bluuebunny/crossref_metadata_2025_split huggingface dataset:
Selecting the architecture of a class of back-propagation neural networks used as approximators
Authors: Carpenter William C. , Hoffman Margery E. 
Published: March 2010

AbstractThis paper examines the architecture of back-propagation neural networks used as approximators by addressing the interrelationship between the number of training pairs and the number of input, output, and hidden layer nodes required for a good approximation. It concentrates on nets with an input layer, one hidden layer, and one output layer. It shows that many of the currently proposed schemes for selecting network architecture for such nets are deficient. It demonstrates in numerous examples that overdetermined neural networks tend to give good approximations over a region of interest, while underdetermined networks give approximations which can satisfy the training pairs but may give poor approximations over that region of interest. A scheme is presented that adjusts the number of hidden layer nodes in a neural network so as to give an overdetermined approximation. The advantages and disadvantages of using multiple output nodes are discussed. Guidelines for selecting the number of output nodes are presented.
Case-based design: A review and analysis of building design applications
Authors: Watson Ian , Perera Srinath 
Published: March 2010

AbstractThis paper presents a review of CBD and its application to building design in particular. Case-based design is the application of case-based reasoning to the design process. Design maps well to case-based reasoning because designers use parts of previous design solutions in developing new design solutions. This paper identifies problems of case representation, retrieval, adaptation, presentation, and case-based maintenance along with creativity, legal, and ethical issues that need to be addressed by CBD systems. It provides a comprehensive review of CBD systems developed for building design and provides a detailed comparison of the CBD systems reviewed.
ADD+: Including rhetorical structures in active documents
Authors: Bicharra Garcia Ana Cristina , De Souz Clarisse Sieckenius 
Published: March 2010

AbstractA design is a plan containing guidelines to build and understand an artifact. Generally, this plan is constructed by a team of designers with different tasks, but sharing a common objective, that is, to create a high-quality, low-cost integrated artifact. Active Design Documents (ADDs) are powerful tools for cooperative design because they account for revealing the rationale among design participants while assisting each of them in their own. Design rationale capture and retrieval are critical issues on building documentation assistant tools. In this paper, we propose to achieve more efficient and effective delivery of design and designers intent by resorting to rhetorical means. The wealth of knowledge kept in ADD’s knowledge bases is organized into high-level Rhetorical Structure Theory (RST) schema and mapped onto input and output screen configurations that gear the interaction between systems and users. We illustrate the effects of such an organization with evidences from an implemented version of ADD for the domain of offshore platform.
Extending the scope and use of design rationale records
Authors: King Josh M.P. , Bañares-Alcántara René 
Published: March 2010

AbstractDuring the course of the design of a complex artifact many thousands of objects will be created that will refer to many different types of information. Thus, an effective design support system must be able to store various types of data and allow easy navigation of the resulting extensive network of objects. In addition, the quality of the design records (both the record of the design artifact and rationale) is increased by the quality and quantity of information which the designer is able to record. In this paper we describe two new developments to Kbds a design support system for chemical process design, which enable easier navigation of the design network, and a fuller representation of the design process. In addition, we show how these extensions may be used together to improve the quality of the design information recorded—both for the evolution of the design artifact and the supporting rationale. The first development enables the designer to record a variety of complementary types of document within the process design history, fulfilling the task of improving the design information recorded. The second enhancement to Kbds eases the navigation of the design history by categorizing design objects according to a user-defined set of keywords. The categorization of design objects is carried out semiautomatically using, in part, the various design representations (documents) enabled through the first extension and enables rapid navigation of the design network. Finally, a method of checking the consistency of design rationale structures using keywords is also described. Thus, various representations may be used to generate keywords that in turn may be used to improve the quality of design rationale records. An example showing this situation is described.
The application of neural network techniques to structural analysis by implementing an adaptive finite-element mesh generation
Authors: Jadid Mansour Nasser , Fairbairn Daniel R. 
Published: March 2010

AbstractThis study focuses on the application of neural network techniques to adaptive remeshing of an idealized squareshaped structure and individual triangle by using triangular elements. The backpropagation learning algorithm is implemented by a supervised training technique to deal with the problem of remeshing structural elements in a structural analysis. A recent study introduced a structural remeshing that incorporated a finite-element analysis with an adaptive mesh generation technique. The main objective of the study is to demonstrate how neural networks can be employed to remesh structural elements without using numerically intensive computations. One essential requirement of this approach is the selection of feasible and appropriate training and testing data. The exploration of neural network in remeshing structural elements is a fundamental technique that looks beyond the finite-element and adaptive mesh generation techniques. It also demonstrates the capability of neural network to representn-dimensional space and track each individual characteristic in that separate space. In general, an overview is presented, and the potential of neural networks to use the backpropagation algorithm instead of the more conventional approach of numerical methods is demonstrated.
Comparison of some computer-based task management approaches
Authors: Diaz-Calderon Antonio , Hendrickson Chris 
Published: March 2010

AbstractThis article presents an assessment of four management systems to expose the essential characteristics of each management system, including planning techniques, problem representation, concurrency, and flexibility. The experimental part of the research shows that existing management systems can be used to attack a variety of problems. The authors conclude that flexible planning systems are quite beneficial since they can be used to solve a variety of design problems by making small modifications in the definition of their tools.
An optimization approach to order of magnitude reasoning
Authors: Kalagnanam Jayant R. , Diwekar Urmila M. 
Published: March 2010

AbstractAn approach for transforming the order of magnitude relation between two variables into an algebraic equality or inequality constraint is provided. In order to derive the order of magnitude relation between any two variables, a nonlinear optimization problem is solved for the minimum and maximum values of the ratio between the two variables, subject to two classes of constraints. The first class of constraints corresponds to the quantitative model and the second class of constraints corresponds to the qualitative model. The optimization approach is shown to provide more precise inferences as compared to the conventional constraint satisfaction approaches. Moreover, this approach provides a crucial step in developing unified frameworks that allow the incorporation of qualitative information at various levels of abstraction into numerical frameworks used for reasoning with quantitative models.
Recording and reuse of design strategies in an integrated case-based design system
Authors: Wang Jenmu , Howard H. Craig 
Published: March 2010

AbstractHuman designers often adopt strategies from previous similar cases to guide their search in new design tasks. We have developed an approach for automated design strategy capture and reuse. That approach has been implemented in DDIS, a prototype structural design system that uses a blackboard framework to integrate case-based and domain-based reasoning. Plans, goals, and critical constraints from user-selected previous cases are combined with case-independent reasoning to solve underconstrained parametric structural design problems. This article presents a detailed example of design strategy recording and reuse in base plate design for electrical transmission poles.
Integrating knowledge-based systems and artificial neural networks for engineering
Authors: Kartam Nabil , Flood Ian , Tongthong Tanit 
Published: March 2010

AbstractThe feasibility and relative merits of integrating knowledge-based systems (KBSs) and artificial neural networks (ANNs) for application to engineering problems are presented and evaluated. The strength of KBSs lies in their ability to represent human judgment and solve problems by providing explanations from and reasoning with heuristic knowledge. ANNs demonstrate problem solving characteristics not inherent in KBSs, including an ability to learn from example, develop a generalized solution applicable to a range of examples of the problem, and process information extremely rapidly. In this respect, KBSs and ANNs are complementary, rather than alternatives, and may be integrated into a system that exploits the advantages of both technologies. The scope of application and quality of solutions produced by such a hybrid extend beyond the boundaries of the individual technologies. This paper identifies and describes how KBSs and ANNs can be integrated, and provides an evaluation of the advantages that will accrue in engineering applications.
Application of a Bayesian network to integrated circuit tester diagnosis
Authors: Mittelstadt Daniel , Paasch Robert , D’Ambrosio Bruce 
Published: March 2010

AbstractResearch efforts to implement a Bayesian belief-network-based expert system to solve a real-world diagnostic problem – the diagnosis of integrated circuit (IC) testing machines – are described. The development of several models of the IC tester diagnostic problem in belief networks also is described, the implementation of one of these models using symbolic probabilistic inference (SPI) is outlined, and the difficulties and advantages encountered are discussed. It was observed that modeling with interdependencies in belief networks simplifies the knowledge engineering task for the IC tester diagnosis problem, by avoiding procedural knowledge and focusing on the diagnostic component’s interdependencies. Several general model frameworks evolved through knowledge engineering to capture diagnostic expertise that facilitated expanding and modifying the networks. However, model implementation was restricted to a small portion of the modeling, that of contact resistance failures, which were due to time limitations and inefficiencies in the prototype inference software we used. Further research is recommended to refine existing methods, in order to speed evaluation of the models created in this research. With this accomplished, a more complete diagnosis can be achieved.
A parametric design assistant for concurrent engineering
Authors: Kuokka Daniel , Jefferson Stanley , Barford Lee , Frayman Felix 
Published: March 2010

AbstractThe Explorer parametric design assistant, an interactive tool that provides intelligent support for searching concurrent-engineering trade-spaces under multiple, conflicting objectives, is described. The system provides a convenient means for specifying multiple, cross-disciplinary constraints in terms of tables, formulas, and logical sentences. Based on these data, the system performs interactive constraint checking, computes feasible designs, and provides graphical analysis facilities, allowing users to compare designs based on multiple criteria. As a first application, Explorer has been used as a printed circuit board (PCB) construction design assistant. In initial tests, Explorer has helped users to find design configurations not previously considered that yield comparable performance and cost while offering better manufacturability and reliability. The capabilities and use of the Explorer system are described in detail, the underlying technologies are outlined, and an evaluation of the prototype system is presented.
The Virtual Design Team: Modeling organizational behavior of concurrent design teams
Authors: Jin Yan , Levitt Raymond E. , Christiansen Tore R. , Kunz John C. 
Published: March 2010

AbstractConcurrent engineering is a systematic approach to the integrated, concurrent design of products and the related processes of manufacturing and support. This approach is intended to cause the developers, from the outset, to consider all elements of the product life cycle from concept through disposal, including quality, cost, schedule, and user requirements. To achieve successful concurrent-engineering design, one needs an integrated framework, a well-organized design team, and adequate design tools. The research on concurrent engineering to date has focused on developing communication infrastructure, design tools, and product data representations. Little attention has been paid to developing tools to address the organizational issues involved in concurrent engineering. The authors’ research on the Virtual Design Team (VDT) attempts to develop a computerized analysis tool to sup-port the systematic design of organization structures for concurrent engineering projects. VDT is a computer simulation system. It takes descriptions of design tasks, actors (i.e., designers and managers), and organization structure as input, and produces predicted historical records of the actors’ design and coordination behavior, project du-ration, cost, and design process quality as output. VDT has been applied to model more than ten realistic engineering projects, and the results are qualitatively consistent with the predictions from theory and project managers. The VDT framework for modeling concurrent-engineering teams is described, and examples of VDT applications are presented to demonstrate the effectiveness of the Virtual Design Team approach to modeling the organizational behavior of concurrent design teams.
Towards a foundation for evaluating AI planners
Authors: Kartam Nabil A. , Wilkins David E. 
Published: March 2010

There exists a large body of Artificial Intelligence (AI) research on generating plans, i.e. linear or non-linear sequences of actions, to transform an initial world state to some desired goal state. However, much of the planning research to date has been complicated, ill-understood, and unclear. Only a few of the developers of these planners have provided a thorough description of their research products, and those descriptions that exist are usually unrealistically favorable since the range of applications for which the systems are tested is limited to those for which they were developed. As a result, it is difficult to evaluate these planners and to choose the best planner for a different domain. To make a planner applicable to different planning problems, it should be domain independent. However, one needs to know the circumstances under which a general planner works so that one can determine its suitability for a specific domain.This paper presents criteria for evaluating AI planners; these criteria fall into three categories: (1)performance issues, (2)representational issues, and (3)communication issues. This paper also assesses four non-linear AI planners (NOAH, NONLIN, SIPE and TWEAK) based on a study of the published literature and on communication (via electronic mail, meetings and correspondence) with their developers.
Interpretation of CAD models through neutral geometric knowledge
Authors: Nnaji Bartholomew O. , Kang Tzong-Shyan 
Published: March 2010

A generalized approach to fast interpretation of objects and their features has so far eluded researchers. In manufacturing, this interpretation can be approached from the vision point of view or from the CAD data perspective. Presently, CAD systems are widely used in several aspects of manufacturing production. It is therefore more efficient to use CAD data for object reasoning in manufacturing, especially when systems will eventually be data driven. Components can be modelled on a CAD system using various modelling techniques and the representation of their geometric information is still CAD system dependent. However, the advent of the Initial Graphics Exchange Specification (IGES) now makes it possible to represent CAD data in a neutral and standard manner.This paper describes a scheme for recognizing and representing features for CAD data extracted using the IGES interface. The concepts developed are based on graph-based feature representation, where features are represented by a set of faces as well as their topological adjacency.Strategies for classifying features and methods of decomposing a complicated feature into several simpler features for recognition purposes are discussed.
Preference-directed design
Authors: D’Ambrosio Joseph G. , Birmingham William P. 
Published: March 2010

AbstractCurrent design practices mandate that engineering designs be evaluated based on multiple attributes, e.g., cost, power, and area. For multiattribute design problems, generation and evaluation of the Pareto optimal set guarantees the optimal design will be found, but is not practical for a large class of problems. Iterative techniques can be applied to most problems, but sacrifice optimality. In this paper, we introduce a new technique that extends the set of design problems that can be solved optimally. By first constructing an imprecise value function, the number of nondominated alternatives that must be generated is reduced. We describe an implementation based on combinatorial optimization and constraint satisfaction which achieves additional performance gains by decomposing the value function to identify dominated design-variable assignments. Test results indicate that our approach extends the set of problems that can be solved optimally.
Generalized set-propagation operations over relations of more than three variables
Authors: Finch William W. , Ward Allen C. 
Published: March 2010

AbstractThis paper extends previously developed generalized set propagation operations to work over relationships among an arbitrary number of variables, thereby expanding the domain of engineering design problems the theory can address. It then narrows its scope to a class of functions and sets useful to designers solving engineering problems: monotonic algebraic functions and closed intervals of real numbers, proving formulas for computing the operations under these conditions. The work is aimed at the automated optimal design of electro-mechanical systems from catalogs of parts; an electronic example illustrates.
Intelligently helping the human planner in industrial process planning
Authors: Famili A. , Turney P. 
Published: March 2010

The function of a process planning system is to determine the methods by which a product is to be manufactured economically and competitively. In a modern manufacturing environment, a process planning system consists of highly trained people and complex software. The plans prepared by a process planning system are not always executed as planned. It is useful if the system can discover why plans fail, when they do fail. In order to learn why plans fail, the system must analyse a number of plans, both successful and unsuccessful, to find patterns in the failures of plans. This type of analysis is difficult for people, who are much better at analysing single events than multiple events.The aim of the project described here is to design and implement a computer program which will help human planners in a process planning system to understand why plans fail. To achieve this aim, a program called IMAFO (Intelligent MAnufacturing FOreman) has been developed. IMAFO uses decision tree induction to analyse examples of both successful and unsuccessful plans.The difficulties presented by this application are discussed and solutions are presented. Problems addressed include finding an appropriate set of attributes for describing the plans, using data efficiently, consolidating input from distinct sources, and presenting decision trees in an understandable form. Potential applications and directions for future research are considered.
Conceptual geometric reasoning by the manipulation of models based on prototypes
Authors: Brown K.N. , Williams J.H. Sims , McMahon C.A. 
Published: March 2010

AbstractThe ability to understand the implications of the geometry of solid objects is an important aspect of intelligent behavior. This paper presents work designed to enable reasoning with relatively loose conceptualizations of geometry. The method operates by comparing target geometry to known geometry, and involves the manipulation of models based upon prototypes. In particular, three techniques of simplification, approximation, and transformation are discussed. Finally, an application of the method to the domain of stress concentration prediction is presented.
Intelligent automated quality control for computational simulation
Authors: Gelsey Andrew 
Published: March 2010

AbstractComputational simulation of physical systems generally requires human experts to set up a simulation, run it, evaluate the quality of the simulation output, and repeatedly invoke the simulator with modified input until a satisfactory output quality is achieved. This reliance on human experts makes use of simulators by other programs difficult and unreliable, though invocation of simulators by other programs is critical for important tasks such as automated engineering design optimization. Presented is a framework for constructing intelligent controllers for computational simulators that can automatically detect a wide variety of problems that lead to low-quality simulation output, using a set of evaluation methods based on knowledge of physics and numerical analysis stored in a data/knowledgebase of models and simulations. An experimental implementation of this framework in an intelligent automated controller for a widely used computational fluid dynamics simulator is described.
Performing calculus operations on poorly understood engineering functions using neural networks
Authors: Flood Ian 
Published: March 2010

AbstractThe paper describes a novel means of performing calculus operations on poorly understood engineering functions using networks of radial Gaussian neurons. The network architecture and training algorithm used for this purpose is described briefly. Once trained, a network can be converted into a form that provides the differential or integral of the learned function, by a simple substitution of the type of activation function used at the hidden neurons. A range of substitute activation functions, for conversion to first- and second-order partial differential and integral forms of the network, are derived. Following this, the technique is tested on a selection of calculus operations for two example civil engineering problems: assessing motion in tall structures; and modeling moisture penetration in porous materials. The converted networks produced in these experiments provide accurate models of the actual differentials and integrals of the function the original networks had been taught. A method of improving the accuracy of results by training the original network beyond the region in which the converted networks operate, is described. The paper concludes by identifying some areas for further development of the technique.