Evolution of Sensor Suites for Complex Environments
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K-对策者 K—strategistisn维超体积资源空间 n—dimensional hyper—volume n维生态位 n-dimensional nicheRaunkiaer定律 Law of Frequencyr-对策者 r-strategistis奥陶纪 Ordovician period白垩土草地 chalk grassland斑块 patch斑块性 patchiness斑块性种群 patchy population半荒漠 semi-desert半矩阵或星系图 constellation diagrams伴生种 companion species饱和密度 saturation density饱和期 asymptotic phase保护哲学 conservation philosophy北方针叶林 northern conifer forest被动取样假说 passive sampling hypothesis本能 instinct本能行为 instinctive behavior避敌 avoiding predator边缘效应 edge effect变异性 variability标志重捕法 mark recapture methods标准频度图解 frequency diagram表现型适应 phenotypic adaptation并行的 simultaneous并行同源 paralogy捕食 predation不重叠的 non—overlapping残存斑块 remnant patch残余廊道 remnant corridor操作性条件作用 operant conditioning草原生态系统 grassland system层次性结构 hierachical structure产卵和取食促进剂 oviposition and feeding stimulant 产业生态学 industry ecology长日照植物 long day plant超体积生态位 hyper—volume niche成本外摊 externalized cost程序化死亡 programmed cell death尺度效应 scaling effect抽彩式竞争 competive lottery臭氧层破坏 ozone layer destruction出生率 natality或birth rate初级生产 primary production初级生产力 primary productivity初级生产者 primary producer传感器 sensor串行的 serial垂直结构 vertical structure春化 vernalization次级生产 secondary production次级生产力 secondary productivity次生演替 secondary successon粗密度 crude density存活曲线 survival curve存活值 survival value存在度 presence搭载效应 hitchhiking effect大陆—岛屿型复合种群 mainland-island metapopulation 带状廊道 strip corridor单联 single linkage单体生物 unitary organism单位努力捕获量 catch per unit effort单元的 monothetic淡水生态系统 fresh water ecosystem氮循环 nitrogen cycling等级(系统)理论 hierarchy theory等级的 hierarchical底内动物 infauna底栖动物 benthos地表火 surface fire地带性生物群落 biome地理信息系统 geographic information system地面芽植物 hemicryptophytes地上芽植物 chamaephytes地植物学 geobotany第三纪 Tetiary period第四纪 Quaternary period点突变 genic mutation或point mutation电荷耦合器 charge coupled device, CCD顶极阶段 climax stage顶极群落 climax community顶极种 climax species动态率模型 dynamic pool model动态平衡理论 dynamic equilibrium theory动态生命表 dynamic life table动物痕迹的计数 counts of animal signs动物计数 counts of animals冻原 tundra短日照植物 short day plant断层 gaps多波段光谱扫描仪 multichannel spectrum scanner, MSS 多度 abundance多样化 variety多元的 poly thetic厄尔尼诺El Nino反馈feedback反射reflex泛化种generalist防卫行为defennce behavior访花昆虫flower visitor非等级的non—hierarchical非空间模型non-spatial model非内稳态生物non-homeostatic organism非平衡态复合种群nonequilibrium metapopulation非平衡态跟踪生境复合种群nonequilibrium habitat-tracking metapopulation非平衡态下降复合种群nonequilibrium declining metapopulation非生态位non-niche非生物环境physical environment非线性关系nonlinear分布dispersion分解者decomposer分支过程branching process分子分类学molecular taxonomy分子进化的中性理论the neutral theory of molecular evolution分子生态学molecular ecology分子系统学molecular systematics浮游动物plankton负反馈negative feedback)负荷量carrying capacity负相互作用negative interaction负选择negative selection附底动物epifauna复合种群metapopulation富营养化现象eutrohication改良relamation盖度coverage盖度比cover ratio干扰disturbance干扰斑块disturbance patch干扰廊道disturbance corridor干扰作用interference高度height高斯假说Coarse's hypothesis高斯理论Coarse's theory高位芽植物phanerophytes格林威尔造山运动Grenville Orogenesis 个体individual个体论概念individualistic concept更新renewal功能生态位functional niche攻击行为aggressive behavior构件modules构件生物modular organism关键种keystone species关联系数association coefficients光饱和点light saturation point光补偿点light compensation point光周期photoperiod过滤器filter哈德-温伯格原理Hardy—Weinberg principle 海洋生态系统Ocean ecosytem寒武纪Cambrian period旱生植物siccocolous河流廊道river corridor恒有度contancy红树林mangrove呼吸量respiration互利mutualism互利素synomone互利作用synomonal化感作用allelopathy化学防御chemical defence化学生态学chemical ecology化学物质allelochemicals化学隐藏chemocryptic划分的divisive环境environment环境伦理学environmental ethics环境容纳量environmental carryin capacity环境资源斑块environmental resource patch环境资源廊道environmental resource corridor 荒漠desert荒漠化desertification荒漠生态系统desert ecosystem黄化现象eitiolation phenomenon恢复生态学restoration ecology混沌学chaos混合型mixed type活动库exchange pool获得性行为acquired behavior机体论学派organismic school基础生态位Fundamental niche基质matrix极点排序法polar ordination集群型clumped寄生parasitism加速期accelerating phase价值value价值流value flow间接排序indirect ordination间接梯度分析indirect gradiant analysis减速期decelerating phase简单聚合法lumping碱性植物alkaline soil plant建群种constructive species接触化学感觉contact chemoreception解磷菌或溶磷菌Phosphate-solubiIizing Microorganisms, PSM 进化适应evolutionary adaptation经典型复合种群classic metapopulation经济密度economic density景观landscape景观格局landscape patten景观过程模型process based landscape model景观结构landscape structure景观空间动态模型spatial dynamic landscape model景观生态学landscape ecology净初级生产量net primary production竞争competition竞争排斥原理competition exclusion principle静态生命表static life table局部种群local population距离效应distance effect聚合的agglomerative均匀型uniform菌根mycorrhiza抗毒素phytoalexins可持续发展sustainable development 空间结构spatial structure空间模型spatial model空间生态位spatial niche空间异质性spatial heterogeneity 库pool矿产资源mineral resources廊道corridor离散性discrete利己素allomone利己作用allomona利他行为altruism利他作用kairomonal连续体continuum联想学习associative learning猎食行为hunting behavior林冠火crown fire磷循环phosphorus cycling零假说null hypothesis领悟学习insight learning领域性territoriality流flow绿色核算green accounting逻辑斯谛方程logistic equation铆钉假说Rivet hypothesis密度density密度比density ratio密度制约死亡density-dependent mortality 面积效应area effect灭绝extinction铭记imprinting模拟hametic模型modeling牧食食物链grazing food chain内禀增长率intrinsic rate of increase内稳态homeostasis内稳态生物homeostatic organisms内源性endogenous内在的intrinsic耐阴植物shade-enduring plants能量分配原则principle of energy allocation 能量流动energy flow能源资源energy resources能值emergy泥盆纪Devonian period拟寄生parasitoidism逆分析inverse analysis年龄分布age distribution年龄结构age structure年龄性别锥体age—sex pyramid年龄锥体age pyramids偶见种rare species排序ordination配额quota配偶选择mate selection偏害amensalism偏利commensalism频度frequency平衡选择balancing selection平台plantform平行进化parallel evolution栖息地habitat期望值外推法extrapolation by expected value 气候驯化acclimatisation器官organs亲本投资parental investment亲族选择kin selection趋光性phototaxis趋化性chemotaxis趋同进化convergent evolution趋性taxis趋异进化divergent evolution趋异适应radiation adaptation取食促进剂oviposition and feeding stimulant 取样调查法sampling methods去除取样法removal sampling全联法complete linkage全球global全球变暖global warnning全球定位系统global Positioning System全球生态学global ecology确限度fidelity群丛association群丛单位理论association unit theory群丛组association group群落community群落的垂直结构vertical structure群落生态学community ecology群落水平格局horizontal pattern群落外貌physiognomy群落演替succession群系formation群系组formation group热带旱生林tropical dry forest热带季雨林tropical seasonal rainforest热带稀树草原tropical savanna热带雨林tropical rainforest热力学第二定律second law of thermodynamics 热力学第一定律first law of thermodynamics 人工斑块introduced patch人工廊道introduced corridor人口调查法cencus technique人口统计学human demography日中性植物day neutral plant冗余redundancy冗余种假说Redundancy species hypothesis三叠纪Triassic period森林生态系统forest ecosystem熵值entropy value上渐线upper asymptotic社会性防卫行为defence behavior社会优势等级dominance hierarchy摄食行为feed behavior生活史life history生活史对策life history strategy生活小区biotope生活型life form生活周期life cycle生境habitat生境多样性假说habitat diversity hypothesis 生理出生率physiological natality生理死亡率physiological mortality生命表life table生态出生率ecological natality生态对策bionomic strategy生态反作用ecological reaction生态幅ecological amplitude生态工程ecological engineering生态工业ecological industry生态规划ecological planning生态恢复ecological restoration生态经济ecological economics生态旅游ecotourism生态密度ecological density生态农业ecological agriculture生态入侵ecological invasion生态设计ecological design生态适应ecological adaptation生态死亡率ecological mortality生态位niche生态位宽度niche breadth生态位相似性比例niche proportional similarity 生态位重叠niche overlap生态文明ecological civilization生态系统ecosystem生态系统产品ecosystem goods生态系统多样性ecosystem diversity生态系统服务ecosystem service生态系统生态学ecosystem ecology生态系统学ecosystemology生态型ecotype生态学ecology生态因子ecological factor生态元ecological unit生态作用ecological effect生物organism生物地球化学循环biogecochemical cycle生物多样性biodiversity生物量biomass生物潜能biotic potential生物群落biotic community,biome生物群落演替succession生殖潜能reproductive potential剩余空间residual space失共生aposymbiosis湿地wetland湿地生态系统wetland ecosystem湿地植物hygrophyte时间结构temporal structure实际出生率realized natality实际死亡率realized mortality食草动物herbivores食肉动物carnivores食物链food chain食物网food wed矢量vector适合度fitness适应辐射adaptive radiation适应值adaptive value适应组合adaptive suites收获理论harvest theory收益外泄externalized profit衰退型种群contracting population 水平格局horizontal pattern水土流失soil and water erosion 水循环water cycling瞬时增长率instantaneous rate死亡率mortality & death rate松散垂直耦连loose vertical coupling松散水平耦连loose horizontal coupling溯祖过程coalescent process溯祖理论coalescent theory酸性土理论acid soil plant酸雨acid rain随机型random碎屑食物链detritus food chainK-对策者K-strategistisn维超体积资源空间n-dimensional hyper—volume n维生态位n-dimensional nicheRaunkiaer定律Law of Frequencyr-对策者r-strategistis奥陶纪Ordovician period白垩土草地chalk grassland斑块patch斑块性patchiness斑块性种群patchy population半荒漠semi-desert半矩阵或星系图constellation diagrams伴生种companion species饱和密度saturation density饱和期asymptotic phase保护哲学conservation philosophy北方针叶林northern conifer forest被动取样假说passive sampling hypothesis本能instinct本能行为instinctive behavior避敌avoiding predator边缘效应edge effect变异性variability标志重捕法mark recapture methods标准频度图解frequency diagram表现型适应phenotypic adaptation并行的simultaneous并行同源paralogy捕食predation不重叠的non—overlapping残存斑块remnant patch残余廊道remnant corridor操作性条件作用operant conditioning草原生态系统grassland system层次性结构hierachical structure产卵和取食促进剂oviposition and feeding stimulant 产业生态学industry ecology长日照植物long day plant超体积生态位hyper—volume niche成本外摊externalized cost程序化死亡programmed cell death尺度效应scaling effect抽彩式竞争competive lottery臭氧层破坏ozone layer destruction出生率natality或birth rate初级生产primary production初级生产力primary productivity初级生产者primary producer传感器sensor串行的serial垂直结构vertical structure春化vernalization次级生产secondary production次级生产力secondary productivity次生演替secondary successon粗密度crude density存活曲线survival curve存活值survival value存在度presence搭载效应hitchhiking effect大陆—岛屿型复合种群mainland-island metapopulation 带状廊道strip corridor单联single linkage单体生物unitary organism单位努力捕获量catch per unit effort单元的monothetic淡水生态系统fresh water ecosystem氮循环nitrogen cycling等级(系统)理论hierarchy theory等级的hierarchical底内动物infauna底栖动物benthos地表火surface fire地带性生物群落biome地理信息系统geographic information system 地面芽植物hemicryptophytes地上芽植物chamaephytes地植物学geobotany第三纪Tetiary period第四纪Quaternary period点突变genic mutation或point mutation电荷耦合器charge coupled device, CCD顶极阶段climax stage顶极群落climax community顶极种climax species动态率模型dynamic pool model动态平衡理论dynamic equilibrium theory动态生命表dynamic life table动物痕迹的计数counts of animal signs动物计数counts of animals冻原tundra短日照植物short day plant断层gaps多波段光谱扫描仪multichannel spectrum scanner, MSS多度abundance多样化variety多元的poly thetic厄尔尼诺El Nino反馈feedback反射reflex泛化种generalist防卫行为defennce behavior访花昆虫flower visitor非等级的non—hierarchical非空间模型non-spatial model非内稳态生物non-homeostatic organism非平衡态复合种群nonequilibrium metapopulation非平衡态跟踪生境复合种群nonequilibrium habitat—tracking metapopulation非平衡态下降复合种群nonequilibrium declining metapopulation非生态位non—niche非生物环境physical environment非线性关系nonlinear分布dispersion分解者decomposer分支过程branching process分子分类学molecular taxonomy分子进化的中性理论the neutral theory of molecular evolution 分子生态学molecular ecology分子系统学molecular systematics浮游动物plankton负反馈negative feedback)负荷量carrying capacity负相互作用negative interaction负选择negative selection附底动物epifauna复合种群metapopulation富营养化现象eutrohication改良relamation盖度coverage盖度比cover ratio干扰disturbance干扰斑块disturbance patch干扰廊道disturbance corridor干扰作用interference高度height高斯假说Coarse's hypothesis高斯理论Coarse's theory高位芽植物phanerophytes格林威尔造山运动Grenville Orogenesis个体individual个体论概念individualistic concept更新renewal功能生态位functional niche攻击行为aggressive behavior构件modules构件生物modular organism关键种keystone species关联系数association coefficients光饱和点light saturation point光补偿点light compensation point光周期photoperiod过滤器filter哈德-温伯格原理Hardy—Weinberg principle 海洋生态系统Ocean ecosytem寒武纪Cambrian period旱生植物siccocolous河流廊道river corridor恒有度contancy红树林mangrove呼吸量respiration互利mutualism互利素synomone互利作用synomonal化感作用allelopathy化学防御chemical defence化学生态学chemical ecology化学物质allelochemicals化学隐藏chemocryptic划分的divisive环境environment环境伦理学environmental ethics环境容纳量environmental carryin capacity环境资源斑块environmental resource patch环境资源廊道environmental resource corridor 荒漠desert荒漠化desertification荒漠生态系统desert ecosystem黄化现象eitiolation phenomenon恢复生态学restoration ecology混沌学chaos混合型mixed type活动库exchange pool获得性行为acquired behavior机体论学派organismic school基础生态位Fundamental niche基质matrix极点排序法polar ordination集群型clumped寄生parasitism加速期accelerating phase价值value价值流value flow间接排序indirect ordination间接梯度分析indirect gradiant analysis减速期decelerating phase简单聚合法lumping碱性植物alkaline soil plant建群种constructive species接触化学感觉contact chemoreception解磷菌或溶磷菌Phosphate-solubiIizing Microorganisms, PSM 进化适应evolutionary adaptation经典型复合种群classic metapopulation经济密度economic density景观landscape景观格局landscape patten景观过程模型process based landscape model景观结构landscape structure景观空间动态模型spatial dynamic landscape model 景观生态学landscape ecology净初级生产量net primary production竞争competition竞争排斥原理competition exclusion principle静态生命表static life table局部种群local population距离效应distance effect聚合的agglomerative均匀型uniform菌根mycorrhiza抗毒素phytoalexins可持续发展sustainable development空间结构spatial structure空间模型spatial model空间生态位spatial niche空间异质性spatial heterogeneity库pool矿产资源mineral resources廊道corridor离散性discrete利己素allomone利己作用allomona利他行为altruism利他作用kairomonal连续体continuum联想学习associative learning猎食行为hunting behavior林冠火crown fire磷循环phosphorus cycling零假说null hypothesis领悟学习insight learning领域性territoriality流flow绿色核算green accounting逻辑斯谛方程logistic equation铆钉假说Rivet hypothesis密度density密度比density ratio密度制约死亡density-dependent mortality 面积效应area effect灭绝extinction铭记imprinting模拟hametic模型modeling牧食食物链grazing food chain内禀增长率intrinsic rate of increase内稳态homeostasis内稳态生物homeostatic organisms内源性endogenous内在的intrinsic耐阴植物shade-enduring plants能量分配原则principle of energy allocation 能量流动energy flow能源资源energy resources能值emergy泥盆纪Devonian period拟寄生parasitoidism逆分析inverse analysis年龄分布age distribution年龄结构age structure年龄性别锥体age-sex pyramid年龄锥体age pyramids偶见种rare species排序ordination配额quota配偶选择mate selection偏害amensalism偏利commensalism频度frequency平衡选择balancing selection平台plantform平行进化parallel evolution栖息地habitat期望值外推法extrapolation by expected value 气候驯化acclimatisation器官organs亲本投资parental investment亲族选择kin selection趋光性phototaxis趋化性chemotaxis趋同进化convergent evolution趋性taxis趋异进化divergent evolution趋异适应radiation adaptation取食促进剂oviposition and feeding stimulant 取样调查法sampling methods去除取样法removal sampling全联法complete linkage全球global全球变暖global warnning全球定位系统global Positioning System全球生态学global ecology确限度fidelity群丛association群丛单位理论association unit theory群丛组association group群落community群落的垂直结构vertical structure群落生态学community ecology群落水平格局horizontal pattern群落外貌physiognomy群落演替succession群系formation群系组formation group热带旱生林tropical dry forest热带季雨林tropical seasonal rainforest热带稀树草原tropical savanna热带雨林tropical rainforest热力学第二定律second law of thermodynamics 热力学第一定律first law of thermodynamics 人工斑块introduced patch人工廊道introduced corridor人口调查法cencus technique人口统计学human demography日中性植物day neutral plant冗余redundancy冗余种假说Redundancy species hypothesis三叠纪Triassic period森林生态系统forest ecosystem熵值entropy value上渐线upper asymptotic社会性防卫行为defence behavior社会优势等级dominance hierarchy摄食行为feed behavior生活史life history生活史对策life history strategy生活小区biotope生活型life form生活周期life cycle生境habitat生境多样性假说habitat diversity hypothesis 生理出生率physiological natality生理死亡率physiological mortality生命表life table生态出生率ecological natality生态对策bionomic strategy生态反作用ecological reaction生态幅ecological amplitude生态工程ecological engineering生态工业ecological industry生态规划ecological planning生态恢复ecological restoration生态经济ecological economics生态旅游ecotourism生态密度ecological density生态农业ecological agriculture生态入侵ecological invasion生态设计ecological design生态适应ecological adaptation生态死亡率ecological mortality生态位niche生态位宽度niche breadth生态位相似性比例niche proportional similarity 生态位重叠niche overlap生态文明ecological civilization生态系统ecosystem生态系统产品ecosystem goods生态系统多样性ecosystem diversity生态系统服务ecosystem service生态系统生态学ecosystem ecology生态系统学ecosystemology生态型ecotype生态学ecology生态因子ecological factor生态元ecological unit生态作用ecological effect生物organism生物地球化学循环biogecochemical cycle 生物多样性biodiversity生物量biomass生物潜能biotic potential生物群落biotic community,biome生物群落演替succession生殖潜能reproductive potential剩余空间residual space失共生aposymbiosis湿地wetland湿地生态系统wetland ecosystem湿地植物hygrophyte时间结构temporal structure实际出生率realized natality实际死亡率realized mortality食草动物herbivores食肉动物carnivores食物链food chain食物网food wed矢量vector适合度fitness适应辐射adaptive radiation适应值adaptive value适应组合adaptive suites收获理论harvest theory收益外泄externalized profit衰退型种群contracting population水平格局horizontal pattern水土流失soil and water erosion水循环water cycling瞬时增长率instantaneous rate死亡率mortality & death rate松散垂直耦连loose vertical coupling松散水平耦连loose horizontal coupling溯祖过程coalescent process溯祖理论coalescent theory酸性土理论acid soil plant酸雨acid rain随机型random碎屑食物链detritus food chainK-对策者K—strategistisn维超体积资源空间n-dimensional hyper—volume n维生态位n—dimensional nicheRaunkiaer定律Law of Frequencyr-对策者r-strategistis奥陶纪Ordovician period白垩土草地chalk grassland斑块patch斑块性patchiness斑块性种群patchy population半荒漠semi-desert半矩阵或星系图constellation diagrams伴生种companion species饱和密度saturation density饱和期asymptotic phase保护哲学conservation philosophy北方针叶林northern conifer forest被动取样假说passive sampling hypothesis 本能instinct本能行为instinctive behavior避敌avoiding predator边缘效应edge effect。
2023—2024学年(下)高二年级期末考试英语考生注意:1.答题前,考生务必将自己的姓名、考生号填写在试卷和答题卡上,并将考生号条形码粘贴在答题卡上的指定位置。
2.回答选择题时,选出每小题答案后,用铅笔把答题卡对应题目的答案标号涂黑。
如需改动,用橡皮擦干净后,再选涂其他答案标号。
回答非选择题时,将答案写在答题卡上。
写在本试卷上无效。
3.考试结束后,将本试卷和答题卡一并交回。
第一部分听力(共两节,满分30分)做题时,先将答案标在试卷上。
录音内容结束后,你将有2分钟的时间将试卷上的答案转涂到答题卡上。
第一节(共5小题;每小题1.5分,满分7.5分)听下面5段对话。
每段对话后有一个小题,从题中所给的A、B、C 三个选项中选出最佳选项。
听完每段对话后,你都有10秒钟的时间来回答有关小题和阅读下一小题。
每段对话仅读一遍。
例:How much is the shirt?A. ₤ 19.15.B. ₤ 9.18.C. ₤ 9.15.答案是C。
1. Why won't David go to the movies?A. He has to study.B. He has to work.C. He has a cold.2. When should the woman arrive at the laboratory on Tuesday?A. At 5:50 p. m.B. At 6:10 p. m.C. At 7:50 p. m.3. Where are the speakers probably?A. At a cinema.B. At a store.C. At an office.4. What will the man most probably do next?A. Dry the clothes for another 45 minutes.B. Examine the dryer for potential damage.C. Take the clothes out of the dryer immediately.5. What are the speakers doing?A. looking at an old picture.B. Preparing for a family trip.C. Talking about their grandmother.第二节(共15小题;每小题1.5分,满分22.5分)听下面5段对话或独白。
智能手机英语作文Title: The Evolution of Smartphones: A Revolution in Communication。
In today's fast-paced world, smartphones have become an indispensable part of our daily lives. With their myriad features and functionalities, they have transformed the way we communicate, work, and interact with the world around us. In this essay, we will delve into the evolution of smartphones, exploring their history, impact, and future prospects.The journey of smartphones began in the late 20th century, with the introduction of devices like the IBM Simon Personal Communicator in 1994, often regarded as the first smartphone. However, it was not until the early 2000s that smartphones gained widespread popularity, with the advent of devices like the BlackBerry and Palm Treo, which offered email, web browsing, and basic productivity tools.The real breakthrough came with the launch of the iPhone by Apple Inc. in 2007. With its intuitive touchscreen interface, robust app ecosystem, and sleek design, the iPhone revolutionized the smartphone industry and set the benchmark for future innovations. Following the iPhone's success, numerous other manufacturers entered the market, launching their own smartphones running on operating systems like Android and Windows Mobile.Over the years, smartphones have evolved rapidly in terms of design, hardware, and software capabilities. Today's smartphones boast powerful processors, high-resolution displays, advanced cameras, and a plethora of sensors, enabling users to perform a wide range of tasks with ease. From browsing the web and checking emails to streaming videos and playing games, smartphones have become multifunctional devices that cater to our diverse needs and preferences.One of the most significant impacts of smartphones has been on communication. With features like voice calls, text messaging, instant messaging, and social media apps,smartphones have made it easier than ever to stay connected with others, regardless of time and location. Whether it's keeping in touch with friends and family or collaborating with colleagues and clients, smartphones have become indispensable tools for modern communication.Moreover, smartphones have revolutionized the way we access information and entertainment. With internet connectivity and a wide range of apps, users can access news, information, and multimedia content on the go. From reading news articles and watching videos to listening to music and podcasts, smartphones have transformed how we consume media, offering unparalleled convenience and accessibility.In addition to communication and entertainment, smartphones have also become essential tools for productivity and creativity. With productivity apps like email clients, calendar apps, note-taking apps, and office suites, smartphones have turned into portable offices, allowing users to work remotely and stay productive while on the move. Similarly, with creative apps like photoeditors, video editors, and music production tools, smartphones have empowered users to unleash theircreativity and express themselves in new and innovative ways.Looking ahead, the future of smartphones promises even more exciting advancements and possibilities. Emerging technologies like artificial intelligence, augmented reality, and 5G connectivity are poised to reshape the smartphone landscape, enabling new experiences and applications that were previously unimaginable. From AI-powered assistants and immersive AR experiences to blazing-fast internet speeds and seamless connectivity, the smartphones of tomorrow hold the potential to further revolutionize how we live, work, and interact with the world around us.In conclusion, smartphones have come a long way since their inception, evolving from basic communication devices to powerful multifunctional tools that have transformed every aspect of our lives. With their ability to connect us to the world, entertain us, boost our productivity, andunleash our creativity, smartphones have become indispensable companions in our journey through the digital age. As we look to the future, the possibilities are limitless, and smartphones are poised to continue shaping the way we live and communicate for years to come.。
2024-2025学年江苏省苏州市苏州中学上学期高二期中测试英语试题If you were wondering whether there were any quiet, peaceful, undeveloped beaches left in Mykonos, you have found it. Featuring a wild landscape on a rocky bay in the northern part of the island, Fokos Beach is one of Mykonos’ “hidden beaches”, free of crowds. It’s faced by a taverna (小餐馆), but is usually nearly deserted, with only a few sunbathers. This is the top destination for those looking for a peaceful beach and natural beauty.There are better beaches for swimming — here the sea can be quite rough and it’s often windy. It is, however, a popular spot for riding, so don’t be surprised if you see horses coming down the road towards the beach.How to Get to Fokos BeachThere are no buses to Fokos, so you’ll need to rent a car. It’s about 13km and a 20-minute drive from Mykonos Town, partly through a dirt road before you reach the beach.Where to stay in Fokos BeachThere are no hotels in Fokos, but it’s close enough to the many choices in the center of the island: Hotel Adonis: Just a short walk from the Fabrika bus terminal (终点站), with different types of classically-styled rooms.Leto Hotel: Facing the sea in the old port, with spacious rooms and an open-air restaurant.Mykonos Theoxenia Boutique Hotel: Next to the windmills, with a wonderful garden and pool area.Mykonos Town Suites: A combination of traditional Cycladic style and contemporary design, with apartments where you can prepare your meals.1. Why is Fokos Beach considered a “hidden beach” in Mykonos?A.It is available only to sunbathers. B.It is only accessible by bus.C.It is rarely crowded with visitors. D.It is ideal for swimming.2. What is a favored activity on Fokos Beach?A.Horse riding. B.Mountain climbing.C.Swimming. D.Surfing.3. Which hotel best suits a guest passionate about cooking?A.Mykonos Theoxenia Boutique Hotel. B.Mykonos Town Suites.C.Hotel Adonis. D.Leto Hotel.The familiar sound of rustling and clanking fills the house—it’s the sound of my mother preparing breakfast. My morning alarm.As I drag my body tow ard the kitchen, I’m greeted by my mother standing in front of the stove. Shed effortlessly cooks a dish that blends Western and Eastern styles, a beloved breakfast classic in our family. This is my grandmother’s recipe, which mirrored her upbringing.Sin ce my grandmother’s passing, I’ve become more aware of my mother’s aging and her dedication (奉献) to cooking for us. She has cooked for her family for more than 30 years, dividing her time between three countries—Korea, Canada and Germany. When my parents visit us from Korea, they stay with us for several months. My mother helps around the house, showing her cooking skills to provide delicious meals for me, my partner and our kids. In alternating years, she and my dad will travel to Berlin to spend a couple of weeks with my sister and her partner.According to Statista, most Canadians claim to spend between 31 and 60 minutes preparing an average weekday dinner for themselves and others in their household.10 percent of the respondents to the 2022 survey stated that they spend more than an hour preparing their evening meal. My mother belongs to that 10 percent. And her daily cooking begins much earlier at the grocery store where she examines produce and finds the best deals. She takes everyone’s preferences and needs into account. The meal she creates becomes a ritual (仪式), bringing the family together to connect and share.In an era where convenience is king, with microwave dinners and meal kits flourishing (繁荣) in kitchens, the tough process of creating a homemade meal from scratch might seem highly inefficient. However, my 68-year-old mother embraces it with such dignity.“Nope, that’s not how you cut your carrots.” “Lower the heat, or you'll bum the butter.”“No, you shouldn’t use that bowl for this meal.”Helping her out in the kitchen is not easy. Yet, I know it’s her way of expressing love—that extra ingredient that goes into our every meal.4. What do we know about the author’s mother from the text?A.She lives with the author in Korea.B.She has three daughters.C.She has great cooking skills.D.She invented the author’s favourite breakfast.5. What is the author’s purpose in mentioning statistics about meal preparation time?A.To remind people to spend more time on home cooking.B.To ask the reader s to follow her mother’s example.C.To prove her mother’s enthusiasm for cooking.D.To show her mother’s devotion to family.6. Why does the author say helping her mother in the kitchen is not easy?A.Her mother wants to teach herB.Her mother is demanding in cooking everything.C.Her mother dislikes being disturbed. D.Her mother is easily annoyed.7. What is the best title for the passage?A.The Art of Cooking Traditional Meals. B.My Mother’s Cooking: A Family Ritual.C.The Convenience of Modern Cooking. D.Cooking from Scratch: A DyingTradition.A starfish has five identical arms with a layer of “tube feet” beneath them that can help the marine creature move along the seafloor, causing naturalists to puzzle over whether sea stars have defined front and back ends — and whether they have heads at all. But new genetic research suggests the opposite — sea stars are largely heads that lack trunks or tails and likely lost those features evolutionarily over time?Sea stars belong to a group called echinoderms (棘皮动物). The unusual animals have unique body plans (平面图) arranged in five equal sections that greatly differ from the bodies of bilateral animals, which have left and right sides mirroring each other. Sea stars begin as fertilized eggs (受精卵) that hatch and become larvae (幼体) that float in the ocean for weeks to months before settling on the ocean floor. There, they go through a process that transforms from a bilateral body into a star shape, or pentaradial body.“This has been a zoological mystery for centuries,” said senior study co-author Christopher Lowe at Stanford University. “How can you go from a bilateral body plan to a pentaradial plan? And how can you compare any part of the starfish to our own body plan?”Researchers used new methods of genetic sequencing (测序) to create an unprecedented (前所未有的) 3D map to determine where genes were expressed as sea stars developed and grew. They found that genetic features associated with the development of a head were detected all over the sea stars, espe cially concentrated in the center of the star and the center of each “arm”. Meanwhile, gene expression for trunk and tail sections was largely absent. This suggested that sea stars “have the most dramatic example of decoupling (分离) of the head and the trunk regions that we are aware of today,” said lead study author Laurent Formery.Animal research largely targets those that share similarities with humans. But studying groups like echinoderms could solve some of the most complex mysteries about the evolution of life on Earth. “Most animals are modest ones that live in burrows (洞穴) in the ocean. People are generally not drawn to these animals, and yet they probably represent how much of life got started,” Lowe said. Understanding how animals like sea stars have developed could also allow insights into the varied ways that different species remain healthy. “It’s certainly harder to work with creatures that are less frequently studied,” said study co-author Daniel Rokhsar at the University of California. “But if we take the opportunity to explore unusual animals that are operating in unusual ways, that means we are broadening our perspective on biology. This is eventually going to help us solve both ecological and biomedical problems.”8. What is the focus of the new research?A.The reason sea stars have no heads. B.The way sea stars sense direction.C.The body structure of sea stars. D.The function of sea stars’ arms.9. What did the researchers find by using genetic sequencing techniques?A.Gene expression related to the trunk of sea stars was completely missing.B.Head-related gene expressions were widespread in sea stars.C.How sea stars achieved the remarkable separation of their head and trunk.D.Why sea stars changed their body shape while they were on the ocean floor.10. Why is studying sea stars and other “modest” marine organisms important?A.It predicts how life on Earth evolved.B.It will challenge our understanding of marine creatures.C.It could provide insights into solving ecological and biomedical problems.D.It shows their unique body plans.11. What is the purpose of the text?A.To present a new research. B.To introduce a sea animal.C.To popularize a new concept. D.To promote a new technology.In December 2016 Edgar M. Welch drove six hours from his home to Washington DC, where he opened fire in a pizzeria with a gun. He had previously read an online news story about the restaurant being the headquarters of a group of child abusers run by Hillary Clinton. He decided to investigate for himself; fortunately, no one was hurt.The story about Hillary Clinton is one of the most famous examples of the growing phenomenon called “fake news”. The conspiracy (阴谋) theory about the pizzeria began to appear on websites and social networks in late October, before the US election. This was quickly denounced (谴责) by publications such as The New York Times and The Washington Post, However, many people thought that these papers were themselves lying for political ends and instead of disappearing, the fake story snowballed. Tweets from “Representative Steven Smith of the 15th District of Georgia” claimed that the mainstream media were telling falsehoods. Even though both this name and district were invented, the message was re-tweeted many times. A YouTube refutation of the New York Times article got 250,000 hits.Fake news stories can be hard to control for several reasons. Many people mistrust established news sources and others just don’t read them, so the debunk ing (揭穿) of a fake story by a serious newspaper or TV channel has limited effect. In addition, the internet is very hard to police. When users are caught misusing one media platform, they simply go to another one or start up a website themselves.There are also various reasons why people create fake news. Some have political motives, to belittle or incriminate their opponents. Other websites, like The Onion, deliberately publish fake news as satire — humorous comment on society and current affairs. Another group is in it for the profit: many people clicking on entertaining fake news stories can bring in a lot of advertising revenue. One man running fake news sites from Los Angeles said he was making up to US $30,000 a month in this way. There are also those, like the small-town teenagers in Macedonia who wrote fake news stories about Donald Trump, who seem to be motivated partly by money and partly by boredom.So, what can we do to stop fake news spreading? First, make sure that the websites you read are legitimate, for example by looking carefully at the domain name and the About Us section. Check the sources of any quotes or figures given in the story. Remember that amazing stories about famous people will be covered by the mainstream media if they are true. Only share stories you know are true and let your friends know, tactfully, when they unknowingly share fake news. Together we can turn around the post-truth world!12. Why did Elgar Welch go to the pizzeria?A.He was trying to rob the restaurant.B.He hated all supporters of Hillary Clinton.C.He was working as a private investigator and investigating a crime.D.He had become concerned after reading an untrue news story.13. Why did many people not believe The Washington Post and The New York Times when they denounced the pizzeria story?A.They checked the facts and found that the articles were incorrect.B.They didn’t trust anybody.C.They thought the newspapers had a political agenda.D.They thought the newspapers had not researched the story carefully enough.14. Which reason for the difficulty of controlling fake news stories is not given in the article?A.Many people don t read the mainstream mediaB.Online media platforms don’t check stories before publishing them.C.People are doubtful about the mainstream media.D.Fake news stories can easily switch to other websites and platforms if caught.15. How does the author feel about stopping fake news spreading?A.indifferent B.doubtful C.positive D.pessimisticIf you were to say that you have faith in others, a cynic (愤世嫉俗者) might accuse you of being naive. In an era of growing social division, cynicism—the belief that people-are fundamentally selfish and dishonest—has become more widespread. 16One popular misconception about cynics is that they are wiser than non-cynics. 17 . By never trusting, cynics believe they can protect themselves from betrayal and disappointment, but they also “shut down opportunities for collaboration, love and community, all of which require trust”, as Zaki told Time magazine.18 By focusing only on what’s wrong, cynics lose sight of what could improve. They see a broken system aa mirror of the broken nature of people, believing there’s no way to change the status quo. This belief rationalizes their decision to stop volunteering, protecting or speaking out for themselves.Cynical thinking affects how we treat others and how they respond to us, creating a vicious (恶性的) cycle that erodes trust. To break this cycle, Zaki promotes skep ticism, which he describes as “a scientific mindset where we focus on evidence to decide who we can trust.” Unlike cynics who presume bad or selfish intentions behind everything, skeptics stay open to evidence, even if it challenges their existing beliefs. 19Replacing cynicism with skepticism can lead us to a clearer view of society. 20 . As Zaki put it, “What we think and feel isn’t just for us; it’s for our communities. Our ability to believe in each other now goes hand in hand with creating the futu re we want.”Snow is a normal occurrence in Buffalo, New York. So when a snowstorm was ______, many people went to work as usual. ______ , this time the awful weather sook many by surprise and they were unable to get home. Despite many ______ stories about the storm, there were also many stories about snow angles who opened their homes and businesses ______ for people who were stuck.A group of ten tourists had an unexpected experience daring the snowstorm when their van was______ in the snow. The tourists were on their way to Washington DC and were ______ of the weather reports about the storm. But a nice couple came to their ______. Alexander Campagna______ a knock on his door from two of the tourists asking to borrow shovels (铲子) to ______ the van that was stuck. Campagna and his wife asked the ______ travelers in and provided their unexpected guests with a place to sleep.As the snowstorm struck Amherst, a suburb of Buffalo, on Friday afternoon, McDonald’s employees ______ people that were stuck on the street to come to the fast-food restaurant. “We accepted the______ that we weren’t going home, so we might as well open up.” an employee said. “We ______ that someone might need help.” More than 50 people ______ the storm at the restaurant.There’re countless other s who are willing to go the extra mile. These snow angles performed acts of ______ that’ll be remembered forever.21.A.revealed B.predicted C.claimed D.assumed22.A.However B.Besides C.Therefore D.Otherwise23.A.familiar B.impressive C.sad D.true24.A.shades B.shelters C.gifts D.habitats25.A.frozen B.crashed C.struck D.caught26.A.uncertain B.unafraid C.unaware D.unworthy27.A.rescue B.defence C.mind D.knowledge28.A.suffered B.considered C.caused D.received29.A.break into B.dig out C.look for D.keep off30.A.trapped B.disabled C.satisfied D.skilled31.A.invited B.convinced C.required D.inspired32.A.message B.advice C.fact D.challenge33.A.figured B.doubted C.concluded D.confirmed34.A.weathered B.watched C.faced D.fought35.A.bravery B.sacrifice C.kindness D.creation阅读下面短文,在空白处填入适当的词,如有括号提示,请以提示词的正确形式填空。
月球车设计思路英语作文Lunar Rover Design Concepts: A Comprehensive Analysis.The exploration of extraterrestrial environments, particularly the Moon, has captivated scientists, engineers, and the general public alike. Lunar rovers, unmannedvehicles capable of traversing the lunar surface, play a pivotal role in these endeavors, enabling the study of the Moon's geology, composition, and potential resources.Design Considerations.The design of lunar rovers is a complex undertaking, influenced by a myriad of factors, including:Mobility: Rovers must possess the ability to navigate the challenging terrain of the Moon, which includes craters, boulders, and loose regolith. This requires a robust suspension system, powerful wheels or tracks, and advanced navigation and control algorithms.Endurance: Lunar missions typically span several daysor weeks, necessitating rovers with extended range and endurance. This involves designing energy-efficient systems, optimizing battery life, and incorporating solar panels or other power sources.Payload Capacity: Rovers must carry a variety of instruments and scientific equipment, as well as camerasand communication systems. This requires a well-designed payload bay that can accommodate both scientific and operational payloads.Reliability: Operating in the harsh lunar environment, with extreme temperatures, radiation, and dust, poses significant challenges to the reliability of rovers. Robust engineering and rigorous testing are essential to ensurethat rovers can withstand these conditions.Science Objectives: The specific science objectives of a mission dictate the design requirements of the rover. For example, a rover intended for geological exploration mayrequire a drill or an X-ray spectrometer, while a rover focused on searching for water may necessitate a specialized sensor package.Historical Evolution.The design of lunar rovers has evolved significantly over the years, reflecting advancements in technology and the evolving needs of scientific exploration.Early Rovers: The first lunar rovers, deployed during the Apollo missions in the 1960s and 1970s, were relatively simple vehicles designed primarily for astronaut mobility and local exploration. These rovers relied on human control and were limited in range and payload capacity.Modern Rovers: Contemporary lunar rovers, such as the Yutu-2 and Zhurong rover, incorporate sophisticated technologies to enhance their capabilities. These rovers feature autonomous navigation, advanced sensors, and extensive payload suites, enabling them to conduct complex exploration missions.Key Innovations.Recent innovations in lunar rover design have focused on improving mobility, endurance, and scientific capabilities:Adaptive Suspension Systems: Rovers now utilize advanced suspension systems that adapt to changing terrain conditions, providing increased mobility and stability. These systems employ actuators, sensors, and sophisticated algorithms to optimize wheel placement and traction.Solar Electric Propulsion: Solar electric propulsion (SEP) systems utilize solar panels to generate electricity, which powers ion thrusters that provide gentle but sustained thrust. This extends the endurance of rovers, allowing them to travel longer distances and explore larger areas.Micro-Rovers: Miniaturization of electronic components has led to the development of micro-rovers, which arelightweight, compact, and agile. These rovers can access narrow spaces, explore difficult terrain, and complement larger rovers in scientific exploration.Artificial Intelligence (AI): AI algorithms are integrated into rover systems to enhance autonomous navigation and decision-making. AI enables rovers to identify hazards, plan trajectories, and adapt to changing conditions, improving their safety and efficiency.In-Situ Resource Utilization (ISRU): ISRU technologies allow rovers to utilize lunar resources, such as water or regolith, for propellant, building materials, or other purposes. This reduces the need for Earth-based resources and extends the duration of exploration missions.Future Directions.As lunar exploration continues, the design of lunar rovers will continue to evolve, driven by emerging technologies and the pursuit of new scientific discoveries.Long-Range Exploration: Rovers with increased rangeand endurance will enable the exploration of distant lunar regions, such as the poles or far side, providing valuable insights into lunar geology and resource distribution.Scientific Payload Enhancements: Future rovers will carry more advanced and specialized scientific payloads, enabling detailed studies of lunar composition, mineralogy, and biology. New sensor technologies will allow for more precise and comprehensive data collection.Human-Robot Collaboration: Rovers will increasingly collaborate with human astronauts, providing support for scientific investigations and exploration activities. This will involve the development of autonomous systems that can interact effectively with human operators.Lunar Base Support: Rovers will play a crucial role in the establishment of a lunar base, providing transportation, construction support, and scientific exploration capabilities. Rovers will be designed to operate in close proximity to human habitats and support extended humanmissions.Conclusion.The design of lunar rovers is an ongoing endeavor, driven by the pursuit of scientific knowledge and the advancement of space exploration capabilities. By incorporating innovative technologies and addressing the unique challenges of the lunar environment, lunar rovers continue to push the boundaries of robotic exploration and pave the way for new discoveries and advancements in our understanding of the Moon.。
高科技在我的生活英语作文High-tech has become an integral part of our daily lives, seamlessly integrating into various aspects and transforming the way we live, work, and interact. As a tech-savvy individual, I have witnessed firsthand the profound impact of technological advancements on my personal life. From the convenience of smart devices to the boundless possibilities of the digital world, high-tech has revolutionized the way I approach everyday tasks, stay connected, and explore new frontiers.One of the most significant ways high-tech has influenced my life is through the use of smartphones. These compact, yet powerful devices have become my constant companions, serving as versatile tools that cater to a wide range of needs. With a simple tap or swipe, I can access a wealth of information, stay connected with friends and family, manage my schedule, and even control various aspects of my smart home. The integration of features like voice assistants, augmented reality, and mobile payments has further enhanced the functionality of these devices, making my daily routine more efficient and convenient.Beyond the realm of smartphones, high-tech has also revolutionized the way I consume and interact with media. The rise of streaming platforms has transformed my entertainment experience, granting me instant access to a vast library of movies, TV shows, and music. I can now enjoy my favorite content on-demand, without the constraints of traditional broadcasting schedules. Moreover, the integration of smart home technologies has allowed me to seamlessly control my entertainment systems, adjusting lighting, temperature, and even home security with a few voice commands or taps on my smartphone.The impact of high-tech extends beyond the realms of communication and entertainment, as it has also transformed the way I approach education and professional development. Online learning platforms have opened up a world of opportunities, enabling me to access a diverse range of educational resources, from virtual classrooms to interactive tutorials. I can now learn new skills, expand my knowledge, and even pursue higher education without the need for physical attendance, thanks to the flexibility and accessibility offered by these technologies.In the professional realm, high-tech has become an indispensable tool for productivity and collaboration. Cloud-based productivity suites and project management software have streamlined my workprocesses, allowing me to seamlessly share documents, collaborate with colleagues in real-time, and access my work from any device, regardless of location. The integration of video conferencing and virtual meeting platforms has also revolutionized the way I conduct business, enabling me to connect with clients, partners, and team members across the globe, without the need for physical travel.The influence of high-tech extends even to the realm of personal finance and healthcare. Mobile banking apps and digital payment systems have simplified my financial management, allowing me to track expenses, transfer funds, and even invest with just a few taps on my smartphone. Furthermore, the advancements in wearable technology and health-monitoring apps have empowered me to take a more proactive approach to my wellbeing, monitoring my fitness, sleep patterns, and overall health with greater precision and convenience.Beyond the practical applications, high-tech has also enriched my personal life in unexpected ways. The advent of social media and virtual communication platforms has enabled me to stay connected with a global community, fostering meaningful relationships and allowing me to share experiences, ideas, and passions with like-minded individuals. The integration of augmented reality and virtual reality technologies has even allowed me to explore new worlds, immersing myself in captivating experiences that transcend theboundaries of the physical realm.As I look to the future, I am excited by the endless possibilities that high-tech holds. The rapid advancements in fields like artificial intelligence, robotics, and biotechnology hold the potential to revolutionize the way we live, work, and interact with the world around us. I eagerly anticipate the emergence of new technologies that will further enhance my quality of life, streamline my daily tasks, and open up new avenues for personal and professional growth.While the integration of high-tech in my life has undoubtedly brought about numerous benefits, I am also mindful of the potential challenges and ethical considerations that come with these advancements. Issues such as data privacy, cybersecurity, and the societal impact of automation are important factors that I continuously strive to navigate with care and responsibility.In conclusion, the role of high-tech in my life has been transformative, touching every aspect of my daily existence. From the convenience of smart devices to the boundless possibilities of the digital world, these advancements have revolutionized the way I live, work, and engage with the world around me. As I look to the future, I am excited to see how the continued evolution of technology will shape and enhance my personal and professional experiences, while also remaining cognizant of the ethical considerations that comewith these advancements. High-tech has undoubtedly become an integral part of my life, and I am eager to continue embracing its potential to unlock new opportunities and enrich my everyday experiences.。
你对软件的看法英语作文The Evolution and Impact of Software in Our Lives.Software, a term often overlooked in its true significance, has revolutionized the way we live, work, and interact with the world. It is the invisible force that powers our devices, automates tasks, and enables us to access information and connect with people instantaneously. Its presence is felt in every facet of modern life, from the smartphones we carry in our pockets to the complex systems that govern international space stations.The earliest forms of software were simple programs designed to perform specific tasks, such as calculating mathematical equations or managing databases. As technology advanced, software became more complex and interconnected, evolving into suites of programs that worked together to perform a wide range of tasks. Today, we have operating systems that power our computers and mobile devices, applications that allow us to communicate, create, andconsume content, and even artificial intelligence systems that can learn and adapt to our needs.The impact of software on society is profound. It has transformed the way we work, enabling remote collaboration and automation that has increased productivity and efficiency. In the medical field, software has enabled precise diagnostics, personalized treatments, and even remote patient monitoring. In education, it has opened up new possibilities for learning, with online courses and virtual classrooms becoming the norm.Software has also had a significant impact on our personal lives. It has made communication easier, with messaging apps, social media, and video conferencing tools connecting people across the globe. It has revolutionized entertainment, with streaming services, gaming platforms, and interactive media experiences providing endless hours of fun. Even our daily routines are influenced by software, with smart home systems automating tasks like lighting, heating, and security.However, the rise of software has also presented challenges. With increasing dependency on technology, there are concerns about privacy, security, and the potential for abuse. Cybercrime and hacking have become serious threats, and the need for robust security measures is paramount. Furthermore, as software becomes more pervasive, there are ethical and philosophical questions about its impact on jobs, society, and individual freedoms.Looking ahead, the future of software is exciting. With advances in artificial intelligence, machine learning, and other emerging technologies, we can expect software to become even more intelligent, adaptive, and interconnected. It will power the development of smart cities, autonomous vehicles, and personalized healthcare systems. It will enable new forms of creativity and expression, as well as new ways of working and learning.In conclusion, software is a fundamental part of our lives, shaping the way we interact with the world and each other. Its impact is felt across all sectors of society, from the most advanced technological advancements to thesimple tasks we perform daily. As we move into the future, it is important to consider the ethical and social implications of this technology and ensure that it serves the needs of all people, not just a privileged few.。
英语作文-电影机械制造行业的技术创新In the realm of film production, the mechanical manufacturing industry plays a pivotal role, constantly driven by technological innovation. This article delves into the profound impact of technological advancements within this sector.Technological innovation has revolutionized the mechanical manufacturing processes in the film industry, enhancing efficiency and enabling unprecedented creativity. The evolution from traditional mechanical methods to advanced automated systems has streamlined production timelines and elevated the quality of film equipment. 。
Firstly, precision engineering has emerged as a cornerstone of technological innovation. Modern CNC (Computer Numerical Control) machining has replaced manual operations, offering unparalleled precision in manufacturing camera parts and accessories. This precision not only ensures consistency but also enables the development of complex mechanisms crucial for specialized cinematic effects.Moreover, additive manufacturing, commonly known as 3D printing, has redefined prototyping and customization within the industry. Production teams can now rapidly iterate designs, reducing time-to-market for new equipment and modifications. This capability has been particularly transformative for indie filmmakers and experimental projects, democratizing access to tailored equipment solutions.Furthermore, advancements in materials science have expanded the possibilities for film equipment durability and performance. Lightweight yet robust materials such as carbon fiber and titanium alloys are now commonplace in camera rigging and support systems. These materials not only reduce equipment weight for portability but also enhance structural integrity under demanding shooting conditions.Additionally, automation has optimized manufacturing workflows, integrating robotics and AI-driven systems for assembly and quality control. Automated assembly lines ensure consistent output while minimizing human error, crucial for meeting stringent film production deadlines without compromising on quality.In parallel, sensor and imaging technologies have undergone exponential growth, enhancing the capabilities of film cameras. From high-resolution sensors to low-light performance improvements, these innovations empower cinematographers with unprecedented creative flexibility. Coupled with advances in lens technology and optical stabilization, filmmakers can achieve cinematic shots previously deemed impossible, pushing the boundaries of visual storytelling.Beyond hardware, software innovations have revolutionized post-production processes. Integrated editing suites and visual effects software leverage AI algorithms for real-time rendering and seamless integration of CGI (Computer-Generated Imagery). This convergence of hardware and software accelerates the pace of film production, enabling directors to visualize and refine their creative vision with precision and efficiency.In conclusion, the technological landscape of mechanical manufacturing within the film industry continues to evolve, driven by innovation and the pursuit of excellence. From precision engineering to additive manufacturing and advanced materials, each advancement contributes to enhancing film equipment performance and expanding creative possibilities. As technology progresses, the future promises even greater integration of AI, sustainable materials, and immersive technologies, further shaping the cinematic experiences of tomorrow.。
Evolution of Sensor Suites for Complex Environments Annie S.Wu,Ayse S.Yilmaz,and John C.Sciortino,Jr.Abstract—We present a genetic algorithm(GA)based deci-sion tool for the design and configuration of teams of unmanned ground sensors.The goal of the algorithm is to generate candidate solutions that meet cost and performance constraints. The GA evolves the membership,placement,and characteristics of a team of cooperating sensors.Previous work shows that this algorithm can generate successful teams in simple,obstacle free environments.This work examines the performance of our algorithm in environments that include obstacles.I.I NTRODUCTIONThe pervasiveness of technology in today’s military have extended the military theater into the realm of the electro-magnetic(EM)spectrum.Activity such as radio communi-cation,laser guided control,and radar emissions all reside within the EM spectrum.Electronic Warfare(EW)refers to military actions focused on the control and use of the EM spectrum.EW is accomplished using offensive electronic attack(EA)and defensive electronic protection(EP)actions. The choice and implementation of EA and EP actions are determined by a third component of EW,electronic warfare support(ES).ES involves actions which intercept,identify, and analyze enemy radiations with a goal of detecting threat conditions and recognizing offensive opportunities.This work addresses a general problem in ES:determining an appropriate team and organization of sensors that provides maximal detection capabilities in a given scenario.Identifi-cation and location of enemy emitters allow intelligence to be formed about the enemy order of battle,both electronic and physical.This knowledge allows for the planning of surveillance and reconnaissance.These capabilities are part of Command and Control Warfare(C2W)which is designed to prevent an enemy from exercising control over their units or at least degrading such control.Once emitter locations are known,they can be eliminated.Since emitters are associated with weapons systems,this knowledge also eliminates the weapons systems.Battle damage assessment can also be undertaken through electronic surveillance.Previous work has shown that a genetic algorithm(GA) approach can successfully address this problem of the forma-tion and organization of teams of unattended ground sensors [6].This work focused on simple problem environments and investigated the GA’s ability to design optimal teams of sensors for given enemy scenarios.In addition tofinding good solutions in terms of the number and organization of sensors,the GA approach exhibits an added advantage of not being scenario specific,that is,the GA requires little or no Annie S.Wu and Ayse S.Yilmaz are with the School of Electrical Engineering and Computer Science,University of Central Florida,Orlando, FL32816-2362,USA(email:aswu,selen@).John C.Sciortino,Jr.is with the Naval Research Laboratory,Washington, DC20375(email:john.sciortino@).Fig.1.Example problem environment.reconfiguration from one problem scenario to the next.Re-lated work in evolutionary robotics have found evolutionary algorithms to be an effective approach for designing sensor suites for autonomous agents[1],[2],[3].These problems are more complex in that the possible sensor configurations are restricted by the physical parameters of autonomous robots. In this paper,we extend our previous studies[6]to examine more complex environments that include obstacles. The addition of obstacles greatly restricts the placement and reach of sensors and complicates the problem of building and organizing effectively cooperating teams of sensors. We examine a series of test scenarios and evaluate the composition and placement of the evolved teams.Results indicate that the GA is able to intelligently design sensor placements that minimize the negative effects of obstacles in the environment.II.T EST PROBLEMOur problem environment is an abstract simulation envi-ronment consisting of a two dimensional working area in which obstables and a collection of enemy radar are placed. Figure1shows an example environment consisting of twelve randomly placed enemy radar and no obstacles.Radar are represented as points surrounded by gradually fading circles. The location,power,and frequencies of the enemy radar are configured beforehand and remain static throughout a run. Radar can only be detected by sensors that are configured to sense on the same frequency.A radar must be detected by atFig.2.Sensor characteristics:=detection range and=orientation. least three sensors to be fully detected.(Three measurements are necessary for triangulation of position.)Radar that are detected by two sensors are partially detected and radar that are detected by one sensor are minimally detected.The obstacles in our environment are modeled as solid rectangular objects that can vary in size.The location and size of an obstacle are predefined and remain unchanged during the course of a run.Obstacles that intersect the direct line between a sensor and a radar block that sensor’s ability to detect that radar.Sensor placement is specified as x and y coordinates and direction of orientation.As shown in Figure2,orientation is specified as an angle,,which runs counter clockwise with zero degrees at due east.Sensor characteristics include detection angle,power threshold,and frequency range.The detection angle,,is centered around the direction of ori-entation within which a sensor can detect rger values provide greater detection capability.Both orientation and detection angle range from zero to360degrees.The power emitted by a radar decreases proportionally with the distance squared.Radar power must exceed the minimum power threshold of a sensor in order for that sensor to detect the radar.Frequency is represented as discrete intervals that are turned on or off.The number of available frequency intervals is a pre-defined constant.We examine two types of sensors in our experiments. Long-range sensors have a maximum sensing range that covers the entire working area.As a result,any sensor can potentially evolve characteristics that would allow it to detect all radar in the working area.Short-range sensors have a maximum sensing range that covers at most one quarter of the environment.We expect solutions with short range sensors to consist of more sensors due to their comparatively limited capabilities.Figure3shows an example of a candidate solution.The pie shaped elements indicate sensors and their detection angle and orientation.Lines indicate detection of a radar by a sensor.III.G ENETIC ALGORITHM DETAILSThe GA[4],[5]is a learning algorithm based on princi-ples from genetics and evolutionary biology.Where nature evolves organisms that meet the requirements necessary for survival in a particular environment,GAs evolve solutions that meet the requirements necessary for solvingspecificFig.3.Problem environment with candidate solution.procedure GA{initialize population;while termination condition notsatisfied do{evaluate current population;select parents;apply genetic operators to parentsto create offspring;set current population equal tothe new offspring population;}}Fig.4.Basic steps of a typical genetic algorithm.problems.A typical GA works with a population of individ-uals,where each individual represents a potential solution to the problem to be solved.These potential solutions are evaluated and the better solutions are used to create a new population of potential solutions using genetics-inspired operators.Over multiple“generations”,the quality of the evolved solutions will improve.Key features of a GA include the following.A GA works with a population of individuals where each indi-vidual represents a potential solution to the problem to be solved.Idealized genetic operators explore the search space by forming new solutions out of existing ones.Genetic operators define how encoded information is manipulated and changed by a GA.A selection function selects individuals for reproduction based on theirfitness.Selection exploits useful information currently existing in a population.Afitness function evaluates the utility of each individual as a solution. Figure4shows the basic steps of a GA.The initial population may be initialized randomly or with user-defined individuals.The GA then iterates thru an evaluate-select-Fig.5.Problem representation for a team of sensors. reproduce cycle until either a user-defined stopping condition is satisfied or the maximum number of allowed generations is exceeded.A.Problem representationEach individual in a GA population specifies the com-position and arrangement of a team of sensors encoded as a vector of genes.Each gene encodes the evolvable characteristics for a single sensor.Figure5shows an example individual which represents a team of N+1sensors.Example parameter values for Sensor2are shown in detail.As the optimal number of sensors may not be known in advance, we allow the GA to evolve variable length individuals. Initially,each individual contains20randomly configured sensors.The maximum possible length of an individual is 100,indicating a maximum team size of100sensors. Multiple sensors in an individual may have the same location in the environment.When that occurs,thefirst (leftmost)sensor at a given location is active.The remaining are inactive and are unable to detect any radar;however,all sensors are included in the cost component of thefitness function.B.Fitness evaluationThefitness of each candidate solution generated by the GA is evaluated by inserting the solution(sensor team)in the test problem simulation and evaluating its performance within the simulation.Obstacles are not directly factored into thefitness evaluation.They indirectly affectfitness evaluation because an obstacle that intersects the direct line between a sensor and a radar will prevent that sensor from detecting the corresponding radar.Thefitness function consists of two components,the detection capability and the total cost of a solution.The fitness function is:(1) where is the rawfitness,is the detection capability, and is the total cost of a solution.To calculate,we count the number of radar that are fully,partially,and minimally detected.The detection capability is calculated by the following equation:Population size20Parent Selectionone-pointCrossover rate0.01(per gene)Deletion Mutation rate0.1(per individual)Max number of generations100TABLE IGA PARAMETER SETTINGS USED.and cover almost the entire working area.This configuration tests the algorithm’s ability to evolve solutions that provide maximum coverage of the working area.In the cluster configuration,enemy radar are randomly laid out in several clusters.This configuration tests the algorithms ability to focus on specific areas of the working area.Table I gives the GA parameter settings used in our ex-periments.These values were selected based on performance in previous experiments.We begin with the simplest case of one obstacle.A single rectangular obstacle is placed vertically down the middle of the environment,dividing the environment into two regions.An intuitive solution for this problem is to treat the two regions independently,positioning three sensors in each region.Recall that a minimum of three sensors are necessary to fully detect a radar.Figure7shows an example solution for the grid configuration.The GA does indeedfind a solution with six sensors that can fully detect all radar.Interestingly, however,the sensors do not focus solely on one region; four of the six sensors attempt to straddle both regions. Figure8shows the number of sensors evolved and the detection percentage averaged over100runs.The number of sensors levels off around seven for the best individual,which balances the minimum cost and the maximum detection.The best individual clearly achieves100%detection.We repeat this experiment in the cluster configuration. Figure9shows an example solution from the cluster experi-ments.The GA generates a team of six sensors that can fully detect all radar.Again,some sensors are arranged so that they straddle both halves.Figure10shows the average behavior over100runs.The number of sensors for the best individual levels off around seven and the detection percentage is100%. We test increasing numbers of obstacles in a variety of positions and sizes to increase the difficulty of the problem. Figure11shows some example results from two,three,and multiple obstacles experiments on both the grid and cluster configurations.In all cases,the GA is able tofind optimal or near-optimal solutions in which all or almost all radar are detected by at least three sensors.The most striking feature of these example results is how the GA minimizes the team size by consistently attemptingto arrange sensors close to the ends of the obstacles where they are more likely to be able to sense on both sides of an obstacle.In the two obstacle scenarios,sensors are arranged to take advantage of the small gap between the obstacles.As the number of obstacles increases,sensors are still arranged at locations where most can take advantage of a near-360degree detection range.Whereas the teams evolved in obstable free environments tended to place sensors centrally within clusters of radar,in these experiments,the GA does occasionally place sensors outside of the radar region to allow a sensors to“reach”around obstacles.In the more dense grid environment,increased team size is unavoidable as the number of obstacles increases.In the more sparse clustered environment,the GA is able to maintain team sizes close to six even in the multiple obstacle scenario.V.C ONCLUSIONWe apply a GA to the problem of designing teams of sensors that work together to detect and monitor multiple enemy radar.This problem is an important concern for electronic warfare support to aid in the detection,offensive, and assessment activities of electronic warfare.The GA evolves the count,placement,and characteristics of the sensors of a team.The goal of the GA is to design a team that maximizes the detection percentage while minimizing cost. Previous results indicate that a GA is able to successfully evolve efficient teams that can detect all or almost all radar. In this work,we test the effectiveness of the GA in more complex environments that include obstacles that can limit the detection capabilities of sensors.The sizes,locations,and the number of the obstacles affect the solutions generated by the GA.Although the detection percentage is robust to environmental changes,in terms of both the obstacle and radar configurations,the size of the evolved teams tends to increase with increasing size and number of obstacles. Emergent strategies of how the GA arranges sensors are interesting.The currentfitness function does not penalize for large detection angles.The GA takes advantage of this lack by favoring sensors with large detection angles.With no obstacles,the GA attempts to place sensors close to the center of all radar.This placement in combination with large detection angles maximizes the number of radar that a single sensor can detect.When there are obstacles in the environment,the GA either places sensors close to the center of a group of radar or at the corners of obstacles which allow the sensors to work on both sides of an obstacle.Both strategies are logical approaches to maximizing the efficiency of a sensor.A CKNOWLEDGEMENTSThis work is sponsored by the Naval Research Labora-tory,ITT Industries Incorporated,and the National Science Foundation.Fig.7.Example solution for experiments using long range sensors for the grid configuration with one obstacle.0 10 20 30 40 50 60 70 80L e n g t hGenerationsAverage of the 100 Runs - LengthP e r c e n t a g e o f D e t e c t i o nGenerationsAverage of the 100 Runs - Percentage of Detection Fig.8.Length (Number of sensors)and percentage of detection averaged over 100runs for long range sensors in the grid configuration with one obstacle.Fig.9.Example solutions for experiments using long range sensors for the cluster configuration with one obstacle.R EFERENCES[1]Karthik Balakrishnan and Vasant Honavar.On sensor evolution inrobotics.In Proc.1996Genetic Programming Conference ,1996.[2]M.D.Bugajska and A.C.Schultz.Co-evolution of form and functionin the design of autonomous agents:Micro air vehicle project.In GECCO-2000Workshop on Evolution of Sensors in Nature,Hardware and Simulation ,Las Vegas,NV ,2000.[3]M.D.Bugajska and A.C.Schultz.Co-evolution of form and function inthe design of micro air vehicles.In NASA/DoD Conference on Evolvable HW ,2002.[4] D.E.Goldberg.Genetic algorithms in Search,Optimization andMachine Learning .Addison-Wesley,1989.[5]John H.Holland.Adaptation in Natural and Artificial Systems .University of Michigan Press,Ann Arbor,MI,1975.[6]Ayse S.Yilmaz,Brian N.McQuay,Han Yu,Annie S.Wu,and John C.Sciortino,Jr.Evolving sensor suites for enemy radar detection.In Genetic and Evolutionary Computation Conference -GECCO 2003,volume 2724,pages 2384–2395.Springer Verlag,Berlin,2003.0 10 20 30 40 50 60 70 80L e n g t hGenerationsAverage of the 100 Runs - Length0 20 40 60 80 100P e r c e n t ag eofD e t e c t i o nGenerationsAverage of the 100 Runs - Percentage of Detection Fig.10.Length (Number of sensors)and percentage of detection averaged over 100runs for long range sensors in the cluster configuration with one obstacle.Two obstaclesThree obstacles Multiple obstaclesFig.11.Example results from experimental scenarios containing multiple obstacles.。