CONTENTS Paper Formal Semantics, Pragmatics, and Situated Meaning

Semantic Feature Extractionusing Mpeg Macro-block ClassificationFabrice Souvannavong,Bernard Merialdo and Benoˆıt HuetD´e partement Communications Multim´e diasInstitut Eur´e com2229,route des crˆe tes06904Sophia-Antipolis-France(Fabrice.Souvannavong,Bernard.Merialdo,Benoit.Huet)@eurecom.frAbstractIn this paper,we present somefirst results in the extractionof semantic features from video sequences.Our approachis based on the classification of Mpeg DCT macro-blocks.Although it is clear that using macro-blocks imposes se-vere restrictions on the analysis accuracy of the image,ithas the advantage of avoiding the complete decoding ofthe Mpeg stream.Our objective is to evaluate the qualityof the Semantic Feature Extraction that can be obtainedwith this direct approach,to serve as a comparative base-line with more elaborate approaches.Keywords:Semantic classification,Discrete CosineTransform,Gaussian Mixture Models,Compressed Do-main.1IntroductionThe large amount of visual information,carried by videodocuments as well as still images,requires efficient andeffective indexing and search tools[2,6].The U.S.In-stitute of Standards and Technology sponsors the serie ofTREC12002conferences to promote progress in content-based retrieval from digital video.Our work takes placein this context where we focus on the feature extraction2Macro-block ClassificationIn the context of supervised classification,three steps are involved:feature extraction and representation,class modelisation and parameter estimation,finally classifica-tion with respect to decision rules.In our approach,features are directly provided by the video stream after parsing since we work only on I-frames,which are encoded somehow like jpeg pictures. These frames are composed of macro-blocks that contain 6DCT blocks,4for Y color component,1for U and1 for V i.e.4:2:0video format.We can represent a DCT macro-block by a vector of size64corresponding to the zigzag scan of the DCT block coefficients and then make the concatenation of the6vectors to obtain the feature vector of the whole region.Since thefirst DCT coeffi-cients are the most important i.e:to eye sensitivity and noise,the feature space dimension is simply reduced to 60by truncation.Moreover coefficients are scaled with respect to their importance in order to increase the sen-sitivity of the classifier to important components and at the same time to slightly improve the initialisation of the training algorithm,which is usually obtained via k-means algorithm as explained in the next subsection.We assume a mixture model to describe the distribu-tion of macro-blocks for each class,and specifically a multi-dimensional Gaussian distribution.Gaussian mod-els can capture the characteristics of a macro-block,while modeling the variation due to motion or lighting condi-tions.Moreover in[5],m and J.W.Goodman have proven that the distribution of macro-block DCT coeffi-cients can be well approximated by a Gaussian when the variance is constant;in the classification situation,the lat-ter hypothesis is more or less true and mixtures should compensate it.So the probability density function can be written as follows:For X C i P XΦi∑jαj p j X whereαiℜΦiµjσj and p j X NµjσjThe GMM parametersαjµj andσj are estimated using the traditional Expectation-Maximization algorithm[1] which is initialized with a classical k-means algorithm. In our current experiments,we also make the hypothesis that feature vector components are independent,thusσi is a diagonal matrix,or that only color components of the same frequency are correlated,thusσi is a matrix diago-nal by block.Finally the choice of the number of mixtures is simply achieved by looking at the test set loglikelihood evolution of the EM algorithm for various mixture num-bers.It should not increase to much in order to avoid data overfitting.Given an unlabeled macro-block X,the maximum a posteriori rule:ˆC arg maxiPΦi Xgives an estimation of the class it belongs to.The poste-rior probabilities can be expanded by Baye’s rule:PΦi XP XΦi PΦidata set proportionl o g −l i k e l i h o o dFigure 1:Threshold selectionHigher-level semanticson the upper part of the graph that are difficult to extract directly,but can be in-duced by a combination of lower-level features.Trec concepts,enclosed in boxes,that are spread in either of the previously stated categories.1.sian Mixtures,pute a detection score for each feature.The detection score of the feature i whose elementary childrens are J is simply defined by:Ds i∑jPj where jJP jNumber of macro-blocks with label jSelected sequences461814384226211710464714642133274562003549152218791401 Features total 1472409771584636183925505586398572971437text skin clothes sky tree building grass tarmac hair water ground Diagonal by block3826234922123417105840 recallprecision7553428364366777438078 Table2:Precision and recall during the development of the low level features.surprisingly good ranking in text ovelay detection.5ConclusionWe have presented a method based on DCT information of macro-blocks to detect Trec visual features from video shots in a single framework.Since macro-blocks carry only local information,a heuristic hierarchy was intro-duced to build thefinal decision rule at the frame-level and region-level.In gereral this evaluation is encouraging knowing the small extract of the development set used.In future works we plan to investigate methods to automati-cally elaborate the hierarchy.This will set up a complete probabilistic framework to detect features from low level observations and a more realistic manual annotation at the shot level will be required to train models. References[1]J.A.Bilmes.A gentle tutorial of the em algorithmand its application to parameter estimation for gaus-sian mixture and hidden markov models.ICSI-TR, 1997.[2]S.-F.Chang,W.Chen,H.Meng,H.Sundaram,andD.Zhong.A fully automated content-based videosearch engine supporting spatiotemporal queries.In IEEE Transactions on Circuits and Systems for Video Technology,volume8,pages602–615,1998.[3]S.-F.Chang and H.Sundaram.Structural and se-mantic analysis of video.In ICME,2000.[4]A.Girgensohn and J.Foote.Video classificationusing transform coefficients.In Proceedings of the International Conference on Acoustics,Speech, and Signal Processing,volume6,pages3045–3048, 1999.[5]m and J.W.Goodman.A mathematical anal-ysis of the dct coefficient distribution for images.In IEEE Transactions on Image Processing,volume9, pages1661–1666,October2000.[6]A.Pentland,R.Picard,and S.Sclaroff.Photobook:Content-based manipulation of image databases.In SPIE Storage and Retrieval for Image and Video Databases,february1994.[7]M.Saeed,W.Karl,T.Nguyen,and H.Rabiee.A new multiresolution algorithm for image seg-mentation.In IEEE International Conference on Acoustics,Speech,and Signal Processing,volume5, pages2753–2756,1998.0.20.40.60.8100.10.20.30.40.50.60.70.8P r e c i s i o nRecallPrecision-Recall(a)Outdoors00.20.40.60.810.10.20.30.40.50.60.70.8P r e c i s i o nRecallPrecision-Recall(b)CityscapeFigure 3:Classification Evaluation[8]F.Souvannavong,B.Merialdo,and B.Huet.Clas-sification semantique des macro-blocs mpeg dans le domaine compresse.In Compression et Repre-sentation des Signaux Audiovisuels ,pages 235–238,2003.[9]J.Verbeek,N.Vlassis,and B.Kr.Greedy gaussianmixture learning for texture segmentation.In Work-shop on Kernel and Subspace Methods for Com-puter Vision ,2001.[10]H.Wang and S.-F.Chang.A highly efficient systemfor automatic face region detection in mpeg video.In IEEE Transactions on Circuits and Systems for Video Technology ,volume 7,pages 615–628,Au-gust 1997.0.20.40.60.810.10.20.30.40.50.60.70.8P r e c i s i o nRecallPrecision-Recall(a)Text0.20.40.60.8100.10.20.30.40.50.60.70.8P r e c i s i o nRecallPrecision-Recall(b)FaceFigure 4:Classification Evaluation。

Chapter 1 Introduction1.Explain the following definition of linguistics: Linguistics is the scientific study oflanguage. 请解释以下语言学的定义:语言学是对语言的科学研究。

Linguistics investigates not any particular languagebut languages in general.Linguistic study is scientific because it is baxxxxsed on the systematic investigation of authentic language data.No serious linguistic conclusion is reached until after the linguist has done the following three things: observing the way language is actually usedformulating some hypothesesand testing these hypotheses against linguistic facts to prove their validity.语言学研究的不是任何特定的语言，而是一般的语言。

语言研究是科学的，因为它是建立在对真实语言数据的系统研究的基础上的。

只有在语言学家做了以下三件事之后，才能得出严肃的语言学结论:观察语言的实际使用方式，提出一些假设，并用语言事实检验这些假设的正确性。

1.What are the major branches of linguistics? What does each of them study?语言学的主要分支是什么?他们每个人都研究什么?Phonetics-How speech sounds are produced and classified语音学——语音是如何产生和分类的Phonology-How sounds form systems and function to convey meaning音系学——声音如何形成系统和功能来传达意义Morphology-How morphemes are combined to form words形态学——词素如何组合成单词Sytax-How morphemes and words are combined to form sentences句法学-词素和单词如何组合成句子Semantics-The study of meaning ( in abstraction)语义学——意义的研究(抽象)Pragmatics-The study of meaning in context of use语用学——在使用语境中对意义的研究Sociolinguistics-The study of language with reference to society社会语言学——研究与社会有关的语言Psycholinguistics-The study of language with reference to the workings of the mind心理语言学:研究与大脑活动有关的语言Applied Linguistics-The application of linguistic principles and theories to language teaching and learning应用语言学——语言学原理和理论在语言教学中的应用1.What makes modern linguistics different from traditional grammar?现代语言学与传统语法有何不同?Modern linguistics is descxxxxriptive;its investigations are baxxxxsed on authenticand mainly spoken language data.现代语言学是描述性的，它的研究是基于真实的，主要是口语数据。

International Journal Information theory & applications, Volume 9, Number 2, (51-60)Formal Languages for Image Primitives DescriptionPeter L. Stanchev, David Green Jr.Kettering University, Flint, MI 48504, {pstanche, dgreen}@How do people recognize things in the images? We do not know theanswer of this question. But in this paper we try to present some of the methodsused by the artificial intelligence to recognize primitives into an image. We willanalyze methods where images could be presented, as primitive’s strings. Suchimages are CAD/CAM engineering drawings, handwrite and typed characters,chromosome images, bubble chamber images, computer graphics images, etc.Syntactic description is most easily applied to images that have the followingproperties: (1) they can be decomposed into a set of primitives and (2) theprimitives are recognizable by an automatic procedure.Keywords:Formal Languages, Pattern Recognition1.F o r m a l D e f i n i t i o n sA n alphabet V, is any finite set of symbols. A string over analphabet V is any string of finite length composed of symbols from thealphabet. A string with length 0 is called the empty string, which is usuallydenoted by λ. V* - the free monoid over the set V is the set of all stringscomposed of symbols from V, including the empty string. The symbol V+denotes the set of strings V* - λ. A language is any set of strings over analphabet. A string grammar is a four-tuple G = (V N, V T, P, S), where V N is afinite set of nonterminals (variables), V T is a finite set of terminals(constants), (V T∩ V N = ∅), P is a finite set of productions and S is the start(root) symbol (S ∈V N). A language generated by G, denoted by L(G), is aset of strings that satisfy two conditions:a)each string is composed only of terminals;b)each string can be derived from S by suitable applications ofproductions from the set P.A grammar, in which the productions have the general form α→β, is called a phase structure grammar. According to the type ofrestrictions placed on the production rules the grammars may becategorized into four types:a) a grammar in which the form of production rules α→β, where α∈(V N∪ V T)+, β∈ (V N∪ V T)* is allowed, is called unrestricted grammar;b) a grammar in which the form of production rules is α1 A α2→α1βα2,where α1, α2∈ (V N∪ V T)* , β∈ (V N∪ V T)*, A ∈ V N, is called context-sensitive grammar;c) a grammar in which the form of production rules is A →β, where A∈V N, β∈ (V N∪ V T)+, is called context-free grammar;d) a grammar in which the form of production rules is A → a B or A →α,where A, B∈ V N, a ∈ V T, is called regular grammar.It is easy to see that all regular grammars are context-free, all context-free grammars are context-sensitive, and all context-sensitive grammars are unrestricted. The most often used grammars for image element description, are context-free and regular grammars. We will describe some of the most popular grammars concerned with some particular applications.2.A G r a m m a r f o r C h r o m o s o m e D e s c r i p t i o nThis grammar is proposed by Ledley at al. ([Ledl65]) and it is used to characterize submedian and telocentric chromosomes. The grammar isFigure 1. Set of chromosome primitivesG is given by G = (V N, V T, P, S) where V N =grammarThe{<submedian chromosome>, <arm pair>, <left part>, <right part>, <arm>, <side>}, V T = {a, b, c, d, e}, S={<submedian chromosome>}, and P:<submedian chromosome> →<arm pair> <arm pair><arm pair> →<side> <arm pair><arm pair> →<arm pair> <side><arm pair> →<arm> <right part><arm pair> →<left part> <arm><left part> →<arm> c<right part> → c <arm><side> → b <side><side> →<side> b<side> → b<side> → d<arm> → b <arm>b<arm> → <arm><arm> → aAn example of submedian chromosome is given in Figure 2. Their string representation is "babcbabdbabcbabd".3.T h e P i c t u r e D e s c r i p t i o n L a n g u a g e(P D L)Another interesting example for image element description is the picture description language (PDL), proposed by Shaw ([Shaw69]). In PDL each terminal symbol is labeled at two distinguished points, a tail and a head. Four binary and a unary operations between primitives are defined. The corresponding operation descriptions and interpretations are given in the Figure 3.Figure 3. PDL descriptionLet consider the following example concerning a house drawing description. The set of the primitives is given in the Figure 4.a b c dFigure 4. Set of a house drawing primitivesG =(V N, V T, P, S) is given by: V N = {house, roof,grammarThewall}, V T = { a, b, c, d, +, x , - , *, ~ , “,” },P: <roof> →((b + c)*a)<wall> →(((~d )+a)+d)<house> →(roof * wall)The PDL structural description ( ( ( b + c ) + a ) * ( ( ( ~ d ) + a ) + d ) ) corresponds to the house drawing in Figure 5.Figure 5. A house drawingPDL is often used to express characters, for the purpose of their recognition.4.G r a m m a r s f o r T w o o r T h r e e D i m e n s i o n a l P a t t e r nD e s c r i p t i o nIn our considerations up till now the only relation between primitives was the concatenation. A natural generalization is to use some other useful relations. This is a more effective in describing two or three-dimensional pattern.For example in the grammar proposed by [Ledl62] for house description, the following relations are included as terminal symbols:→ (X, Y) means that X is to the right of Y;Ο (X, Y) means that X is inside of Y;Θ (X, Y) means that X is inside on the bottom of Y;↑ (X, Y) means that X rests on tops of Y;→ (X, Y) means that X rests to the right of Y.The grammar is defined as G = (V N, V T, P, S). An example of V T is given in Figure 6, where V N= {<door>, <windows>, <chimney>, <wall>, <gable>, <roof>, <front view>, <side view>, <house> } , S={<house>}→ΟΘ↑ ( ) Figure 6. Definition of V T in example for house descriptionThe production set P can be defined as:<door> →<windows> →<windows><chimney><chimney><wall> →<wall> →Θ<wall> →Ο<gable> →<gable> →↑ (<chimney>, )<roof> →<roof> →↑ ( <chimney>, )<front view> →↑ ( <gable>, <wall> )<side view> →↑ ( <roof>, <wall> )<house> → <front view><house> → (<house>, <side view>)The following string corresponds to the house drawing shown in→(↑( ↑Figure 7. Drawing of a house5.T r e e G r a m m a rAregular tree grammar is a five-tuple G = (V N, V T, r, P, S), where V N is a finite set of nonterminals, V T is a finite set of terminals (V T∪V N = ∅), S is the start symbol (S ∈ V N), P is a finite set of productions of the form Ω→Ψ , where Ω and Ψ are trees, r is a ranking function, which denotes the number of direct descendants of a node whose label is a terminal in the grammar ([Moay76]). A tree grammar is an expansive tree grammar iff each production in P is of the formA → aA1A2....A N o r A→a,w h e r e a∈V T,A,A1,A2,...,A N∈V N.A house drawing and the corresponding tree representation is given in the Figure 8.Housea b c dSet of primitives$c db a baFigure 8. Tree representation of a house drawing6.F u z z y G r a m m a rLet X be a classical set of objects, called the universe, whose generic elements are denoted as x. Membership in a classical subset A of X is often viewed as a characteristic function from X to {0, 1}, such as µA(x) = 0 iff x ∉ A; and µA(x) = 1 iff x ∈ A. {0, 1} is called a valuation set . If the valuation set is measured on the real interval [0, 1], A is called a fuzzy set [Zade65]. µA(x) is the grade of membership of x in A.Informally, a fuzzy grammar may be viewed as a set of rules for generating the elements of a fuzzy set [Lee69]. More precisely, a fuzzy grammar is a quadruple G=(V N,V T ,P, S), where V T is a set of terminals, V N is a set of non-terminals (V T∩V N =∅), P is a finite set of productions, S ∈V N is the initial symbol. The elements of P define fuzzy sets in (V N∪ V T)* (referred as f uzzy productions) and for the case of context-free fuzzy grammars are expressions of the form: A ρ→β, A ∈ V N, β∈ (V N∪ V T)*, where 0 ≤ρ≤ 1 is the grade of membership of β given A. In case of general grammars, let α1, α2, ..., αm be strings in (V N∪ V T)* andα1ρ2→α2, α2ρ3→α3, ..., αm-1ρm→αm, where 0 ≤ρi≤1 be productions. The expressionα1ρ2→α2, α2ρ3→α3, ..., αm-1ρm→αm, will be referred to as a derivation chain from α1to αm. A string x of V T* is said to be in the fuzzylanguage L(G) iff x is derivable from S. The grade of membership µG(x) of x in L(G) is given by:µG(x) = sup min (µ ( S ρ1→α1), µ (α1ρ2→α2), ..., µ (αmρm+1→ x)), where µ (αIρi+1→αi+1) is the non-null ρi+1 such as (αIρi+1→αi+1) ∈ P, for i = 0, 1, ... , m, if α0 = S and αm+1 = x. The supremum is taken over all derivation chains from S to x. In any derivation chain, the minimum ρi is taken.A fuzzy grammar for a house drawing used in [Rabi87] isFigure 9. Set of primitivesThe fuzzy grammar G is given by G = (V N, V T, P, S), where V N = {<house>, <facade>, <front>, <sideview>, <wall>, <window>, <door>, <chimney>, <roof>}; V T = {in, inW, inN, inS, inE, inNW, inSW, inNE, inSE, outN, outS, outE, outNE, outSE, intersect, “,” , square, triangle, rhomboid, trapezoid}.The position symbols are presented in Figure 10, where I, W, N, S, denote the four cardinal points and "in" and "out" denote that an object is inside or outside another object. Other position terminal symbols are "intersect" for intersection, "(...)" for enclosure, etc.Figure 10. Relation symbolsS = <house> and P:<house> (1.0)→ <sideview> outE <house> ;<house> (1.0)→ <facade> ;<door> (1.0)→ <square> ;<window> (0.8)→ <square> ;<window> (1.0)→ square outE square ;<chimney> (0.8)→ trapezoid ;<wall> (1.0)→ square ;<wall> (1.0)→ ( <window> in square ) ;<wall> (0.8)→ ( <window> <door> in square ) ;<front> (1.0)→ triangle ;<front> (1.0)→ <chimney> outS triangle ;<roof> (1.0)→ rhomboid ;<roof> (1.0)→ <chimney> outS rhomboid ;<facade> (0.95)→ <front> outS <wall> ;<sideview> (1.0)→ <roof> outS <wall> ;<chimney> (0.9)→ square ;<wall>(0.95)→ (<door> inS square).For the house drawing in Figure 11 the following string corresponds: "(square outS rhomboid outS (square in square)) outE (triangle outS (square inS square ))". After processing by the given grammar the object "house" is recognized with grade of membership 0.8.Figure 11. A house drawing7.A t t r i b u t e R e l a t i o n a l G r a p hThe Attributed Relational Graph (ARG) is proposed in [Eshe84]. It is a relational structure, which consists of a set of nodes and a set of branches representing the relations between the nodes. Both nodes and branches may have some attributes assigned to them.Formally an ARG is defined as G = (N, B, A, E, G N, G B), where N (N = {n1, n2, ..., n|N|) - a finite set of nodes; |N| is the number of nodes in N;B (B = { b1, b2,...,b|N|}) - a set of ordered node pairs (or directed branches), i.e., b=(n i, n j) for some 1 ≤ i, j ≤ |N| denotes the branch emanating from node n i to node n j and |B| is the number of branches in B; A - an alphabet of node attributes; E - an alphabet of branch attributes; G N - a function (or a set of functions) for generating the node attributes; G B - a function (or a set of functions) for generating the branch attributes.Nodes are used to represent the basic elements in the image, while their properties are assigned as attributes to the respective nodes. Attributed branches between the corresponding nodes represent the relations between two basic elements. As an example we choose the area of House-furnishing design [Rabi89]. We limited the example to the basic elements shown in Figure 12, with the associated attributes, and the relations shown in Figure 13.Figure12. Basic elementsFigure 13. RelationsFigure 14. House furnishing design planThe corresponding ARG representation of the house furnishing plan from Figure 14 is: N (set of nodes)n1 → line ([0.0, 0.0], [0.7, 0.0])n2→ line ([0.0, 0.0], [0.0, 1.2])n3→ line ([2.3, 0.0], [4.8, 0.0])n4→ line ([6.1, 0.0], [6.6, 0.0])n5→ line ([0.0, 2.7], [0.0, 4.0])n6→ line ([6.6, 0.0], [6.6, 4.0])n7→ line ([0.0, 4.0], [6.6, 4.0])n8→ rectangle([0.7,-0.25],[2.3,-0.25], [0.7,0.25],[2.3, 0.25])n9→ rectangle([-0.25,1.2],[0.25, 1.2],[-0.25,2.7],[0.25, 2.7])n10→ rectangle([3.5, 2.5], [5.8, 2.5], [3.5, 4.0], [5.8, 4.0])n11→ door (1, [4.8, 0.0], [6.1, 0.0])n12→ bed (1, [0.75, 3.25])n13→ bed (1, [1.25, 3.25])n14→ wardrobe (1, [3.7, 0.7], 2, wood)n15→ chair (1, [2.5, 2.5])Some of the G B elements are:b1→ parallel (n12, n13),b2→ parallel (n12, n3),b3 → parallel (n13, n3).8.C o n c l u s i o n sThis paper presents some methods on understanding and interpretation of primitives in automated image analysis and processing. A new strategy using extended linear combination and fast two pass parallel pattern matching techniques is proposed in [Wang98]. This new method is able to distinguish objects with very similar patterns which is a limitation in the described methods.R e f e r e n c e s[Eshe84] Eshera M., Fu K., "A Graph Distance Measure for Image Analysis" , IEEE Trans. Syst., Man, Cyber., Vol. SMC.-14, No.3, pp.398-408 (May/June 1984)[Ledl62] Ledley R., "Programming and Utilising Digital Computers", DigitalComputers, McGraw-Hill, N.Y. (1962)[Ledl65] Ledley R., Rotolo L., Golab T., Jacobsen J., Ginsberg M., Wilson J., "FIDAC: Film Input to Digital Automatic Computer and Associated Syntax-Directed Pattern-Recognition Programming System" , in "Optical and Electro-Optical Information Processing" , Tippet J. et al., (edts.), MIT Press, pp.591-614 (1965)[Lee69] Lee E., Zadeh L., "Note on fuzzy languages", Information Sciences, Vol.1, pp.421-434 (1969).[Moay76] Moayer B., Fu K., "A Tree System Approach for Fingerprint Pattern Recognition" , IEEE Trans. Comput., C-25, pp.262-274 (Mar. 1976)[Rabi87] Rabitti F., Stanchev P., "An Approach to Image Retrieval from Large Image Databases", Proc. ACM-SIGIR Conf., New Orleans, pp.284-295 (1987)[Rabi89] Rabitti F., Stanchev P., "GRIM_DBMS - a GRaphical IMage DataBase System", in "Visual Database Systems", T. Kunii (edt.) North-Holland 1989 (415-430).[Shaw69] Shaw A., "A Formal Picture Description Scheme as a Basis for Picture Processing Systems" , Inf. Control, No. 14, pp.9-52 (1969)[Wang98] Wang P., Analysis, Learning, and Recognition of Articulated Line Drawing Images, Int. J. CSIM, Special Issue on Image Recognition, Vol 1-2, (1998).[Zade65] Zadeh L., "Fuzzy Sets", Inf. Control, No. 8, pp.338-353 (1965)。

英国论文Paper各部分如何写作英国留学要想写出高质量的paper，就必须写好paper的每个部分。

下面英国智酷小编就为大家介绍一下paper各部分如何写作吧！一篇Paper基本是由下面这九个部分组成的：Preparation, Structure, Title, Abstracts, Introduction, Conclusion, Body of Paper, Recursion, Acknowledgment.让我们先来看看paper写作都有哪些需要特别注意：Preparation（前期的准备工作）准备工作就是收集写作资料，找出灵感和写作方向，这步骤基本都会泡在图书馆里完成，当然也可可以适当结合网络资源库。

Structure（结构框架是重点）一篇paper的写作结构应该是两个triangle组成的：上面一个倒三角，下面一个正三角，可能Freshman就不懂了，没事往下看，这两三角形其实就是：选题可以宽一点(wide)，然后研究方向要窄，最后的conclusion又要扩散思维。

在paper的body前后都必须有declarative statement，用最少的字句表达出自己的观点，以吸引你的教授。

Title（标题要清晰简短）表达出自己唯一的topic以提升读者的兴趣(promote the interest of reader)，然而title中切记不能出现abbreviation和自己的result。

Abstract（摘要其实就是整篇Paper的浓缩版）简明扼要，一般情况下不要超过两百字，单独成段，，Abstract的写作顺序可以这样写：介绍主要研究对象(subject)、实验设计(design)、实验步骤(procedures)以及最后结果(results)Introduction（前言一样要求精简）顺序是一般背景介绍、别人工作成果、自己的研究目的及工作简介，其中介绍别人工作时只需介绍和自己最相关的方面(very relevant)，而对自己的工作介绍不用说明细节，因为这个要放到body中去。

英国留学生毕业论文写作技巧英国留学生毕业论文写作技巧写作的目的，一方面是要求考生对本专业的根底知识和专业知识学习的总结，另一方面也是考核自考生对所学理论进行科研能力的训练，下面是搜集的英国留学生毕业技巧，欢送阅读查看。

平时的小作业有essay 和 report 两种格式essay --- 结构分为introduction, main body, 和 conclusion. 不用太复杂的结构Report ----- 要有 executive summary, 结构要求很高，文章分为几个局部，每个局部都要有大标题，下面还要有副标题，等等。

(可以参考一起附上的report例文的结构)文章一定要有references (), 就是引用别人文章中的观点，但是这个引用不能整断整段的直接用书上，网上的文章，或者杂志上的文章的内容。

如果一段话中有超过三个词是引用的，就要说明references. (如果完全是用自己的语言将别人的观点说出来了，引用的词是两个或更少，就可以不用标出references)。

*如果整段要直接引用原话，要用引号标出，而且这样的引用的比率不能超过全文字数的5%。

*全文注明references的文字,就是引用的文字不能超过全文字数的30%.*References ()可以是书，也可以是学术杂志上发表的文章，或者网上的文章，但是引用的文章最好大多数是近十年的文章，而且References一定要按照正确方法标注。

References 在文中是在文中用自己的话说出别人书中或文章中的内容后，用括号标出作者和年代，而在文后的references列表中一定要用Harvard references system的格式来标出。

的数量也是有要求的，一般是每1000 字要有5个references.字数也是要按照要求写的，否那么会扣分文后的references列表和附录 (appendix)是不算字的。

比方，文章要求如果是4000字，那正文的字数就是4000 +/- 10% 字。

《学术论文写作（英）》课程教学大纲一、课程基本信息课程代码：17002204课程名称：学术论文写作（英）英文名称：Academic English Writing课程类别：通识课学时：64学分：4适用对象: 国际商学院财务管理中外联合培养项目班级；考核方式：考试先修课程：商务英语阅读II，商务英语写作II二、课程简介《学术论文写作（英）》专门针对广东财经大学中外人才培养实验班二年级学生开设的大学英语系列改革课程之一。

该课程是一门桥梁课程，旨在提高中国学生的学术研究与论文写作能力，帮助他们适应接下来的留学学习；课程以学术研究与论文写作各环节和分项技能的训练为纲，帮助学生培养良好的学术研究和写作习惯，并且注重技能的巩固和整合，强调学以致用。

同时，课程注重中西结合，在学术阅读和写作中加强爱国主义教育，增加学生文化自信，培养学生批判性思维，使之既要继承中华优秀传统文化又要弘扬时代精神，既要立足本国又要面向世界，即把中华传统文化以及现代文化的创新成果继承下来，传播出去，发扬光大，最终促使他们成为向世界介绍中国、传播中华文化且具有国际视野的高端双语复合型人才。

该课程教学采取以学生为中心, 教师讲授为引导，学生写作训练、主题讨论以及雅思写作模拟练习为辅助的模式；将面授与机助学习，课内讲授和课后自主学习紧密结合起来。

课堂教学采用外语教学与研究出版社引自的Garnet Education的经典学术英语教材《学术研究与论文写作》和《学术英语阅读》。

本课程的教学评估包括形成性评估和终结性评估。

三、课程性质与教学目的学术论文写作（英）是一门通识必修课，其主要目的是为我校必须参加雅思考试的中外人才培养实验班同学提供系统学习学术英语语言、培养学术论文写作能力和增强雅思写作考试技巧，同时通过大量阅读输入提高学生的学术英语素养、学术英语交流和跨文化交际能力，提升他们的批判性思维能力和跨文化交际意识。

学生学完该门课程后，应能达到以下要求：1）掌握基本学术论文写作技能，包括撰写abstract, introduction, definition, conclusion 的方法和paraphrasing 和referencing 的技巧、规范；2）掌握学术研究的基本方法，包括选题、收集和分类资料、运用论据论证观点、对论据的分析和解释等；3）学生的语篇分析和概括能力，特别是改述(paraphrase)和综述(summarise)的能力显著提升，语言表达丰富多样化；4）学生的批判性思维、西方逻辑思维和东西方文化差异意识通过写作、教师引导、和讨论得以相当的提升；提升学生在学术交流中的辩证性思考能力，能够坚定文化自信，向世界“讲好中国故事，传播好中国声音，阐释好中国特色”，进一步帮助学生树立正确价值观和加强爱国主义教育。

scientific paper 的含义特点-概述说明以及解释1.引言1.1 概述概述在科学研究领域，科学论文是学术交流的基础和重要手段之一。

科学论文是科学家们将自己的研究成果进行记录、总结和传播的方式，旨在向同行学者、研究机构和学术界提供全面而详实的研究结果。

通过科学论文的发表，研究者们可以分享他们的研究思路、实验方法、数据结果和结论，从而推动科学知识的进一步发展和学科的进步。

科学论文具有多种形式和格式，包括原始研究论文、综述论文、评论论文、案例报告等。

不同类型的科学论文有着不同的写作要求和结构，但它们都需要遵循科学研究的基本规范和准则。

科学论文具有一些共同的特点。

首先，科学论文应该是基于科学方法和实证研究得出的结论，而不是主观意见或个人观点的陈述。

其次，科学论文应该有明确的目的和研究问题，并通过严谨的实验设计和可靠的数据来解决这些问题。

此外，科学论文还应该具备可重复性，即其他研究者能够根据提供的方法和数据重新进行实验，以验证研究结果的可靠性和可信度。

科学论文的发表对科研人员来说具有重要意义。

首先，科学论文的发表能够扩大研究人员的影响力和声誉，提高个人的学术地位和职业发展。

其次，科学论文的发表可以促进学术交流和合作，有助于不同领域的研究者相互学习和借鉴。

另外，科学论文的发表还可以为学术界提供一个评价研究质量的标准，推动科学研究朝着更高的水平发展。

综上所述，科学论文作为科学研究和学术交流的重要手段，具有明确的定义和特点。

它们通过记录和传播研究成果，推动科学知识的发展和学科的进步。

科学论文的发表对于研究人员的个人发展和学术界的进步都起到了重要的推动作用。

1.2文章结构文章结构部分的内容可以如下编写：1.2 文章结构在科学论文撰写过程中，良好的文章结构是确保逻辑清晰性和读者易于阅读的重要因素。

一个典型的科学论文通常由以下部分组成：1.2.1 标题科学论文的标题应该简明扼要地概括研究的主题和目的。

一个好的标题可以吸引读者的注意力，并在最初阅读材料之前提供信息。

Chapter Five SemanticsTeaching Focus▪1. What is semantics?▪2. Meanings of “meaning”▪3. Sense and reference▪4. Sense relations▪5. Componential analysis --- a way to analyze lexical meaning▪6. Predication analysis --- a way to analyze sentence meaning1. What is semantics?▪Semantics is the study of meaning in language.▪Or specifically, it is the study of the meaning of linguistic units, words and sentences in particular.✦Different focus of the study in semantics:▪Logical semantics/philosophical semantics: Logicians and philosophers have tended to concentrate on a restricted range of sentences (typically, statements, or …propositions‟) within a single language.▪Linguistic semantics: The linguistic approach is broader in scope, aiming to study the properties of meaning in a systematic and objective way, with reference to as wide a range of utterances and languages as possible.2. Meanings of “Meaning”▪The word “meaning” has different meanings.▪It has been studied for thousands of years by philosophers, logicians and linguists.✦The naming theory: Plato & Aristotle✦Words are just names or labels for things.✦Can you show the limitations of this theory?▪The semantic triangle: C. K. Ogden & I. A. Richards (1923) → The Meaning of Meaning.▪There is no direct link between a linguistic form and what it refers to. In the interpretation of meaning they are linked through the mediation of concepts in the mind. ▪thought/reference (concept)symbolizes refers tosymbol/form referent(word, phrase) stands for(object)▪Geoffrey Leech (1974, 1981). Semantics: The Study of Meaning. Seven types of meaning:✦Conceptual meaning✦Connotative meaning✦Social meaning✦Affective meaning associative meaning✦Reflected and meaning✦Collocative meaning✦Thematic meaning(1) Conceptual meaning▪It makes the central part of meaning.✦Refers to logical, cognitive or denotative content.✦Concerned with the relationship between a word and the thing it denotes, or refers to.(2) Connotative meaning▪The communicative value an expression has by virtue of what it refers to, over and above its purely conceptual content.✦A multitude of additional, non-criterial properties, including not only physical characteristics but also psychological and social properties, as well as typical features. ▪Involving the …real world‟ experience one associates with an expression when one uses or hears it.✦Unstable: they vary considerably according to culture, historical period, and the experience of the individual.▪Any characteristic of the referent, identified subjectively or objectively, may contribute to the connotative meaning of the expression which denotes it.(3) Social meaning▪What a piece of language conveys about the social circumstances of its use.✦Dialect: the language of a geographical region or of a social class.✦Time: the language of the 18th c., etc.✦Province: language of law, of science, of advertising, etc.✦Status: polite, colloquial, slang, etc.✦Modality: language of memoranda, lectures, jokes, etc.✦Singularity: the style of Dickens, etc.▪domicile: very formal, official steed: poetic▪residence: formal horse: general▪abode: poetic nag: slang▪home: general gee-gee: baby language (4) Affective meaning▪Reflecting the personal feelings of the speaker, including his attitude to the listener, or his attitude to something he is talking about.✦You‟re a vicious tyrant and a villainous reprobate, and I hate you for it!✦I‟m terribly sorry to interrupt, but I wonder if you would be so kind as to lower your voices a little. or✦Will you belt up.(5) Reflected meaning▪Arises in cases of multiple conceptual meaning, when one sense of a word forms part of our response to another sense.✦When you hear …click the mouse twice‟, you think of Gerry being hit twice by Tom so you feel excited.▪Many taboo terms are result of this.(6) Collocative meaning▪The associations a word acquires on account of the meanings of words which tend to occur in its environment.✦pretty: girl, boy, woman, flower, garden, colour, village, etc.✦handsome: boy, man, car, vessel, overcoat, airliner, typewriter, etc.(7) Thematic meaning▪What is communicated by the way in which a speaker or writer organizes the message, in terms of ordering, focus, and emphasis.✦Mrs Bessie Smith donated the first prize.✦The first prize was donated by Mrs Bessie Smith.✦They stopped at the end of the corridor.✦At the end of the corridor, they stopped.3. Sense and reference▪Sense and reference are two terms often encountered in the study of word meaning. They are two related but different aspects of meaning.✦Sense is concerned with the inherent meaning of the linguistic form. It is the collection of all the features of the linguistic form; it is abstract and de-contextualized. It is the aspect of meaning dictionary compilers are interested in.✦Reference means what a linguistic form refers to in the real, physical world; it deals with the relationship between the linguistic element and the non-linguistic world of experience.▪Every word has a sense, but not every word has a reference.✦Grammatical words like but, if ,and do not refer to anything. And words like God, ghost and dragon refer to imaginary things.▪Therefore it is suggested that we should study meaning in terms of sense rather than reference.4. Sense relations▪Synonymygradable▪Antonymy complementaryconverse▪Hyponymy▪Polysemy4.1 Synonymy▪Synonymy refers to the sameness or close similarity of meaning. Words that are close in meaning are called synonyms.▪Complete synonyms are rare. According to the way they differ, synonyms can be divided into the following groups:▪i. Dialectal synonyms --- used in different regional dialects✦British English American English✦autumn fall✦lift elevator✦flat apartment✦tube underground▪ii. Stylistic synonyms --- differing in style✦kid, child, offspring✦kick the bucket, pop off, die, pass away, decease▪iii. Synonyms that differ in their emotive or evaluative meaning✦collaborator, accomplice▪iv. Collocational synonyms✦accuse, charge▪v. Semantically different synonyms✦surprise, amaze, astound4.2 Antonymy▪The term antonymy is used for oppositeness of meaning. Words that are opposite in meaning are antonyms.▪There are three types of antonyms.▪i. Gradable: Can be modified by adverbs of degree like very; Can have comparative forms; Can be asked with how.✦good, bad✦young, old✦hot, cold▪ii. Complementary: the denial of one member of the pair implies the assertion of the other.✦alive, dead✦male, female✦present, absent▪iii. Converse or relational: exhibit the reversal of a relationship between the pair; one presupposes the other.✦husband, wife✦buy, sell✦before, after4.3 Hyponymy▪Hyponymy refers to the sense relation between a more general word and a more specific word. It is a kind of inclusiveness.▪Superordinate: the more general word▪Hyponyms: the more specific words▪Co-hyponyms: hyponyms of the same superordinate✦flower, rose, lily✦animal, cat, dog✦furniture, bed, desk4.4 Polysemy▪Polysemy refers to the sense relation that the same one word has more than one meaning. Such a word is called a polysemic word.✦table: a piece of furniture; orderly arrangement of facts, figures5. Componential analysis---a way to analyze lexical meaning▪Componential analysis is a way proposed by the structural semanticists to analyze word meaning.▪The approach is based upon the belief that the meaning of a word can be dissected into meaning components, called semantic features.▪HUMAN✦man (ADULT, MALE)✦woman (ADULT, FEMALE)✦boy (NON-ADULT, MALE)✦girl (NON-ADULT, FEMALE)▪father: PARENT (x, y) & MALE (x)✦x is a parent of y, and x is male.▪take: CAUSE (x, (HA VE (x, y)))✦x causes x to have y.▪give: CAUSE (x, (~HA VE (x, y)))✦x causes x not to have y.▪Componential analysis provides an insight into the meaning of words and a way to study the relationships between words that are related in meaning.6. Predication analysis --- a way to analyze sentence meaning▪The meaning of a sentence is obviously related to the meanings of the words used in it, but it is also obvious that sentence meaning is not simply the sum total of the words.▪Predication analysis: proposed by the British linguist G. Leech▪The basic unit in this method is called prediction. It is the abstraction of the meaning of a sentence.▪A predication consists of argument(s) and predicate.✦An argument is logical participant in a predication, largely identical with the nominal element(s) in a sentence.✦A predicate is something said about an argument or it states the logical relation linking the arguments in a sentence.▪Tom smokes.▪Tom is smoking.▪Tom has been smoking. TOM (SMOKE)▪Does Tom smoking?▪Tom does not smoke. argument predicate▪Kids like apples. → KID, APPLE (LIKE)▪It is hot. → (BE HOT)Assignments▪How can words opposite in meaning be classified? To which category does each of the following pairs of antonyms belong?▪north/south vacant/occupied▪literate/illiterate above/below▪doctor/patient wide/narrow▪poor/rich father/daughter▪honest/dishonest normal/abnormalExercises▪I. Multiple choice.▪1. The naming theory seems applicable to ___ only.▪A. verbs B. adjectives C. adverbs D. nouns▪2. Hyponyms of the superordinate “flower” do not include “___”.▪A. wardrobe B. tulip C. lily D. rose▪3. Predication analysis is a way to analyze ___ meaning.▪A. phoneme B. word C. phrase D. sentence▪II. Make judgments (true or false)▪1. In the diagram of the classic semantic triangle, the word “symbol” refers to the object in the world of experience.▪2. When the same one word has more than one meaning we call it a polysemic word. ▪3. Complete synonyms, i.e. synonyms that are mutually substitutable under all circumstances, are rare in English.。

研究生学术英语读写教程unit7研究生学术英语读写教程 Unit7 的内容如下:主题：学术论文的结构和写作技巧本单元重点:- 了解学术论文的基本组成部分以及各自的作用- 掌握正确的学术论文写作技巧和风格- 学会如何优化学术论文的结构和排版本单元拓展:- 学术论文的阅读和撰写对于研究生来说是非常重要的技能。

通过本单元的学习，学生将学会如何有效地阅读和撰写学术论文，从而提高学术能力。

- 学术论文的结构和写作技巧是研究生学术英语读写教程中的重要部分。

通过学习本单元的内容，学生将能够更好地理解学术论文的结构和组织方式，从而更好地撰写学术论文。

具体内容:1. Introduction- 介绍学术论文的背景和目的- 阐述学术论文的基本组成部分以及各自的作用- 举例说明如何有效地组织 Introduction 部分2. Literature Review- 介绍文献综述的作用和意义- 阐述文献综述的基本组成部分以及各自的作用- 举例说明如何有效地组织 Literature Review 部分3. Methods- 介绍研究方法的重要性- 阐述研究方法的基本组成部分以及各自的作用 - 举例说明如何有效地组织 Methods 部分4. Results- 介绍研究结果的重要性- 阐述研究结果的基本组成部分以及各自的作用 - 举例说明如何有效地组织 Results 部分5. Discussion- 介绍讨论部分的作用和意义- 阐述讨论部分的基本组成部分以及各自的作用 - 举例说明如何有效地组织 Discussion 部分 6. Conclusion- 总结学术论文的主要内容- 强调学术论文的结论和贡献- 举例说明如何有效地撰写 Conclusion 部分 7. References- 列举学术论文中所引用的文献- 注意文献引用的准确性和完整性8. Format and 排版- 了解学术论文的排版格式- 学会如何优化学术论文的结构和排版本单元重点:- 了解学术论文的基本组成部分以及各自的作用- 掌握正确的学术论文写作技巧和风格- 学会如何有效地阅读和撰写学术论文，从而提高学术能力总结:研究生学术英语读写教程 Unit7 主要介绍了学术论文的结构和写作技巧。

太原科技大学毕业设计（论文）题目：遗传算法的参数分析姓名___ 张心悦__学院（系）应用科学学院专业_信息与计算科学班级 0381指导教师___ 刘斌___年月日太原科技大学毕业设计（论文）任务书（由指导教师填写发给学生）学院（直属系）：时间：年月日说明：一式两份，一份装订入学生毕业设计（论文）内，一份交学院（直属系）。

目录摘要 (Ⅲ)ABSTRACT (Ⅳ)第1章绪论 (1)1.1 遗传算法的产生背景 (1)1.1.1 遗传算法产生的生物学基础 (4)1.1.2 从生物进化到演化计算 (6)1.1.3 遗传算法的特点 (9)1.2 遗传算法的发展及研究状况 (11)1.3 本文的主要工作 (15)第2章遗传算法简介 (16)2.1 遗传算法的基本流程 (18)2.2 遗传算法的基本实现技术 (20)2.2.1 编码 (21)2.2.2 适应性的度量 (22)2.2.3 选择算子 (23)2.2.4 交叉算子 (24)2.3 遗传算法的收敛性分析 (28)第3章参数对遗传算法性能影响实例分析 (29)3.1 基本遗传算法的实现 (30)3.2 遗传算法运行参数分析 (32)3.2.1 确立评价目标函数 (36)3.2.2 分析各参数的影响 (38)3.3 对基本遗传算法的改进 (40)3.3.1适应值函数的改进 (42)3.3.2 自适应遗传算法 (46)参考文献 (49)致谢 (50)附录 (55)附录Ⅰ中文译文....................................................................................... ..55 附录Ⅱ英文原文 (62)(注1：如果还有其他附录，可放在中文译文之前，中文译文、英文原文编号顺延) (注2：先将目录排好，基本对齐，然后选择段落-对齐方式-分散对齐)遗传算法的参数分析摘要思维进化计算是模拟人类思维过程提出的一种很有潜力的新型演化算法。

框架语义学Charles J. Fillmore 原著詹卫东 译一 引 言“框架语义学”在我的脑海中是一个经验主义语义学的研究计划，同时也是一个用来呈现这类研究的结果的一个描述框架。

框架语义学提供了观察词语的意义的一种特别的方式，同时也试图刻画一种语言产生新词和新短语，以及向已有的词语里增加新的意义，或将一段文章中各成分的意义组装到一起，从而形成整篇文章的全部意义等等所需要遵循的原则。

通过“框架”这个术语，我在脑海中建立起了全部的概念系统。

理解一个概念系统中的任何一个概念，必须以理解它所适应的整个结构为前提。

当这样一个概念结构中的诸多概念中的一个被置入到一个文本、或一次交谈中时，（该概念结构中）其他所有的概念都自动被激活。

我在这里使用“框架”这个词作为一个覆盖面很广的术语，来涵盖那些讨论自然语言理解问题的文献中提到过的一系列概念，诸如“图式”（schema）、“脚本”（script）、“情景”（scenario）、“观念框架”（ideational scaffolding）、“认知模式”（cognitive model）、“民俗理论”（folk theory）等等1。

框架语义学出自经验主义语义学传统，而不是形式语义学。

它更像是民族学意义上的语义学。

有点像人类学家的工作。

一个人类学学者进入一种异族的文化，会问一些诸如此类的问题，比如“当这个言语社团的成员用语言交谈时，哪些经验范畴会通过他们所选用的语言形式来编码？”框架语义学的大纲跟形式语义学的工作和结果是不矛盾的（或没有必要是矛盾的），但它跟形式语义学仍有重要的不同，差别主要在于，前者强调语言与经验之间的连续性（continuities），而不是非连续性。

我在这篇论文中要表达的观点与其说是经验主义语义学的真正理论，倒不如说是提出了这样一种理论必须处理的一系列问题。

我宁愿把本文所讨论的内容称为“先于形式化的”（pre-formal），而不是“非形式化的”（non-formalist）。

formal representation 语言学
（原创版）
目录
1.形式化表示的定义与重要性
2.形式化表示的方法与应用
3.形式化表示在语言学中的发展与影响
正文
形式化表示是语言学中一个重要的概念，它指的是将语言中的符号、规则和结构用形式化的方式进行描述和表示。

这种表示方式能够使语言学家更好地理解语言的内在规律，从而为语言学的研究提供重要的理论基础。

形式化表示的方法主要有两种：一种是通过数学模型进行表示，如使用上下文无关文法（CFG）来描述语言的句法结构；另一种是通过逻辑符
号进行表示，如使用谓词逻辑来描述语言的语义结构。

这两种方法各有优势，可以根据研究者的需要和研究对象的特点进行选择。

形式化表示在语言学中的应用广泛，例如在自然语言处理（NLP）领域，通过形式化表示可以设计出高效的算法和模型，实现对自然语言的自动分析和生成。

同时，形式化表示也为语言学理论的建构提供了重要的支持，如在生成语言学中，通过形式化表示可以清晰地展示语言的生成过程和规律。

形式化表示在语言学中的发展可以追溯到 20 世纪中叶，随着计算机技术的发展和应用，形式化表示的方法和理论得到了迅速的发展和完善。

如今，形式化表示已经成为语言学研究的一个重要方向，它的发展和变化也直接影响着语言学的研究和应用。

总的来说，形式化表示是语言学中的一个重要概念，它通过特定的方法和形式，对语言的符号、规则和结构进行描述和表示。

文字排版术语英语词汇文字排版术语英语词汇引导语：文字是人类文化的重要组成部分.无论在何种视觉媒体中，文字和图片都是其两大构成要素，文字排列组合的好坏,直接影响着版面的视觉传达效果。

以下是店铺分享给大家的文字排版术语英语词汇，欢迎阅读!版口 margins 版心边沿至成品边沿的空白区域。

版面 packageprinting 印刷成品幅面中图文和空白部分的总和。

版面远程传输remote page transmission 将排版成品图像以无线或有线的方式传输到异地。

版式 page layout 出版物的组合设计要求。

背题 bottom line title 禁上将某一级次的标题排于版末,题下无正文行的排版禁则。

倍数铅空 editing and page make-up system 以微机控制可进行编辑、排版、校改、组版的设备。

编辑排版装置 proofing 将正体文字通过光学原件或其他成像方式变你成长、扁、斜等形状的文字。

变形文字 deformed letters 将正体文字通过光学原件或其他成像方式变你成长、扁、斜等形状的文字。

标题级序 title series 标题大小及层次顺序的排列，排版时同一级序标题的字体字号及规格要统一。

串文 illustration and text juxtaposed setting 在标题,插图,表格一侧排入正文。

打字排版 typewriter composition 用打字机通过色带将文字打在载体上组成版面的.排版工艺。

单字铸排 individual type composing and casting 依照原稿选模，铸成单字并排成毛条的排版工艺。

倒空 turned letter 用同号活字倒置排入以暂代缺字。

地脚 foot margin 版心下边沿至成品连沿的区域。

点阵式字符 dot matrix character 以不同精度按X、Y方向排列的点阵构成的字符体形。