Introduction to DynamicSemantics

Arbitrariness ---任意性，最先由
Saussure提出，语言学之父。 Arbitrary relationship between the sound of a morpheme and its meaning.
Duality（二重性） 语言是层级性的，主要是由
syllables morphemes word phrase sentence discourse这么个系统组成的。 (浙大）问答题：Explain what the term duality means as it is used to describe a property of human lg.
讲义一 Introduction to Linguistics
Grace Tan
T/F
1.The relation between form and meaning in human
language is natural. 2.When lg is used to get information from others , it serves an informative function. 3.The reason for French to use Cheval and English to use horse to refer to the same animal is inexplicable. 4.Most animal communication systems lack the primary level of articulation. 5.Halliday′s linguistic potential is similar to the notions of parole and performance. 6.Descriptive linguistics are concerned with how lgs work, not with how they can be improved.

编译原理英文版课后答案Chapter 1: Introduction to Compilation1. What is compilation?Compilation is the process of translating a high-level programming language code into a low-level machine language code that can be directly executed by a computer.2. What are the main components of a compiler?The main components of a compiler are:•Lexer: also known as a tokenizer, it breaks the source code into a sequence of tokens.•Parser: it verifies the syntax of the source code and builds an intermediate representation such as an abstract syntax tree (AST).•Semantic Analyzer: it checks for semantic correctness and assigns meaning to the program.•Intermediate Code Generator: it generates a representation of the program that can be easily translated into machine code.•Optimizer: it improves the efficiency of the program by performing various optimizations.•Code Generator: it translates the intermediate code into the target machine code.3. What are the advantages of compilation over interpretation?•Performance: Compiled code runs faster than interpreted code as the compilation process optimizes the code for a specific target machine.•Portability: Once a program is compiled, it can be executed on any machine that supports the target machine code, eliminating the need for aruntime environment.•Security: The source code is not distributed with the compiled program, making it harder for others to access and modify the code.4. What are the disadvantages of compilation?•Longer development cycle: Compilation requires additional time and effort compared to interpretation, as it involves multiple stages such as code generation and optimization.•Platform dependency: Compiled code is specific to the target machine, so it may not run on different architectures or operating systems withoutrecompilation.•Lack of flexibility: Changes made to the source code may require recompilation of the entire program.5. What is the difference between a compiler and an interpreter?A compiler translates the entire source code into machine code before execution, while an interpreter translates and executes the source code line by line.Chapter 2: Lexical Analysis1. What is lexical analysis?Lexical analysis, also known as tokenization, is the process of dividing the source code into a sequence of tokens.2. What are tokens?Tokens represent the basic building blocks of a programming language. They can be keywords, identifiers, constants, operators, or punctuation symbols.3. What is a regular expression?A regular expression is a sequence of characters that defines a search pattern. It is used in lexical analysis to describe the patterns of tokens.4. What are regular languages?Regular languages are a class of formal languages that can be described by regular expressions. They can be recognized by finite automata.5. What is a finite automaton?A finite automaton is a mathematical model of a computation process. It consists of a finite set of states and transitions between those states based on input.Chapter 3: Parsing1. What is parsing?Parsing is the process of analyzing the structure of a program according to the rules of a formal grammar. It involves constructing an abstract syntax tree (AST) from the given source code.2. What is an abstract syntax tree (AST)?An abstract syntax tree is a hierarchical representation of the syntactic structure of a program. It captures the relationships between different elements of the code, such as expressions and statements.3. What is a context-free grammar (CFG)?A context-free grammar is a formal way to describe the syntax of a programming language. It consists of a set of production rules that define how valid program statements can be constructed.4. What is the difference between a parse tree and an abstract syntax tree (AST)?A parse tree represents the complete syntactic structure of a program, including all the intermediate steps taken during parsing. An abstract syntax tree (AST) is a simplified version of the parse tree, where redundant information is removed, and only the essential structure of the program is retained.5. What is ambiguous grammar?An ambiguous grammar is a grammar that allows for multiple parse trees for a single input string. It can lead to parsing conflicts and difficulties in determining the correct interpretation of a program.Chapter 4: Semantic Analysis1. What is semantic analysis?Semantic analysis is the phase of the compilation process that checks the semantic correctness of a program. It assigns meaning to the code and ensures that it adheres to the rules and constraints of the programming language.2. What are static semantics?Static semantics are the properties of a program that can be determined at compile-time. These include type checking, scope rules, and variable declarations.3. What are dynamic semantics?Dynamic semantics are the properties of a program that can only be determined at runtime. These include program behavior, control flow, and runtime errors.4. What is type checking?Type checking is the process of verifying that the types of expressions and variables in a program are compatible according to the rules of the programming language. It prevents type-related errors during execution.5. What is symbol table?A symbol table is a data structure used by the compiler to store information about variables, functions, and other symbols in a program. It enables efficient semantic analysis and name resolution.Note: These answers are for reference purposes only and may vary depending on the specific context and requirements of the course or textbook.。

论文收录检索证明报告华北电力大学图书馆论文作者: Zhuxiao,Wang; Wang,Zhuxiao论文发表年限: 2012-2015检索数据库: Ei Compendex检索结果 :8篇收录Title:1. An Extension of Distributed Dynamic Description Logics for the Representation of Heterogeneous Mappings2. An architecture description language based on dynamic description logics for self-healing systems3. An architecture description language based on dynamic description logics4. An Architecture Dynamic Modeling Language for Self-Healing Systems5. A Tableau-Based Reasoning Algorithm for Distributed Dynamic Description Logics6.A formal model for attack mutation using dynamic description logics7. Linear cryptanalysis and security tradeoff of block ciphering systems with channel errors8. Research on sentiment analysis in sentence and text levels with priors特此证明!(盖章)检索报告人:年月日附件:收录情况：1. Accession number: 20132016337096Title: An extension of distributed dynamic description logics for the representation of heterogeneous mappingsAuthors: Wang, Zhuxiao1 ; Guo, Jing2 ; Chen, Fei3 ; Wu, Kehe3 ; Wang, Peng4Author affiliation: 1 School of Control and Computer Engineering, State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, 102206 Beijing, China2 National Computer Network Emergency Response Technical Team, Coordination Center of China, 100029 Beijing, China3 School of Control and Computer Engineering, North China Electric Power University, 102206 Beijing, China4 Institute of Information Engineering, Chinese Academy of Sciences, 100195 Beijing, China Corresponding author: Wang,Z.(****************.cn)Source title: Journal of SoftwareAbbreviated source title: J. Softw.Volume: 8Issue: 1Issue date: 2013Publication year: 2013Pages: 243-250Language: EnglishISSN: 1796217XDocument type: Journal article (JA)Publisher: Academy Publisher, P.O.Box 40,, OULU, 90571, FinlandAbstract: As a family of dynamic description logics, DDL(X) is constructed by embracing actions into the description logic X, where X represents well-studied description logics ranging from the ALC to the SHOIQ. To efficiently support automated interoperability between ontology-based information systems in distributed environments, we have to design an expressive mapping language to semantically understand resources from remote and heterogeneous systems. Distributed Dynamic Description Logics D3L(X) is a natural generalization of the DDL(X) framework, which is designed to model the distributed dynamically-changing knowledge repositories interconnected by semantic mappings and to accomplish reasoning in distributed, heterogeneous environments. In this paper, we propose an extension of Distributed Dynamic Description Logics D3L(X) and investigate the reasoning mechanisms in D3L(X). © 2013 ACADEMY PUBLISHER.Number of references: 16Main heading: Data descriptionControlled terms: Formal languages - Interoperability - Mapping - Semantics Uncontrolled terms: Distributed Dynamic Description Logics - Distributed reasonings - Dynamic description logic - Semantic mapping - Tableau algorithmClassification code: 716 Telecommunication; Radar, Radio and Television - 717 Optical Communication - 718 Telephone Systems and Related Technologies; Line Communications -723 Computer Software, Data Handling and Applications - 902.1 Engineering Graphics - 903.2 Information DisseminationDOI: 10.4304/jsw.8.1.243-250Database: CompendexCompilation and indexing terms, © 2013 Elsevier Inc.2. Accession number: 20124415623183Title: An architecture description language based on dynamic description logics for self-healing systemsAuthors: Wang, Zhuxiao1 ; Peng, Hui2 ; Guo, Jing3 ; Wu, Kehe4 ; Cui, Wenchao4 ; Wang, Xiaofeng5Author affiliation: 1 School of Control and Computer Engineering, State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China2 Education Technology Center, Beijing International Studies University, Beijing 100024, China3 National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing 100029, China4 School of Control and Computer Engineering, Institute of Electric Information Security Engineering Research Center of Power Information, North China Electric Power University, Beijing 102206, China5 Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China Corresponding author: Wang,Z.(****************.cn)Source title: International Journal of Advancements in Computing Technology Abbreviated source title: Intl. J. Adv. Comput. Technolog.Volume: 4Issue: 18Issue date: October 2012Publication year: 2012Pages: 89-96Language: EnglishISSN: 20058039E-ISSN: 22339337Document type: Journal article (JA)Publisher: Advanced Institute of Convergence Information Technology, Myoungbo Bldg 3F,, Bumin-dong 1-ga, Seo-gu, Busan, 602-816, Korea, Republic ofAbstract: As biological systems exhibit adaptation, healing and robustness in the face of changing environmental behavior, this paradigm has actuated research dealing with the concept of self-healing systems, which attempt to heal themselves in the sense of recovering from malicious attacks and rectifying of system faults. The goal of self-healing systems is to provide survivable systems that require high dependability, robustness, adaptability, and availability. Such systems maintain one or more models, whether external or internal, at run time as a basis for identifying problems and resolving them. This article describes an architectural description language, called ADML, which is being developed as a new formal language and/or conceptual model forrepresenting evolving software architectures. The ADML embraces dynamic change as a fundamental consideration, supports a broad class of adaptive changes at the architectural level, and offers a uniform way to represent and reason about both static and dynamic aspects of self-healing systems. Because the ADML is based on the Dynamic Description Logic DDL(SHON (D)), which can represent both dynamic semantics and static semantics under a unified logical framework, architectural ontology entailment for the ADML languages can be reduced to knowledge base satisfiability in DDL(SHON (D)), and dynamic description logic algorithms and implementations can be used to provide reasoning services for ADML. In this article, we present the syntax of ADML, explain its underlying semantics using the Dynamic Description Logic DDL(SHON (D)), and exemplify our approach by applying it to the domain of load balancing a wireless remote-access system; the preliminary results certify the potential of the approach. Number of references: 14Main heading: Data descriptionControlled terms: Formal languages - Knowledge based systems - Knowledge representation - Semantics - Software architectureUncontrolled terms: Architecture description languages - Dynamic adaptations - Dynamic description logic - Knowledge representation and reasoning - Self-healing systemsClassification code: 723 Computer Software, Data Handling and Applications - 903.2 Information DisseminationDOI: 10.4156/ijact.vol4.issue 18.11Database: CompendexCompilation and indexing terms, © 2013 Elsevier Inc.3. Accession number: 20125015790730Title: An architecture description language based on dynamic description logicsAuthors: Wang, Zhuxiao1 ; Peng, Hui2 ; Guo, Jing3 ; Zhang, Ying1 ; Wu, Kehe1 ; Xu, Huan1 ; Wang, Xiaofeng4Author affiliation: 1 School of Control and Computer Engineering, State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China2 Education Technology Center, Beijing International Studies University, Beijing 100024, China3 National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing 100029, China4 Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China Corresponding author: Wang,Z.(****************.cn)Source title: IFIP Advances in Information and Communication TechnologyAbbreviated source title: IFIP Advances in Information and Communication Technology Volume: 385 AICTMonograph title: Intelligent Information Processing VI - 7th IFIP TC 12 International Conference, IIP 2012, ProceedingsIssue date: 2012Publication year: 2012Pages: 157-166Language: EnglishISSN: 18684238ISBN-13: 9783642328909Document type: Conference article (CA)Conference name: 7th IFIP International Conference on Intelligent Information Processing, IIP 2012Conference date: October 12, 2012 - October 15, 2012Conference location: Guilin, ChinaConference code: 94249Sponsor: IFIP TC12; Guilin University of Electronic Technology; Chinese Academy of Sciences, Institute of Computing TechnologyPublisher: Springer New York, 233 Spring Street, New York, NY 10013-1578, United States Abstract: ADML is an architectural description language based on Dynamic Description Logic for defining and simulating the behavior of system architecture. ADML is being developed as a new formal language and/or conceptual model for representing the architectures of concurrent and distributed systems, both hardware and software. ADML embraces dynamic change as a fundamental consideration, supports a broad class of adaptive changes at the architectural level, and offers a uniform way to represent and reason about both static and dynamic aspects of systems. Because the ADML is based on the Dynamic Description Logic DDL( (D)), which can represent both dynamic semantics and static semantics under a unified logical framework, architectural ontology entailment for the ADML languages can be reduced to knowledge base satisfiability in DDL( (D)), and dynamic description logic algorithms and implementations can be used to provide reasoning services for ADML. In this article, we present the syntax of ADML, explain its underlying semantics using the Dynamic Description Logic DDL( (D)), and describe the core architecture description features of ADML. © 2012 IFIP International Federation for Information Processing.Number of references: 14Main heading: Data descriptionControlled terms: Formal languages - Knowledge based systems - Knowledge representation - Semantics - Software architectureUncontrolled terms: Architectural description languages - Architectural levels - Architecture description - Architecture description languages - Conceptual model - Distributed systems - Dynamic adaptations - Dynamic changes - Dynamic description logic - Dynamic semantic - Hardware and software - Knowledge base - Knowledge representation and reasoning - Logical frameworks - ON dynamics - Satisfiability - Static and dynamic - Static semantics - System architecturesClassification code: 723 Computer Software, Data Handling and Applications - 903.2 Information DisseminationDOI: 10.1007/978-3-642-32891-6_21Database: CompendexCompilation and indexing terms, © 2013 Elsevier Inc.4. Accession number: 20121214883239Title: An architecture dynamic modeling language for self-healing systemsAuthors: Wang, Zhuxiao1 ; Guo, Jing2; Wu, Kehe1; He, Hui1; Chen, Fei1Author affiliation: 1 School of Control and Computer Engineering, State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China2 National Computer Network Emergency Response Technical Team, Coordination Center of China, Beijing 100029, ChinaCorresponding author: Wang,Z.(****************.cn)Source title: Procedia EngineeringAbbreviated source title: Procedia Eng.Volume: 29Monograph title: 2012 International Workshop on Information and Electronics Engineering Issue date: 2012Publication year: 2012Pages: 3909-3913Language: EnglishISSN: 18777058Document type: Conference article (CA)Conference name: 2012 International Workshop on Information and Electronics Engineering, IWIEE 2012Conference date: March 10, 2012 - March 11, 2012Conference location: Harbin, ChinaConference code: 89020Sponsor: Harbin University of Science and Technology; International Science and Engineering Research CenterPublisher: Elsevier Ltd, Langford Lane, Kidlington, Oxford, OX5 1GB, United Kingdom Abstract: As modern software-based systems increase in complexity, recovery from malicious attacks and rectification of system faults become more difficult, labor-intensive, and error-prone. These factors have actuated research dealing with the concept of self-healing systems, which employ architectural models to monitor system behavior and use inputs obtaining therefore to adapt themselves to the run-time environment. Numerous architectural description languages (ADLs) have been developed, each providing complementary capabilities for architectural development and analysis. Unfortunately, few ADLs embrace dynamic change as a fundamental consideration and support a broad class of adaptive changes at the architectural level. The Architecture Dynamic Modeling Language (ADML) is being developed as a new formal language and/or conceptual model for representing dynamic software architectures. The ADML couple the static information provided by the system requirements and the dynamic knowledge provided by tactics, and offer a uniform way to represent and reason about both static and dynamic aspects of self-healing systems. Because the ADML is based on the Dynamic Description Logic DDL, architectural ontology entailment for the ADML languages can be reduced to knowledge base satisfiability in DDL. © 2011 Published by Elsevier Ltd.Number of references: 10Main heading: ArchitectureControlled terms: Data description - Electronics engineering - Embedded systems -Formal languages - Knowledge based systems - Knowledge representation - Software architectureUncontrolled terms: Architecture description languages - Dynamic adaptation - Dynamic description logic - Knowledge representation and reasoning - Self-healing systemsClassification code: 723 Computer Software, Data Handling and Applications - 722 Computer Systems and Equipment - 718 Telephone Systems and Related Technologies; Line Communications - 717 Optical Communication - 716 Telecommunication; Radar, Radio and Television - 715 Electronic Equipment, General Purpose and Industrial - 714 Electronic Components and Tubes - 713 Electronic Circuits - 402 Buildings and TowersDOI: 10.1016/j.proeng.2012.01.593Database: CompendexCompilation and indexing terms, © 2013 Elsevier Inc.5. Accession number: 20124315590040Title: A tableau-based reasoning algorithm for distributed dynamic description logics Authors: Wang, Zhuxiao1 ; Guan, Zhitao1 ; Li, Wei1 ; Wu, Kehe1 ; Guo, Jing2 ; Tian, Guanhua3Author affiliation: 1 School of Control and Computer Engineering, State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, 102206 Beijing, China2 National Computer Network Emergency Response Technical Team, Coordination Center of China, 100029 Beijing, China3 Institute of Automation, Chinese Academy of Sciences, 100190 Beijing, China Corresponding author: Wang,Z.(****************.cn)Source title: Communications in Computer and Information ScienceAbbreviated source title: Commun. Comput. Info. Sci.Volume: 307 CCISIssue: PART 1Monograph title: Information Computing and Applications - Third International Conference, ICICA 2012, ProceedingsIssue date: 2012Publication year: 2012Pages: 192-199Language: EnglishISSN: 18650929ISBN-13: 9783642340376Document type: Conference article (CA)Conference name: 3rd International Conference on Information Computing and Applications, ICICA 2012Conference date: September 14, 2012 - September 16, 2012Conference location: Chengde, ChinaConference code: 93206Sponsor: National Science Foundation of China; Hunan Institute of Engineering; YanshanUniversity; Northeastern University at Qinhuangdao; Chengde Petroleum CollegePublisher: Springer Verlag, Tiergartenstrasse 17, Heidelberg, D-69121, Germany Abstract: As a family of dynamic description logics, DDL(X) is constructed by embracing actions into the description logic X, where X represents well-studied description logics ranging from the ALC to the SHOIQ. The usage of distributed computation techniques in reasoning is an important premise for the adoption of Dynamic Description Logics in a real-world setting. Practical scalability of DDL(X) reasoning inspired recently a proposal of Distributed Dynamic Description Logics (D3L) framework. D3L is a natural generalization of the DDL(X) framework, which is designed to model the distributed dynamically-changing knowledge repositories interconnected by semantic mappings and to accomplish reasoning in distributed, heterogeneous environments. In this paper, we investigate the reasoning mechanisms in D3L and propose a tableau-based reasoning algorithm for D3L, built as a composition of the state of the art tableaux reasoners for DDL(X). © 2012 Springer-Verlag.Number of references: 15Main heading: Data descriptionControlled terms: Algorithms - Formal languages - Inference engines - Semantics Uncontrolled terms: Description logic - Distributed computations - Distributed dynamics - Distributed Reasoning - Dynamic description logic - Heterogeneous environments - Knowledge repository - Natural generalization - Reasoning algorithms - Reasoning mechanism - Semantic mapping - State of the art - Tableau algorithm - Tableaux reasonersClassification code: 723 Computer Software, Data Handling and Applications - 903.2 Information Dissemination - 921 MathematicsDOI: 10.1007/978-3-642-34038-3_27Database: CompendexCompilation and indexing terms, © 2013 Elsevier Inc.6. Accession number: 20150400451745Title: A formal model for attack mutation using dynamic description logicsAuthors: Wang, Zhuxiao1 Email author ****************.cn;Guo, Jing2 Email ********************************;Shi,******************************.cn;He,Hui1Email author ***************.cn;Zhang, Ying1 Email author *******************.cn;Peng, Hui3 ***************************.cn;Tian,*************************************.cn Author affiliation: 1 School of Control and Computer Engineering, State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China2 National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing, China3 Education Technology Center, Beijing International Studies University, Beijing, China4 Institute of Automation, Chinese Academy of Sciences, Beijing, ChinaCorresponding author: Wang, ZhuxiaoSource title: IFIP Advances in Information and Communication TechnologyAbbreviated source title: IFIP Advances in Information and Communication Technology V olume: 432V olume title: Intelligent Information Processing VII - 8th IFIP TC 12 International Conference, IIP 2014, ProceedingsIssue date: 2014Publication year: 2014Pages: 303-311Language: EnglishISSN: 18684238ISBN-13: 9783662449790Document type: Journal article (JA)Publisher: Springer New York LLCAbstract: All currently available Network-based Intrusion Detection Systems (NIDS) rely upon passive protocol analysis which is fundamentally flawed as an attack can evade detection by exploiting ambiguities in the traffic stream as seen by the NIDS. We observe that different attack variations can be derived from the original attack using simple transformations. This paper proposes a semantic model for attack mutation based on dynamic description logics (DDL(X)), extensions of description logics (DLs) with a dynamic dimension, and explores the possibility of using DDL(X) as a basis for evasion composition. The attack mutation model describes all the possible transformations and how they can be applied to the original attack to generate a large number of attack variations. Furthermore, this paper presents a heuristics planning algorithm for the automation of evasion composition at the functional level based on DDL(X). Our approach employs classical DL-TBoxes to capture the constraints of the domain, DL-ABoxes to present the attack, and DL-formulas to encode the objective sequence of packets respectively. In such a way, the evasion composition problem is solved by a decidable tableau procedure. The preliminary results certify the potential of the approach. © IFIP International Federation for Information Processing 2014.Number of references: 9Main heading: Data descriptionControlled terms: Algorithms - Formal languages - Intrusion detection - Knowledge representation - SemanticsUncontrolled terms: Advanced evasion techniques - Dynamic description logic - Intrusion detection/prevention systems - Knowledge representation and reasoning - MultiprotocolsClassification code: 723 Computer Software, Data Handling and Applications - 903.2 Information DisseminationDatabase: CompendexCompilation and indexing terms, © 2015 Elsevier Inc.7. Accession number: 20130115855490Title: Linear cryptanalysis and security tradeoff of block ciphering systems with channel errorsAuthors: Guo, Jing1 ; Wang, Zhuxiao2Author affiliation: 1 National Computer Network Emergency Response Technical Team/Coordination Center of China (CNCERT/CC), Beijing 100029, China2 School of Control and Computer Engineering, State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, ChinaCorresponding author: Guo,J.(**************************)Source title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Abbreviated source title: Lect. Notes Comput. Sci.Volume: 7645 LNCSMonograph title: Network and System Security - 6th International Conference, NSS 2012, ProceedingsIssue date: 2012Publication year: 2012Pages: 405-416Language: EnglishISSN: 03029743E-ISSN: 16113349ISBN-13: 9783642346002Document type: Conference article (CA)Conference name: 6th International Conference on Network and System Security, NSS 2012 Conference date: November 21, 2012 - November 23, 2012Conference location: Wuyishan, Fujian, ChinaConference code: 94688Publisher: Springer Verlag, Tiergartenstrasse 17, Heidelberg, D-69121, Germany Abstract: Channel errors are usually treated as an obstacle in designing an encrypted wireless system. So we are supposed to reduce them as much as possible due to the potential error bursts contributed by an avalanche effect of block ciphers. In this paper, we propose that channel errors are to be explored for the benefit of security enhancement as they could be translated to additional efforts in cryptanalysis for an adversary node. To achieve this, a system with an outer block channel coder and an inner block cipher is presented. A framework for linear cryptanalysis is established under which an eavesdropper takes advantage of linear relationship among coded symbols, as well as linear approximation of ciphers. Also presented is an analysis on the tradeoff between security enhancement and performance degradation in the presence of channel errors. © 2012 Springer-Verlag.Number of references: 13Main heading: CryptographyControlled terms: Commerce - Errors - Network securityUncontrolled terms: Avalanche effects - Block ciphers - Channel error - Coded symbols - Linear approximations - Linear cryptanalysis - Linear relationships - Performance degradation - Potential errors - Security enhancements - Wireless systems Classification code: 723 Computer Software, Data Handling and Applications - 731 Automatic Control Principles and Applications - 911.2 Industrial Economics - 921 MathematicsDOI: 10.1007/978-3-642-34601-9_31Database: CompendexCompilation and indexing terms, © 2013 Elsevier Inc.8. Accession number: 20123915464951Title: Research on sentiment analysis in sentence and text levels with priorsAuthors: He, Hui1, 3 ; Chen, Bo2 ; Wang, Zhuxiao3Author affiliation: 1 School of Control and Computer Engineering, North China Electric Power University, Beijing, China2 Beijing University of Posts and Telecommunications, Beijing, China3 Postdoctoral Working Station, China United Network Communications Group Company Limited, Beijing, ChinaCorresponding author: He,H.(****************)Source title: International Journal of Digital Content Technology and its Applications Abbreviated source title: Int. J. Digit. Content Technol. Appl.Volume: 6Issue: 15Issue date: August 2012Publication year: 2012Pages: 518-525Language: EnglishISSN: 19759339E-ISSN: 22339310Document type: Journal article (JA)Publisher: Advanced Institute of Convergence Information Technology, 707 Seokjang-dong, Gyeongju, BI Center, Room 207, Gyeongju, Gyeongbuk, 780-714, Korea, Republic of Abstract: Recently, sentiment analysis of text is becoming a hotspot in the study of natural language processing, which has drawn interesting attention due to its research value and extensive applications. This paper introduces a sentiment analysis system, which is to satisfy two aspects of sentiment analysis requirement in sentence and text levels. They are sentence orientation analysis and text sentiment retrieval. An improved Maximum Entropy (MaxEnt) with priors is used to judge the sentence orientation, which combined with Indri is used to retrieve sentiment texts according to interested terms. This sentiment analysis system has been applied in Chinese Opinion Analysis Evaluation (COAE). Promising results and analysis are presented at the end of this paper. Number of references: 26Main heading: Maximum entropy methodsControlled terms: Computational linguistics - Data mining - Information retrieval - Natural language processing systemsUncontrolled terms: Hot spot - Indri - Maximum entropy - NAtural language processing - Opinion analysis - Orientation analysis - Prior - Sentiment analysis Classification code: 716.1 Information Theory and Signal Processing - 721.1 Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory - 723.2 Data Processing and Image Processing - 723.5 Computer ApplicationsDOI: 10.4156/jdcta.vol6.issue15.59Database: CompendexCompilation and indexing terms, © 2013 Elsevier Inc.。

Introduction to Dynamic Parallelism Stephen JonesNVIDIA CorporationImproving ProgrammabilityDynamic Parallelism Occupancy Simplify CPU/GPU Divide Library Calls from Kernels Batching to Help Fill GPU Dynamic Load Balancing Data-Dependent ExecutionRecursive Parallel AlgorithmsWhat is Dynamic Parallelism?The ability to launch new grids from the GPUDynamicallySimultaneouslyIndependentlyCPU GPU CPU GPU Fermi: Only CPU can generate GPU work Kepler: GPU can generate work for itselfWhat Does It Mean?CPU GPU CPU GPU GPU as Co-ProcessorAutonomous, Dynamic ParallelismData-Dependent ParallelismComputationalPower allocated toregions of interestCUDA Today CUDA on KeplerDynamic Work GenerationInitial GridStatically assign conservativeworst-case gridDynamically assign performancewhere accuracy is requiredFixed GridCPU-Controlled Work Batching CPU programs limited by singlepoint of controlCan run at most 10s of threadsCPU is fully consumed withcontrolling launchesCPU Control Threaddgetf2 dgetf2 dgetf2CPU Control Threaddswap dswap dswap dtrsm dtrsm dtrsmdgemm dgemm dgemmCPU Control ThreadMultiple LU-Decomposition, Pre-KeplerCPU Control ThreadCPU Control ThreadBatching via Dynamic ParallelismMove top-level loops to GPURun thousands of independent tasksRelease CPU for other workCPU Control ThreadCPU Control ThreadGPU Control Threaddgetf2 dswap dtrsm dgemm GPU Control Thread dgetf2 dswap dtrsm dgemm GPU Control Threaddgetf2dswapdtrsmdgemmBatched LU-Decomposition, Kepler__device__ float buf[1024];__global__ void dynamic(float *data) {int tid = threadIdx.x; if(tid % 2)buf[tid/2] = data[tid]+data[tid+1]; __syncthreads();if(tid == 0) {launch<<< 128, 256 >>>(buf); cudaDeviceSynchronize(); }__syncthreads();cudaMemcpyAsync(data, buf, 1024); cudaDeviceSynchronize(); }Programming Model BasicsCode ExampleCUDA Runtime syntax & semantics__device__ float buf[1024];__global__ void dynamic(float *data) {int tid = threadIdx.x; if(tid % 2)buf[tid/2] = data[tid]+data[tid+1]; __syncthreads();if(tid == 0) {launch<<< 128, 256 >>>(buf); cudaDeviceSynchronize(); }__syncthreads();cudaMemcpyAsync(data, buf, 1024); cudaDeviceSynchronize(); }Code ExampleCUDA Runtime syntax & semanticsLaunch is per-thread__device__ float buf[1024];__global__ void dynamic(float *data) {int tid = threadIdx.x; if(tid % 2)buf[tid/2] = data[tid]+data[tid+1]; __syncthreads();if(tid == 0) {launch<<< 128, 256 >>>(buf); cudaDeviceSynchronize(); }__syncthreads();cudaMemcpyAsync(data, buf, 1024); cudaDeviceSynchronize(); }Code ExampleCUDA Runtime syntax & semanticsLaunch is per-threadSync includes all launches by any thread in the block__device__ float buf[1024];__global__ void dynamic(float *data) {int tid = threadIdx.x; if(tid % 2)buf[tid/2] = data[tid]+data[tid+1]; __syncthreads();if(tid == 0) {launch<<< 128, 256 >>>(buf); cudaDeviceSynchronize(); }__syncthreads();cudaMemcpyAsync(data, buf, 1024); cudaDeviceSynchronize(); }CUDA Runtime syntax & semanticsLaunch is per-threadSync includes all launches by any thread in the blockcudaDeviceSynchronize() does not imply syncthreadsCode Example__device__ float buf[1024];__global__ void dynamic(float *data) {int tid = threadIdx.x; if(tid % 2)buf[tid/2] = data[tid]+data[tid+1]; __syncthreads();if(tid == 0) {launch<<< 128, 256 >>>(buf); cudaDeviceSynchronize(); }__syncthreads();cudaMemcpyAsync(data, buf, 1024); cudaDeviceSynchronize(); }Code ExampleCUDA Runtime syntax & semanticsLaunch is per-threadSync includes all launches by any thread in the blockcudaDeviceSynchronize() does not imply syncthreadsAsynchronous launches only__device__ float buf[1024];__global__ void dynamic(float *data) {int tid = threadIdx.x; if(tid % 2)buf[tid/2] = data[tid]+data[tid+1]; __syncthreads();if(tid == 0) {launch<<< 128, 256 >>>(buf); cudaDeviceSynchronize(); }__syncthreads();cudaMemcpyAsync(data, buf, 1024); cudaDeviceSynchronize(); }Code ExampleCUDA Runtime syntax & semanticsLaunch is per-threadSync includes all launches by any thread in the blockcudaDeviceSynchronize() does not imply syncthreadsAsynchronous launches only(note bug in program, here!)__global__ void libraryCall(float *a,float *b, float *c) {// All threads generate datacreateData(a, b);__syncthreads();// Only one thread calls library if(threadIdx.x == 0) {cublasDgemm(a, b, c);cudaDeviceSynchronize();}// All threads wait for dtrsm__syncthreads();// Now continueconsumeData(c);} CPU launcheskernelPer-block datagenerationCall of 3rd partylibrary3rd party libraryexecutes launchParallel useof resultSimple example: QuicksortTypical divide-and-conquer algorithmRecursively partition-and-sort dataEntirely data-dependent executionNotoriously hard to do efficiently on Fermi3 2 6 3 9 14 25 1 8 7 9 2 58 3 2 6 3 9 1 4 2 5 1 8 7 9 2 58 2 1 2 1 2 36 3 94 5 8 7 9 5 8 3 6 3 4 5 8 7 58 1 2 2 2 3 3 4 1 5 6 7 8 8 9 95 eventually...Select pivot valueFor each element: retrieve valueRecurse sort into right-handsubsetStore left if value < pivotStore right if value >= pivotall done?Recurse sort into left-hand subset NoYes__global__ void qsort(int *data, int l, int r) {int pivot = data[0];int *lptr = data+l, *rptr = data+r;// Partition data around pivot valuepartition(data, l, r, lptr, rptr, pivot);// Launch next stage recursively if(l < (rptr-data))qsort<<< ... >>>(data, l, rptr-data); if(r > (lptr-data))qsort<<< ... >>>(data, lptr-data, r); }。