658 research outputs found
Deriving design and innovation strategies from cultural heritages for design research, practice and education
Culture can be reflected in design with different symbolisms and representations, and it is one of the main sources for innovations in product design. In the countries or regions where culture resources and intangible heritages are rich, it is often necessary to identify strategies or develop methodologies for the preservation of such resources, and to translate, transform and transcend their values in a sustainable way that is consistent with the time in the evolving context of economic developments of our time. This paper presents a case study on culture based innovation in product design, based on an exhibition and the analysis of the folk art, handicrafts, and intangible culture heritages from Shaanxi province involving a group of local prominent artists. The motivation of this case study is to find out the strength of creative culture industries in western China, and to develop a framework supporting culture based product innovation, through which the knowledge of local artists or craftsmen/women can be integrated to form a collaborative design force. The results of this case study provides strategies and insights on how to build design tools and systems for supporting the emerging creative industry western China. Keywords: Culture heritage, design innovation, crafts, paper cuts, sculpture
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
Effects of behavioral response and vaccination policy on epidemic spreading - an approach based on evolutionary-game dynamics
date of Acceptance: 23/06/2014 This work was supported by the National Natural Science Foundation of China (Grant Nos. 11331009, 11135001, 11105025). Y.-C.L. was supported by AFOSR under Grant No. FA9550-10-1-0083.Peer reviewedPublisher PD
DETC2006-99149 AN AGENT-BASED APPROACH TO COLLABORATIVE PRODUCT DESIGN
ABSTRACT The growth of computer science and technology has brought new opportunities for multidisciplinary designers and engineers to collaborate with each other in a concurrent and coordinated manner. The development of computational agents with unified data structures and software protocols can contribute to the establishment of a new way of working in collaborative design, which is increasingly becoming an international practice. In this paper, we first propose a computational model of collaborative product design management aiming to improve the efficiency and effectiveness of the cooperation and coordination among participating disciplines. Then, we present a new framework of collaborative design which adopts an agent-based approach and relocates designers, managers, systems, and supporting agents in a unified knowledge representation scheme for product design. An agent-based system is now being implemented and the design of a set of dinning table and chairs is chosen to demonstrate how the system can help designers in the management and coordination of the collaborative product design process. INTORDUCTION Increasing product complexity, explosive global competition, and rapidly changing customer's demands are forcing product manufacturers to improve the efficiency of design decision-making and shrink design cycle times. Advances in the computer science and technology have opened new opportunities for multidisciplinary designers and engineers to collaborative with each other more efficiently and effectively. Collaborative design can create added value in the design and production process by bringing the benefit of team work and cooperation in a concurrent and coordinated manner. Also, it help reduce the loss of efficiency resulted from potential conflicts and misunderstandings among team members. However, the difficulties arising from the requirements for design coordination mixed with differences among heterogeneous system architectures and information structures tend to undermine the effectiveness and the success of collaborative design among multidisciplinary designers. Recently, agent technology has been recognized by more and more researchers as a promising approach to analyzing, designing, and implementing industrial distributed systems. An intelligent agent consists of self-contained knowledge-based systems capable of perceiving, reasoning, adapting, learning, cooperating, and delegating in a dynamic environment to tackle specialist problems. The way in which intelligent software agents residing in a multi-agent system interact and cooperate with one another to achieve a common goal is similar to the way that human designers collaborate with each other to carry out a product design project. Thus, we believe that a collaborative product design environment implemented by taking an agentbased approach will be capable of assisting human designers or design teams effectively and efficiently in collaborative product design. In this paper, based on the analysis of the characteristics of a collaborative design process, we first propose a computational model of collaborative product design management to improve
Comparing One with Many -- Solving Binary2source Function Matching Under Function Inlining
Binary2source function matching is a fundamental task for many security
applications, including Software Component Analysis (SCA). The "1-to-1"
mechanism has been applied in existing binary2source matching works, in which
one binary function is matched against one source function. However, we
discovered that such mapping could be "1-to-n" (one query binary function maps
multiple source functions), due to the existence of function inlining.
To help conduct binary2source function matching under function inlining, we
propose a method named O2NMatcher to generate Source Function Sets (SFSs) as
the matching target for binary functions with inlining. We first propose a
model named ECOCCJ48 for inlined call site prediction. To train this model, we
leverage the compilable OSS to generate a dataset with labeled call sites
(inlined or not), extract several features from the call sites, and design a
compiler-opt-based multi-label classifier by inspecting the inlining
correlations between different compilations. Then, we use this model to predict
the labels of call sites in the uncompilable OSS projects without compilation
and obtain the labeled function call graphs of these projects. Next, we regard
the construction of SFSs as a sub-tree generation problem and design root node
selection and edge extension rules to construct SFSs automatically. Finally,
these SFSs will be added to the corpus of source functions and compared with
binary functions with inlining. We conduct several experiments to evaluate the
effectiveness of O2NMatcher and results show our method increases the
performance of existing works by 6% and exceeds all the state-of-the-art works
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