急剧地 sharply16. n. 害羞 shyness17. n. 署名;信号 signature18. a. 重大的;有意义的 significant19. n.真诚 sincerity20. a.纯真的 single-minded21. n. 形势;处境 situation22. ad. 稍微,轻微地 slightly23. 某某人 so-and-so24. n. 软件 software25. n. 解决措施 solutionDay Twenty Two1. n. 来源 source2. vt. 使专门化 specialize3. vt.喷射 spray4. vi. 跳跃n. 春天;弹簧 spring5. a. 铭刻的 stamped6. a. 政治家 statesmen7. vt. 伸展 stretch8. a. 引人注目的 striking9. n. 替代品 substitute10. a.充足的 sufficient11. a. 超容易的 super-easy12. n. 手术 surgery13. ad. 惊人地 surprisingly14. a. 周围的 n. 环境 surrounding15. n. 生存;幸存者 survival16. a. 可持续的 sustainable17. a. 肿的 swollen18. a. 表示同情的 sympathetic19. n. 症状 symptom20. n. 技术;工艺 technology21. n. 温度 temperature22. a. 暂时的 n. 临时工 temporary23. n. 趋势 tendency24. a. 忘恩的 thankless25. ad. 完全地 thoroughlyDay Twenty Three1. vt. 容忍;宽恕 tolerate2. n. 悲剧 tragedy3. a. 横贯大陆的 transcontinental4. n.传送 transmission5. n. 运输 transport6. n. 财富 treasure7. a. 颤抖的 trembling8. n. 选拔赛 tryout9. vt. 拧;扭曲 twist10. a. 典型的 typical11. a. 没有魅力的 unattractive12. a. 不可避免的 unavoidable13. a. 难以置信的 unbelievable14. a. 无法改变的 unchangeable15. a. 不文明的 uncivilized16. ad.不舒服地 uncomfortably17. a. 失去知觉的 unconscious18. vt. 低估 under-evaluate19. a. 较一般人矮小的 undersize20. a. 失业的 unemployed21. a. 意外的 unexpected22. ad. 不幸地 unfortunately23. a. 不间断的 uninterrupted24. a. 独特的,稀罕的 unique25. n. 一般概念;普通性 universal Day Twenty Four1. a. 明显的 unmistakable2. a. 不必要的 unnecessary3. a. 没有计划的 unplanned4. n.不安 unrest5. a. 未刮脸的 unshaven6. a. 不表同情的 unsympathetic7. a.未洗的;不清洁的 unwashed8. a.贵重的;有价值的 valuable9. n.受害者 victim10. a.虚拟的 virtual11. a.看得见的 visible12. a.生动的vivid13. ad. 自动地;自发地 voluntarily14. a. 普遍的 widespread15. n. 荒地;大量wilderness16. a. 双赢的;互利互惠的win-win17. n.智慧 wisdom18. n. 工作量 workload19. n. 世界观 worldview20. a.全世界范围的 worldwide21. a. 穿破了的;疲惫不堪的 worn-out22. n.皱纹 v.(使)起皱纹 wrinkle23. v.收回;撤消;撤退 withdraw24. a.值得(做)的 worthwhile25. vi.急速移动;猛涨 zoom。
英语考研2024真题答案### English Postgraduate Entrance Examination 2024: Sample Answers#### Part I: Reading Comprehension (40 points)Passage 1: The Impact of Technology on EducationThe article discusses the profound influence of technology on modern education. It highlights how digital tools have revolutionized teaching methods, making learning more interactive and personalized. The integration of AI in classrooms has allowed for the creation of adaptive learning environments that cater to the needs of individual students. Moreover, the use of online platforms has expanded access to education, breaking down geographical barriers and providing opportunities for lifelong learning.Questions:1. What is the primary focus of the article?- The primary focus is the impact of technology on the field of education.2. How has AI been utilized in classrooms?- AI has been used to create adaptive learning environments tailored to individual students' needs.3. What benefits does online education offer?- Online education offers expanded access, overcoming geographical limitations and promoting lifelong learningopportunities.Passage 2: Climate Change and Its Effects on BiodiversityThis passage examines the alarming effects of climate change on global biodiversity. It underscores the rapid loss of species due to habitat destruction and altered ecosystems. The text also discusses the potential for climate change to exacerbate existing threats to biodiversity, such as overfishing and deforestation. The urgency for global action to mitigate these effects is emphasized, with the need for sustainable practices and conservation efforts.Questions:1. What is the main concern of the passage?- The main concern is the impact of climate change on biodiversity and the rapid loss of species.2. Which factors contribute to the threats to biodiversity mentioned in the passage?- Factors include habitat destruction, altered ecosystems, overfishing, and deforestation.3. What solutions does the passage suggest?- The passage suggests global action, sustainable practices, and conservation efforts as solutions.#### Part II: Cloze Test (20 points)In the cloze test section, candidates are required to fill in the blanks with the most appropriate word from the given options to ensure the passage makes sense both contextually and grammatically. This section tests the ability tounderstand context and the correct usage of vocabulary.#### Part III: Translation (20 points)English to Chinese:Translate the following sentence into Chinese, ensuring accuracy and fluency.- "The rapid development of urbanization has led to a series of environmental issues."Chinese to English:Translate the following sentence into English, maintaining the original meaning and ensuring natural language flow.- "随着科技的不断进步,我们的生活变得越来越便利。
北京市八一学校2024-2025学年高一上学期10月月考英语试题一、完形填空Last year I decided to do some voluntary work. I began to research on the Internet and discovered Volunteer USA. Three months later, I 1 myself on a plane to Phoenix, Arizona. I was 2 at the thought of living with loads of new people for three months. However, within fifteen minutes of arriving, my worries had gone. Everyone was so friendly and like-minded that it was very easy to feel at home.I was sent to the Coronado National Forest for my first 8-day 3 . We had to carry everything we needed and walk three miles to where we worked. It may not seem like a 4 way, but in 35℃ heat and with a heavy pack, my legs were on fire.My job was to 5 a stairway out of rock. This 6 climbing up and down the side of a mountain inhabited (栖息) by mountain lions, although I should say they were only heard, never seen.Three days later, a beautiful stairway came into being. The 7 of knowing that my work will be on that mountainside for years to come is massive.But on the last night we were caught in a thunderstorm. I woke up at midnight to find a swimming pool in my tent. The temperature was close to 8 . I had to spend the rest of the night trembling in the only dry part of my tent.Needless to say, I suffered a lot. But I know whatever I have to face in my life. I was there and I 9 . I think I am much 10 for having taken part in the project.1.A.imagined B.found C.enjoyed D.introduced 2.A.annoyed B.surprised C.nervous D.excited 3.A.project B.tour C.campaign D.course 4.A.nice B.safe C.long D.quick 5.A.build B.test C.clean D.guard 6.A.helped B.meant C.allowed D.ended 7.A.satisfaction B.ambition C.expectation D.intention 8.A.boiling B.average C.normal D.freezing9.A.recovered B.resisted C.escaped D.survived 10.A.smarter B.stronger C.happier D.busier二、其他请写出下列句子的句子基本类型以及划线部分的句子成分。
ALCAZARWelcome to the grand life.For those with a passion for the refined things in life and those who want to explore for themselves, presenting to you the new Hyundai ALCAZAR.For those who dare to be different, who want finer experiences and never compromise on quality, the Hyundai ALCAZAR ushers in a new dimension of driving sophistication. Drawing its inspiration from the royal lineage of castles and palaces, denoting grandeur, spaciousness, and solidity, this SUV has been crafted as the SUV of choice for the visionaries and leaders of tomorrow. A true testament to its regal inspiration, the Hyundai ALCAZAR stands tall as the embodiment of premiumness.Tough, yet graceful. Dominating, yet elegant. Hyundai ALCAZAR pairs a bold and tall stance with the elegant design that is unmistakably premium. A haven of refinement, where aesthetic design meets supreme craftsmanship. For people with an exquisite palate, equipped with features that add a sophisticated touch to the bold and solid exterior.The Hyundai ALCAZAR features contemporary trio beam LED headlamps and tail lamp design flowing into the lines of the body. The superior poise of the stylish chrome radiator grille and the expertly styled twin tip exhaust adds a sense of grace to the Hyundai ALCAZAR’s effortless stature.Elegance from every angle.Other features: LED positioning lamps I Crescent glow LED DRLs I Trio beam LED headlamps Dark chrome exterior signature cascading grille I LED fog lampsOther features: Large day light opening (DLO) area I Side foot step (1st in segment)Shark fin antennaHoney-comb inspired LED tail lamps Puddle lamps with Hyundai logoprojectionTwin tip exhaustDark chrome exterior finish outsidedoor handlesR18 (D=462 mm) Diamond cut alloysThe interior of the Hyundai ALCAZAR immerses you in uncluttered design. Complete with premium dual tone cognac brown interiors, the 64 colours ambient lighting offers a regal touch to the cabin. Carefully selected materials accentuate the aesthetic, complete with Hyundai ALCAZAR’s advanced technology, ensuring that your entertainment knows no bounds. Experience serenity thanks to a voice controlled panoramic sunroof and an auto healthy air purifier. The tranquil sanctuary is also outfitted with an HD touchscreen system with powerful Bose premium sound system, immersing you in a richand balanced premium audio experience.Premium dual tone cognac brown interiors Panoramic sunroof26.03 cm (10.25”) HD touchscreen system Auto healthy air purifier with AQI displayBose premium sound system (8 speakers)26.03 cm (10.25”) Multi display digitalcluster with personalized themesExtravagant comfort. Plush ride.Leather pack: Perforated D-cut steering wheel I Perforated gear knob I Cognac brown and black seat upholstery IDoor armrest Power driver seat – 8 wayInside the Hyundai ALCAZAR, you always travel first class. For short jaunts or epic getaways, envelope yourself in sublime comfort with immersive front row ventilated seats. Extravagantly comfortable captain seats in the second row (6 seater) complete with the versatility to tip, tumble, slide and recline let you sit back in pure comfort. Relax, lean back and unwind in the tranquility of the Hyundai ALCAZAR.Adore your private palatial retreat on wheels wherever the journey takes you.Fluidly adapts to your needs.Multiple seating designsFront row sliding sunvisor 4 USB chargers for 3 rowsFront row seatback table with retractable cup-holder and IT device holder2nd row - one touch tip tumble captain & split seats3rd row AC vents with speed control (3-stage)2nd row headrest cushion1st & 2nd row smartphone wireless charger2nd row captain seats with premium console armrestEach element of the Hyundai ALCAZAR has been designed to provide excellence, in comfort and in safety. Complete with highly accurate front & rear parking sensors and state-of-the-art security alerts like speed alert system, you’re always one step ahead of unexpected events on the road. Each journey in the Hyundai ALCAZAR inspires awe and admiration as it carries passengers in uncompromised safety.A new paradigm in safety.Other features: Emergency stop signal I Speed alert system I Speed sensing auto door lock I Driver rear view monitor Impact sensing auto door unlock I Child seat anchor (ISOFIX) IElectric parking brake with auto holdStrong body structure with AHSSWith ESCWithout ESCParking assist: Front and rear parking sensors6 Airbags Hill start assist control (HAC)Rear disc brakes Tyre pressure monitoring system (Highline)Surround view monitor (SVM)Electronic stability control (ESC)Vehicle stability managment (VSM)Blind view monitor (BVM)Other features: Cruise control I Paddle shifters (1st in segment)Desert sands. Mountain slopes. Rugged river valleys. No frontier is out of bounds for the Hyundai ALCAZAR. The power to control your drive is at your fingertips. Equipped with powerful petrol or diesel engines that give you the perfect balance between performance and efficiency, the Hyundai ALCAZAR conquers every landscape with effortless ease. Whether you’re taking to the road or exploring out into the unknown you’ll always have a great drive.Conquer any horizon.Max torque191 Nm (19.5 kgm) / 4 500 r/min2.0 l petrol MPi engine1.5 l diesel CRDi engine6-speed manual & automatic transmission options available for both petrol & diesel engines.Max power117 kW (159 PS) / 6 500 r/minMax torque 250 Nm (25.5 kgm) / 1 500-2 750 r/minMax power84.6 kW (115 PS) / 4 000 r/minWe’ve created technology to serve you and make your life easier, intuitively and simply. Stay seamlessly connected with your Hyundai ALCAZAR and the world, with Bluelink. The Hyundai ALCAZAR offers outstanding capability on and off the road. Choose between driving modes for everyday driving or traction modes for any terrain you need to conquer.Technology that takes you further.Drive mode select Traction control modesAdvanced Bluelink with OTA map updatesOther features: Welcome greetings I Voice recognition commands (I want to see the sky / What’s the Indian cricket score? / When is the soccer match?) I Bluelink integrated smartwatch appwith 60+ features and OTA map updatesKey featuresTechnical specificationsDimensionsOverall length (mm) 4 500 Overall width (mm) 1 790 Overall height (mm) 1 675^^ Wheelbase (mm) 2 760 Fuel tank capacity (l) 50EngineConfiguration 4 Cylinders,16 Valves4 Cylinders, 16 ValvesCam typeDOHCDisplacement (cm ) 1 9991 493Fuel system Multi-point injection (MPi) Common rail direct injection (CRDi)Max power 117 kW (159 PS) / 6 500 r/min84.6 kW (115 PS) / 4 000 r/minMax torque 191 Nm (19.5 kgm) / 4 500 r/min 250 Nm (25.5 kgm) / 1 500-2 750 r/minTransmission6-speed manual 6-speed manual Type 6-speed automatic6-speed automaticSuspensionFront McPherson strut with coil spring Rear Coupled torsion beam axle (CTBA) Brakes Front Disc RearDiscTyre 215/60 R17 (D=436.6 mm) alloy (prestige executive)Size 215/55 R18 (D=462 mm) alloy (platinum, signature)Spare wheel215/60 R17 (D=436.6 mm) steel (all trims)Engine & trim plan 2.0 l petrol 6 seater - - - ● ● ●MPi engine 7 seater ● - ● ● - ●1.5 l diesel 6 seater ● - - ● ● ●CRDi engine 7 seater ● ● ● ● - ●SafetyRear disc brakes S S S S S S ABS with EBD S S S S S S Electronic stability control (ESC) S S S S S S Vehicle stability management (VSM) S S S S S S Hill start assist control (HAC) S S S S S S Automatic headlamps S S S S S S LED fog lamps S S S S S S Tyre Pressure Monitoring System S S S S S S Electro chromic mirror (ECM) - - S S S S Emergency stop signal (ESS) S S S S S S Speed alert system S S S S S SStandard safety Speed sensing auto door lock S S S S S SLane change indicator flash adjustment S S S S S S Rear defogger with timer S S S S S S Driver rear view monitor S S S S S S Rear parking sensors S S S S S S Rear camera with steering adaptiveS S S S S S parking guidelinesDriver & passenger seatbelt reminder S S S S S S Front seat belts with pretensioner S S S S S S Impact sensing auto door unlock S S S S S S Child seat anchor (ISOFIX) S S S S S S Driver & passenger airbags S S S S S S Burglar alarm - - S S S SFront parking sensors - - - - S S Side & curtain airbags - - S S S S Surround view monitor (SVM) - - S S S S Blind view monitor (BVM) - - S S S S Height adjustable front seatbelts - driver & passenger - - S S S S Exterior Trio beam LED headlamps S S S S S S LED positioning lamps S S S S S S Crescent glow LED DRLs S S S S S S Honey-comb inspired LED tail lamps S S S S S S Puddle lamps with Hyundai logo projection - - S S S S LED turn indicators on outside mirrors S S S S S SSignature cascading grille S S S S S SDark chrome Fog lamp garnish S S S S S S exterior finish Outside door handles - - S S S STailgate garnish S S S S S SBody colour dual tone bumpers S S S S S S Front & rear skid plate S S S S S SORVMBody colour S S S S S SBlack - - - - Dual Tone Dual ToneA-Pillar piano black finish S S S S S S B-Pillar black-out tape^ S S S S S S C-Pillar garnish piano black finish S S S S S S Integrated Silver S S S S S S roof rails Matte Black - - - - Dual Tone Dual Tone Shark fin Body colour S S S S S S antenna Black - 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ADORE: Adaptive Object Recognition1Bruce A. Draper, Jose Bins, Kyungim BaekDepartment of Computer ScienceColorado State UniversityFort Collins, CO, USA. 80523(draper|bins|baek)@Abstract. Many modern computer vision systems are built by chainingtogether standard vision procedures, often in graphical programmingenvironments such as Khoros, CVIPtools or IUE. Typically, these proceduresare selected and sequenced based on a programmer’s intuition rather than soundscientific principles. This paper presents a theoretically sound method forconstructing object recognition strategies by modeling object recognition as aMarkov Decision Problem (MDP). The result is a system called ADORE(Ad aptive O bject Re cognition) that automatically learns object recognitionstrategies from training data. Experimental results are presented in whichADORE is trained to recognize five types of houses in aerial images, and whereits performance can be (and is) compared to optimal.1 IntroductionAs the field of computer vision matures, fewer and fewer vision systems are built “from scratch”. Instead, computer vision systems are built by sequencing together standard vision procedures, including (but by no means limited to): image smoothing and enhancement, edge and corner extraction, region segmentation, straight line and curve extraction, grouping, symbolic model matching (including Hausdorf matching, key feature matching, and heuristic search), appearance matching, pose determination, and depth from stereo, motion or focus. Separately, each of these procedures address part of the computer vision problem. Together, they form end-to-end vision systems that perform specific tasks.Computer vision software environments help application programmers build end-to-end systems by providing libraries of image processing and/or computer vision procedures; often, they also provide a visual programming language and GUI for chaining these procedures together. In Khoros, for example, programmers build applications by selecting procedures (called “glyphs”) from menus and graphically connecting the output of one procedure to the input of another [27]. CVIPtools is a similar software environment intended primarily for academic use [33]. The Image Understanding Environment (IUE) is primarily an object-oriented software library, but also includes a GUI for sequencing procedures [23]. (The IUE is still under 1 This work was supported by DARPA through the U.S. Army TEC under contract DACA76-97-K-0006development at the time of writing, but a preliminary version is available from /AAI/IUE/IUE.html.)Software tools such as Khoros, CVIPtools and IUE make it easier for programmers to form and test sequences of vision procedures. Unfortunately, they do not help programmers select procedures for specific tasks, or compare one control strategy to another. Programmers are left to choose vision procedures based on intuition, and to refine sequences of procedures by trial and error.The goal of the Adaptive Object Recognition (ADORE) project is to provide a theoretically sound mechanism for dynamically selecting vision procedures for specific tasks based on the current state of the interpretation. In the future, we hope to build systems that can adapt to any recognition task by dynamically selecting actions from among dozens (if not hundreds) of vision procedures. At the moment, however, this ambitious goal exceeds our grasp. This paper describes an initial prototype of ADORE that learns to find houses in aerial images using a library of ten vision procedures. The result is a prototype end-to-end object recognition system that dynamically selects vision procedures based on a Markov decision process (MDP) model. This paper describes two experiments with the prototype of ADORE – one in which ADORE succeeds in finding a nearly optimal recognition strategy, and one where it is less successful.2 Examples of Static and Dynamic ControlBefore describing ADORE in detail, let us first illustrate the problem it will be asked to solve. Figure 1 shows a nadir-view aerial image. The task is to find instances of specific styles of houses, such as the duplex in Figure 2, using a library of ten general-purpose vision procedures. (Descriptions of all ten procedures can be found in Section 5.2.) To adapt to the task, ADORE is given access to training images; each training image comes with a training signal that gives the positions and orientations of duplexes in the training image. ADORE’s role is to dynamically select and execute procedures so as to produce duplex (and only duplex) hypotheses.ADORE recognizes objects (in this case, duplexes) by iteratively selecting and executing vision procedures. For example, ADORE might begin by selecting to apply a rotation-free correlation procedure [28] to extract regions of interest from the image. Alternatively, it might apply a statistical distribution test [25] or a probing routine for the same purpose. All three procedures generate object hypotheses, but ADORE learns from the training data that for this task – where the duplexes are almost identical to each other, and lighting differences and perspective effects are minimal –pixel-level correlation outperforms the other two procedures. ADORE therefore chooses to begin with the rotation-free correlation procedure.The next step is more complex. Figure 3 shows three ROIs produced by correlation. The ROI on the left of Figure 3 matches the position and orientation of a duplex very well. In fact, none of the ten procedures in current procedure library can improve this hypothesis, so the best strategy for ADORE is to accept it. The ROI on the right in Figure 3, on the other hand, does not correspond to a duplex. The best strategy is therefore to reject it.Fig. 1: A nadir-view image of a residential section of Ft. Hood, TX The ROI in the middle of Figure 3, on the other hand, is more interesting. This ROI roughly matches a duplex, but the ROI is below and slightly rotated from the true position of the duplex. In this case, the best strategy is to refine the hypothesis by resegmenting the image chip [10] and applying a Generalized Hough Transform [5] to align the extracted region boundary with the object template. Figure 4 shows the resulting hypothesis after these two procedures are applied.Fig. 2. A DuplexExamples like the one in Figure 3 demonstrate the importance of dynamic control. In all three cases, the first procedure was the same: correlation. The choice of the next procedure, however, depended on the quality of the data (in this case, ROI) produced by the previous step. In general, control strategies should choose procedures based not only on static properties of the object class and image domain, but also on properties of the data produced by previous procedures.3 Related WorkLong before the appearance of software support tools like Khoros, researchers argued for specialized recognition strategies built from reusable low-level components. As far back as the 1970s, Arbib argued from psychological evidence for specializedvisual “schemas” built from reusable procedures [4]. In the 1980’s, Ullman developed a similar theory, in which primitive “visual routines” are combined to form specialized recognition strategies [32]. Later, Aloimonos [2] and Ikeuchi & Hebert [16] argued for specialized recognition strategies made from primitive vision operations in the context of visual robotics.Fig. 3. A demonstration of dynamic control: the three ROIs above were all created by rotation-free correlation, yet the best strategy for refining these hypotheses depends on the quality of the ROIs, not the history of how they were created. In this case, the best strategy is to 1) accept the ROI on the left, 2) reject the ROI to the right, and 3) refine the ROI in the middle through segmentation [10] followed by the Generalized Hough Transform [5].In practice, researchers have been building systems with special-purpose recognition strategies for twenty years. In the late ‘70s and early ‘80s, researchers built AI-style production and blackboard systems to select and sequence vision procedures for specific tasks. Nagao & Matsuyama’s production system for aerial image interpretation [24] was one of the first, and lead to several long-term development efforts, including SPAM [22], VISIONS/SCHEMA [11], SIGMA [15], PSEIKI [3] and OCAPI [9]. More recently, other researchers [8,17,19] have applied AI-style planning technology to infer control decisions from databases describing the task and the available procedures.Fig. 4. The middle ROI from Figure 3 after refinement via segmentation [10] and theGeneralized Hough Transform [5].Unfortunately, knowledge-based systems were often ad-hoc. Researchers formulated rules for selecting procedures based on their intuition, and refined these rules through trial and error. (See [12] for a description of the knowledge engineering process in object recognition.) As a result, there is no reason to believe that thecontrol policies emerging from these heuristics were optimal or even good, nor was there any way to directly compare systems or evaluate their control policies.Recently, researchers have tried to put the control of object recognition on a stronger theoretical foundation using Bayes nets (e.g. TEA1 [29] and SUCCESSOR [21]). Unfortunately, the design of Bayes nets can itself become an ad-hoc knowledge engineering process. Other researchers try to eliminate the knowledge acquisition bottleneck by learning control policies from examples. Researchers at Honeywell use genetic algorithms to learn target recognition strategies [1], while reinforcement learning has been used by Draper to learn control strategies [13] and by Peng & Bhanu to learn parameters for vision procedures [26]. Maloof et. al. train classifiers to accept or reject data instances between steps of a static sequence of procedures [20].4 Object Recognition as a Supervised Learning TaskThe goal of the adaptive object recognition (ADORE) project is to avoid knowledge engineering by approaching object recognition as a supervised learning task. Developers train ADORE to recognize a specific object by providing training images and training signals, where a training signal gives the desired output for a training image. ADORE learns control strategies that recreate the training signal as closely as possible. These control strategies can then be used to hypothesize new object instances in novel images.ADORE learns control strategies by modeling object recognition as a Markov decision process. In general, a Markov decision problem is defined in terms of a set of states, a set of actions, and a control policy that maps states onto actions. In this case, the state of the system is determined by data tokens produced by vision procedures. For example, the state of the system might be a region of interest (ROI), a set of 2D line segments, or a 2D contour. The actions are vision procedures, such as correlation and the Generalized Hough Transform. Actions change the state of the system by producing new data tokens from the current data tokens. A control strategy (or control policy) is a function that maps states onto actions. In the context of ADORE, control policies map data tokens onto vision procedures, thereby selecting the next action in the recognition process.At the software level, ADORE is divided into two distinct components: an off-line learning system that learns object-specific recognition strategies from training images, and a run-time execution monitor that implements these control strategies by iteratively applying vision procedures to data. Since the goal of the learning process is to develop a control strategy that maximizes the performance of the execution monitor, we will describe the run-time execution monitor first and the learning system second.4.1 The Execution MonitorThe run-time execution monitor is a three-step loop that implements dynamic control policies. On each cycle, the execution monitor:1.Measures properties of the current data, producing a feature vector. The length andcontents of this feature vector depend on the type of the data; for example, the features describing an image (average intensity, entropy, etc.) are different from those describing a 2D contour (length, curvature, contrast).2.Selects a vision procedure. This selection is made according to the control policy,which is a function mapping feature vectors onto vision procedures (see Section4.2 below).3.Applies the selected procedure to the current data, thereby producing new data. Ifthe selected procedure is one of the special procedures accept() or reject(), then the procedure will not return a new data token and the loop terminates. (Accept() presents the hypothesis to the user as an object instance; reject() does not, and is a mechanism for discarding incorrect hypotheses.)The loop begins when an image is presented to the system as the initial data; the monitor then executes the loop above until the accept() or reject() procedure fails to return any data, at which point the recognition process stops.Of course, this simple description glosses over some important details. The most important is that many vision procedures return multiple outputs. For example, the peak detection procedure (see Section 5.1) may detect several peaks in a likelihood image corresponding to possible hypotheses. Similarly, other detection, matching and grouping routines may return multiple hypotheses. When this happens, we assume that the outputs hypothesize unique instances of the target object class, and fork as many new instances of the execution monitor as are needed to pursue these hypotheses.In terms of software, the execution monitor is independent of the vision procedure library. Each vision procedure is an independent unix executable; a library file tells the execution monitor the number and type of input arguments for each procedure, the number and type of output arguments, and the unix pathname. The design goal is to allow vision procedures to be added or removed from the system by simply editing the library file. Similarly, the execution monitor is independent of particular data representations, since all data tokens are kept in files. For each data type, the library file tells the execution monitor 1) the name of the data type (so the monitor can match data tokens with arguments to vision procedures); 2) the length of the feature vector; and 3) the path of the unix executable for measuring features. Thus new data types, like new vision procedures, can easily be added to the system.4.2 Control PoliciesControl strategies are represented by policies that select vision procedures based on data feature vectors. Since good control strategies depend on the target object class and image domain, a different strategy is learned for every object recognition task.To learn theoretically justifiable control strategies, object recognition is modeled as a Markov Decision Problem (MDP). Although a general introduction to MDPs is beyond the scope of this article, they are structurally similar to finite state machines. The system begins in some state s1 and applies an action a1, thereby creating atransition to a new state s2. This process repeats itself, creating a series of states andactions, s1, a1, s2, a2, s3,…. Unlike a finite state machine, however, the state transitionsin an MDP are probabilistic; when an action a i is applied in state s n, the resulting stateis selected from a probability distribution associated with the state/action pair <s n,a i>. Because every state/action pair has a different probability distribution, the system selects which action to apply at every state. This selection is made by a controlpolicy, which is a mapping of states onto actions. Finally, every state transition has a reward (a.k.a. penalty) associated with it. The goal in a Markov decision problem is to find the control policy that maximizes the expected reward over time.In ADORE, object recognition is cast as a Markov decision problem by equatingactions with computer vision procedures (e.g. correlation, hough transform). Theseprocedures produce and consume data tokens such as images, regions and line groups.The state of the system is determined by a feature vector that describes the currentdata token. Vision procedures are modeled as probabilistic because even though weknow the type of data they produce – for example, edge detection procedures createedges -- we do not know in advance what feature values that resulting data will have.The rewards associated with state transitions are determined by task-specificreward functions. When the user’s goal is to optimize recognition rates regardless of cost, the reward associated with every procedure other than accept() is zero. When the system invokes accept(), it signals that it has found an instance of the object class, and it is rewarded (or penalized) according to how well that hypothesis matches thetraining signal. (The error function used to compare hypotheses to the training signalis also task-specific; for the duplex example, we use the percent of overlap betweenthe hypothesis and the ground truth.) If the goal is to optimize a cost/quality tradeoff, every procedure other than accept and reject is penalized according to its runtime.In this framework, a control policy is a function that maps feature vectors ontoactions. This mapping is limited by the practical constraint that most visionprocedures can only be applied to one type of data. The control policy is built from aset of Q-functions, one for every vision procedure. In Markov control theory, Q(s,a)is the function that predicts the expected reward over time that will follow from applying action a in state s. For example, ADORE trains a Q-function to predict the future reward that will follow from segmenting ROIs (in the context of the currenttask), based on the features of the ROI. It also trains a Q-functions for predicting therewards that follow image correlation, curve matching, and every other procedure inthe procedure library. The control policy evaluates these Q-functions on the currentdata and selects the procedure with the highest Q-value.It is important to note that the Q-function predicts the total future reward thatfollows a procedure, not just the immediate reward. As described above, in mostobject recognition tasks the system does not get a positive reward until the final stepwhen it accepts a (hopefully correct) hypothesis. As a result, Q-functions predict thequality of the hypothesis that eventually follows a procedure, even if it takes several additional steps to form or refine that hypothesis.4.3 Off-Line LearningThe control and artificial intelligence literatures contain many techniques for learning optimal Q-functions for control problems with discrete state spaces. If the transition probabilities associated with the actions are known (a so-called process model), dynamic programming will estimate Q-values and produce an optimal control policy. In the absence of a process model, reinforcement learning (most notably the temporal difference [30] and Q-learning [34] algorithms) have been shown to converge to optimal policies in a finite number of steps.Unfortunately, the object recognition problem as defined here depends on a continuous state space of feature vectors. These feature vectors measure the quality of aspects of the intermediate representations returned by the vision procedures, but it is not obvious how to divide the space of feature vectors into a finite set of states a-priori. Fortunately, Tesauro [31] and Zhang & Dietterich [35] have shown empirically that neural nets can approximate Q-functions over continuous feature spaces within a reinforcement learning system and still produce good control policies. Unfortunately, their method required hundreds of thousands of training cycles to converge. ADORE has a sequence of continuous feature spaces, one for each data representation (images, ROIs, contours, etc.) and would require getting a sequence of neural nets to converge on a single control policy. Although theoretically possible, we have not yet succeeded in making this work.Instead, we train Q-functions by optimistically assuming that the best control policy always selects the action that yields the highest possible future reward for every data token. Strictly speaking, this assumption is not always true: a control policy maps points in feature space onto actions, and it is possible for two different tokens to have the same feature measurements and yet have different “optimal”actions. Nonetheless, the optimistic assumption is approximately true, and it breaks the dependence between Q-functions, allowing each neural net to be trained separately.In particular, we approximate Q-functions by training backpropagation neural networks. The training samples are data tokens extracted from the training images. We apply all possible sequences of procedures to every training sample, in order to determine which procedure yields the maximum reward. A neural network Q-function is trained for every vision procedure using the data features as input and the maximum reward as the output. In this way, the neural net learns to approximate the future reward from an action under the optimistic control assumption. (Complicating the picture somewhat, we “bag” the neural nets to reduce variance; see [14].)5Experiments5.1 Task #1: Duplex RecognitionTo test ADORE in a tightly controlled domain, we trained it to recognize houses in aerial images like the one in Figure 1. In the first experiment, the goal is to find duplexes of the type shown in Figure 2. The training signal is a bitmap that shows the position and orientation of the duplexes in the training images; Figure 5 shows the training signal matching the image shown in Figure 1. The reward function is the percentage of pixel overlap between the hypothesis and the training signal. This evaluation function ranges from one (perfect overlap) to zero (no overlap).Fig. 5. The duplex training signal for the image shown in Figure 1.5.2 The Vision Procedure LibraryThe vision procedure library contains ten vision procedures, as depicted in Figure 6. Three of the procedures produce likelihood images (with orientation information) from intensity images and a template2. The rotation-free correlation procedure [28] correlates the template at each position in the image by first rotating the template until the direction of the edge at the center of the template corresponds to the edge direction at the center of the image window. The TAStat procedure is a modification of the algorithm in [25]. For every image window it also rotates a mask of the object until it aligns with the local edge data, and then measures the difference between the intensity distributions of the pixels inside and outside of the mask. The greater the difference between the intensity distributions, the more likely the mask matches an object at that location and orientation in the image. Finally, the probing procedure also uses edge information to rotate the template for each image window, and then samples pairs of pixels in the image window, looking for edges that match the location of edges in the template.2 In all of our experiments, we assume that a template of the object is available.Fig. 6. A visual depiction of ADORE’s vision procedure library. Note that the peak detection procedure produces approximately twenty ROIs each time it is called.Regions of interest (ROIs) are image chips that are hypothesized to correspond to object instances; each ROI includes a mask that details the hypothesized position and orientation of the object. ROIs can be extracted from likelihood images using a peak detection procedure, which finds the top N peaks in a likelihood image. For these experiments, the peak detection procedure was parameterized to extract twenty peaks from each likelihood image.Five procedures can be applied to any ROI. Two of these actions are the special procedures mentioned in Section 4.1, accept() and reject(). The other three options are: 1) an active contour procedure [18] that modifies the outline of an ROI mask to maximize the energy under the boundary; 2) a segmentation procedure [10] that extracts the boundary of a new region (as a 2D contour) within the image chip; or 3) a straight line extraction procedure [7].A Generalized Hough Transform procedure [5] matches 2D image contours to the contour of a template, thus creating a new ROI. A symbolic line matching procedure (LiME; [6]) finds the rotation, translation and scale that maps template (model) lines onto image lines, again producing an ROI. It should be noted that LiME transforms hypotheses in scale as well as rotation and translation, which puts it at a disadvantage in this fixed-scale domain.5.3 Duplex ResultsTo test the system’s ability to learn duplex recognition strategies, we performed N-fold cross-validation on the set of eight Fort Hood images. In other words, we divided the data into seven training images and one test image, trained ADORE on seven training images, and evaluated the resulting strategy on the test image. We repeated this process eight times, each time using a different image as the test image. All the results presented this paper are from evaluations of test images.Figure 7 shows the results of two tests, with the ROIs extracted by ADORE outlined in white on top of the test images. As a crude measure of success, ADORE found 21 out of 22 duplexes, while producing 6 false positives. The only duplex not found by ADORE can be seen in the image on the right of Figure 7– it is the duplex that is half off the bottom right-hand corner of the image. Every duplex that lies completely inside an image was recognized. (The right side of Figure 7 also shows one of the six false positives.)Fig. 7. Duplexes extracted from two images. In the image on the left, all three duplexes were correctly identified. On the right image, a false positive appears on the upper right side. The half-visible duplex to the bottom right is the only false negative encountered during testing.It would be incomplete to just analyze ADORE in terms of false positives and false negatives, however. Much of the benefit of ADORE’s dynamic strategies lies in their ability to refine imperfect hypotheses, not just make yes/no decisions. ADORE maximizes its reward function by creating the best hypotheses possible, given the procedure library. Table 1 gives a quantitative measure of ADORE’s success. The left most entry in Table 1 gives the average reward across all 22 positive duplex instances from the optimal strategy, where the optimal strategy is determined by exhaustive search. The second entry gives the average reward generated by the strategy learned by ADORE. As further points of comparison, we implemented three static control strategies, all of which begin by applying the rotation-free correlation procedure. The third entry in Table 1 gives the average reward for duplex instances ifthe correlation ROIs are accepted or rejected without further refinement. The fourth entry gives the average reward if the ROIs created by correlation are segmented and then repositioned by matching the region boundary to the duplex template boundary via a Generalized Hough Transform. (This is the sequence of actions shown in Figure X.). The fifth entry gives the average reward if active contours (i.e. snakes) are applied to the correlaiton ROIs, followed once again by the Generalized Hough Transform. These last three procedures correspond to the three best “static” control policies, i.e. the three best strategies that do not dynamically select procedures based on token features, other than to classify (accept or reject) hypotheses.Optimal Policy ADOREPolicyAccept orRejectSegment ActiveContoursAvgReward0.89910.88030.78930.86530.7775Table 1. Comparison between the optimal policy, the policy learned by ADORE, and the four best static policies.Two conclusions can be drawn from Table 1. First, the strategy learned by ADORE for this (admittedly simple) task is within about 98% of optimal. Second, the dynamic strategy learned by ADORE, although not perfect, is better than any fixed sequence of actions. As a result, our intuitions from Section 2 are validated: we achieve better performance with dynamic, rather than static, control strategies.5.3 Task #2: Finding Smaller HousesHaving succeeded in finding a good strategy for recognizing duplexes, we changed the training signals and templates to recognize four other styles of houses. (The templates for these styles are shown in Figure 8). The same procedure library and token features were used for these styles as for the duplex. After training, ADORE identified 18 of 19 instances of the house style A but generated 22 false positives. Combining the results from house styles A through D, ADORE found 47 out of 61 instances, while generating 85 false positives.(A)(B)(C)(D)。