The design and analysis of boundary data structures

The thesis is concerned with the efficient interrogation of CAD data. CAD data finds use in diverse range of applications which necessitates extension and integration of the CAD data base. By an exhaustive categorization of such application requirements and analysis of various CAD techniques, it is shown that boundary data structures are the most suitable in CAD, CAM and advanced robotic applications. Several boundary data structures have been proposed since the classic Winged edge data structure, these aimed at reducing the storage requirement and increasing information retrieval speeds. In this thesis methodologies are developed which enable us to discover compact and fast access time schemes and analyze and fine tune for individual applications. We demonstrate how the application of the optimality concepts can lead us to the discovery of more efficient data structures than popular data structures. All the boundary data structures proposed to date have been based on the underlying assumption that all the data resides in main memory. We show that in an integrated CAD environment (characterized by virtual a memory environment or a data base environment), these data structures are inefficient in both storage and time. We propose a new data structure shaped like A which is the most compact as well as more efficient in access time, under certain conditions of real memory and virtual memory. Experiments reveal a paradoxical phenomenon: access time increases with storage, violating the classic law of storage vs. time. Recently non-manifold boundary geometric modeling has become popular to meet the growing needs such as uniform treatment of wire frame, surface and solid modeling and design by features. We introduce a uniform terminology and notation to distinguish and critically analyze several non-manifold boundary data structures. It is hoped to fulfill the need for a ready reference for the design of efficient boundary data structures. The other aspects dealt with are the validity and conversion of Boundary data structures. To verify the concepts developed, in practice, a whole suite of fast algorithms have been implemented for model manipulation, visualization and data conversion

An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term

On Interpretability of Deep Learning based Skin Lesion Classifiers using Concept Activation Vectors

Deep learning based medical image classifiers have shown remarkable prowess in various application areas like ophthalmology, dermatology, pathology, and radiology. However, the acceptance of these Computer-Aided Diagnosis (CAD) systems in real clinical setups is severely limited primarily because their decision-making process remains largely obscure. This work aims at elucidating a deep learning based medical image classifier by verifying that the model learns and utilizes similar disease-related concepts as described and employed by dermatologists. We used a well-trained and high performing neural network developed by REasoning for COmplex Data (RECOD) Lab for classification of three skin tumours, i.e. Melanocytic Naevi, Melanoma and Seborrheic Keratosis and performed a detailed analysis on its latent space. Two well established and publicly available skin disease datasets, PH2 and derm7pt, are used for experimentation. Human understandable concepts are mapped to RECOD image classification model with the help of Concept Activation Vectors (CAVs), introducing a novel training and significance testing paradigm for CAVs. Our results on an independent evaluation set clearly shows that the classifier learns and encodes human understandable concepts in its latent representation. Additionally, TCAV scores (Testing with CAVs) suggest that the neural network indeed makes use of disease-related concepts in the correct way when making predictions. We anticipate that this work can not only increase confidence of medical practitioners on CAD but also serve as a stepping stone for further development of CAV-based neural network interpretation methods.Comment: Accepted for the IEEE International Joint Conference on Neural Networks (IJCNN) 202

Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation

Substructure Discovery Using Minimum Description Length and Background Knowledge

The ability to identify interesting and repetitive substructures is an essential component to discovering knowledge in structural data. We describe a new version of our SUBDUE substructure discovery system based on the minimum description length principle. The SUBDUE system discovers substructures that compress the original data and represent structural concepts in the data. By replacing previously-discovered substructures in the data, multiple passes of SUBDUE produce a hierarchical description of the structural regularities in the data. SUBDUE uses a computationally-bounded inexact graph match that identifies similar, but not identical, instances of a substructure and finds an approximate measure of closeness of two substructures when under computational constraints. In addition to the minimum description length principle, other background knowledge can be used by SUBDUE to guide the search towards more appropriate substructures. Experiments in a variety of domains demonstrate SUBDUE's ability to find substructures capable of compressing the original data and to discover structural concepts important to the domain. Description of Online Appendix: This is a compressed tar file containing the SUBDUE discovery system, written in C. The program accepts as input databases represented in graph form, and will output discovered substructures with their corresponding value.Comment: See http://www.jair.org/ for an online appendix and other files accompanying this articl

Framework for Product Lifecycle Management integration in Small and Medium Enterprises networks

In order to improve the performance of extended enterprises, Small and Medium Enterprises (SMEs) must be integrated into the extended networks. This integration must be carried out on several levels which are mastered by the Product Lifecycle Management (PLM). But, PLM is underdeveloped in SMEs mainly because of the difficulties in implementing information systems. This paper aims to propose a modeling framework to facilitate the implementation of PLM systems in SMEs. Our approach proposes a generic model for the creation of processes and data models. These models are explained, based on the scope and framework of the modeling, in order to highlight the improvements provided

Teaching Construction in the Virtual University: the WINDS project

This paper introduces some of the Information Technology solutions adopted in Web based INtelligent Design Support (WINDS) to support education in A/E/C design. The WINDS project WINDS is an EC-funded project in the 5th Framework, Information Society Technologies programme, Flexible University key action. WINDS is divided into two actions: ·The research technology action is going to implement a learning environment integrating an intelligent tutoring system, a computer instruction management system and a set of co-operative supporting tools. ·The development action is going to build a large knowledge base supporting Architecture and Civil Engineering Design Courses and to experiment a comprehensive Virtual School of Architecture and Engineering Design. During the third year of the project, more than 400 students all over Europe will attend the Virtual School. During the next three years the WINDS project will span a total effort of about 150 man-years from 28 partners of 10 European countries. The missions of the WINDS project are: Advanced Methodologies in Design Education. WINDS drives a breakdown with conventional models in design education, i.e. classroom or distance education. WINDS implements a problem oriented knowledge transfer methodology following Roger Schank's Goal Based Scenario (GBS) pedagogical methodology. GBS encourages the learning of both skills and cases, and fosters creative problem solving. Multidisciplinary Design Education. Design requires creative synthesis and open-end problem definition at the intersection of several disciplines. WINDS experiments a valuable integration of multidisciplinary design knowledge and expertise to produce a high level standard of education. Innovative Representation, Delivery and Access to Construction Education. WINDS delivers individual education customisation by allowing the learner access through the Internet to a wide range of on-line courses and structured learning objects by means of personally tailored learning strategies. WINDS promotes the 3W paradigm: learn What you need, Where you want, When you require. Construction Practice. Construction industry is a repository of ""best practices"" and knowledge that the WINDS will profit. WINDS system benefits the ISO10303 and IFC standards to acquire knowledge of the construction process directly in digital format. On the other hand, WINDS reengineers the knowledge in up-to-date courses, educational services, which the industries can use to provide just-in-time rather than in-advance learning. WINDS IT Solutions The missions of the WINDS project state many challenging requirements both in knowledge and system architecture. Many of the solutions adopted in these fields are innovative; others are evolution of existing technologies. This paper focuses on the integration of this set of state-of-the-art technologies in an advanced and functionally sound Computer Aided Instruction system for A/E/C Design. In particular the paper deals with the following aspects: Standard Learning Technology Architecture The WINDS system relies on the in progress IEEE 1484.1 Learning Technology Standard Architecture. According to this standard the system consists of two data stores, the Knowledge Library and the Record Database, and four process: System Coach, Delivery, Evaluation and the Learner. WINDS implements the Knowledge Library into a three-tier architecture: 1.Learning Objects: ·Learning Units are collections of text and multimedia data. ·Models are represented in either IFC or STEP formats. ·Cases are sets of Learning Units and Models. Cases are noteworthy stories, which describes solutions, integrate technical detail, contain relevant design failures etc. 2.Indexes refer to the process in which the identification of relevant topics in design cases and learning units takes place. Indexing process creates structures of Learning Objects for course management, profile planning procedures and reasoning processes. 3.Courses are taxonomies of either Learning Units or a design task and Course Units. Knowledge Representation WINDS demonstrates that it is possible and valuable to integrate a widespread design expertise so that it can be effectively used to produce a high level standard of education. To this aim WINDS gathers area knowledge, design skills and expertise under the umbrellas of common knowledge representation structures and unambiguous semantics. Cases are one of the most valuable means for the representation of design expertise. A Case is a set of Learning Units and Product Models. Cases are noteworthy stories, which describe solutions, integrate technical details, contain relevant design failures, etc. Knowledge Integration Indexes are a medium among different kind of knowledge: they implement networks for navigation and access to disparate documents: HTML, video, images, CAD and product models (STEP or IFC). Concept indexes link learning topics to learning objects and group them into competencies. Index relationships are the base of the WINDS reasoning processes, and provide the foundation for system coaching functions, which proactively suggest strategies, solutions, examples and avoids students' design deadlock. Knowledge Distribution To support the data stores and the process among the partners in 10 countries efficiently, WINDS implements an object oriented client/server as COM objects. Behind the DCOM components there is the Dynamic Kernel, which dynamically embodies and maintains data stores and process. Components of the Knowledge Library can reside on several servers across the Internet. This provides for distributed transactions, e.g. a change in one Learning Object affects the Knowledge Library spread across several servers in different countries. Learning objects implemented as COM objects can wrap ownership data. Clear and univocal definition of ownerships rights enables Universities, in collaboration with telecommunication and publisher companies, to act as "education brokers". Brokerage in education and training is an innovative paradigm to provide just-in-time and personally customised value added learning knowledg

A unified approach for composite cost reporting and prediction in the ACT program

The Structures Technology Program Office (STPO) at NASA Langley Research Center has held two workshops with representatives from the commercial airframe companies to establish a plan for development of a standard cost reporting format and a cost prediction tool for conceptual and preliminary designers. This paper reviews the findings of the workshop representatives with a plan for implementation of their recommendations. The recommendations of the cost tracking and reporting committee will be implemented by reinstituting the collection of composite part fabrication data in a format similar to the DoD/NASA Structural Composites Fabrication Guide. The process of data collection will be automated by taking advantage of current technology with user friendly computer interfaces and electronic data transmission. Development of a conceptual and preliminary designers' cost prediction model will be initiated. The model will provide a technically sound method for evaluating the relative cost of different composite structural designs, fabrication processes, and assembly methods that can be compared to equivalent metallic parts or assemblies. The feasibility of developing cost prediction software in a modular form for interfacing with state of the art preliminary design tools and computer aided design (CAD) programs is assessed

NASA space station automation: AI-based technology review. Executive summary

Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics