University of Central Florida at TRECVID 2006 High-Level Feature Extraction and Video Searc

第44卷　第4期2010年4月西　安　交　通　大　学　学　报JO URNA L OF XI ′AN JIAO TONG UN IVE RSITYVol .44　№4A pr .2010收稿日期:2009-09-02.　作者简介:温浩(1979-),男,博士生;郭崇慧(联系人),男,教授,博士生导师.　基金项目:国家自然科学基金资助项目(60802075).利用粒子群优化的人脸特征提取识别算法温浩1,郭崇慧2(1.西安电子科技大学综合业务网理论及关键技术国家重点实验室,710071,西安;2.大连理工大学系统工程研究所,116024,辽宁大连)摘要:针对如何提高人脸图像识别率问题,提出了利用粒子群优化(PSO )的人脸特征提取识别算法.采用小波变换和张量主成分分析(PCA )方法对人脸图像进行特征提取,利用PSO 对提取的特征进行加权处理,根据特征的每一维元素的聚类正确率进行优化选择,从而达到对人脸提取关键性特征的目的.实验结果表明,所提算法能减小光照、表情和姿态变化的影响,在英国曼彻斯特科技大学人脸数据库上的识别率比张量PCA 方法提高了12.75%.关键词:小波变换;张量主成分分析;粒子群优化;人脸识别中图分类号:TP391.41　文献标志码:A 文章编号:0253-987X (2010)04-0048-04Face Recognition with Features Extraction Based onParticle Swarm OptimizationW EN H ao 1,G UO Cho ng hui 2(1.S tate Key Lab oratory of Integrated S ervice Netw orks ,Xidian University ,Xi ′an 710071,China ;2.In stitu te ofSys tems Engineering ,Dalian University of T ech nology ,Dalian ,Liaoning 116024,Chin a )A bstract :A face recognitio n algo rithm w ith optim al features extraction based o n particle sw arm optimization (PSO )is propo sed to enhance the reco gnition rate .Features of each face image are e xtracted by using the w avele t transfo rmation and the tenso r principal component analy sis (PCA )algorithm .Weig hts of the features 'elements are then determined using PSO according to the right clustering rate o f each element ,so that the o bject to extract the key features o f the faces can be realized .Ex perimental re sults on the UM IS T database show that the impact of changes in ex -pression ,lig ht and posture can be reduced by the proposed alg orithm ,and that the recog nition ratio is increased by 12.75%co mpared w ith tenso r PCA .Keywords :w avelet transfo rm s ;tensor principal co mpo nent analy sis ;particle sw arm optimiza -tion ;face recog nition 人脸识别是模式识别领域的一个研究热点[1-2],并且具有广泛的应用前景.如何提取人脸图像的特征是人脸识别的关键因素.常用的人脸特征提取方法是基于统计特征的[2],其经典算法是主成分分析(PCA )方法[3].文献[4-5]针对PCA 提出了二维PCA (2DPCA )方法,近年来又出现了其他基于PCA 的改进方法,其中张量PCA (Tensor PCA )是一种效果较好的方法[6-7],文献[6]还证明了2DPCA 是张量PCA 的一种特例.如果直接对人脸图像进行特征提取,会受到光照不均、表情变化等因素的干扰,人脸图像的维数较高,还需做降维预处理.小波变换具有良好的局部时(空)频分析特性,具有下二采样性质[8],能够消除图像中的干扰,进行降维维护,所以被广泛应用于人脸图像的特征提取[9-10].研究发现,对所提特征的每一维元素赋予适当的权值,亦即进行优化选择,会进一步提高识别率,然而需要优化的权值较多,权值的数值变化规律难以用数学模型准确描述.如果采用人工试凑法或网格搜索法确定权值,计算量会很大,而且很难逼近最优解[11].粒子群优化算法(PSO)是一种全局搜索方法,它需要调节的参数少,无需考虑数据的维数和搜索模型的形式,能获得最优解[11].因此,本文提出基于PSO的有效人脸特征提取方法,即首先用小波和张量PCA提取人脸图像特征,然后用PSO对已提取的特征进行处理,以确定权值,从而达到人脸识别的目的.1　人脸图像特征提取原始人脸图像存在着光照、表情、饰物变化等因素的干扰[10],而且图像的维数比较高,要进行预处理,以降低图像的维数、消除干扰,因此需选用小波变换作为预处理工具.图像经过小波变换后得到4个子图:低频(LL)子图、垂直方向高频(LH)子图、水平方向高频(H L)子图和对角方向高频(H H)子图.每个子图的长宽为原图的1/2.后续的若干层小波变换都是基于上一层的LL子图进行的.图1给出了一个人的2幅人脸图像的原图和其一层小波变换的子图. (a)第1幅人脸原图　(b)图1a的L L子图 (c)第2幅人脸原图　(d)图1c的L L子图图1　一个人脸2幅图像及其上一层小波变换子图 从图1可以看出,这2幅原图有明显的饰物差别和细微的表情差异,但在LL子图中这些差别不明显.LL子图对原始图像的预处理效果比较好,所以本文只对LL子图做进一步的特征提取.为了得到有效的特征,可采用张量PCA方法提取LL子图的特征.张量PCA方法能够提取出图像的低维张量子空间特征,而在特征提取过程中却未破坏图像的几何空间结构,所以能获得比PCA方法和2DPCA 方法更好的特征提取效果[6].对于灰度图像的特征提取,张量PCA方法的基本思想可概括为:求解n个大小均为X i∈R C×H的图像(C和H分别表示图像X i的长和宽)投影矩阵U 和V(U∈R C×l,V∈R H×m),并通过投影矩阵对X i进行计算,得到一个新的二阶张量Y i=U T X i V∈R l×m(1) Y i∈R l×m(l和m分别表示矩阵Y i的行数和列数).设Y i的均值Y M=1n∑Y i,则Y i和Y M满足max∑ni=1‖Y i-Y M‖=∑ni=1U T X i V-1n∑ni=1U T X i V(2)其中U、V的最佳解为U＊、V＊,U＊、V＊可通过迭代计算得到(文献[6,12-13]给出了U＊、V＊的求解过程).设{X TR i i=1,…,n}为经过预处理的训练样本图像集,n为训练样本数;{X TE j j=1,…,m}为经过预处理的测试样本图像集,m为测试样本数.据此,本文张量PCA方法的特征提取过程可概括为:根据{X TR i i=1,…,n},得到投影矩阵U＊、V＊;按照式(1)对{X TR i i=1,…,n}中的每一幅图像进行计算,得到训练样本特征矩阵集合{Y TR i i=1,…,n};对{X TE j j=1,…,m},利用U＊、V＊按照式(1)进行相应计算,得到测试样本特征矩阵集合{Y TE j j= 1,…,m}.2　基于PSO的特征优化选择经过特征提取后得到的特征中的每一维元素在识别中所起的作用有所不同,对这些元素赋予适当的权值可以进一步提高识别率.由于权值的个数与任意特征矩阵中的元素个数相同,所以权值可以矩阵形式记为W,而W的最优解为W＊.W中的元素个数很多,W和W＊之间也没有确切的数学模型来描述,所以利用传统的人工试凑法和网格搜索法很难找到最优解,为此本文采用粒子群优化算法(PSO)来获得W＊.PSO算法确定W＊的基本思想为:设m个粒子{Z1,Z2,…,Z m}在与W的维数相同的空间中进行搜索,每个粒子Z i的位置为W的一个解,即Z i的位置是和W的维数相同的矩阵;根据每个粒子的位置来确定该粒子的适应度函数值.粒子适应度函数值的确定方法如下:首先用{Y TR i i=1,…,n}的每一49　第4期 温浩,等:利用粒子群优化的人脸特征提取识别算法个元素和对应Z i 位置的每一维元素相乘,记为W ·×Y TR i (“·×”表示矩阵W 的每一维元素和Y TR i 中的每一维元素相乘,W ·×Y TR i 的维数与Y TR i 的维数相同);然后对此时的W ·×Y TR i 进行聚类,得到训练样本的聚类正确率.其实,粒子Z i 的适应度函数值就是聚类正确率,每个粒子在自身求解过程中得到的最好适应度所对应的粒子的位置为局部最优解(记为p id ),所有粒子在局部最优解中的最高适应度值所对应的解为全局最优解(记为p d ),每个粒子的运动速度为{V 1,V 2,…,V m }(V i 也是与W 的维数相同的矩阵).传统的粒子群算法一般通过迭代来调整每个粒子的速度和位置,即v id (t +1)=wv id (t )+η1r 1(p id -z id (t ))+η2r 2(p d -z id (t ))(3)z id (t +1)=z id (t )+v id (t +1)(4)式中:v id (t +1)为第i 个粒子的速度在t +1次迭代中的第d 维的元素值;z id (t +1)为第i 个粒子的位置在t +1次迭代中第d 维的元素值;w 为惯性权重;η1、η2为常数;r 1、r 2为0～1之间的随机数.为防止PSO 算法出现早熟或陷入局部极小化,本文参照文献[14]给出PSO 粒子速度更新公式,即v id (t +1)=wv id (t )+η1r 1(p b -p id (t ))+η2r 2(p g -p id (t ))+η3r 3(p a -p id (t ))(5)w =w max -tw max -w min8(6)式(5)中:p a 项为粒子当前局部最优解的平均值[14],利用它可防止PSO 算法出现早熟或陷入局部极小化;p b 为粒子当前局部最优解.本文设置w max 为1,w min 为0,这样可以使粒子初始时在较大的数值范围进行搜索,接近最优解时在较小的数值范围进行搜索.根据经验,η1～η3为2,r 1～r 2为0～1的随机数.w 的范围为[0,1],如果w 的某一维值在迭代过程中大于1或小于0,则置为1或0.当所有粒子迭代完成后,或者其位置不再发生变化,此时得到的p g 即为所求的最优解W ＊.最优权值W ＊确定后,{Y TR i i =1,…,n }的每一维值和对应权值相乘便得到W ＊·×Y TR i ,同样利用{Y TE j j =1,…,m }可得到W ＊·×Y TE j .训练样本图像特征矩阵与测试样本图像特征矩阵之间的距离为D =dis (W ＊·×Y TE j ,W ＊·×Y TR i )(7)其中dis (·)算子的计算方法如下.假设X ∈RC ×H,Y ∈RC ×H ,则有dis (X ,Y )=∑C i =1∑H j =1(x ij -y ij )21/2(8)根据式(8)采用最近邻方法便可进行图像特征识别.3　实验结果与分析本文在ORL 、UM IS T 和自建库上进行了对比实验,对比的算法包括:本文算法(算法1)、张量PCA 算法(算法2)、结合小波变换和张量的PCA 算法(算法3).实验环境:IBM R51e 笔记本电脑.编程语言:M A TLAB7.4.3.1　ORL 库上的实验结果与分析ORL 库是英国剑桥大学制作的,其中包含40个人,每人10幅112×92像素的人脸图像,每张图像有表情、姿态、光照和角度的变化.本文从每个人中随机选取5幅或8幅图像组成训练样本集,余下的图像作为测试样本集.实验进行了10次,最后的识别率为10次实验结果的平均值,如表1所示.表1　ORL 库上不同算法的识别率比较算法训练样本数特征维数识别率/%算法15814×63×1096.7399.63算法2584×25×793.3097.25算法3585×1115×793.7598.83由表1可见,本文算法的识别率大于其他2种相关算法,算法3的识别率高于算法2的识别率.可见,对图像进行小波变换能起到良好的预处理效果,而在此基础上进行PSO 调节权值可进一步提高识别率.当训练样本为5时,本文方法的识别率达到了96.73%;当训练样本为8时,本文方法的识别率接近100%.3.2　UMIST 库上的实验结果与分析UMIST 库由英国曼彻斯特科技大学制作,该库包含20个人的信息.本文把每个人中的前20幅图像归一化为112×92像素进行实验,并随机选取前20幅图像中的10幅或16幅进行训练,剩余的图像作为测试所用,最终的识别率为10次实验结果的平均值,如表2所示.可以看出,表2中的识别率比表1中的低,尤其是在训练样本数较少的情况下.这是因为:UM IS T 库中的图像角度变化非常大,每个人的前10幅图像可以看作是人脸正面图像,而后10幅图像可以看作是人脸侧面图像.从表2还可以看出,算法1在10个训练样本时的识别率仍然比其他2种算法高,比50西　安　交　通　大　学　学　报 第44卷　算法2提高了12.78%,比算法3提高了8.28%,可见本文算法能较好地抗角度变化的干扰.3.3　自建库上的实验结果与分析自建库是笔者从所在的实验室采集制作的,共11个人,每个人有6幅520×400像素的人脸图像,每张图像的表情、角度和饰物都有变化.本文采用2折交叉验证算法进行实验,结果如表3所示.表2　UM IS T库上不同算法的实验结果方法训练样本数特征维数识别率/%算法1101615×210×588.5399.50算法210168×312×375.7595.02算法310164×62×1080.2596.70表3　自建库上不同算法的实验结果方法训练样本数特征维数识别率/%算法134×4987.87算法235×1081.80算法337×983.33从表3可以看出,在自建库上算法的识别率较低.这是因为:自建库中人脸图像的表情、姿势、角度、饰物变化很大,而且训练样本数比较少.但是,算法1的识别率仍然比其他2种算法高,相对于算法2、算法3识别率分别提高了7.07%和4.54%.4　结束语人脸识别是模式识别学科中的研究热点.如何有效地对人脸图像进行特征提取是人脸识别的关键.本文提出了一种新的人脸识别方法,其结合了小波变换、PSO算法、张量PCA算法,对人脸图像能够提取出可有效识别的关键特征.在ORL库、UM IS T库和自建库上的实验表明,本文算法获得了比较高的识别率,特别是在UM IS T库上,识别率比算法2提高了12.75%.参考文献:[1]　CH EL LA PP A R,W LSO N C L,SRO HEY S.H umanand machine recog nitio n o f faces:a survey[J].P rocI EEE,1995,83(5):705-740.[2]　刘青山,卢汉青,马颂德.综述人脸识别中的子空间方法[J].自动化学报,2003,29(16):900-911.LI U Qing shan,L U H anqing,M A So ng de.A surv ey:subspace analy sis fo r face recog nitio n[J].Acta A uto-ma tica Sinica,2003,29(16):900-911.[3]　高全学,潘泉,梁彦,等.基于描述特征的人脸识别研究[J].自动化学报,2006,32(3):386-391.G A O Q uanxue,P AN Q ua n,LIA N G Y an,et al.Facerecog nitio n based on ex pressive fea tur es[J].Acta Au-tomatica Sinica,2006,32(3):386-391.[4]　YA NG Jian,ZH A NG D,A LEJAN D F,et al.T wo-dime nsio nal PCA:a new approach to appeara nce-ba sedface re pre sentatio n and recog nitio n[J].IEEE T ranson P attern A naly sis and M achine Inte lligence,2004,26(1):131-137.[5]　YA N G Jian,LI U Cheng jun.Ho rizontal and ve rtical2DP CA-based discriminate analy sis fo r face ve rificationon a la rge-scale database[J]IEEE T ra ns o n I nfo rma-tion Fo rensics and Security,2007,2(4):781-792. [6]　XU Do ng,Y AN Shuicheng,Z HA NG Lei.Concur rentsubspace analy sis[C]∥P ro ceedings o f the2005IEEECo mputer So ciety Co nference o n Co mputer Visio n a ndPat te rn Reco gnition.Piscataw ay,N J,U SA:IEEE,2005:203-208.[7]　Z H AN G Xinsheng,G A O Xinbo,WA N G Y ing.M i-c rocalcification clusters detection w ith tenso r subspacelear ning and twin SV M s[C]∥I EEE P ro ceedings o fthe7th Wo rld Cong ress on Inte lligent Co ntro l and Au-tomatio n.Piscataw ay,N J,U SA:I EEE,2008:1758-1763.[8]　M A L LA T S G.A theor y for multiresolution sig nal de-co mpo sitio n the wavelet represe ntation[J].IEEET r ans on Pat te rn Analy sis and M achine I ntellig ence,1989,11(7):674-693.[9]　ZH A NG G uo yun,PENG Shiy u,LI Ho ng bi-natio n of dual-tree co mplex wav elet and SV M for facerecog nitio n[C]∥IEEE P roceeding s o f the7th Inter na-tional Co nfere nce o n M achine Lear ning and Cyber net-ics.Piscataw ay,N J,U SA:IEEE,2008:2815-2819.[10]Z HO U Xiaofei,SH I Yong.A ffine subspace nea restpo ints classificatio n algo rithm fo r wave let face reco gni-tion[C]∥IEEE W or ld Co ng re ss o n Co mputer Scienceand Infor mation Enginee ring.Piscataway,N J,US A:IEEE,2009:684-688.[11]EBERHA RT R C,K EN NEY J.A new optimizerusing particle swar m theory[C]∥P ro ceeding o f the6th I nter national Sympo sium on M icr o M achine a ndHuman Scie nce.Pisca taw ay,N J,US A:I EEE,1995:39-43.(下转第118页)51　第4期 温浩,等:利用粒子群优化的人脸特征提取识别算法除眼电伪差效果比较好的方法进一步去除眼电伪差干扰,这也是今后的研究内容之一.参考文献:[1]　G RA T T O N G,CO L ES M G,DO NC HIN E.A newmethod for off-line remo val o f o cular ar tifact[J].Elec-tro encephalog raphy&Clinica l N euro physio lo gy,1983,55(4):486-484.[2]　高军峰,郑崇勋,王沛.基于独立成分分析和流形学习的眼电伪差去除[J].西安交通大学学报,2010,44(2):113-118.G AO Junfeng,Z H EN G Cho ngx un,W AN G Pei.ICAand manifo ld-based ocular a rtifacts remov al[J].Jour-nal of Xi′an Jiaoto ng Univ ersity,2010,44(2):113-118.[3]　U R RES T A RAZ U E,I RIA RT E J,A LEG RE M,e t al.Independent co mpo nent analy sis remo ving artifacts inictal recor ding s[J].Epilepsia,2004,45(9):1071-1078.[4]　A M A RI S,CICH OCK I A,Y AN G H H.A newlea rning alg orithm for blind sig nal separa tion[M].Cambridge,M A,U SA:M I T P ress,1996:757-763.[5]　M A K EIG S,BEL L A J,JU N G T P,et al.Independ-ent compone nt analy sis o f electr oencepha lg raphic data[M].Cambridg e,M A,U SA:M IT P ress,1996:145-151.[6]　V ERG U LT A,CL ERCQ W D,P A LM I NI A,et al.Impro ving the interpreta tion o f icta l scalp EEG:BSS-CCA algo rithm fo r muscle artifac t removal[J].Epi-lepsia,2007,48(5):950-958.[7]　周仲兴,明东,朱誉环,等.基于扩展Infor max ICA的站起想象动作脑电特征提取[J].仪器仪表学报,2009,30(3):459-464.Z HO U Zho ng xing,M IN G Do ng,Z H U Y uhuan,etal.EEG feature ex traction fo r imag inary standing upbased o n ex tended Info rmax independent componentanalysis[J].Chinese Journal o f Scientific Instrume nt,2009,30(3):459-464.[8]　S HA O Shiy un,S HEN Kaiquan,ON G C J,et al.Au-to matic EEG ar tifact remova l:a w eighted suppo rt vec-to r machine appro ach w ith e rro r co r rection[J].IEEET ransactions o n Bio medical Eng ineering,2009,56(2):336-344.[9]　JUN G T P,M A K EIG S,H UM PH RIES C et al.Re-mo ving e lectroe ncephalog raphic ar tifacts by blindso urce separa tion[J].P sy chophy siolog y,2000,37: 163-178.[10]C LERCQ W D,VERG U L T A,V A N RU M ST E B,etal.Cano nical co rrelatio n analy sis applied to remov emuscle a rtifacts fr om the electroencephalog ram[J].IEEE T ransactions o n Biomedical Engineering,2006,53(12):2583-2587.[11]D ELO RM E A,M A K EIG S.EEG LA B:an o penso urce toolbox for a naly sis of sing le-trial EEG dy nam-ics including independent co mpo nent analy sis[J].Jo urnal o f N euro science M ethods,2004,134(1):9-21.(编辑　杜秀杰)(上接第51页)[12]H E Xiaofei,CA I Deng,N IY OG I P.Tensor subspaceanaly sis[M]∥A dvance in Neural I nfo rmatio n P ro-cessing Sy stem18.Cambridge,M A,U SA:M I T,2006:249-256.[13]T A O Dacheng,LI Xeuho ng,W U Xindong,e t al.General tensor discriminant analysis and G abor fea-tures for g ait recog nition[J].IEEE T rans on Patter nA naly sis and M achine Intellige nce,2007,29(10):1700-1715.[14]王峰,刑科义,徐小平.系统辩识的粒子群优化方法[J].西安交通大学学报,2009,43(2):116-120.WA NG Feng,XIN G K eyi,X U Xiao ping.A sy stemidentifica tion metho d using pa rticle sw arm optimization[J].Jo urnal o f Xi′an Jiao to ng Unive rsity,2009,43(2):116-120.(编辑　苗凌)118西　安　交　通　大　学　学　报 第44卷　。

万方数据万方数据万方数据第１期黄波：基于多尺度自卷积归一化直方图的仿射不变量模式识别６７５仿真实验分析及结果实验中ＭＳＡｇｈｉｓｔ，ＭＳＡ｝ｌｉｓｔ和ＭＳＡｔｈｉｓｔ分别使用相同的３对参数（口，口）＝｛（一ｌ，１），（一０．４，０．４），（０．２，０．４）｝构造４５个特征值；由于ＭＳＡ的参数选择和识别率间没有明确关系，为了较全面的体现ＭＳＡ的性能，本文比较ＭＳＡ在两组参数下的错误识别率，其中一组为文献［１４］中提供的２９对参数，另一组为从文献［１４］中的（口，口）最小平面中选择的１３对参数，分别表示为ＭＳＡ２９和ＭＳＡｌ３，其中１３对参数为（口，口）＝｛（一ｌ，１），（一０．８，０．８），（一０．６，０．６），（一０．６，０．８），（一０．４，０．６），（一０．４，０．４），（一０．２，０．２），（一０．２，０．４），（一０．２，０．６），（０，０．２），（０，０．４），（０．２，０．２），（０．２，０．４）｝．本文采用互相关系数表示目标的相似程度，作为分类依据，互相关系数值最大的两个目标即视为同一目标．实验ｌ以ＭａｒｉａＰｅｔｒｏｕ提供的“ｆｉｓｈ”测试数据库【２１Ｊ为学习样本，测试ＭＳＡｇｈｉ，ｔ，ＭＳＡｔｈｉｓｔ和ＭＳＡ在目标图像受噪声，遮挡和光照变化条件下产生形变时的错误识别率．实验中没有加入ＭＳＡｈｉｓｔ的比较，因为图像变形较大时，其错误识别率高．从“ｆｉｓｈ”数据库中选取有代表性的１５种鱼｝冬Ｉ像，对它们进行１０种随机仿射变换，得到１５０幅鱼图像仿射变换形式的样本图像，部分原始鱼图像如图ｌ（口）．在样本图像中加入零均值高斯噪声，通过改变噪声的方差ｔ，值来模拟图像受噪声干扰时的变形程度，加入噪声后的部分测试样本如图ｌ（ｂ），噪声对识别率的影响如图２（口）．在样本图像七随机放置尺寸为ｄ×ｄ，各点灰度值为１２８的方块模拟遮挡物，方块覆盖鱼体的面积尽量大，以增加识别的难度，加入遮挡后的部分测试样本如图ｌ（ｃ），不同遮挡尺寸ｄ对识别率的影响如图２（６）．照度的变化体现在图像上为灰度值的变化，均匀增减目标像素灰度值模拟图像受均匀照度影响的情况，或以图像中心为起始点线性增加目标像素点灰度圈１目标图像样本亮度仿变化Ｃ（口）亮度均匀变化丰¨铺误识别率关系高Ｊ堑仇变化斜率Ｓ（６）亮度ＩＩ线ｒ｝变化年¨锵墩识别率关系圈３照废变化下的错误识别睾万方数据电子学报２０１１年值模拟图像受非线性照度影响的情况．均匀变化值ｃ、线性斜率ｓ与识别率的关系分别如图３（口）和３（６）．实验２以“ｃｏｉｌ．１００”数据库－２２ｊ为实验样本，测试纯视角变化对ＭＳＡ小ｓｔ，ＭＳＡｈｉｓｔ，ＮＳＡｆｌｌｉｓｔ和ＭＳＡ识别率的影响．“ｃｏｉｌ一１００”数据库中包含１００种不同目标，每种目标包含不同角下度获取的７２幅图像，角度间隔为５０．在“ｃｏｉｌ．１００”数据库中选取视角为酽一３５。

✧重要引用论文2011.07 DWW Paper reference◆(reference) Extending GIS-based visual analysis the concept of visual scapes(非reference)A comparison of algorithms used to compute hill slope as a property of the DEM（非reference)Re-presenting GIS（非reference）The Landscape of Parallel Computing Research（非reference）Modelling the Continuity of Surface Form Using Digital Elevation Models（非reference）VIEWSHED ANALYSIS AND VISUALIZA TION OF LANDSCAPE VOXEL MODELSBuilding Past Landscape Perception With GIS Understanding Topographic ProminenceEstimating visual properties of Rocky Mountain landscapes using gisFirst experiments in viewshed uncertainty simulating fuzzy viewshedsGIS approaches to regional analysis: A case study of the island of HvarIntervisibility on terrainsModelling Environmental Cognition of the View With GISSpatial Analysis of Visible Areas from the Bronze Age Cairns of MullTailoring GIS Software for Archaeological Applications: An Example Concerning Viewshed AnalysisVision, Perception and GIS developing enriched approaches to the study of archaeological visibility 对DEM的功能之一：计算山体坡度的算法比较（关键词kw：坡度，梯度，立面，山坡线，DEM）重新解读GIS计算机并行处理的特点（06年写的，双核处理器刚刚做出来）用DEM做出连贯的表皮模型（kw：DEM, 复杂的表皮结构，形态学）可视域分析和voxel体素景观模型的实现深入了解地形地貌：地形学的重要性（kw: GIS, 地形研究，平价，认知）利用GIS分析落基山脉的可视地形特征（kw: GIS，视野分析的，景观模型，）对视野分析不确定性的开创性实验：导致模糊视野分析GIS应用于区域分析；对HA VR岛的案例分析不同地域的互见度以GIS为工具的视图的环境意识建模英国Mull岛青铜时代石冢群的视域分析修改GIS软件以适应考古应用：一个可视域分析的例子（kw: 编程，打猎者，中石器时代南赫布里底群岛研究项目）视界，感官与GIS开发：为考古可视性研究探索新的方法◆(reference) Viewsphere a GIS-based 3D visibility analysis(非reference)a method for estimating changes in the visibility of land cover(非reference)Analysing Mental Geography of Residential Environment in Singapore using GIS-based 3D Visibility AnalysisA 3D-GIS EXTENSION FOR SKY VIEW FACTORS ASSESSMENT IN URBAN ENVIRONMENTGeographic Information Systems and ScienceSpace is the Machine A Configurational Theory of ArchitectureStreet Design and Urban Canopy Layer Climateusing arcgis 3d analysis(说明书) 估量土地覆盖可视化的变化的一个方法(kw: 视觉资源，视觉影响，空间分析)应用三维可视性分析方法分析新加坡居民对其居住环境的感知（空间感知，环境光阵，公众住房）拓展三维GIS以评估城市环境中影响天空视角的因素地理信息系统和科学空间一种机器：建筑学的构造理论街道设计和城市上空表层气候三维曲线GIS 使用分析◆Benedikt M.L.-To take hold of space: isovists and isovist fields对空间的有效利用Isovist: 从空间中某一点所能看到的一组点点和他们与环境的关系Isovist fields：视区？◆Extending GIS-based visual analysis the concept of visualscapes 对基于GIS的视觉分析的延展：“可视景观”概念的提出◆Perry Pei-Ju Y ang_Viewsphere a GIS-based 3D visibility analysis for urbandesign evaluation视觉球体：基于GIS的用于城市设计评估的三维可视性分析WebA Tour through the Visualization ZooHome §Center for Geographic Analysis, Harvard UniversityMIT SENSEable City LabPicturing Usenet：Mapping Computer-Mediated Collective ActionProfessor Howard T aylor Fisher 穿过想象的世界（把想象形象化，很混乱）哈佛大学地理分析主页和中心麻省理工可感知的城市实验室刻画用户交流网：绘制以计算机为媒介的群体活动Howard T aylor Fisher教授的简介Visualization (computer graphics) - wiki 可视化（电脑制图学）--维基百科✧AlgorithmAlgorithms for the Automatic Generation of Urban Streets and Buildings自动生成城市街道和建筑的算法✧Fractal-techAssessing urban character: the use of fractal analysis of street edgesFractal analysis of street vistas: a potential tool for assessing levels of visual variety in everyday street scenespdf名：Pierre F_2004Cost10fractales Comparing the morphology of urban patterns in Europe –a fractal approach Fractals, skylines, nature and beauty 分析城市特征：街道边缘的分形分析街道深景的分形分析：衡量日常街道场景的不同可视程度的一个可能的工具比较欧洲城市布局的形态学-- 一个分形分析方法分形，天际线，自然，美观✧GIS-Viewshed （Gis可视域）Exploring multiple viewshed analysis using terrain features and optimisation techniquesViewshed characteristics of urban pedestrian trails, Indianapolis, Indiana, USA 利用地区特征和优化技术探索多种可视域分析方法城市人行道的可视域特征，印第安纳波利斯，印第安纳，美国✧Mapping-tech （绘图技术）Eidetic Operations and New LandscapesPdf名：ackerson_thesisA GIS Approach to Evaluating Streetscape and Neighborhood Walkabilitycorner_agency_of_mapping：Pdf名字：papers_longpapers_004 - Peponis Allen French Scoppa BrownSTREET CONNECTIVITY AND URBAN 逼真的操作及新的景观学用GIS的方法衡量街景和住宅区的行走便利程度绘图的作用：猜想，批判和探索（XXX和XXX的长篇论文）街道连接和城市密度：空间测量方法和他DENSITY: spatial measures and their correlationSergio--Linking urban design to sustainability: formal indicators of social urban sustainability field research in Perth, Western AustraliaSpatial Metrics and Image Texture for Mapping Urban Land Use 们的相互关系Sergio写的-- 结合城市设计与可持续发展：社会城市可持续发展的布局整齐的指示物，对西奥地利波斯的实地考察空间度量学和图像结构绘制城市用地图✧Rast- DIM-tech （光栅DIM技术）21st Century Milan: using new image processing techniques to assess the environmental quality of the Milan Trade Fair masterplanRaster analysis of urban formRaster analysis of urban formThe lineage of the line: space syntax parameters from the analysis of urban DEMsTucker C_etc_2005Spatial configuration within residential facadesUrban Texture Analysis with Image Processing TechniquesURBAN TEXTURE ANAL YSIS 二十一世纪的米兰：利用新的图像处理技术评估米兰商品交易会的总平面图的环境质量城市形式的光栅分析同上线条的来源：城市dem（数字高程模型）分析而得出的空间句法的限定性因素住宅正面的空间构造利用图像处理技术分析城市结构城市结构分析✧SOI-IsovistA digital image of the city-3D isovists in Lynch's urban analysisBatty M._Exploring isovist fields: space and shape in architectural and urban morphologyBenedikt M.L.-To take hold of space isovists Lynch城市分析的三维城市视区电子图像探索“视区”：建筑和城市形态学里的空间和形状掌握空间视点和视区and isovist fieldsDafna Fisher-Gewirtzman Spatial openness as a practical metric for evaluating built-up environmentsDafna Fisher-Gewirtzman_A 3-D visual method for comparative evaluation of dense built-up environmentsDafna Fisher-Gewirtzman_Spatial openness as a practical metric for evaluating built-up environmentsDafna Fisher-Gewirtzman_View-oriented three-dimensional visual analysis modelsExploring isovist fields space and shape in architectural and urban morphologyM. LLOBERA_Extending GIS-based visual analysis：the concept of visualscapes (Geographical Information ScienceMaking isovists syntactic_ isovist integration analysisMeasuring_Surrounding_Space_to_Assess_t he_Pedestrian_Visual_Aperture_Angle_in_th e_Urban_Fabric_-_Toward_a_Kurtosis-Base d_Isovist_IndicatorMorello_Ratti__A Digital Image of the City：3D isovists in Lynch's urban analysis Osmond P_2009APPLICA TION OF NEAR-INFRARED HEMISPHERICAL PHOTOGRAPHYTO ESTIMA TE LEAF AREA INDEX OF URBAN VEGETA TIONPerry Pei-Ju Yang _Computing the sense of time in urban physical environment Gewirtzman （这是一个德国人）的空间开放性作为一个实用的度量方式来评价建筑环境一个三维可视方法相对地评估建筑物密集的环境Gewirtzman的空间开放性作为一个实用的度量方式来评价建筑环境基于视图的三维视景分析模型探索“视区”：建筑和城市形态学里的空间和形状拓展基于GIS的视觉分析：“可视景观”概念的提出（地理信息系统）使“视点”符合句法，整合视点分析测量周围空间来估计城市结构中步行者的视觉光圈（穿孔，缝隙）角度--引向一个基于峰度的视点指示物一个城市的电子图像：林钦城市分析的的三维视点群近红外半球形摄影术的应用：估算城市植被树叶区的指数计算城市自然环境的时间感Perry Pei-Ju Y ang_Viewsphere a GIS-based 3D visibility analysis for urban design evaluationUsing the spatial openness metric for comparative evaluation of urban environmentsSOI：A Graphic Tool For Calculating Spatial Openness IndexIsovists, enclosure, and permeability theoryStamps-Isovists, enclosure, and permeability theoryTeller_A spherical metric for the field-oriented analysis of complex urban open spacesTucker C_A method for the visual analysis of the streetscapeTurner A _Analysing the visual dynamics of spatial morphologyTurner A, Penn A_Making isovists syntactic isovist integration analysisTurner A_From isovists to visibility graphs：a methodology for the analysis of architectural space 基于GIS的对评估城市设计的三维可视分析利用空间开放性度量方式比较评估城市环境计算空间开放指数的图表工具视点，封闭区，渗透性理论同上用于对复杂城市开放空间做侧重实地作业的分析的一个球面度量方式街景视觉分析的一个方法空间形态学的视觉动态分析使“视点”符合句法，整合视点分析从视点到可视性图表：建筑空间分析的方法论Space Syntax 空间句法The automatic definition and generation of axial lines and axial mapsDursun P-SPACE SYNTAX IN ARCHITECTURAL DESIGNItzhak O_Bin J_08Topological Qualities of Urban Streets and 自动清晰化和生成轴线和轴状图建筑设计中的空间句法城市街道和城市映像的拓扑质量：一个多the Image of the City: A Multi-Perspective ApproachJiang B _Chengke L_07Street-based Topological Representations and Analyses for Predicting Traffic Flow in GISJiang B_09The Image of the City: From the Medial Axes to the Axial LinesJiang B_T-GIS2002-295-309Lucas F_ Luiz A_08Decoding the urban grid: or why cities are neither trees nor perfect gridsLucas F_2006Continuity lines in the axial systemPORTA S-THE NETWORK ANALYSIS OF URBAN STREETS A PRIMAL APPROACHRatti C_Urban texture and space syntax: some inconsistenciesThe Image of the City From the Medial Axes to the Axial LinesTopological Qualities of Urban Streets and the Image of the City A Multi-Perspective Approach 角度方法基于街道的拓扑重现与在GIS里的交通流预测分析城市映像：从中轴线到轴向线把空间句法整合入GIS：城市形态学新认识解码城市网格：为什么城市既不是树状结构也不是理想的网状结构？轴向系统中的连续线条城市街道的网格分析：一个原始构想城市结构和空间句法：一些矛盾的地方城市映像：从中轴线到轴向线城市街道和城市映像的拓扑质量：一个多角度方法Urban 3D Model 城市三维模型3D urban models_ Recent developments in the digital modelling of urban environments in three-dimensions3D-GIS for Urban PurposesAN INTEGRA TED SYSTEM FOR URBAN MODEL GENERA TION 城市环境三维电子模型的发展近况三维DIS的城市用途生成城市模型的一个完整系统Binary Encoding of a Class of Rectangular Built-FormsElements of a representation framework for performance-based designThree Dimensional Information Visualisation 一类三角形建筑形式的二进制编码基于绩效的设计中表现构架的元素三维信息形象化Urban Form 城市形式Dela21-2004-41-52FROM URBAN FORM TO URBAN RELA TIONS:IN SEARCH FOR A NEW KIND OF REFLEXIVE AND CRITICAL KNOWLEDGE IN URBAN GEOGRAPHY AND CITY MONITORINGmethod-reading citypattern 2：Shopping StreetsUrban Pattern Specification 从城市形式到城市关系：寻找一种新的城市地理和监控系统的自反性批判性知识方法论—解读城市形态2：购物街城市形态详细说明。

地理专业词汇英语翻译(U地理专业词汇英语翻译(U-Z)地理专业词汇英语翻译(U-Z)u shaped valleyu形谷ubiquists随遇植物udalf湿淋溶土udershrub小灌木udert湿变性土udoll湿软土udometer雨量器udult湿老成土ulexite钠硼解石ullmannite锑硫镍矿ulmic acid棕腐酸ulmin棕腐质ultimate form终地形ultimate plain终平原ultimate wilting point极限凋萎点ultisol老成土ultra microchemistry超微量化学ultrabasic rock超基性岩ultraclay超粘土ultrafiltration超滤ultrafine dust超细粉末ultramafic rock超基性岩ultrametamorphism超变质ultramicrofossil微化石ultramicroscope超显微镜ultraplankton超微浮游生物ultraviolet image紫外影像ultraviolet microscope紫外线显微镜ultraviolet radiation紫外线辐射ultraviolet spectroscopy紫外线光谱学ultraviolet spectrum紫外线光谱umbraquult暗色潮老成土umbrept暗始成土umbric epipedon暗色表层unavialable water无效水uncomformity不整合unconditioned reflex非条件反射unconformity不整合unconformity spring不整合泉unconscious selection无意识的选择uncontaminated soil未污染土壤undefined structure无定型结构under soil心土underclay底粘土undercurrent暗流undercut slope暗掘坡underdevelopment显影不足underdrainage地下排水underexposure曝光不足underflow潜流underground flow地下水流underground part地下部underground resources地下资源underground river地下河underground water潜水undergrowth林下植物underlying bed下伏层underrun潜流undershrub小灌木丛undersize筛下产品underthrust俯冲断层underwater acoustics水中声学underwater camera水下照相机underwater television水下电视undifferentiated alluvium均匀冲积物undisturbed sample原状试样undulant fever布鲁菌病undulating land波状土地undulation波动undulation of the geoid大地水准面起伏undulatory movements波形运动uneven settlement不均匀沉降unfilled porosity非饱和孔隙度unfixed soil非固定土壤ungulates有蹄类unhumified organic matter未腐解有机物质uniaxial volcano单轴火山uniform development均匀发育uniform flow等速流uniform motion匀速运动uniform profile均质剖面uniformitarianism均变说uniformity coefficient均匀性系数unirrigated soil非灌溉土壤unit area单位面积unit cell单位晶格unit of enzyme酶单位unit value of symbol地图符号价值单位unit weight单位重量unity整体universal theodolite万能经纬仪universal time世界时universal transverse mercator projection通用横墨卡托投影universe宇宙unpaired electron不成对电子unproductive soil不毛之土壤unsaturated rock不饱和岩unsaturated soil不饱和土壤unsaturated solution不饱和溶液unstable channel不稳定河槽unstable equilibrium不稳定平衡unstable isotope不稳定同位素unstable stratification不稳定层结unsymmetrical fold不对称褶皱unweathered mineral soil未风化矿质土壤updraft向上气流upheaval隆起uphill sloping profile升坡剖面upland高地upland moor高位沼泽upland savanna高地热带琉林uplide motion上滑运动upper air observation高空气象观测upper atmosphere高层大气upper clouds高云upper crust上地壳upper culmination上中天upper layer clouds上层云upper mantle上地幔upper pool上水池upper pool elevation上游水位upper trade高空信风upper wind observation高空风测upright fold直立褶皱uprise of salts盐分上升uprooting挖除伐根upslope fog上坡雾upstream deposits上游沉积物upstream facing of weir堰的上游护面upthrow fault上投断层upthrow side上投侧upthrust fault上投断层upward evolution of relief地形的隆起演化upward movement of water水分上升运动upwarping向上挠曲uraninite沥青铀矿uranite铀云母uranium铀uranium deposit铀矿床uranium mine铀矿uranium ore铀矿uranocircite钡铀云母uranophane硅钙铀矿uranopilite铀钙矿uranothorite铀钍矿uranyl compound铀酰化合物urban agglomeration城市群urban ecological system城市生态系统urban environment城市环境urban function城市功能urban information system城市信息系统urban morphology城市形态urban photogrammetry城市摄影测量urban planning城市规划urban planning information system城市规划信息系统urban remote sensing城市遥感urban sewage城市污水urban size城市规模urbanization城市化urea尿素usefull mineral有用矿物ustalf干淋溶土ustert干变性土ustoll干软土ustox干氧化土ustult干老成土uvala坞洼uvanite钒铀矿vacant field空地vacant lattice site未填满晶格结点vaccin菌苗vacuum frame抽气晒版机vadose water渗廉valence原子价valence crystal价晶格valence electron价电子valency原子价valent state价态valentinite锑华valley谷valley bog河地沼泽valley bottom谷底valley breeze谷风valley fill河谷填积valley fog谷雾valley glacier谷冰川valley in valley谷中谷valley pattern河谷型valley slope河谷坡降valley water divide河谷分水界valuation评价value值value class数值等级vanadite钒铅锌矿vanadium钒vanadium pollution钒污染vapor pressure deficit饱和差vaporous water气态水variability变异性variability index变化指数variable变量variable standardization变量标准化variable wind转向风variance方差variance analysis方差分析variant of association变异群落variation变异variation diagram变化图variation of latitude纬度变化variegated sandstone杂色砂岩variegation彩斑variety变种variogram变量图variolite球颗玄武岩variometer升降速度表varve clay纹泥varved clay带状粘土vascular plant维管植物vauclusian spring龙潭vector analysis向量分析vegetable garden菜园vegetable remains植物残余vegetal reign植物界vegetation植被vegetation coverage map植被覆盖度图vegetation deterioration植被破坏vegetation form植被型vegetation index植被指数vegetation maps植被图vegetation parameter植被参数vegetation regionalization植被区划vegetation resources植被资源vegetation succession植被演替vegetation type植被型vegetation type map植被类型图vegetation zone植被带vegetative hybrid无性杂种vegetative propagation营养繁殖vegetative season生长期vegetative shoot营养枝veil灰雾vein rock脉石veinlet细脉velocity速度velocity head临水头velocity measurement速度测定velocity meter速度测量器测速计velocity of propagation传播速度veneer复面层veneer rock覆盖层ventilated psychrometer通风干湿表verification检验verification scheme检查简图verisimilitude逼真性vermiculite蛭石vermudoll填土动物穴湿软土vermuth step蒿草原vernacular name土名vernadskite水铜矾vernalization春化处理vernalization stage春化阶段vernier游标vernier microscope游标显微镜vernier reading游标读数vernier theodolite游标经纬仪vertebrate palaeontology脊椎动物古生物学vertebrates脊椎动物vertic cambisols变性始成土vertic chernozems变性黑土vertic luvisols变性淋溶土vertical垂线vertical aerial photography垂直航空摄影vertical angle竖角vertical circle竖直度盘vertical displacement竖直位移vertical distribution竖直分布vertical exaggeration垂直夸张vertical fault垂直断层vertical fold直立褶皱vertical ground visibility垂直地面可见度vertical hill shading直照晕渲法vertical line垂线vertical parallax上下视差vertical photography竖直摄影vertical plane竖直平面vertical position竖直位置vertical scale垂直比例尺vertical section垂直剖面vertical seismograph垂直震仪vertical stratification垂直成层结构vertical surface竖面vertical temperature gradient温度垂直梯度vertical thread竖直丝vertical velocity curve临垂直分布曲线vertical visibility垂直视距vertical wind shear风的垂直切变vertically distributed agriculture立体农业vertigo眩晕vertisols变性土very large scale integrated circuit超大规模集成电路vesicular structure多孔状构造vetch巢菜viability生活力vibrating screen振动筛vibration spectrum振动光谱vicariad替代种vicarism替代性video amplifier视频放大器video camera digitizer电视摄像数字化仪video data可视数据video disk电视唱片video file可见文件video frequency视频video information system视频信息系统video monitor可视监视器video signal视频信号vidicon光导摄像管viewfinder取景器viewing观察viewing angle视场角vignetting渐晕village自然村vinyl乙烯基vinyl alochol乙烯醇vinyl chloride乙烯基氯vinylon维尼纶violent earthquake大地震virgation分岐virgin forest原始林virgin land处女地virgin soil生荒地virtual image虚象virtual memory虚拟存储器virtual model虚模型virtual temperature虚温virus disease病毒疾病virus infection病毒感染viscosity粘度viscous consistence粘滞结持visibility可见度visibility curve可见度曲线visibility meter可见度测定器可见度测定计visible cloud image可见光云图visible horizon视地平visible radiation可见光visible region可贝区vision视力vision angle视角visual acuity视敏度visual balance of elements on a map地图表示因素的低visual field视野visual interpretation目视判读visual line视线visual observation目力观察visual range可视距离visual remote sensing可见光遥感visual sense视觉visualization目测vital capacity生存能力vitality生活力vitrain镜煤vitrandept碎屑火山灰始成土vitreous lustre玻璃光泽vitric andosols玻璃质暗色土vitric tuff玻璃凝灰岩vitriol spring硫酸盐泉vivianite蓝铁矿void孔隙void ratio孔隙比volatilization蒸发volcanic action火山活动volcanic ash火山灰volcanic ash soil火山灰土volcanic block火山块volcanic breccia火山角砾岩volcanic chain火山脉volcanic clay火山粘土volcanic cone火山锥volcanic conglomerate火山砾岩volcanic cycle火山轮回volcanic detritus火山岩屑volcanic detritus soil火山岩屑土volcanic dome火山穹丘volcanic dust火山尘volcanic earthquake火山地震volcanic ejecta火山喷出物volcanic explosion火山爆发volcanic front火山前沿volcanic gases火山气体volcanic hazard火山灾害volcanic islands火山岛volcanic lake火山湖volcanic landscape火山景观volcanic mountains火山volcanic mud火山泥volcanic mudflow火山泥溜volcanic plateau熔岩高原volcanic plug火山栓volcanic product火山喷出物volcanic rent火山裂缝口volcanic rock火山岩volcanic row火山列volcanic rumbling火山地震声volcanic sand火山沙volcanic soil火山土壤volcanic spine火山碑volcanic thunderstorm火山雷雨volcanic tremor火山脉动volcanic tuff凝灰岩volcanic vent火山口volcanic zone火山带volcanism火山酌volcano火山volcano tectonic depression火山沉陷地volcanogenic soil火山土volubile plant缠绕植物volume体积volume of flood flow洪水量volume of reservoir水库容积volume of runoff径量volume shrinkage容积收缩volume weight容重volumetric coefficient容积系数volumetric flowmeter体积量计volumetric method of measuring discharge容积法测流volumetric procedure容量法vomiting呕吐vortex涡旋vortex chain卡曼涡voyage航海wacke玄土wad锰土wadi干谷walking步行wall map挂图wall rock alteration围岩蚀变walnut mountain forest胡桃山林wandering fan徘徊扇wandering river游荡性河流waning development凹坡发育warm air mass暖气团warm current暖流warm front暖锋warm high暖高压warm sector暖区warm temperate zone暖温带warm tongue暖气舌warm trough暖槽warm wave热浪warning coloration警戒色warp淤积物warp clay淤积粘土washed off soil淋洗土壤washed out soil淋洗土壤washing洗涤washing bottle洗瓶washing water洗水waste岩屑waste disposal废物处理waste gas废气waste heat废热waste land荒地waste lye废液waste oil废油waste paper废纸waste pile废石堆waste product废产物waste rubber废橡胶waste water废水waste water treatment废水处理water水water absorbing capacity吸水能力water absorption吸水water and soil reservation information system水土保持信息系统water balance水分平衡water bearing bed含水层water bearing formation含水层water bird水禽water bloom湖靛water body水团water bottle采水器取水器water budget水分平衡water capacity容水量water clouds水云water conductivity水分传导度water consumption水分耗损water content含水量water content of snow雪含水量water control水分控制water control pivot水利枢纽water course水道water culture溶液培养water cycle水循环water delivery供水water dispersion halo水分散晕water divide分水岭water droplets in clouds云水滴water economy水利water edge水边;水边线water equivalent水当量water equivalent of snow雪的水当量water equivalent of snow cover积雪水当量water erosion水蚀water evaporimeter水蒸发器water extract水提取物water gage水尺water gall水蚀穴water gap峡谷water hemisphere水半球water holding capacity持水量water intake进水口water leaf水叶water level水位water level amplitude水位变幅water level fluctuations水位波动water level recorder水位计water line水位线water management水管理water mass水团water microorganism水微生物water migration水迁移water migration coefficient of element元素的水迁移系数water molecule水分子water of crystallization结晶水water of infiltration渗入水water parting divide分水界water percolating capacity水分渗透能力water perocolation渗水water plane水面water plants水生植物water pollution map水污染地图water power plant水电站water quality水质water quality monitoring水质监测water regime水分状况water regime of soil土壤的水分状况water relationship水分状况water representation水系表示法water requirement需水量water reservoir贮水池water resources水资源water resources management水资源管理water retaining capacity保水能力water retention保水water saturation含水饱和度water self purification水体自净酌water solubility水溶性water sprout徒长枝water stage measurement水位测定water storage蓄水water stream水流water supply给水water surface水面water surface slope水面坡度water table地下水位water table contour地下水位等高线water temperature水温water tight structure不透水结构water vapor水汽water vapor cloud image水汽态云图water vein水脉water year水文年;水年water yield硫总出水量watercourse水道waterfall瀑布waterfall erosion瀑布侵蚀watering灌溉waterlining波状水线waterlogged soil渍水土壤watershed分水岭watershed area分水岭地区watershed line地形线waterspout海龙卷waterstable aggregate水稳性团聚体waterway水道wave analyzer波形分析器wave band波段wave base波浪酌的限界深度wave crest波锋wave current波流wave cut notch浪蚀龛wave cut plain浪蚀平原wave cut platgorm浪蚀台wave cut terrace海蚀阶地wave cyclone波动性气旋wave deformation波的变形wave diffraction波浪绕射wave erosion浪蚀wave height波高wave length波长wave mark波痕wave of translation移动波wave particle duality波粒二象性wave path波道wave reflection波反射wave refraction波折射;波浪折射wave sand body浪成沙体wave velocity波速wavemeter波长计waves波waxing development上升发展weak acid弱酸weak earthquake弱震weak rock软弱岩石weak structure脆弱结构weakened profile弱发育剖面weakly leached brown soil轻度淋溶棕壤weather天气weather analysis天气分析weather analysis and forecasting天气分析和预报weather chart气象图weather conditions气象条件weather divide天气区划分weather doppler radar天气多普勒雷达weather forecast天气预报weather information气象情报weather map天气图weather map analysis天气图分析weather message天气报告weather radar气象雷达weather satellite气象卫星weather station气象站weather surve气象服务weather system天气系统weathered pebble风化砾weathered zone风化带weathering风化weathering agent风化因子weathering crust风化壳weathering residues风化残留物weathering sequence风化系列weathering solutions风化溶液wedge of high pressure高压楔wedging thin尘灭weed杂草weed control除草weed killer除草剂weeding除草weight权weight coefficient权系数weight function权函数weight method称重法weight of observation观测权weight unit单位权weighted mean加权平均值weighted product加权积weighted sum加权和weighting bottle称瓶weir堰welded tuff熔结凝灰岩well井well curb井口护井圈well drilling凿井well function井函数west point毋westerlies偏午westerly wind偏午wet adiabat湿绝热线wet adiabatic change湿绝热变化wet adiabatic lapse rate湿绝热递减率wet adiabatic process湿绝热过程wet analysis湿法分析wet bulb temperature湿球温度wet bulb thermometer湿球温度表wet meadow soil湿草甸土wet sample湿试样wet soil渍水土壤wet solonchak湿盐土wet year多水年wetted area受潮面积wetting front湿润锋wheat小麦wheat cultivation小麦栽培wheat yield estimation小麦估产whirler旋转涂膜机whirlpool旋涡whirlwind涡旋风white clay高岭土white light白光white mica白云母whitecap白浪whole pipette全量吸移管whooping cough百日咳whorl轮生wichtisite玻基粗粒玄武岩wide angle camera宽角射影机wide angle lens宽角物镜wide bandpass filter宽带滤光片width of the channel渠宽willow stand柳林wilting凋萎wilting coefficient萎蔫系数wilting point凋萎点wilting range凋萎含水量范围wind风wind blown soil风积土wind break forest防风林wind carving风蚀wind current风海流wind damage风害wind direction风向wind direction meter风向测定器wind divide风向界线wind drift飞砂wind driven current吹流风海流wind driven waves强制波wind effected phenomena风力效应现象wind erosion风蚀wind erosion pillar蕈状石wind finding radar测风雷达wind force风力wind forest strip防护林带wind load风压负载wind measurement风速测定法wind path风程wind pollination风媒wind resistance抗风性wind ripples风成波痕wind rose风向图wind rotation风向转变wind sack风向袋wind shear风切变wind shift风向转变wind speed风速wind system风系wind tunnel风洞wind vane风向标wind velocity vector风速向量wind zone风带windbreak风障windfall风倒木windpressure风压windstorm大风windward迎风面windward bank向风岸windward coast向风海岸windward slope向风面wine soil葡萄园土winter dormancy冬眠winter flood冬季洪水winter half year冬半年winter hardiness耐寒性winter solstice冬至wintering越冬woadwaxen brake染料木丛林wolframite黑钨矿wollastonite硅灰石wombat袋熊wood木材wood cutting area伐区wood peat木质泥炭woodcutter's encephalitis春季森林脑炎woody mire木本沼泽woody plant示word length字长work sheet编绘原图workable可耕的workable soil适耕土壤worker职蚁working aperture有效孔径working capacity劳动能力working map工棕图world aeronautical chart世界航空图world atlas世界地图集world map世界地图world map series世界图组world refernece system世界参考系统worm's eye view仰视图wrench fault横推断层xxy 平面x axis横轴x rayx射线x ray absorption spectrumx射线吸收谱x ray camera伦琴室x ray crystallographyx射线结晶学x ray diffractionx射线衍射x ray fluorescence analysisx射线荧光分析x ray imagex射线照片x ray patternx射线图样x ray photographyx射线照相x ray refractive indexx射线折射指数x ray spectrometerx射线分光计x ray spectroscopic analysis伦琴射线光谱分析x ray spectroscopyx射线光谱学x ray tubex射线管x raysx射线xanthic ferralsols黄色铁铝土xanthic pigment黄色色素xanthophyll叶黄素xanthosis黄病xenolith捕虏岩xenomorphic他形的xenon氙xenothermal deposit浅成高温矿床xeralf干热淋溶土xerert季节性干旱变性土xerography静电复印xeroll干热软土xeromorphism旱生形态xerophilous plant旱生植物xerophilous plants喜旱植物xerophils适旱植物xerophyte旱生植物xerophytic vegetation旱生植被xeropsamment季节性干旱砂新成土xerosere旱生演替系列xerosols干旱土xerothermic plant干热植物xerult干热老成土xylem木质部y axisy轴y coordinate纵坐标y planexy 平面year of publication出版年代yearly ring生长轮yeast酵母yellow aphids黄蚜yellow brown soil黄棕壤yellow brown soils黄棕色土壤yellow fever黄热病yellow fever virus黄热病病毒yellow filter黄滤光镜yellow podzolic soils灰化黄壤yellow sand黄沙yellow soil黄壤yellowing黄化yelow mud黄泥yermosols漠境土yew grove紫杉林yield factors产量因素yield forecast单产预报yield index产量指标yield model产量模型yield of grass产草量yield programming产量程序设计yielding收获量yielding capacity生产量young forest幼龄林young mountains幼年山young platform幼年性台地young stage幼年期young topography幼年地形young valley幼年谷ytterbium镱yttrium钇yttrocrasite钛钇钍矿zechstein镁灰岩zenith天顶zenith distance天顶距zenith photography天顶摄影zenith point天顶点zenithal rains天顶季雨zeolite沸石zeolite facies沸石相zeolitization沸石化zero correlation零相关zero direction零方向zero indicator零点指示器zero position零位zeta potential动电位zinc锌zinc blende闪锌矿zinc pollution锌污染zincaluminite锌茂zinnwaldite铁锂云母zircon锆土zirconium锆zirconium deposit锆矿床zirkelite钛锆钍矿zodiacal light黄道光zoisite帘石zonal aberration区域像差zonal circulation纬向环流zonal distribution显域分布zonal flow纬向气流zonal index of circulation纬向指数zonal soil profile分带土壤剖面zonal soils显域土zonal structure带状构造zonal swamp地带性沼泽zonation分带zone带zone of dissipation消融区zone of faulting断层带zone of fracture破裂带zone of mathematical climate数理气候带zone of percolation渗漏带zone of saturation饱和带zone plate波带片zone time区时zoning of primary halos原生晕分带zoobenthos水底动物zoochores动物传布zoochory动物传布zoocoenose动物群落zoogeographic region动物地理区zoogeography动物地理学zoolith动物岩zoology动物学zoom stereoscope可变焦距立体镜zoophilous plant动物媒植物zooplankton浮游动物zootope动物生境zwitter ion两性离子zygospore接合孢子zygote合子zymology酶学地理专业词汇英语翻译(U-Z) 相关内容:。

新视野大学英语（第三版）第二册课后翻译答案及原文Unit 1原文： English is known as a world language, regularly used by many nations whose English is not their first language. Like other languages, English has changed greatly. The history of the English language can be divided into three main periods: Old English, Middle English and Modern English. The English language started with the invasion of Britain by three Germanic tribes during the 5th century AD, and they contributed greatly to the formation of the English language. During the medieval and early modern periods, the influence of English spread throughout the British Isles, and from the early 17th century its influence began to be felt throughout the world. The processes of European exploration and colonization for several centuries led to significant change in English. Today, American English is particularly influential, due to the popularity of American cinema, television, music, trade and technology, including the Internet.翻译：人们普遍认为英语是一种世界语言，经常被许多不以英语为第一语言的国家使用。

FINAL PROGRAMTHE 2007 ACM SIGAPPSYMPOSIUM ON APPLIED COMPUTING/conferences/sac/sac2007Seoul, Korea March 11 - 15, 2007Organizing CommitteeRoger L. Wainwright Hisham M. Haddad Sung Y. ShinSascha Ossowski Ronaldo MenezesLorie M. Liebrock Mathew J. Palakal Jaeyoung Choi Tei-Wei Kuo Jiman HongSeong Tae Jhang Yookun Cho Yong Wan KooH OSTED BYSeoul National University, Seoul, Korea Suwon University, Gyeonggi-do, KoreaSPONSORED BYSAC 2007 I NTRODUCTIONSAC 2007 is a premier international conference on applied com-puting and technology. Attendees have the opportunity to hear from expert practitioners and researchers about the latest trends in research and development in their fields. SAC 2007 features 2 keynote speakers on Monday and Wednesday, from 8:30 to 10:00. The symposium consists of Tutorial and Technical programs. The Tutorial Program offers 3 half-day tutorials on Sunday March 11, 2007, starting at 9:00am. The Technical Program offers 38 tracks on a wide number of different research topics, which run from Monday March 12 through Thursday March 15, 2007. Regular sessions start at 8:30am and end at 5:00pm in 4 parallel sessions. Honorable ChairsYookun Cho, Honorable Symposium ChairSeoul National University, KoreaYong Wan Koo, Honorable Program ChairUniversity of Suwon, KoreaOrganizing CommitteeRoger L. Wainwright, Symposium ChairUniversity of Tulsa, USAHisham M. Haddad, Symposium Chair, Treasurer, Registrar Kennesaw State University, USASung Y. Shin, Symposium ChairSouth Dakota State University, USASascha Ossowski, Program ChairUniversity Rey Juan Carlos, Madrid, SpainRonaldo Menezes, Program ChairFlorida Institute of Technology, Melbourne, FloridaJaeyoung Choi, Tutorials ChairSoongsil University, KoreaTei-Wei Kuo, Tutorials ChairNational Taiwan University, ChinaMathew J. Palakal, Poster ChairIndiana University Purdue University, USALorie M. Liebrock, Publication ChairNew Mexico Institute of Mining and Technology, USAJiman Hong,Local Organization ChairKwangwoon University, KoreaSeong Tae Jhang,Local Organization ChairUniversity of Suwon, KoreaSAC 2007 Track OrganizersArtificial Intelligence, Computational Logic, and Image Analysis (AI)C.C. Hung, School of Computing and Soft. Eng., USAAgostinho Rosa, LaSEEB –ISR – IST, PortugalAdvances in Spatial and Image-based Information Systems (ASIIS)Kokou Yetongnon, Bourgogne University, FranceChristophe Claramunt, Naval Academy Research Institute, France Richard Chbeir, Bourgogne University, FranceKi-Joune Li, Prusan National University, KoreaAgents, Interactions, Mobility and Systems (AIMS)Marcin Paprzycki, SWPS and IBS PAN, PolandCostin Badica, University of Craiova, RomaniaMaria Ganzha, EUH-E and IBS PAN, PolandAlex Yung-Chuan Lee, Southern Illinois University, USAShahram Rahimi, Southern Illinois University, USAAutonomic Computing (AC)Umesh Bellur, Indian Institute of Technology, IndiaSheikh Iqbal Ahamed, Marquette University, USABioinformatics (BIO)Mathew J. Palakal, Indiana University Purdue University, USALi Liao, University of Delaware, USAComputer Applications in Health Care (CACH)Valentin Masero, University of Extremadura, SpainPierre Collet, Université du Littoral (ULCO), France Computer Ethics and Human Values (CEHV)Kenneth E. Himma, Seattle Pacific University, USAKeith W. Miller, University of Illinois at Springfield, USADavid S. Preston, University of East London, UKComputer Forensics (CF)Brajendra Panda, University of Arkansas, USAKamesh Namuduri, Wichita State University, USAComputer Networks (CN)Mario Freire, University of Beira Interior, PortugalTeresa Vazao, INESC ID/IST, PortugalEdmundo Monteiro, University of Coimbra, PortugalManuela Pereira, University of Beira Interior, PortugalComputer Security (SEC)Giampaolo Bella, Universita' di Catania, ItalyPeter Ryan, University of Newcastle upon Tyne, UKComputer-aided Law and Advanced Technologies (CLAT) Giovanni Sartor, University of Bologna, ItalyAlessandra Villecco Bettelli, University of Bologna, ItalyLavinia Egidi, University of Piemonte Orientale, ItalyConstraint Solving and Programming (CSP)Stefano Bistarelli, Università degli studi "G. D'Annunzio" di Chieti-Pescara, ItalyEric Monfroy, University of Nantes, FranceBarry O'Sullivan, University College Cork, IrelandCoordination Models, Languages and Applications (CM) Alessandro Ricci, Universita di Bologna, ItalyBernhard Angerer, Michael Ignaz Schumacher, EPFL IC IIF LIA, SwitzerlandData Mining (DM)Hasan M. Jamil, Wayne State University, USAData Streams (DS)Jesus S. Aguilar-Ruiz, Pablo de Olavide University, SpainFrancisco J. Ferrer-Troyano, University of Seville, SpainJoao Gama, University of Porto, PortugalRalf Klinkenberg, University of Dortmund, GermanyDatabase Theory, Technology, and Applications (DTTA) Ramzi A. Haraty, Lebanese American University, LebanonApostolos N. Papadopoulos, Aristotle University, GreeceJunping Sun, Nova Southeastern University, USADependable and Adaptive Distributed Systems (DADS)Karl M. Göschka, Vienna University of Technology, AustriaSvein O. Hallsteinsen, SINTEF ICT, NorwayRui Oliveira, Universidade do Minho, PortugalAlexander Romanovsky, University of Newcastle upon Tyne, UK Document Engineering (DE)Rafael Dueire Lins, Universidade Federal de Pernambuco, Brazil Electronic Commerce Technologies (ECT)Sviatoslav Braynov, University of Illinois at Springfield, USADaryl Nord, Oklahoma State University, USAFernando Rubio, Universidad Complutense de Madrid, Spain Embedded Systems: Applications, Solutions and Techniques (EMBS)Alessio Bechini, University of Pisa, ItalyCosimo Antonio Prete, University of Pisa, ItalyJihong Kim, Seoul National University, KoreaEvolutionary Computation (EC)Bryant A. Julstrom, St. Cloud State University, USA Geoinformatics and Technology (GT)Dong-Cheon Lee, Sejong University, KoreaGwangil Jeon, Korea Polytechnic University, KoreaGeometric Computing and Reasoning (GCR)Xiao-Shan Gao, Chinese Academy of Sciences, ChinaDominique Michelucci, Universite de Bourgogne, FrancePascal Schreck, Universite Louis Pasteur, FranceHandheld Computing (HHC)Qusay H. Mahmoud, University of Guelph, CanadaZakaria Maamar, Zayed University, UAEInformation Access and Retrieval (IAR)Fabio Crestani, University of Strathclyde, UKGabriella Pasi, University of Milano Bicocca, ItalyMobile Computing and Applications (MCA)Hong Va Leong, Hong Kong Polytechnic University, Hong KongAlvin Chan, Hong Kong Polytechnic University, Hong KongModel Transformation (MT)Jean Bézivin, University of Nantes, FranceAlfonso Pierantonio, Università degli Studi dell’Aquila, ItalyAntonio Vallecillo, Universidad de Malaga, SpainJeff Gray, University of Alabama at Birmingham, USAMultimedia and Visualization (MMV)Chaman L. Sabharwal, University of Missouri-Rolla, USAMingjun Zhang, Agilent Technologies, USAObject-Oriented Programming Languages and Systems (OOP) Davide Ancona, DISI - Università di Genova, ItalyMirko Viroli, Università di Bologna, ItalyOperating Systems and Adaptive Applications (OSAA)Jiman Hong, Kwangwoon University, KoreaTei-Wei Kuo, National Taiwan University, TaiwanOrganizational Engineering (OE)José Tribolet, Technical University of Lisbon, PortugalRobert Winter, University of St. Gallen, SwitzerlandArtur Caetano, Technical University of Lisbon, Portugal Programming for Separation of Concerns (PSC)Corrado Santoro, Catania University, ItalyEmiliano Tramontana, Catania University, ItalyIan Welch, Victoria University, New ZealandYvonne Coady, Victoria Univeristy, CanadaProgramming Languages (PL)Chang-Hyun Jo, California State University at Fullerton, USAMarjan Mernik, University of Maribor, SloveniaBarrett Bryant, University of Alabama at Birmingham, USAReliable Computations and their Applications (RCA)Martine Ceberio, University of Texas at El Paso, USAVladik Kreinovich, University of Texas at El Paso, USAMichael Rueher, Universite de Nice ESSI, FranceSemantic Web and Application (SWA)Hyoil Han, Drexel University, USASemantic-Based Resource Discovery, Retrieval and Composition (SDRC)Eugenio Di Sciascio, SinsInfLab Politecnico di Bari, ItalyFrancesco M. Donini, University of Tuscia, ItalyTommaso Di Noia, SinsInfLab Politecnico di Bari, ItalyMassimo Paolucci, DoCoMo Euro-Labs, GermanySoftware Engineering (SE)W. Eric Wong, University of Texas at Dallas, USAChang-Oan Sung, Indiana University Southeast, USASoftware Verification (SV)Zijiang Yang, Western Michigan University, USALunjin Lu, Oakland University, USAFausto Spoto, Universita di Verona, ItalySystem On Chip Design and Software Supports (SODSS) Seong Tae Jhang, Suwon University, KoreaSung Woo Chung, Korea University, KoreaTrust, Recommendations, Evidence and other Collaborative Know-how (TRECK)Jean-Marc Seigneur, University of Geneva, SwitzerlandJeong Hyun Yi, Samsung Advanced Institute of Technology, South Korea Ubiquitous Computing: Digital Spaces, Services and Content (UC)Achilles Kameas, Hellenic Open University, GreeceGeorge Roussos, University of London, UKWeb Technologies (WT)Fahim Akhter , Zayed University, UAEDjamal Benslimane, University of Lyon, FranceZakaria Maamar, Zayed University, UAEQusay H. Mahmoud, University of Guelph, CanadaLocal SupportLocal support for SAC 2007 is provided by the Seoul National University in Seoul, Suwon University in Gyeonggi-do, Ministry of Education and Human Resources Development, Samsung, mds technology, KETI, MIC, CVB, and ETRI. The SAC organizing committee acknowledges and thanks the local supporters for their generous contributions to SAC 2007. Their support has been essential to the success of Symposium, and is greatly appreciated. ACM SIGAPPThe ACM Special Interest Group on Applied Computing is ACM's primary applications-oriented SIG. Its mission is to further the interests of the computing professionals engaged in the development of new computing applications and applications areas and the transfer of computing technology to new problem domains. SIGAPP offers practitioners and researchers the opportunity to share mutual interests in innovative application fields, technology transfer, experimental computing, strategic research, and the management of computing. SIGAPP also promotes widespread cooperation among business, government, and academic computing activities. Its annual Symposium on Applied Computing (SAC) provides an international forum for presentation of the results of strategic research and experimentation for this inter-disciplinary environment. SIGAPP membership fees are: $30.00 for ACM Non-members, $15.00 for ACM Members, and $8.00 for Student Members. For information contact Barrett Bryant at bryant@. Also, checkout the SIGAPP website at /sigapp/M ESSAGE FROM THE S YMPOSIUM C HAIRSRoger WaiwrightUniversity of Tulsa, USAHisham M. HaddadKennesaw State University, USASung Y. ShinSouth Dakota State University, USAOn behalf of the Organization Committee, it is our pleasure to welcome you to the 22nd Annual ACM Symposium on Applied Computing (SAC 2007). This year, the conference is hosted by Seoul National University and Suwon University in Gyeonggi-do, Korea. Many thanks for your participation in this international event dedicated to computer scientists, engineers, and practitioners seeking innovative ideas in various areas of computer applications. The sponsoring SIG of this Symposium, the ACM Special Interest Group on Applied Computing, is dedicated to further the interests of computing professionals engaged in the design and development of new computing applications, interdisciplinary applications areas, and applied research. The conference provides a forum for discussion and exchange of new ideas addressing computational algorithms and complex applications. This goal is reflected in its wide spectrum of application areas and tutorials designed to provide variety of discussion topics during this event. The conference is composed of various specialized technical tracks and tutorials. As in past successful meetings, talented and dedicated Track Chairs and Co-Chairs have organized SAC 2007 tracks. Each track maintains a program committee and group of highly qualified reviewers. We thank the Track Chairs, Co-Chairs, and participating reviewers for their commitment to making SAC 2007 another high quality conference. We also thank our invited keynote speakers for sharing their knowledge with SAC attendees. Most of all, special thanks to the authors and presenters for sharing their experience with the rest of us and to all attendees for joining us in Seoul, Korea.The local organizing committee has always been a key to the success of the conference. This year, we thank our local team from Seoul National University and Suwon University. In particular, we thank Dr. Jiman Hong, from Kwangwoon University, and Dr. Seong Tae Jhang, from Suwon University, for chairing the local organization effort. We also thank Dr. Jaeyoung Choi, from Soongsil University, and Dr. Tei-Wei Kuo, from National Taiwan University, for organizing the Tutorials Program. Other committee members we also would like to thank are Lorie Liebrock for her tremendous effort putting together the conference proceedings, Mathew Palakal for coordinating another successful Posters Program, and Sascha Ossowski and Ronaldo Menezes for bringing together the Technical Program. Finally, we extend outthanks and gratitude to our honorable Symposium and Program Chairs Drs. Yookun Cho of Seoul National University and Dr. Yong Wan Koo of Suwon University. Many thanks for hosting the conference and coordinating governmental and local support. Again, we welcome you to SAC 2007 in the lively city of Seoul. We hope you enjoy your stay in Seoul and leave this event enriched with new ideas and friends. Next year, we invite you to participate in SAC 2008 to be held in the costal city of Fortaleza, Brazil. The symposium will be hosted by the University of Fortaleza (UNIFOR) and the Federal University of Ceará (UFC). We hope to see there!M ESSAGE FROM THE P ROGRAM C HAIRSSascha OssowskiUniversity Rey Juan Carlos, SpainRonaldo MenezesFlorida Institute of Technology, USAWelcome to the 22nd Symposium on Applied Computing (SAC 2007). Over the past 21 years, SAC has been an international forum for researchers and practitioners to present their findings and research results in the areas of computer applications and technology. The SAC 2007 Technical Program offers a wide range of tracks covering major areas of computer applications. Highly qualified referees with strong expertise and special interest in their respective research areas carefully reviewed the submitted papers. As part of the Technical Program, this year the Tutorial Program offers several half-day tutorials that were carefully selected from numerous proposals. Many thanks to Jaeyoung Choi from the Soongsil University and Tei-Wei Kuo from the National Taiwan University for chairing the Tutorial Program. Also, this is the fourth year for SAC to incorporate poster papers into the Technical Program. Many thanks to Mathew Palakal from Indiana University Purdue University for chairing the poster sessions. SAC 2007 would not be possible without contributions from members of the scientific community. As anyone can imagine, many people have dedicated tremendous time and effort over the period of 10 months to bring you an excellent program. The success of SAC 2007 relies on the effort and hard work of many volunteers. On behalf of the SAC 2007 Organizing Committee, we would like to take this opportunity to thank all of those who made this year's technical program a reality, including speakers, referees, track chairs, session chairs, presenters, and attendees. We also thank the local arrangement committee lead by Jiman Hong from the Kwangwoon University and Seong Tae Jhang from Suwon University. We also want to thank Hisham Haddad from Kennesaw State University for his excellent job again as the SAC Treasurer, Webmaster, and Registrar.SAC's open call for Track Proposals resulted in the submission of 47 track proposals. These proposals were carefully evaluated by the conference Executive Committee. Some proposals were rejected on the grounds of either not being appropriate for the areas that SAC covers traditionally or being of rather narrow and specialized nature. Some others tracks were merged to form a single track. Eventually, 38 tracks were established, which then went on to produce their own call for papers. In response to these calls, 786 papers were submitted, from which 256 papers were strongly recommended by the referees for acceptance and inclusion in the Conference Proceedings. This gives SAC 2007 an acceptance rate of 32.5% across all tracks. SAC is today one of the most popular and competitive conferences in the international field of applied computing.We hope you will enjoy the meeting and have the opportunity to exchange your ideas and make new friends. We also hope you will enjoy your stay in Seoul, Korea and take pleasure from the many entertainments and activities that the city and Korea has to offer. We look forward to your active participation in SAC 2008 when for the first time SAC will be hosted in South America, more specifically in Fortaleza, Brazil. We encourage you and your colleagues to submit your research findings to next year's technical program. Thank you for being part of SAC 2007, and we hope to see you in sunny Fortaleza, Brazil for SAC 2008.O THER A CTIVITIESReview Meeting: Sunday March 11, 2007, from 18:00 to 19:00 in Room 311A. Open for SAC Organizing Committee and Track Chairs and Co-Chairs.SAC 2008 Organization Meeting: Monday March 12, 2007, from 18:00 to 19:00 in Room 311A. Open for SAC Organizing Committee.SAC Reception: Monday March 12, 2007 at 19:00 to 22:00. Room 402. Open for all registered attendees.Posters Session: Tuesday March 13, 2007, from 13:30 to 17:00 in the Room 311C. Open to everyone.SIGAPP Annual Business Meeting: Tuesday March 13, 2007, from 17:15 to 18:15 in Room 311A. Open to everyone.SAC Banquet: Wednesday March 14, 2007. Rooms 331-334. Open for Banquet Ticket holders. See your tickets for full details. Track-Chairs Luncheon: Thursday April 27, 2006, from 12:00 to 13:30. Hosu (Lake) Food-mall. Open for SAC Organizing Committee, Track Chairs and Co-Chairs.SAC 2008SAC 2008 will be held in Fortaleza, Ceará, Brazil, March 16 – 20, 2008. It is co-hosted by the University of Fortaleza (UNIFOR) and the Federal University of Ceará (UFC). Please check the registration desk for handouts. You can also visit the website at /conferences/sac/sac2008/.M ONDAY K EYNOTE A DDRESSA New DBMS Architecture for DB-IRIntegrationDr. Kyu-Young WhangDirector of Advanced Information Technology Research Center, Korea Advanced Institute ofScience and Technology, Daejeon, Korea M ONDAY M ARCH 12, 2007, 9:00 – 10:00ROOM 310 A, B AND CABSTRACTNowadays, there is an increasing need to integrate the DBMS (for structured data) with Information Retrieval (IR) features (for unstructured data). DB-IR integration becomes one of major challenges in the database area. Extensible architectures provided by commercial ORDBMS vendors can be used for DB-IR integration. Here, extensions are implemented using a high-level (typically, SQL-level) interface. We call this architecture loose-coupling. The advantage of loose-coupling is that it is easy to implement. But, it is not preferable for implementing new data types and operations in large databases when high performance is required. In this talk, we present a new DBMS architectureapplicable to DB-IR integration, which we call tight-coupling. In tight-coupling, new data types and operations are integrated into the core of the DBMS engine in the extensible type layer. Thus, they are incorporated as the "first-class citizens" within the DBMS architecture and are supported in a consistent manner with high performance. This tight-coupling architecture is being used to incorporate IR features and spatial database features into the Odysseus ORDBMS that has been under development at KAIST/AITrc for over 16 years. In this talk, we introduce Odysseus and explain its tightly-coupled IR features (U.S. patented in 2002). Then, we demonstrate excellence of tight-coupling by showing benchmark results. We have built a web search engine that is capable of managing 20~100 million web pages in a non-parallel configuration using Odysseus. This engine has been successfully tested in many commercial environments. In a parallel configuration, it is capable of managing billons of web pages. This work won the Best Demonstration Award from the IEEE ICDE conference held in Tokyo, Japan in April 2005.W EDNESDAY K EYNOTE A DDRESS The Evolution of Digital Evidence asa Forensic ScienceDr. Marc RogersChair of the Cyber Forensics Program,Department of Computer and InformationTechnology, Purdue University, USAW EDNESDAY M ARCH 14, 2007, 9:00 –10:00ROOMS 310 A, B AND CABSTRACTThe field of Digital Evidence while garnering significant attention by academia, the public, and the media, has really just begun its journey as a forensic science. Digital Forensic Science (DFS) in general is an immature discipline in comparison to the other more traditional forensic sciences such as latent fingerprint analysis. Digital Evidence, which falls under the larger umbrella of DFS, truly encompasses the notion of being an applied multi-disciplinary science. The areas of Computer Science, Technology, Engineering, Mathematics, Law, Sociology, Psychology, Criminal Justice etc. all have played and will continue to play a very large role in maturing and defining this scientific field. The presentation will look at the history of Digital Forensic Science and Digital Evidence, the current state of the field, and what might be in store for the future.S EOUL R EPRESENTATIVE A DDRESSKoran IT policy - IT839Dr. Jung-hee SongAssistant MayorChief of Information OfficerInformation System Planning DivisionSeoul Metropolitan Government, KoreaW EDNESDAY M ARCH 14, 2007, 18:30 – 19:00ROOMS 331-334(DURING BANQUET)ABSTRACTKorean IT policy initiated by Ministry of Information and Communication called IT839 Strategy will be introduced. By defining government role in the u-Korea vision pursuit, it removes uncertainties for IT industry and increases its active participation. As capital of Korea, Seoul presented a grand plan to be u-Seoul. An overview of u-Seoul masterplan will be delivered with introduction of 5 specific projects.SAC 2007 S CHEDULES UNDAY M ARCH 11, 200709:00 – 17:00 L OBBYR EGISTRATION09:00 – 10:30 R OOMS 310 A AND BAM T UTORIALS IT1: Introduction to Security-enhanced Linux(SELinux)Dr. Haklin Kimm, Professor, omputer Science Department, ast Stroudsburg University of Pennsylvania, USAT2: Similarity Search - The Metric Space Approach Pavel Zezula, Masaryk University, Brno, Czech RepublicGiuseppe Amato, ISTI-CNR, Pisa, ItalyVlastislav Dohnal, Masaryk University, Brno, Czech Republic10:30 – 11:00 L OBBYC OFFEE B REAK11:00 – 12:30 R OOMS 310 A AND BAM T UTORIALS IIT1: Introduction to Security-enhanced Linux(SELinux)Dr. Haklin Kimm, Professor, omputer Science Department, ast Stroudsburg University of Pennsylvania, USAT2: Similarity Search - The Metric Space Approach Pavel Zezula, Masaryk University, Brno, Czech RepublicGiuseppe Amato, ISTI-CNR, Pisa, ItalyVlastislav Dohnal, Masaryk University, Brno, Czech Republic 12:00 – 13:30 H OSU (L AKE) F OOD-MALL,1ST F LOORL UNCH B REAK13:30 – 15:00 R OOM 310 APM T UTORIAL IT3: Introduction to OWL Ontology Developmentand OWL ReasoningYoung-Tack Park, Professor, School of Computing, SoongsilUniversity,Seoul, Korea15:00 – 15:30 L OBBYC OFFEE B REAK15:30 – 17:00 R OOM 310 APM T UTORIAL IIT3: Introduction to OWL Ontology Developmentand OWL ReasoningYoung-Tack Park, Professor, School of Computing, SoongsilUniversity,Seoul, Korea18:00 – 19:00 R OOM 311A SAC 2007 R EVIEW M EETINGM ONDAY M ARCH 12, 200708:00 – 17:00 L OBBYR EGISTRATION08:30 – 09:00 R OOM 310O PENING R EMARKS09:00 – 10:00 R OOM 310K EYNOTE A DDRESSA New DBMS Architecture for DB-IRIntegrationDr. Whang, Kyu-YoungDirector of Advanced Information TechnologyResearch CenterKorea Advanced Institute of Science andTechnologyDaejeon, Korea10:00 – 10:30 L OBBYC OFFEE B REAK10:30 – 12:00 R OOM 310A(DS) Data StreamsJoao Gama, University of Porto (UP), Portugal RFID Data Management for Effective ObjectsTrackingElioMasciari, CNR, ItalyA Priority Random Sampling Algorithm for Time-based Sliding Windows over Weighted StreamingDataZhang Longbo, Northwestern Polytechnical University, China Li Zhanhuai, Northwestern Polytechnical University, ChinaZhao Yiqiang, Shandong University of Technology, ChinaMin Yu, Northwestern Polytechnical University, China Zhang Yang, Northwest A&F University, ChinaOLINDDA: A Cluster-based Approach forDetecting Novelty and Concept Drift in DataStreamsEduardo Spinosa, University of Sao Paulo (USP), BrazilAndré Carvalho, University of Sao Paulo (USP), Brazil Joao Gama, University of Porto (UP), PortugalA Self-Organizing Neural Network for DetectingNoveltiesMarcelo Albertini, Universidade de Sao Paulo, BrazilRodrigo Mello, Universidade de São Paulo, Brazil10:30 – 12:00 R OOM 310B (AI) Artificial Intelligence, ComputationalLogic and Image AnalysisChih-Cheng Hung, Southern Polytechnic State University, USA Toward a First-Order Extension of Prolog'sUnification using CHRKhalil Djelloul, University of Ulm, GermanyThi-Bich-Hanh Dao, University d'Orléans, FranceThom Fruehwirth, University of Ulm, GermanyA Framework for Prioritized Reasoning Based onthe Choice EvaluationLuciano Caroprese, University of Calabria, ItalyIrina Trubitsyna, University of Calabria, ItalyEster Zumpano, University of Calabria, ItalyA Randomized Knot Insertion Algorithm for Outline Capture of Planar Images using CubicSplineMuhammad Sarfraz, King Fahd University of Petroleum andMinerals, Saudi ArabiaAiman Rashid, King Fahd University of Petroleum and Minerals,Saudi ArabiaEstraction of Arabic Words from Complex ColorImagesRadwa Fathalla, AAST, EgyptYasser El Sonbaty, AAST College of Computing, Egypt Mohamed Ismail, Alexandria University, Egypt10:30 – 12:00 R OOM 310C (PL) Programming LanguagesMarjan Mernik, University of Maribor, Slovenia Implementing Type-Based Constructive Negation Lunjin Lu, Oakland University, USATowards Resource-Certified Software: A Formal Cost Model for Time and its Application to anImage-Processing ExampleArmelle Bonenfant, University of St Andrews, UKZehzi Chen, Heriot-Watt University, UKKevin Hammond, Univestiy of St Andrews, UKGreg Michaelson, Heriot-Watt University, UKAndy Wallace, Heriot-Watt University, UKIain Wallace, Heriot-Watt University, UK。