A method of constructing an inspiration library driven by user-perceived preference evaluation data for biologically inspired design

Biologically inspired design (BID) is one of the common methods for product design. To solve the problem of inaccurate acquisition of inspirational creatures due to the lack of user perception preference analysis, a data-driven intelligent service model for BID considering user perception needs is proposed based on Kansei engineering. Firstly, by extracting the perceptual features of creatures from the semantic source elements of products through mapping and encodes them, we proposed a data acquisition method based on intuitionistic fuzzy sets considering different customer preference distributions, bridging the gap caused by the asymmetry between designers and users. Secondly, the functional relationship between biometric features and user-perceived attributes is identified and predicted, and a predictive model of biodata considering user preferences is obtained by multiple linear regression analysis. Finally, based on the data clustering and reorganization theory to understand the organization and dynamics of the database, the construction of a BID library was completed, and the design resources in the library were used as analyzed knowledge for designers to plan design activities. Taking the bionic design of a UAV product as an example, a prototype of a computer-aided design service system was developed based on the theory proposed in the article, and the analyzed knowledge was used to improve the efficiency and science of the design, effectively verifying the usefulness of this study for design. To a certain extent, this study addresses the problem of cognitive limitations of designers and cognitive differences between designers and users, promotes the application of bioinspiration in product design, and improves the marketability of design solutions.     

基于桥连接的词典学习方法的语义解析

现阶段的语义解析方法大部分都基于组合语义,这类方法的核心就是词典。词典是词汇的集合,词汇定义了自然语言句子中词语到知识库本体中谓词的映射。语义解析一直面临着词典中词汇覆盖度不够的问题。针对此问题,该文在现有工作的基础上,提出了基于桥连接的词典学习方法,该方法能够在训练中自动引入新的词汇并加以学习,为了进一步提高新学习到的词汇的准确度,该文设计了新的词语—二元谓词的特征模板,并使用基于投票机制的核心词典获取方法。该文在两个公开数据集(WebQuestions和Free917)上进行了对比实验,实验结果表明,该文方法能够学习到新的词汇,提高词汇的覆盖度,进而提升语义解析系统的性能,特别是召回率。     

带类型λ—演算

一、引言补演算是一个用函数描述计算的形式理论体系[1J,它由许多计算模型所组成。文〔1〕指出,应用认-演算比纯粹补演算更接近程序语言.但是由于内建函子和常数的引入常会发生一些问题,例如.常数O和函子+在机器中同样看待     

A Refinement Calculus for Shared-Variable Parallel and Distributed Programming

Parallel computers have not yet had the expected impact on mainstream computing. Parallelism adds a level of complexity to the programming task that makes it very error-prone. Moreover, a large variety of very different parallel architectures exists. Porting an implementation from one machine to another may require substantial changes. This paper addresses some of these problems by developing a formal basis for the design of parallel programs in the form of a refinement calculus. The calculus allows the stepwise formal derivation of an abstract, low-level implementation from a trusted, high-level specification. The calculus thus helps structuring and documenting the development process. Portability is increased, because the introduction of a machine-dependent feature can be located in the refinement tree. Development efforts above this point in the tree are independent of that feature and are thus reusable. Moreover, the discovery of new, possibly more efficient solutions is facilitated. Last but not least, programs are correct by construction, which obviates the need for difficult debugging. Our programming/specification notation supports fair parallelism, shared-variable and message-passing concurrency, local variables and channels. The calculus rests on a compositional trace semantics that treats shared-variable and message-passing concurrency uniformly. The refinement relation combines a context-sensitive notion of trace inclusion and assumption-commitment reasoning to achieve compositionality. The calculus straddles both concurrency paradigms, that is, a shared-variable program can be refined into a distributed, message-passing program and vice versa. Received July 2001 / Accepted in revised form May 2002     

A process oriented semantics of the PRAM-language FORK

The parallel language FORK [1], based on a scalable shared memory model, is a PASCAL-like language with some additional parallel constructs. A PRAM (Parallel Random Access Machine) algorithm can be expressed on a high level of abstraction as a FORK program which is translated into efficient PRAM code guaranteeing theoretically predicted runtimes.

In this paper, we concentrate on those features of the language FORK related to parallelism, such as the group concept, a shared memory access and synchronous or asynchronous execution. We present a trace-based denotational interleaving semantics where processes describe synchronous computations. Processes are created or deleted dynamically and run asynchronously. Interleaving rules reflect the underlying CRCW (concurrent-read-concurrent-write) PRAM model.     

Generation and context memory.

Generation enhances memory for occurrence but may not enhance other aspects of memory. The present study further delineates the negative generation effect in context memory reported in N. W. Mulligan (2004). First, the negative generation effect occurred for perceptual attributes of the target item (its color and font) but not for extratarget aspects of context (location and background color). Second, nonvisual generation tasks with either semantic or nonsemantic generation rules (antonym and rhyme generation, respectively) produced the same pattern of results. In contrast, a visual (or data-driven) generation task (letter transposition) did not disrupt context memory for color. Third, generating nonwords produced no effect on item memory but persisted in producing a negative effect on context memory for target attributes, implying that (a) the negative generation effect in context memory is not mediated by semantic encoding, and (b) the negative effect on context memory can be dissociated from the positive effect on item memory. The results are interpreted in terms of the processing account of generation. The original, perceptual-conceptual version of this account is too narrow, but a modified processing account, based on a more generic visual versus nonvisual processing distinction, accommodates the results. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Kripke Semantics for Modal Substructural Logics

We introduce Kripke semantics for modal substructural logics, and provethe completeness theorems with respect to the semantics. Thecompleteness theorems are proved using an extended Ishihara's method ofcanonical model construction (Ishihara, 2000). The framework presentedcan deal with a broad range of modal substructural logics, including afragment of modal intuitionistic linear logic, and modal versions ofCorsi's logics, Visser's logic, Méndez's logics and relevant logics.     

一个面向语义的解释器自动生成技术

本文给出从指称语义自动生成解释器后端的一种技术.解释器被表示成PASCAL_like形式.     

Reasoning with Intensional Negative Adjectivals: Semantics, Pragmatics, and Context

Intensional negative adjectives alleged , artificial , fake , false , former , and toy are unusual adjectives that depending on context may or may not be restricting functions. A formal theory of their semantics, pragmatics, and context that uniformly accounts for their complex mathematical and computational characteristics and captures some peculiarities of individual adjectives is presented.
Such adjectives are formalized as new concept builders, negation‐like functions that operate on the values of intensional properties of the concepts denoted by their arguments and yield new concepts whose intensional properties have values consistent with the negation of the old values. Understanding these new concepts involves semantics, pragmatics and context‐dependency of natural language. It is argued that intensional negative adjectives can be viewed as a special‐purpose, weaker, conntext‐dependent negationin natural language. The theory explains and predicts many inferences licensed by expressions involving such adjectives. Implementation of sample examples demonstrates its computational feasibility. Computation of context‐dependent interpretation is discussed.
The theory allows one to enhance a knowledge representation system with similar concept building, negation‐like, context‐dependent functions, the availability of which appears to be a distinct characteristic of natural languages.