Intelligent systems for traffic flow management: A qualitative modeling approach

An approach for the design of intelligent systems for traffic control is presented. First, the problem characteristics are described. Then, the possible knowledge representation techniques are proposed. the types of knowledge to be represented are:

• — The data interpretation knowledge for problem identification based on the present and predicted situations.
• — The knowledge for proposing control decisions to solve present and predicted problems.
• — The knowledge for possible short-term situations prediction with the present control policy assumed as constant.

The first two types can be represented by traditional techniques such as rules or frames. the predictive knowledge has to be defined on qualitative modeling techniques, an aspect of intensive research nowadays. Two types of predictive modeling techniques are suggested: (a) the qualitative simulation of flow along an axis which is the case of the flow in urban motorways where it is very important the preservation of an operational capacity. A confluence version is proposed for the partial derivative equations of unsteady traffic flow in a lane. (b) the qualitative modeling of the flow in networks where a qualitative version of the flow assignment to paths in the network is used. A proposal of knowledge representation for every prediction type is described. Although specific aspects of traffic control are presented the approach discussed can be considered as a general knowledge representation concept which combines traditional techniques and qualitative models in order to infer decision aspects for management purposes in a professional engineering domain. Finally, some knowledge structuring and acquisition aspects are considered.     

基于本体的产品知识表达

产品开发过程分工的加强、市场和全球化竞争的激烈都要求工厂能够更迅速地生产更廉价和质量更高的产品，而这需要一个更有效并且强有力的产品知识管理系统，以支持产品知识的表达、重用、共享和交流等．研究了产品知识表达的模型，即S—B—F，结合本体描述语言构建了流本体和功能本体，设计出基于本体的产品知识表达，并进一步提出了可行的应用模型。     

Models and technologies for the extraction of aggregated knowledge to control processes of the retrieval of non-structured information

To control the retrieval and to arrange the retrieval of non-structured information in large-scale collections of texts in natural languages, crucially new models of aggregated representation of knowledge about their topic and content (semiotic and semantic characteristics of the text) are proposed. Based on the proposed models, techniques of computational extraction and use of knowledge about the topic and content of text collections are developed. The proposed models and techniques are based on formation of secondary information resources characterizing the topic and content of particular texts in natural languages.     

Accelerating temporal verification of Simulink diagrams using satisfiability modulo theories

Automatic verification of programs and computer systems with input variables represents a significant and well-motivated challenge. The case of Simulink diagrams is especially difficult, because there the inputs are read iteratively, and the number of input variables is in theory unbounded. We apply the techniques of explicit model checking to account for the temporal (control) aspects of verification and use set-based representation of data, thus handling both sources of non-determinism present in the verification. Two different representations of sets are evaluated in scalability with respect to the range of input variables. Explicit (enumerating) sets are very fast for small ranges but fail to scale. Symbolic sets, represented as first-order formulas in the bit-vector theory and compared using satisfiability modulo theory solvers, scale well to arbitrary (though still bounded) range of input variables. To leverage the combined strengths of explicit and symbolic representations, we have designed a hybrid representation which we showed to outperform both pure representations. Thus, the proposed method allows complete automatic verification without the need to limit the non-determinism of input. Moreover, the principle underlying the hybrid representation entails inferring knowledge about the system under verification, which the developers did not explicitly include in the system, and which can significantly accelerate the verification process.     

Temporal knowledge representation and reasoning techniques usingtime Petri nets

In this paper, we present temporal knowledge representation and reasoning techniques using time Petri nets. A method is also proposed to check the consistency of the temporal knowledge. The proposed method can overcome the drawback of the one presented in Yao (1994). It provides a useful way to check the consistency of the temporal knowledge.     

Hybrid architecture for shape reconstruction and object recognition

The proposed architecture is aimed to recover 3-D shape information from gray-level images of a scene: to build a geometric representation of the scene in terms of geometric primitives; and to reason about the scene. The novelty of the architecture is in fact the integration of different approaches: symbolic reasoning techniques typical of knowledge representation in artificial intelligence, algorithmic capabilities typical of artificial vision schemes, and analogue techniques typical of artificial neural networks. Experimental results obtained by means of an implemented version of the proposed architecture acting on real scene images are reported to illustrate the system capabilities. © 1996 John Wiley & Sons, Inc.     

Integrated knowledge acquisition architectures

An architecture for knowledge acquisition systems is proposed based upon the integration of existing methodologies, techniques and tools which have been developed within the knowledge acquisition, machine learning, expert systems, hypermedia and knowledge representation research communities. Existing tools are analyzed within a common framework to show that their integration can be achieved in a natural and principled fashion. A system design is synthesized from what already exists, putting a diversity of well-founded and widely used approaches to knowledge acquisition within an integrative framework. The design is intended to be clean and simple, easy to understand, and easy to implement. A detailed architecture for integrated knowledge acquisition systems is proposed that also derives from parallel cognitive and theoretical studies.     

一种基于案例推理的欺诈分析方法

为了对欺诈行为进行分析和识别，提出一种基于案例推理的欺诈分析方法。研究了应用案例推理方法对各种欺诈信息进行识别的一些关键技术，并通过一个信用卡欺诈行为的分析实例对该方法进行检验。研究结果表明，该方法应用于欺诈行为的分析和识别是有效的。     

机械产品概念设计中的知识表示

研究了计算机辅助概念设计中的关键技术——知识表示．将行为域引入公理化设计作为功能域和载体域之间的转换桥梁，针对该域结构定义扩展“之”字映射，建立了不同层次功能、行为和载体之间的映射关系；构造了概念设计方案的知识表示模型——域结构模板；针对一类产品的知识表示模型——概念空间，给出了基于概念空间的概念设计方案生成过程．最后以工业平缝机为例对所述模型和方法加以说明。     

Energy Theft Detection in Smart Grids: Taxonomy,Comparative Analysis,Challenges, and Future Research Directions

Electricity theft is one of the major issues in developing countries which is affecting their economy badly.Especially with the introduction of emerging technologies,this issue became more complicated.Though many new energy theft detection(ETD)techniques have been proposed by utilising different data mining(DM)techniques,state&network(S&N)based techniques,and game theory(GT)techniques.Here,a detailed survey is presented where many state-of-the-art ETD techniques are studied and analysed for their strengths and limitations.Three levels of taxonomy are presented to classify state-of-the-art ETD techniques.Different types and ways of energy theft and their consequences are studied and summarised and different parameters to benchmark the performance of proposed techniques are extracted from literature.The challenges of different ETD techniques and their mitigation are suggested for future work.It is observed that the literature on ETD lacks knowledge management techniques that can be more effective,not only for ETD but also for theft tracking.This can help in the prevention of energy theft,in the future,as well as for ETD.     

Visual Knowledge Representation and Intelligent Image Segmentation

Automatic medical image analysis shows that image segmentation is a crucial task for any practical AI system in this field.On the basis of evaluation of the existing segmentation methods,a new image segmentation method is presented.To seek the perfct solution to knowledge representation in low level machine vision,a new knowledge representation approach--“Notebbok”approach is proposed and the processing of visual knowledge is discussed at all levels.To integrate the computer vision theory with Gestalt psychology and knowledge engineering,a new integrated method for intelligent image segmentation of sonargraphs- “Generalized-pattern guided segmentation”is proposed.With the methods and techniques mentioned above,the medical diagnosis expert system for sonargraphs can be built The work on the preliminary experiments is also introduced.     

基于语义对象网络模型的产品知识表达方法

为表达产品知识及其语义内涵和约束关系,提出采用语义对象网络模型（Semantic Object Semantic Networks,SOSNs）表达产品知识。SOSNs是基于图并结合面向对象方法表达的知识模型,其中节点表示产品语义对象,有向边显性定义语义对象之间的语义关系,这种基于图的语义模型能够清晰的表示产品功能、行为、原理、结构、配置管理、约束等知识及其语义关系,将与产品开发相关的知识集成为一个逻辑整体,形成分层的结构化语义对象网络结构,便于组织和管理产品知识,易于实现知识的共享和重用。     

面向生成的美术构图表达研究

面向美术作品的自动创作,提出了美术知识的简化表达模型和基于符号矩阵的美术构图表达方法,并针对二维图案的自动生成,给出了生成性美术知识的一个具体表达实例,该实例已在美术图案综合创作系统中予以了实现。     

Collective knowledge systems: Where the Social Web meets the Semantic Web

What can happen if we combine the best ideas from the Social Web and Semantic Web? The Social Web is an ecosystem of participation, where value is created by the aggregation of many individual user contributions. The Semantic Web is an ecosystem of data, where value is created by the integration of structured data from many sources. What applications can best synthesize the strengths of these two approaches, to create a new level of value that is both rich with human participation and powered by well-structured information? This paper proposes a class of applications called collective knowledge systems, which unlock the “collective intelligence” of the Social Web with knowledge representation and reasoning techniques of the Semantic Web.     

支持异地协同产品设计的知识服务模型

提出基于XML元语言，以统一的信息化格式描述设计知识，使用Java技术构建了支持多专家协同设计的基本框架，将各类设计服务封装为Web服务的形式，实现了一种Web使能的知识服务模型(Web-KSS)，并应用该模型实现了支持成套电器产品设计的知识服务系统。     

Knowledge Reuse Enhancement with Motional Visual Representation

The growing complexity of information and documents has made it difficult for knowledge receivers to understand digital contents, therefore, multiple knowledge representation schemes are required for enterprise knowledge services. Traditional schemes for explicit knowledge representation within enterprise and academic circles are primarily text-oriented and thus, a great deal of time and effort are required for knowledge receivers to understand the contents, especially for motion knowledge. In order to enhance knowledge reuse with motion knowledge extraction, representation, and visualization, this research focuses on the development of a motion knowledge representation and visualization (MKRV) model for Chinese documents with three modules, namely the automatic thesaurus definition (ATD) module, the target sentence extraction and formatting (TSEF) module, and the motion knowledge visualization (MKV) module. Moreover, based on the proposed model, a Motion Knowledge Representation and Management System (MKRMS) is established. A real world case of computer assembly is also applied in order to verify the feasibility of the proposed model. The verification results show that the system could achieve a high performance level with a small amount of training data.     

基于对抗学习和全局知识信息的关系检测技术研究

针对现有的知识库关系检测任务对于一些不可见关系无法做到准确的向量表示而出现词汇溢出的问题,提出了基于对抗学习和全局知识信息的关系检测模型。该模型使用对抗学习对知识库关系表示模型进行特征强化,使用TransH(translating on hyperplanes)模型提取全局知识信息,同时通过联合训练,将全局知识信息融合进关系表示模型中,进一步提升关系模型的表示能力。实验结果表明,提出的融合模型对于关系检测效果有一定的提升,并且缓解了词汇溢出的问题。     

网络空间态势信息的特点及其知识表示方法

网络空间中具有纷繁复杂的多种态势要素、要素属性以及要素之间的错综关系。对这些信息能否清晰准确地分析并描述,直接关系到所建立的网络空间态势模型的准确性、完备性 和有效性。本文采用知识表示方法,对网络空间中的关键态势信息要素进行描述。首先分析了网络空间态势信息知识的特点,提出了对网络空间态势信息进行知识表示的重要作用。其次研究了基于本体的知识表示理论,分析了采用本体表示网络空间态势的动机。最后提出了基于本体的网络空间态势信息要素知识表示方法,并详细介绍了该方法的实现手段。本文研究可以有效促进网络空间态势的感知、建模与可视化,为网络空间相关技术的研究提供有效的参考依据。     

Knowledge representation and processing in economics and management

Various techniques for computer-based knowledge representation and processing are widely used in management and economics. Other techniques such as rules and demons have arisen in the artificial intelligence field. These too can be useful in managerial and economics settings. A major issue is how to effectively employ multiple traditional and artificial intelligence techniques when working on a problem. In this paper, we examine the various knowledge management techniques with respect to their applicability to handling distinct types of knowledge. An object-oriented framework is presented as a basis for the unified and coordinated treatment of multiple knowledge management techniques in a single environment. Using this framework, two approaches are identified for delivering these techniques to a knowledge worker: skeletal environments and furnished environments.