scholarly journals Erratum

The following erratum is to correct an omission of a table during the publication phase of the article entitled: “User interface for specification language for case-based mechanical design” by Abhay Dandekar, Ibrahim Zeid, and Theodore Bardasz (AI EDAM, 11(1), p. 18).The table referred to reads:The Editor-In-Chief and Publisher regret the inadvertent mistake.

Author(s):  
Abhay Dandekar ◽  
Ibrahim Zeid ◽  
Theodore Bardasz

AbstractCase-based design (CBD) systems aim to solve a design problem by tailoring previously solved design problems to the current problem. Designers' specifications are used for indexing the knowledge base of the CBD system to retrieve an appropriate design case. Menu-based systems fail to capture designers' specifications effectively due to lack of expressiveness, while natural language systems are too immature to satisfy the goal. This paper presents the development of a graphical user interface (GUI) to implement a mechanical design specification language (MDSL) (Stelling, 1994) used to facilitate indexing in case-based mechanical design. The specification language is context-free and hence computable. It represents mechanical design knowledge in a (feature):(attribute) format suitable for indexing. An augmented transition network (ATN) parser is built using the grammar of the specification language. The parser provides syntactic as well as semantic checks. It also has capabilities to expand grammar and to adapt to a specific user domain. A graphical front end to the parser assists and guides the user through the specification language syntax in entering the design specifications. Provisions have been made to expand or edit the language grammar and vocabulary. The ATN parser was implemented in Common Lisp and the graphical user interface was written using the Gold Hill Windows Toolkit. Sample user interactions with the interface and screen dumps of the GUI are included.


Author(s):  
Theodore Bardsz ◽  
Ibrahim Zeid

Abstract One of the most significant issues in applying case-based reasoning (CBR) to mechanical design is to integrate previously unrelated design plans towards the solution of a new design problem. The total design solution (the design plan structure) can be composed of both retrieved and dynamically generated design plans. The retrieved design plans must be mapped to fit the new design context, and the entire design plan structure must be evaluated. An architecture utilizing opportunistic problem solving in a blackboard environment is used to map and evaluate the design plan structure effectively and successfuly. The architecture has several assets when integrated into a CBR environment. First, the maximum amount of information related to the design is generated before any of the mapping problems are addressed. Second, mapping is preformed as just another action toward the evaluation of the design plan. Lastly, the architecture supports the inclusion of memory elements from the knowledge base in the design plan structure. The architecture is implemented using the GBB system. The architecture is part of a newly developed CBR System called DEJAVU. The paper describes DEJAVU and the architecture. An example is also included to illustrate the use of DEJAVU to solve engineering design problems.


Author(s):  
Fernando Alonso ◽  
José L. Fuertes ◽  
Ángel L. González ◽  
Loïc Martínez

1994 ◽  
Vol 61 (1) ◽  
pp. 26-30
Author(s):  
S. Pasquali

This paper deals with the basic structure of computers (hardware and software) and some of the software applications now offered by technology; these applications can make medical work easier. Some features of advanced software applications are presented here, such as expert systems, case-based reasoning technics, image management, and also call tracking systems and user interface systems. The aim of this paper is to offer an overall view of the opportunity of setting up an efficient information system inside a health structure.


2012 ◽  
Vol 549 ◽  
pp. 1041-1045
Author(s):  
Zhou Fang ◽  
Li Na Zhang

Mechanical Design Handbook oriented standard part library system of jaw clutches is developed based on SolidWorks. The system consists of three elements, namely a dimension parameter database, a user interface, and a modeling function module. The jaw clutch dimension parameter database is designed based on national standards. According to designers’ thinking habit, a visual user interface is customized to make easy use of the dimension parameter database. The data relationship between the modeling function module and dimension parameter database is established by using parametric program driven method. The jaw clutch standard part library with characteristics of friendly user interface and expansible database is easy to use. The approach adopted in the paper can be used to develop other general 3D standard part library on SolidWorks.


Author(s):  
Theodore Bardasz ◽  
Ibrahim Zeid

The architecture and implementation of a mechanical designer's assistant shell called DEJAVU is presented. The architecture is based on an integration of design and CAD with some of the more well known concepts in case-based reasoning (CBR). DEJAVU provides a flexible and cognitively intuitive approach for acquiring and utilizing design knowledge. It is a domain independent mechanical design shell that can incrementally acquire design knowledge in the domain of the user. DEJAVU provides a design environment that can learn from the designer(s) until it can begin to perform design tasks autonomously or semi-autonomously. The main components of DEJAVU are a knowledge base of design plans, an evaluation module in the form of a design plan system, and a blackboard-based adaptation module. The existance of these components are derived from the utilization of a CBR architecture. DEJAVU is the first step in developing a robust designer's assistant shell for mechanical design problems. One of the major contributions of DEJAVU is the development of a clean architecture for the utilization of case-based reasoning in a mechanical designer's assistant shell. In addition, the components of the architecture have been developed, tailored or modified from a general CBR context into a more synergistic relationship with mechanical design.


Author(s):  
Kaoru Hirota ◽  
◽  
Hajime Yoshino ◽  
Ming Qiang Xu ◽  
Yan Zhu ◽  
...  

In legal case-based reasoning (CBR), there exist problems concerning fuzziness, e.g., representation of precedents, their retrieval, and similarity measures. In our proposed fuzzy legal CBR system, the issues and features of precedent are characterized on the basis of the facts of precedent and statute rule. The case rule that is used for interpreting the court judgment, which cannot be obtained from the statute rule directly, is made by experts. Fuzziness is represented by membership functions. Features and case rules, written in terms of Compound Predicate Formula (CPF) and frame, are stored in a case base. Cases similar to a new case are retrieved by issues and features, and an inference is made by case rules. A user interface is devised for this system. The system proposed here will be used for law education, where the target law of the system is contract, especially as it relates to the United Nations Convention on Contracts for the International Sale of Goods (CISG).


1998 ◽  
Vol 10 (6) ◽  
pp. 337-350 ◽  
Author(s):  
Yongsheng Gao ◽  
Ibrahim Zeid ◽  
Theodore Bardasz

2018 ◽  
Vol 10 (10) ◽  
pp. 168781401880464 ◽  
Author(s):  
Jin Qi ◽  
Jie Hu

Using historical cases’ solutions to obtain feasible solution for new problem is fundamentally to successfully applying case-based reason technique in parametric mechanical design. As a well-known intelligent algorithm, the formulation of support vector regression has been taken for case-based reason adaptation, but the standard support vector regression can only be used as a univariate adaptation method because of its single-output structure, which would result in the ignorance of the possible interrelations among solution outputs. To handle the complicated case adaptation task with large number of problem inputs and solution outputs more efficiently, this study investigates the possibility of multivariable case-based reason adaptation with multiple output by applying multiple-output support vector regression. Furthermore, inspired by the fact that training sample which contains two closer cases can provide more useful information than others, this study adds the similarity-related weight into multiple-output support vector regression and gives high weights to the information provided by such useful training sample during multi-dimensional regression estimation. The superiority of proposed multiple-output support vector regression with similarity-related weight is validated by the actual design example and quantitative comparisons with other adaptation methods. The comparative results indicate that multiple-output support vector regression with similarity-related weight achieves the best performance for large-quantity case-based reason adaptation because of its higher accuracy and relatively lower cost.


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