Substantial and formal deductions in logics with vector semantics

The problem of logic deduction for one class of logics with a vector semantics is discussed. In the given logics the trustiness is represented by a vector with components 〈Truth; Lie〉, which do not depend on each other. The problem of organization of “substantial” and “formal” deductions is considered. In the first case the meaning of truth (semantics) of judgements is taken into account, whereas in the second case only the structure of judgements (syntax) is considered.     

Circular expressions: elimination of static environments

Consider the connection between denotational semantics for a language with goto statements and flow diagrams for programs in such a language. The main point of interest is that the denotational semantics uses a recursively defined environment to give the meaning of labels, while a flow diagram merely has a jump to the appropriate program point. A simple reduction called “indirection elimination” strips away the environment from the denotational semantics and extracts an expression with cycles that is very close to the flow diagram of a program. The same idea applies to associating bodies with recursive procedures, or to any construct whose semantics is not wedded to the syntax. In addition to being a useful data structure and conceptual device, expressions with cycles are well defined mathematical objects—their semantics can be given by unfolding them into infinite structures that have been well studied. The practicality of the elimination of environments has been tested by constructing a trial implementation, which serves as the front end of a semantics directed compiler generator. The implementation takes a denotational semantics of a language and constructs a “black box” that maps programs in the language into an intermediate representation. The intermediate representation is a circular expression.     

Hair Interpolation for Portrait Morphing

In this paper we study the problem of hair interpolation: given two 3D hair models, we want to generate a sequence of intermediate hair models that transform from one input to another both smoothly and aesthetically pleasing. We propose an automatic method that efficiently calculates a many‐to‐many strand correspondence between two or more given hair models, taking into account the multi‐scale clustering structure of hair. Experiments demonstrate that hair interpolation can be used for producing more vivid portrait morphing effects and enabling a novel example‐based hair styling methodology, where a user can interactively create new hairstyles by continuously exploring a “style space” spanning multiple input hair models.     

状态逻辑型程序设计语言

本文提出了一种新的纯逻辑式子句型程序设计语言．文中给出了语言的语法，非形式语义，子句的过程解释和基于约束归结的推理系统．对该语言来说，程序包含三类变量：输入变量，输出变量和用于控制机器资源的程序变量；被程序定义的函数符号可用于构造项或子项，并且还可用作为谓词符号；不需要低效的最广合一．由于这些因素，一个子句集本身隐含了顺序，分支，迭代和递归多种控制结构使得容易构造高效的定理证明系统．这种语言将是一种有坚实理论基础的，高效的，实际有用的高级确定性语言．     

Designing habitable dialogues for speech-based interaction with computers

Habitability refers to the match between the language people employ when using a computer system and the language that the system can accept. In this paper, the concept of “habitability” is explored in relation to the design of dialogues for speech-based systems. Two studies investigating the role of habitability in speech systems for banking applications are reported. The first study employed a speech-driven automated teller machine (ATM), using a visual display to indicate available vocabulary. Users made several distinct types of error with this system, indicating that habitability in speech systems cannot be achieved simply by displaying the input language. The second study employed a speech input/speech output home banking application, in which system constraints were indicated by either a spoken menu of words or a “query-style” prompt (e.g. “what service do you require?”). Between-subjects comparisons of these two conditions confirmed that the “menu-style” dialogue was rated as more habitable than the “query-style”. It also led to fewer errors, and was rated as easier to use, suggesting that habitability is a key issue in speech system usability. Comparison with the results of the first study suggests that for speech input, spoken menu prompts may be more habitable than similar menus shown on a visual display. The implications of these results to system design are discussed, and some initial dialogue design recommendations are presented.     

Gestures that people can understand and use

Recent advances in computing devices push researchers to envision new interaction modalities that go beyond traditional mouse and keyboard input. Typical examples are large displays for which researchers hope to create more “natural” means of interaction by using human gestures and body movements as input. In this article, we reflect about this goal of designing gestures that people can easily understand and use and how designers of gestural interaction can capitalize on the experience of 30 years of research on visual languages to achieve it. Concretely, we argue that gestures can be regarded as “visual expressions to convey meaning” and thus are a visual language. Based on what we have learned from visual language research in the past, we then explain why the design of a generic gesture set or language that spans many applications and devices is likely to fail. We also discuss why we recommend using gestural manipulations that enable users to directly manipulate on-screen objects instead of issuing commands with symbolic gestures whose meaning varies among different users, contexts, and cultures.     

以“数据结构”课程为导向的“C语言程序设计”课程的教学研究与实施

以“数据结构”课程为导向,可以指导“C语言程序设计”课程相关内容的应用案例设计。而将“以赛促学”的思想融入计算机大类基础课程中,以成果为导向,分层次学习“C语言程序设计”和“数据结构”,循序渐进,并针对每个知识点的项目案例驱动学习兴趣,可以体现应用型本科学以致用的宗旨。     

Yield grammar analysis and product optimization in a domain-specific language for dynamic programming

Dynamic programming algorithms are traditionally expressed by a set of matrix recurrences—a low level of abstraction, which renders the design of novel dynamic programming algorithms difficult and makes debugging cumbersome.Bellman's GAP is a declarative, domain-specific language, which supports dynamic programming over sequence data. It implements the algebraic style of dynamic programming and allows one to specify algorithms by combining so-called yield grammars with evaluation algebras. Products on algebras allow to create novel types of analyses from already given ones, without modifying tested components. Bellman's GAP extends the previous concepts of algebraic dynamic programming in several respects, such as an “interleaved” product operation and the analysis of multi-track input.Extensive analysis of the yield grammar and the evaluation algebras is required for generating efficient imperative code from the algebraic specification. This article gives an overview of the analyses required and presents several of them in detail. Measurements with “real-world” applications demonstrate the quality of the code produced.     

Knowledge Compilation Meets Database Theory: Compiling Queries to Decision Diagrams

The goal of Knowledge Compilation is to represent a Boolean expression in a format in which it can answer a range of “online-queries” in PTIME. The online-query of main interest to us is model counting, because of its application to query evaluation on probabilistic databases, but other online-queries can be supported as well such as testing for equivalence, testing for implication, etc. In this paper we study the following problem: given a database query q, decide whether its lineage can be compiled efficiently into a given target language. We consider four target languages, of strictly increasing expressive power (when the size of compilation is restricted to be polynomial in the data size): read-once Boolean formulae, OBDD, FBDD and d-DNNF. For each target, we study the class of database queries that admit polynomial size representation: these queries can also be evaluated in PTIME over probabilistic databases. When queries are restricted to conjunctive queries without self-joins, it was known that these four classes collapse to the class of hierarchical queries, which is also the class of PTIME queries over probabilistic databases. Our main result in this paper is that, in the case of Unions of Conjunctive Queries (UCQ), these classes form a strict hierarchy. Thus, unlike conjunctive queries without self-joins, the expressive power of UCQ differs considerably with respect to these target compilation languages. Moreover, we give a complete characterization of the first two target languages, based on the query’s syntax.     

Translatability: Understandability and usability by others

The United States version of the English language, sometimes referred to as “Americanese” is a lively, still developing language. It is frequently interspersed with slang, acronyms, and abbreviations. In daily use, people often employ catch phrases from advertising, television, and “one-liners” voiced by entertainers and other public figures. While this may make for a colorful version of English (deplored by some), it causes untold problems for translators whenever the “colorful” or inconsistent variations creep into documents that must be translated for use in a world market. That language problem is a problem in usability, a human factors problem; not always recognized as such by the computer industry. Akin to the sometimes thoughtless use of idiomatic English, is the bland assumption that what is designed and developed for the U.S. market is satisfactory for other countries. This assumption ignores significant differences in form, format, economic and financial factors, as well as acculturation differences. These are some of the elements that contribute to difficulties experienced by U.S. companies in getting computer programs and other products accepted outside the United States. This article discusses these matters, and four basic steps for alleviating some of the problems.     

Importance–Performance Analysis by Fuzzy C-Means Algorithm

Traditional Importance–Performance Analysis assumes the distribution of a given set of attributes in four sets, “Keep up the good work”, “Concentrate here”, “Low priority” and “Possible overkill”, corresponding to the four possibilities, high–high, low–high, low–low and high–low, of the pair performance–importance. This can lead to ambiguities, contradictions or non-intuitive results, especially because the most real-world classes are fuzzy rather than crisp. The fuzzy clustering is an important tool to identify the structure in data, therefore we apply the Fuzzy C-Means Algorithm to obtain a fuzzy partition of a set of attributes. A membership degree of every attribute to each of the sets mentioned above is determined, against to the forcing categorization in traditional Importance–Performance Analysis. The main benefit is related with the deriving of the managerial decisions which become more refined due to the fuzzy approach. In addition, the development priorities and the directions in which the effort of an economic or non-economic entity would be useless or even dangerous are identified on a rigorous basis and taking into account only the internal structure of the input data.     

论维吾尔语SUBS＋NP结构的形式化描述

该文按照数理逻辑的方法从句法格式,论元及论元模式,动词和名词之间语义关系及逻辑表达式等四个方面对SUBS+NP结构进行初步的形式化描述为自然语言信息处理服务。结果表明维吾尔语SUBS+NP结构中动词与名词之间的多种语义关系决定动词可能选择的表达形式即“”型动名词形式和形动词形式,并且动词与名词之间的语义关系服从句法的编码,借助两种句法形式表现出不同的语义内容。     

Towards scalable synthesis of stochastic control systems

Formal synthesis approaches over stochastic systems have received significant attention in the past few years, in view of their ability to provide provably correct controllers for complex logical specifications in an automated fashion. Examples of complex specifications include properties expressed as formulae in linear temporal logic (LTL) or as automata on infinite strings. A general methodology to synthesize controllers for such properties resorts to symbolic models of the given stochastic systems. Symbolic models are finite abstractions of the given concrete systems with the property that a controller designed on the abstraction can be refined (or implemented) into a controller on the original system. Although the recent development of techniques for the construction of symbolic models has been quite encouraging, the general goal of formal synthesis over stochastic control systems is by no means solved. A fundamental issue with the existing techniques is the known “curse of dimensionality,” which is due to the need to discretize state and input sets. Such discretization generally results in an exponential complexity over the number of state and input variables in the concrete system. In this work we propose a novel abstraction technique for incrementally stable stochastic control systems, which does not require state-space discretization but only input set discretization, and that can be potentially more efficient (and thus scalable) than existing approaches. We elucidate the effectiveness of the proposed approach by synthesizing a schedule for the coordination of two traffic lights under some safety and fairness requirements for a road traffic model. Further we argue that this 5-dimensional linear stochastic control system cannot be studied with existing approaches based on state-space discretization due to the very large number of generated discrete states.     

Fuzzy prolog

Various methods of representing uncertainty are discussed including some fuzzy methods. Representation and calculation of fuzzy expressions are discussed and a symbolic representation of fuzzy quantities coupled with axiomatic evaluation is proposed. This is incorporated into the PROLOG language to produce a fuzzy version. Apart from enabling imprecise facts and rules to be expressed, a natural method of controlling the search is introduced, making the search tree admissible.Formal expression of heuristic information in the same language, FUZZY PROLOG, as the main problem language follows naturally and therefore allows the same executor to evaluate in both “problem” space and “heuristic” space.In addition, the use of variable functors in the specification of bidirectional logic is discussed. The paper shows two areas of application of higher order fuzzy predicates. As an introduction Warren's examples are outlined and used with variable functors to illustrate their use in describing some relatively conventional applications.Translation of English into horn clause format is described and is used to illustrate the simplicity of representation using variable functors. Alternative formulations are also explored, typically the use of the “meta-variable” in MICRO-PROLOG and using the “univ” operator.Representation of rule generation and inference is addressed. Examples are given where the expression of meta-rules in standard PROLOG are compared with the expression of the same rules using “variable” predicate symbols. Some meta-rules illustrated are clearly not universally valid and this leads to the addition of fuzzy tokens.     

Automatic mode inference for logic programs

In general, logic programs are undirected, i.e., there is no concept of “input” and “output” arguments to a procedure. An argument may be used either as an input or as an output argument, and programs may be executed either in a “forward” direction or in a “backward” direction. However, it is often the case that in a given program, a predicate is used with some of its arguments used consistently as input arguments and others as output arguments. Such mode information can be used by a compiler to effect various optimizations. This paper considers the problem of automatically inferring the models of the predicates in a program. The dataflow analysis we use is more powerful than approaches relying on syntactic characteristics of programs. Our work differs from that of Mellish in that (1) we give a sound and efficient treatment of variable aliasing in mode inference; (2) by propagating instantiation information using state transformations rather than through dependencies between variables, we achieve greater precision in the treatment of unification, e.g. through =/2; and (3) we describe an efficient implementation based on the dynamic generation of customized mode interpreters. Several optimizations to improve the performance of the mode inference algorithm are described, as are various program optimizations based on mode information.     

Programming with equalities,subsorts, overloading,and parametrization in OBJ

obj is a declarative language, with mathematical semantics given by order-sorted equational logic and an operational semantics based on order-sorted term rewriting. obj also has user-definable abstract data types with mixfix syntax and a flexible type system that supports overloading and subtypes. In addition, obj has a powerful generic module mechanism, including nonexecutable “theories” as well as executable “objects”, plus “module expressions” that construct whole subsystems. Design and implementation choices for the obj interpreter are described here in detail.     

From machine learning to machine reasoning

A plausible definition of “reasoning” could be “algebraically manipulating previously acquired knowledge in order to answer a new question”. This definition covers first-order logical inference or probabilistic inference. It also includes much simpler manipulations commonly used to build large learning systems. For instance, we can build an optical character recognition system by first training a character segmenter, an isolated character recognizer, and a language model, using appropriate labelled training sets. Adequately concatenating these modules and fine tuning the resulting system can be viewed as an algebraic operation in a space of models. The resulting model answers a new question, that is, converting the image of a text page into a computer readable text. This observation suggests a conceptual continuity between algebraically rich inference systems, such as logical or probabilistic inference, and simple manipulations, such as the mere concatenation of trainable learning systems. Therefore, instead of trying to bridge the gap between machine learning systems and sophisticated “all-purpose” inference mechanisms, we can instead algebraically enrich the set of manipulations applicable to training systems, and build reasoning capabilities from the ground up.     

Production Systems: A Notation for Defining Syntax and Translation

This paper presents the formalism of Production Systems and investigates its applcation to defe the Syntax and trlation of programming languages. Several properties appear well-suited to this task: 1) the formalism can be used to specify exactly the syntax of a computer language, including context-sensitive requirements; 2) the specification of the context-sensitive requirements on syntax can be isolated from the context-free requirements; 3) the same formalism can be used to specify more general structural properties, including the translation of one language into another. The notation has been developed with readabifity as a prime designissue. The following examples are given:1) aspecificationofthesyntaxofasmallbutdifflcultsubset of PL/I;2) a specification of the rules for translating lambda-culus expressions into, normal form.