741,221 research outputs found
Knowledge-based design support and inductive learning
Designing and learning are closely related activities in that design as an ill-structure problem
involves identifying the problem of the design as well as finding its solutions. A
knowledge-based design support system should support learning by capturing and reusing
design knowledge. This thesis addresses two fundamental problems in computational
support to design activities: the development of an intelligent design support system
architecture and the integration of inductive learning techniques in this architecture.This research is motivated by the belief that (1) the early stage of the design process can
be modelled as an incremental learning process in which the structure of a design problem
or the product data model of an artefact is developed using inductive learning techniques,
and (2) the capability of a knowledge-based design support system can be enhanced by
accumulating and storing reusable design product and process information.In order to incorporate inductive learning techniques into a knowledge-based design
model and an integrated knowledge-based design support system architecture, the
computational techniques for developing a knowledge-based design support system
architecture and the role of inductive learning in Al-based design are investigated. This
investigation gives a background to the development of an incremental learning model for
design suitable for a class of design tasks whose structures are not well known initially.This incremental learning model for design is used as a basis to develop a knowledge-based
design support system architecture that can be used as a kernel for knowledge-based
design applications. This architecture integrates a number of computational techniques to
support the representation and reasoning of design knowledge. In particular, it integrates a
blackboard control system with an assumption-based truth maintenance system in an
object-oriented environment to support the exploration of multiple design solutions by
supporting the exploration and management of design contexts.As an integral part of this knowledge-based design support architecture, a design
concept learning system utilising a number of unsupervised inductive learning techniques is
developed. This design concept learning system combines concept formation techniques
with design heuristics as background knowledge to build a design concept tree from raw
data or past design examples. The design concept tree is used as a conceptual structure for
the exploration of new designs.The effectiveness of this knowledge-based design support architecture and the design
concept learning system is demonstrated through a realistic design domain, the design of
small-molecule drugs one of the key tasks of which is to identify a pharmacophore
description (the structure of a design problem) from known molecule examples.In this thesis, knowledge-based design and inductive learning techniques are first
reviewed. Based on this review, an incremental learning model and an integrated
architecture for intelligent design support are presented. The implementation of this
architecture and a design concept learning system is then described. The application of the
architecture and the design concept learning system in the domain of small-molecule drug
design is then discussed. The evaluation of the architecture and the design concept learning
system within and beyond this particular domain, and future research directions are finally
discussed
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A comparative survey of integrated learning systems
This paper presents the duction framework for unifying the three basic forms of inference - deduction, abduction, and induction - by specifying the possible relationships and influences among them in the context of integrated learning. Special assumptive forms of inference are defined that extend the use of these inference methods, and the properties of these forms are explored. A comparison to a related inference-based learning frame work is made. Finally several existing integrated learning programs are examined in the perspective of the duction framework
Creating Intelligent Linking for Information Threading in Knowledge Networks
Informledge System (ILS) is a knowledge network with autonomous nodes and
intelligent links that integrate and structure the pieces of knowledge. In this
paper, we aim to put forward the link dynamics involved in intelligent
processing of information in ILS. There has been advancement in knowledge
management field which involve managing information in databases from a single
domain. ILS works with information from multiple domains stored in distributed
way in the autonomous nodes termed as Knowledge Network Node (KNN). Along with
the concept under consideration, KNNs store the processed information linking
concepts and processors leading to the appropriate processing of information.Comment: 5 Pages, 6 Figures, 2 Tables, India Conference (INDICON), 201
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The effect of multiple knowledge sources on learning and teaching
Current paradigms for machine-based learning and teaching tend to perform their task in isolation from a rich context of existing knowledge. In contrast, the research project presented here takes the view that bringing multiple sources of knowledge to bear is of central importance to learning in complex domains. As a consequence teaching must both take advantage of and beware of interactions between new and existing knowledge. The central process which connects learning to its context is reasoning by analogy, a primary concern of this research. In teaching, the connection is provided by the explicit use of a learning model to reason about the choice of teaching actions. In this learning paradigm, new concepts are incrementally refined and integrated into a body of expertise, rather than being evaluated against a static notion of correctness. The domain chosen for this experimentation is that of learning to solve "algebra story problems." A model of acquiring problem solving skills in this domain is described, including: representational structures for background knowledge, a problem solving architecture, learning mechanisms, and the role of analogies in applying existing problem solving abilities to novel problems. Examples of learning are given for representative instances of algebra story problems. After relating our views to the psychological literature, we outline the design of a teaching system. Finally, we insist on the interdependence of learning and teaching and on the synergistic effects of conducting both research efforts in parallel
Consumers’ Demand for Pork Quality: Applying Semantic Network Analysis, May 2006
Abstract Consideration of consumers’ demand for food quality entails several aspects. Quality itself is a complex and dynamic concept, and constantly evolving technical progress may cause changes in consumers’ judgment of quality. To improve our understanding of the factors influencing the demand for quality, food quality must be defined and measured from the consumer’s perspective (Cardello, 1995). The present analysis addresses the issue of food quality, focusing on pork—the food that respondents were concerned about. To gain insight into consumers’ demand, we analyzed their perception and evaluation and focused on their cognitive structures concerning pork quality. In order to more fully account for consumers’ concerns about the origin of pork, in 2004 we conducted a consumer survey of private households. The qualitative approach of concept mapping was used to uncover the cognitive structures. Network analysis was applied to interpret the results. In order to make recommendations to enterprises, we needed to know what kind of demand emerges from the given food quality schema. By establishing the importance and relative positions of the attributes, we find that the country of origin and butcher may be the two factors that have the biggest influence on consumers’ decisions about the purchase of pork
FIRI - a Far-Infrared Interferometer
Half of the energy ever emitted by stars and accreting objects comes to us in
the FIR waveband and has yet to be properly explored. We propose a powerful
Far-InfraRed Interferometer mission, FIRI, to carry out high-resolution imaging
spectroscopy in the FIR. This key observational capability is essential to
reveal how gas and dust evolve into stars and planets, how the first luminous
objects in the Universe ignited, how galaxies formed, and when super-massive
black holes grew. FIRI will disentangle the cosmic histories of star formation
and accretion onto black holes and will trace the assembly and evolution of
quiescent galaxies like our Milky Way. Perhaps most importantly, FIRI will
observe all stages of planetary system formation and recognise Earth-like
planets that may harbour life, via its ability to image the dust structures in
planetary systems. It will thus address directly questions fundamental to our
understanding of how the Universe has developed and evolved - the very
questions posed by ESA's Cosmic Vision.Comment: Proposal developed by a large team of astronomers from Europe, USA
and Canada and submitted to the European Space Agency as part of "Cosmic
Vision 2015-2025
A graph theoretical analysis of certain aspects of Bahasa Indonesia
In this paper the theory of knowledge graphs is applied to some characteristic features of the Indonesian language. The characteristic features to be considered are active and passive form of verbs and the derived noun
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