An approach to learning mathematics through knowledge engineering

This study deals with an AI approach to learning mathematics, which is realised through the development of expert system knowledge bases by using programming in logic and PROLOG. The paper presents this approach, and examines its theoretical values in the light of recent findings in computer science, mathematics education, didactics, psychology and philosophy. The examined values show evidence for the relevance of the approach to the computer-assisted learning of mathematics.     

A knowledge engineering approach to knowledge management

Knowledge management facilitates the capture, storage, and dissemination of knowledge using information technology. Methods for managing knowledge have become an important issue in the past few decades, and the KM community has developed a wide range of technologies and applications for both academic research and practical applications. In this paper, we propose a knowledge engineering approach (KMKE) to knowledge management. First, a knowledge modeling approach is used to organize and express various types of knowledge in a unified knowledge representation. Second, a verification mechanism is used to verify knowledge models based on the formal semantics of the knowledge representation. Third, knowledge models are classified and stored in a hierarchical ontology system. Fourth, a knowledge query language is designed to enhance the dissemination of knowledge. Finally, a knowledge update process is applied to modify the knowledge storage with respect to users’ needs. A knowledge management system for computer repair is used as an illustrative example.     

Knowledge map: An approach to knowledge acquisition in developing engineering expert systems

This paper addresses the critical issues of knowledge acquisition in developing knowledge-based expert systems for engineering tasks. First, it reviews the role of knowledge acquisition and its current practice in expert system development. Then, a new approach based on three stages of knowledge refinement is suggested to improve the process of knowledge acquisition. This approach, calledrule verification without rule construction, is proposed to allow knowledge engineers and domain experts to experience a more intimate and balanced role in developing intelligent systems. The communication tool developed for this concept is calledknowledge map, which provides a systematic way of indexing and quantifying a piece of knowledge in the problem space by defining important attributes as the axes of the map. This approach is demonstrated by constructing a twodimensional map for a knowledge-based engineering design system, IDRILL, which we are currently developing. Future expansions of this knowledge acquisition technique are summarized as the conclusions of this paper.This paper was presented in part at the 1986 ASME International Computers in Engineering Conference in Chicago, IL, and appeared in the proceedings of that conference.     

An environment for reusing ontologies within a knowledge engineering approach

Domain models can be constructed more easily and made more robust by reusing ontologies in a well-defined way. In this paper the KARO approach is introduced which provides various means of retrieving and adapting components of an ontology as part of a domain model construction process. KARO is based on the knowledge-processing component LILOG-KR provided by the LILOG text-understanding system. Above all, the notion of classification is applied for the retrieval of relevant categories. The upper structure of LILOG-KB serves as an exemplary ontology. By integrating KARO into the Model-based and Incremental Knowledge Engineering Environment (MIKE) the reuse of a predefined ontology can be integrated into the development process of expert systems in a systematic way.     

An engineering approach to sociable robots

Robotics researchers and cognitive scientists are becoming more and more interested in so-called sociable robots. These machines normally have expressive power (facial features, voice,?…) as well as abilities for locating, paying attention to, and addressing people. The design objective is to make robots which are able to sustain natural interactions with people. This capacity falls within the range classed as social intelligence in humans. This position paper argues that the reproduction of social intelligence, as opposed to other types of human ability, may lead to fragile performance, in the sense that tested cases may produce rather different performances to future (untested) cases and situations. This limitation stems from the fact that our social abilities, which appear early in life, are mainly unconscious in origin. This is in contrast with other human abilities that we carry out using conscious effort, and for which we can easily conceive algorithms and representations. This novel perspective is deemed useful for defining the obstacles and limitations of a field that is generating increasing interest. Taking into account the mentioned issues, a development approach suited to the problem is proposed. The use of this approach is demonstrated in the development of CASIMIRO, a robotic head with basic interaction abilities.     

A knowledge engineering approach to developing mindtools for context-aware ubiquitous learning

Recent developments in computing and mobile technologies have enabled the mobile and ubiquitous learning approach, which situates students in an environment that combines real-world and digital-world learning resources. Although such an approach seems to be innovative and interesting, several problems have been revealed when applying it to practical learning activities. One major problem is owing to the lack of proper learning strategies or tools that can guide or assist the students to learn in such a complex learning scenario. Students might feel excited or interested when using the mobile devices to learn in the real world; however, their learning achievements could be disappointing. To cope with this problem, in this study, a knowledge engineering approach is proposed to develop Mindtools for such innovative learning scenarios. Experimental results from a natural science course of an elementary school show that this innovative approach not only enhances learning motivation, but also improves the learning achievements of the students.     

A social software/Web 2.0 approach to collaborative knowledge engineering

Expert systems have traditionally captured the explicit knowledge of a single expert or source of expertise in order to automatically provide conclusions or classifications within a narrow problem domain. This is in stark contrast to social software which enables knowledge communities to share implicit knowledge of a more practical or experiential nature to inform individuals and groups to arrive at their own conclusions. Specialists are often needed to elicit and encode the knowledge in the case of expert systems, whereas one of the (claimed) hallmarks of social software and the Web 2.0 trend, such as Wikis and Blogs, is that everyone, anywhere can chose to contribute input. This openness in authoring and sharing content, however, tends to produce unstructured knowledge that is difficult to execute, reason over or automatically validate. This also poses limitations for its reuse. To facilitate the capture of knowledge-in-action which spans both explicit and tacit knowledge types, a knowledge engineering approach which offers Wiki-style collaboration is introduced. The approach extends a combined rule and case-based knowledge acquisition technique known as Multiple Classification Ripple Down Rules to allow multiple users to collaboratively view, define and refine a knowledge base over time and space.     

An approach to expert assessment in software engineering

An approach is proposed to the solution of formalized problems of assessment of the activity that produces and maintains software systems (SSs). Such assessment is realized by using expertises that form a new assessment process adequate to the activity needs and specifics with an environment common to the expertises. The following mathematical apparatus is elaborated for expertises: a framework (target functions and executing mechanisms), a model and methods (formalisms for improving the quality and reusing the results of expertises) of an assessment process, and tools for integrating the apparatus into software development management processes. The approach is theoretically justified. Prospects of developing the proposed approach are described. Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 151–168, July–August 2009.     

A knowledge based reliability engineering approach to manage product safety and recalls

PurposeManaging processed food products’ safety and recall is a challenge for industry and governments. Contaminated food items can create a significant public health hazard with potential for acute and chronic food borne illnesses. This industry study examines the challenges companies face while managing a processed food recall situation and devise a responsive and reliable knowledge management framework for product safety and recall supply chain for the focal global manufacturing and distribution enterprise.MethodDrawing upon the knowledge management and product safety and recall literature and reliability engineering theory, this study uses a holistic single case based approach to develop a knowledge management framework with Failure Mode Effects and Criticality Analysis (FMECA) decision model. This knowledge management decision framework facilitates analysis of the root causes for each potential major recall issue and assesses the reliability of the product safety and recall supply chain system and its critical components.ResultsThe main reasons highlighted for a recall and associated failure modes in a knowledge management framework are to devise appropriate deployment of resources, technology and procedures to recall supply chain. This study underscores specific information described by managers of a global processed food manufacturer and their perspectives about the product safety and recall process, and its complexities. Full scale implementation of product safety and recall supply chain in the proposed knowledge management framework after the current pilot study will be carried out eventually through expert systems. This operational system when fully implemented will capture the essence of decision making environments comprising goals and objectives, courses of action, resources, constraints, technology and procedures.ImplicationsThe study recognizes the significance of communication, integration, failsafe knowledge management process design framework, leveraging technology such as Radio Frequency Identification (RFID) within all levels of supply chain for product traceability and the proactive steps to help companies successfully manage a recall process and also reestablish trust among the consumers. The proposed knowledge management framework can also preempt product recall by acting as an early warning system. A formal knowledge management framework will enable a company’s knowledge be cumulative for product safety and recall and serve as an important integrating and coordinating role for the organization.     

A hypernetwork-based approach to collaborative retrieval and reasoning of engineering design knowledge

Complex product development increasingly entails creation and sharing of design knowledge in a collaborative and integrated working environment. In this context, it has become a central issue to address the multifaceted feature of design knowledge for such a collaborative knowledge sharing scheme. This paper proposes a hypernetwork-based approach to explicitly capturing the relationships between various elements in a multifaceted knowledge representation. Specifically, a knowledge hypernetwork model is constructed, which is composed of a designer network, a product network, an issue network and a knowledge unit network. The relationships between various nodes from different networks are identified and defined according to specific node properties. In addition, topological characteristics of the hypernetwork structure are analyzed together with the statistical indicators. Based on this model, the Bayesian approach is adopted to conduct the collaborative reasoning process whereby knowledge elements relevant to the current design task are recommended according to the issues to be resolved and the current design context. A case study conducted in this work shows that the proposed approach is effective in capturing the complex relationships between multi-faceted knowledge elements and enables collaborative retrieval and reasoning of knowledge records.     

An approach to support SMEs in manufacturing knowledge organization

Different kinds of technological data are available in manufacturing enterprises, concerning the resources available as well as the processes and the components needed for the production of specific products. These data usually are not stored in a centralized knowledge management system, thus one of the main problem of managers, especially in small enterprises, is to efficiently manage their data and reuse the knowledge deriving from previous products when a new product has to be produced. Starting form the analysis of the technological data available in manufacturing enterprises, we defined a formal model as set of matrices; their analysis allows the definition of a data model to structure the technological information. The model is at the basis of the proposed system, called manufacturing knowledge organization (MAKO) to support managers in structuring and reusing the technological knowledge available in their enterprise. A prototype of the MAKO system was implemented by using open-source software and its potentialities are shown in a case study.     

An approach to user knowledge acquisition in product design

As the world increasingly moves towards a knowledge-based economy, user requirements become an important factor for enterprises to drive product collaborative design evolution. To map user requirements to the product model, user requirements are generally extracted into knowledge that can be used for design decisions. However, because users are interest-driven participants and not professional design engineers, the effect of user knowledge acquisition is not ideal. There are significant challenges for rapid knowledge acquisition with dynamic user requirements. This paper presents an approach to user knowledge acquisition in the product design process, which obtains the tangible requirements of users under the premise that users are adequate for participation. In this approach, the typical information flow is divided into four stages: submission, interaction, knowledge discovery, and model evolution. In the submission stage, natural language processing technology is used to transform text form solutions into data, so that computer technology can be applied to manage large-scale user requirements. In the interaction stage, users are helped to improve their solutions by the iterative recommendation process. In the knowledge discovery stage, after less concerned partial solutions are removed and vacant items are predicted to be supplemented, the final collection of user design information is obtained. Finally, based on rough set theory, design knowledge can be extracted to support the decision of the product model. The washing machine design project is used as a case study to explain the implementation of the proposed approach.     

An agent-based approach to knowledge management in distributed design

The collaboration process among individuals with heterogeneous skills in a distributed virtual environment represents a crucial element of the extended enterprise. In order to achieve global optima in design, there is an increasing need for design teams to establish and maintain cooperative work through effective communication, co-location, coordination and collaboration at the knowledge level. Because of the distributed nature of users and information resources involved in the design process, the need for appropriate knowledge management tools is imperative. This paper proposes an agent-based architecture to support multi-disciplinary design teams that cooperate in a distributed design environment (DDE). Using ontologies and multi-agent systems (MAS), the proposed framework aims to optimise design process operation and management by supporting the dialogue among distributed design actors. Received: February 2005/Accepted: January 2006     

An algebraic approach to revising propositional rule-based knowledge bases

One of the important topics in knowledge base revision is to introduce an efficient implementation algorithm. Algebraic approaches have good characteristics and implementation method; they may be a choice to solve the problem. An algebraic approach is presented to revise propositional rule-based knowledge bases in this paper. A way is firstly introduced to transform a propositional rule-based knowledge base into a Petri net. A knowledge base is represented by a Petri net, and facts are represented by the initial marking. Thus, the consistency check of a knowledge base is equivalent to the reachability problem of Petri nets. The reachability of Petri nets can be decided by whether the state equation has a solution; hence the consistency check can also be implemented by algebraic approach. Furthermore, algorithms are introduced to revise a propositional rule-based knowledge base, as well as extended logic programming. Compared with related works, the algorithms presented in the paper are efficient, and the time complexities of these algorithms are polynomial.     

An approach to multicriterion optimization problems for engineering design

Optimization problems in mechanical engineering design are often modelled as nonlinear programming problems. A multicriterion optimization approach to this problem is developed in this work. The problem formulation is given, and the min-max principle for this problem is discussed. Next, an algorithm is provided for comparing solutions using this principle.The solution which is defined by the min-max principle of optimality may be called the best compromise considering all the criteria simultaneously and on equal terms of importance. This principle is fully formalized mathematically and used to obtain the optimal solution automatically. The algorithm for comparing solutions gives us, from any set of solutions, the one which is optimal in the min-max sense.Seeking the optimal solution in the min-max sense can be carried out in many different ways. Some methods based upon the Monte Carlo method and trade-off studies are proposed.The approach as discussed here is applied to the design of machine tool gearboxes. The problem is formulated as finding the basic constructional parameters (modules, numbers of teeth etc.) of a gearbox which minimizes simultaneously four objective functions: volume of elements, peripheral velocity between gears, width of gearbox and distance between axes of input and output shafts. A detailed example considering a lathe gearbox optimization problem is also presented. This example indicates that for some mechanical engineering optimization problems, using this approach, we can automatically obtain a solution which is optimal and acceptable to the designer.     

An approach to engineering the requirements of data warehouses

We focus exclusively on the issue of Requirements engineering for Data Warehouses (DW). Our position is that the information content of a DW is found in the larger context of the goals of an organization. We refer to this context as the organizational perspective. Goals identify the set of decisions that are relevant which in turn help in determining the information needed to support these. The organizational perspective is converted into the technical perspective, which deals with the set of decisions to be supported and the information required. The latter defines Data warehouse contents. To elicit the technical perspective, we use the notion of an informational scenario. It is a typical interaction between a DW system and the decision maker and consists of a sequence of pairs of the form, <information request, response>. We formulate an information request as a statement in an adapted form of SQL called Specification SQL. The proposals here are implemented in the form of an Informational Scenario Engine that processes informational scenarios and determines Data Warehouse Information Contents.     

An ontology-based knowledge framework for engineering material selection

Engineering material selection intensively depends on domain knowledge. In the face of the large number and wide variety of engineering materials, it is very necessary to research and develop an open, shared, and scalable knowledge framework for implementing domain-oriented and knowledge-based material selection. In this paper, the fundamental concepts and relationships involved in all aspects of material selection are analyzed in detail. A novel ontology-based knowledge framework is presented. The ontology-based Semantic Web technology is introduced into the semantic representation of material selection knowledge. The implicit material selection knowledge is represented as a set of labeled instances and RDF instance graphs in terms of the concept model, which provides a formal approach to organizing the captured material selection knowledge. A knowledge retrieval and reasoning approach integrating ontology concepts, instances, knowledge rules, and semantic queries encoded with Query-enhanced Web Rule Language (SQWRL) is proposed. The presented knowledge framework can provide powerful knowledge services for material selection. Finally, based on this knowledge framework, a case study on constructing a mold material selection knowledge system is provided. This work is a new attempt to build an open and shared knowledge framework for engineering material selection.     

An approach to quality engineering of TTCN-3 test specifications

Experience with the development and maintenance of large test suites specified using the Testing and Test Control Notation (TTCN-3) has shown that it is difficult to construct tests that are concise with respect to quality aspects such as maintainability or usability. The ISO/IEC standard 9126 defines a general software quality model that substantiates the term “quality” with characteristics and subcharacteristics. The domain of test specifications, however, requires an adaption of this general model. To apply it to specific languages such as TTCN-3, it needs to be instantiated. In this paper, we present an instantiation of this model as well as an approach to assess and improve test specifications. The assessment is based on metrics and the identification of code smells. The quality improvement is based on refactoring. Example measurements using our TTCN-3 tool TRex demonstrate how this procedure is applied in practise. B. Zeiss is supported by a Ph.D. scholarship from Siemens AG, Corporate Technology.     

An interactive example-driven approach to graphics recognition in engineering drawings

An interactive example-driven approach to graphics recognition in engineering drawings is proposed. The scenario is that the user first interactively provides an example of a graphic object; the system instantly learns its graphical knowledge and uses the acquired knowledge to recognize the same type of graphic objects. The proposed approach represents the graphical knowledge of an object in terms of its structural components and their syntactical relationships. We summarize four types of geometric constraints for knowledge representation, based on which we develop an algorithm for knowledge acquisition. Another algorithm for graphics recognition using the acquired graphical knowledge is also proposed, which is actually a sequential examination of these constraints. In the algorithm, we first guess the next component’s attributes (e.g., size, position and orientation) by reasoning from an earlier found component and the constraint between them, and then search for this hypothetical component in the drawing. If all of the hypothetical components are found, a graphic object of this type is recognized. For improving the system’s recognition accuracy, we develop a user feedback scheme, which can update the graphical knowledge from both positive (missing) and negative (mis-recognized) examples provided by the user for subsequent recognition. Experiments have shown that our proposed approach is both efficient and effective for recognizing various types of graphic objects in engineering drawings. This paper is an extension of our papers published in ICDAR2003 and GREC2003.