Journal articles on the topic 'Design knowledge'

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1

Cooper, Rachel. "Design Knowledge." Design Journal 4, no. 1 (March 2001): 1–2. http://dx.doi.org/10.2752/146069201789378478.

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2

Drucker, Johanna. "Knowledge Design." Design and Culture 6, no. 1 (March 2014): 65–83. http://dx.doi.org/10.2752/175470814x13823675225117.

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3

Linzner, Felix. "World. Knowledge. Design." Ethnologia Fennica 47, no. 1 (June 25, 2020): 111–14. http://dx.doi.org/10.23991/ef.v47i1.91710.

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4

Addis, T. R. "Knowledge for design." Knowledge Acquisition 2, no. 2 (June 1990): 95–105. http://dx.doi.org/10.1016/s1042-8143(05)80006-8.

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5

Hunter, Bruce. "Knowledge and Design." Philosophy and Phenomenological Research 59, no. 2 (June 1999): 309. http://dx.doi.org/10.2307/2653674.

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6

Logan, B. S. "Conceptualizing design knowledge." Design Studies 10, no. 3 (July 1989): 188–95. http://dx.doi.org/10.1016/0142-694x(89)90037-9.

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7

Manzini, Ezio. "New design knowledge." Design Studies 30, no. 1 (January 2009): 4–12. http://dx.doi.org/10.1016/j.destud.2008.10.001.

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8

Yang, Cheng, Zheng Liu, Haobai Wang, and Jiaoqi Shen. "Reusing design knowledge based on design cases and knowledge map." International Journal of Technology and Design Education 23, no. 4 (March 2, 2013): 1063–77. http://dx.doi.org/10.1007/s10798-013-9239-7.

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9

Nakakoji, Kumiyo, and Yasuhiro Yamamoto. "Knowledge Interaction Design for Creative Knowledge Work." Transactions of the Japanese Society for Artificial Intelligence 19 (2004): 154–65. http://dx.doi.org/10.1527/tjsai.19.154.

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10

Yinhua, Hai. "A Framework Design of Mongolian Idioms Knowledge Base." International Journal of Machine Learning and Computing 4, no. 5 (2014): 428–32. http://dx.doi.org/10.7763/ijmlc.2014.v4.449.

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11

Woo, Chi-Moon, Mi-Kyoung Kim, and Han-Jong Jun. "Design Knowledge Classification based BIM Design System Framework - Representation of Building Scale Estimation Design Knowledge -." Journal of the architectural institute of Korea planning & design 32, no. 7 (July 30, 2016): 21–28. http://dx.doi.org/10.5659/jaik_pd.2016.32.7.21.

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12

Marshall-Baker, Anna. "Knowledge in Interior Design." Journal of Interior Design 31, no. 1 (September 2005): xiii—xxi. http://dx.doi.org/10.1111/j.1939-1668.2006.tb00412.x.

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13

Coyne, R. D., and J. S. Gero. "Design knowledge and context." Environment and Planning B: Planning and Design 12, no. 4 (1985): 419–42. http://dx.doi.org/10.1068/b120419.

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14

Cennamo, Katherine S. "Design as Knowledge Construction." Computers in the Schools 20, no. 4 (December 2003): 13–35. http://dx.doi.org/10.1300/j025v20n04_03.

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15

Yoshikawa, Hiroyuki. "Systematization of Design Knowledge." CIRP Annals 42, no. 1 (1993): 131–34. http://dx.doi.org/10.1016/s0007-8506(07)62409-3.

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16

Haron, Haryani, Mohd Nazri Mustafa, M. Hamiz, and Nor Diana Ahmad. "Modeling Product Design Knowledge." Advanced Science Letters 21, no. 10 (October 1, 2015): 3132–36. http://dx.doi.org/10.1166/asl.2015.6453.

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17

Rutherford, James H., and Thomas W. Maver. "Knowledge-based design support." Automation in Construction 3, no. 2-3 (July 1994): 187–202. http://dx.doi.org/10.1016/0926-5805(94)90019-1.

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18

Akman, V., P. ten Hagen, J. Rogier, and P. Veerkamp. "Knowledge engineering in design." Computer-Aided Design 20, no. 7 (September 1988): 425. http://dx.doi.org/10.1016/0010-4485(88)90250-3.

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19

Kumar, B. "Knowledge-based design systems." Computing Systems in Engineering 2, no. 4 (January 1991): 425. http://dx.doi.org/10.1016/0956-0521(91)90009-t.

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20

Akman, Varol, Paul ten Hagen, Jan Rogier, and Paul Veerkamp. "Knowledge engineering in design." Knowledge-Based Systems 1, no. 2 (March 1988): 67–77. http://dx.doi.org/10.1016/0950-7051(88)90001-9.

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21

Heylighen, Ann, Francis Heylighen, Johan Bollen, and Mathias Casaer. "Distributed (design) knowledge exchange." AI & SOCIETY 22, no. 2 (July 4, 2007): 145–54. http://dx.doi.org/10.1007/s00146-007-0122-5.

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22

Clibbon, Kelvin, and Ernest Edmonds. "Representing strategic design knowledge." Engineering Applications of Artificial Intelligence 9, no. 4 (August 1996): 349–57. http://dx.doi.org/10.1016/0952-1976(96)00038-3.

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23

Joo, Jae-Woo, and Dong-Woo Oh. "User Research Method for Service Design: From Conceptual Knowledge To Design Knowledge." Journal of the Ergonomics Society of Korea 31, no. 1 (February 29, 2012): 15–21. http://dx.doi.org/10.5143/jesk.2012.31.1.15.

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24

Plappert, S., L. Hoppe, P. C. Gembarski, and R. Lachmayer. "APPLICATION OF KNOWLEDGE-BASED ENGINEERING FOR TEACHING DESIGN KNOWLEDGE TO DESIGN STUDENTS." Proceedings of the Design Society: DESIGN Conference 1 (May 2020): 1795–804. http://dx.doi.org/10.1017/dsd.2020.300.

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AbstractFor an optimal preparation of mechanical engineering students for their future work life, the use of problem-based methods in design teaching is investigated. Therefore an intelligent tutoring system for computer aided design education will be developed, which can automatically evaluate computer aided design models of design students. A knowledge-based engineering system will be used to assistance the design students in the execution of design tasks. Using a practice-oriented example, the application and the advantages for teaching will be verified and discussed.
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25

Gruber, Thomas R., and Paul R. Cohen. "Design for acquisition: principles of knowledge-system design to facilitate knowledge acquisition." International Journal of Man-Machine Studies 26, no. 2 (February 1987): 143–59. http://dx.doi.org/10.1016/s0020-7373(87)80088-3.

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26

Garcia, Ana Cristina Bicharra, and H. Craig Howard. "Acquiring design knowledge through design decision justification." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 6, no. 1 (February 1992): 59–71. http://dx.doi.org/10.1017/s0890060400002948.

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Currently design documentation rarely records the designer's decision process or the reasons behind those decisions. This paper describes an effort to improve design documentation by having the computer act as an intelligent apprentice to the designer to capture the rationale during the design process. The apprentice learns about the features that make a specific case different from the standard. Whenever the designer proposes a design action that differs from the apprentice's expectations, the interface will ask for the designer for justifications to explain the differences. Later queries for design rationale are answered using a combination of the apprentice's domain knowledge and the designer-supplied justifications. The apprentice model is being implemented in a prototype system called ADD (Augmenting Design Documentation). The initial focus of the work is on HVAC (Heating, Ventilation, and Air Conditioning) design. Our starting point for implementing the apprentice model is observing how people develop HVAC system designs and then explain those designs.
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27

SATO, Seiki, Satoshi SUZUKI, and Muneyoshi NUMADA. "3D Knowledge Design System in Product Design." Transactions of the Japan Society of Mechanical Engineers Series C 74, no. 745 (2008): 2107–13. http://dx.doi.org/10.1299/kikaic.74.2107.

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28

AOYAMA, Kazuhiro, and Tsuyoshi KOGA. "3318 Design Knowledge Template for Product Design." Proceedings of the JSME annual meeting 2008.4 (2008): 213–14. http://dx.doi.org/10.1299/jsmemecjo.2008.4.0_213.

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29

Zhang, Dong Min, Zi Chao Yin, and Yu Chun Xu. "Knowledge Tracing Modeling for Product Design Knowledge Management." Applied Mechanics and Materials 483 (December 2013): 506–9. http://dx.doi.org/10.4028/www.scientific.net/amm.483.506.

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Knowledge management in advanced manufacturing industries is a complex process. The paper analyzes knowledge application scenarios in product development processing. There are complex relationships between knowledge, product, process and designers, which four key elements are proposed for knowledge tracing modeling. Knowledge tracing modeling based four key elements for product design knowledge management is studied carefully. The research for knowledge tracing modeling will enable software function development.
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30

Benaroch, Michel. "Roles of design knowledge in knowledge-based systems." International Journal of Human-Computer Studies 44, no. 5 (May 1996): 689–721. http://dx.doi.org/10.1006/ijhc.1996.0029.

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31

Nworie, John, and Francis Dwyer. "Knowledge management & instructional design optimizing organizational knowledge." Performance Improvement 43, no. 7 (August 2004): 27–32. http://dx.doi.org/10.1002/pfi.4140430709.

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32

Oxman, Rivka. "Prior knowledge in design: a dynamic knowledge-based model of design and creativity." Design Studies 11, no. 1 (January 1990): 17–28. http://dx.doi.org/10.1016/0142-694x(90)90011-z.

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33

Walch, Michael, and Dimitris Karagiannis. "Design Thinking and Knowledge Engineering: A Machine Learning Case." International Journal of Machine Learning and Computing 10, no. 6 (December 2020): 765–70. http://dx.doi.org/10.18178/ijmlc.2020.10.6.1003.

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34

Kovalenko, O. E. "Knowledge based design of convergent systems of situational management." Mathematical machines and systems 3 (2019): 67–74. http://dx.doi.org/10.34121/1028-9763-2019-3-67-74.

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35

Kozhasova, N. L. "STUDENT TEACHER KNOWLEDGE AND ITS IMPACT ON TASK DESIGN." DULATY UNIVERSITY BULLETIN 2, no. 10 (June 20, 2023): 36–41. http://dx.doi.org/10.55956/vzhm3266.

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This study looked at how student teachers created and altered mathematical assignments using their pedagogical and subject-specific knowledge of mathematics. It also looked at the connection between instructor expertise and a task's cognitive requirements. The framework of Hill, Ball, and Schilling outlines many domains of knowledge in mathematics for instruction. The Stein, Smith, Henningsen, and Silver framework also characterizes the cognitive demands of mathematical tasks in research. Findings show that when student teachers lack the expertise in other areas, particularly subject matter expertise, required to accomplish specific educational tasks, they focus on knowledge of shared content. was shown. When the student's teacher changed the task, the cognitive demands of that task often decreased. These declines are often related to a lack of subject matter expertise.
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36

Zhang, Dong Min, Yan Yun Wu, and Ye Huang. "Design Knowledge Reuse Strategies for Complex Equipment Design." Applied Mechanics and Materials 190-191 (July 2012): 74–77. http://dx.doi.org/10.4028/www.scientific.net/amm.190-191.74.

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Series products and variant products are the basic strategy for enterprise product development. Product designers reuse the knowledge, experience in the various stages of product development. The design reuse strategies for mechanical products are studied. The concepts of product design reuse level and product design reuse dimensions are presented. The enabling techniques for design reuse are concluded, including CBR, KM/KBE, design reuse modeling. A case-based design tool and a design knowledge management tool are developed based on studying product design reuse strategies.
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37

Ko, Jae Sung. "Design Phenomenological Methodology - Tacit Knowledge and Design Paradigm -." JOURNAL OF THE KOREAN SOCIETY DESIGN CULTURE 28, no. 2 (June 30, 2022): 1–15. http://dx.doi.org/10.18208/ksdc.2022.28.2.1.

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38

Maher, Mary Lou, and Heng Li. "Automatically Learning Preliminary Design Knowledge from Design Examples." Computer-Aided Civil and Infrastructure Engineering 7, no. 1 (January 1992): 73–80. http://dx.doi.org/10.1111/j.1467-8667.1992.tb00418.x.

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39

Howard, H. Craig, Jenmu Wang, Francois Daube, and Taufiq Rafiq. "Applying design-dependent knowledge in structural engineering design." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 3, no. 2 (May 1989): 111–23. http://dx.doi.org/10.1017/s0890060400001141.

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Recent knowledge-based expert systems for structural engineering design have focused on design-independent knowledge (abstract reasoning rules for designing), and while great strides have been made in that area, there is still a significant need to develop systems to take advantage of the wealth of knowledge contained in every substantial structural design. On the other hand, previous database-oriented design efforts have focused primarily on knowledge-poor databases of solutions, in which the traditional engineering handbook of solutions has simply been replaced by digital data. The challenge is to find a way to capture and apply the kind of case-based, design-dependent knowledge that structural engineers have traditionally used. The long-term results will be better structural designs and better structural designers. This paper discusses the character of the design-dependent knowledge in a structural engineering context, describes two initial applications of case-based reasoning to component design, and presents a general paradigm for a knowledge-based design system integrating rule-based and case-based reasoning.
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40

Kremer, Gerald, Ina Peter, Berkay Bingoel, and Rainer Stark. "Better Design through Shared Knowledge via Design Heuristics." Procedia CIRP 119 (2023): 957–62. http://dx.doi.org/10.1016/j.procir.2023.03.140.

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41

Jerrard, Bob. "Design-Based Knowledge Transfer Partnerships." Design Journal 9, no. 3 (November 2006): 1–2. http://dx.doi.org/10.2752/146069206789331410.

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42

Bazylev, V. N., I. A. Kuperman, E. V. Chmykhova, and M. L. Aranovich. "Consolidated Knowledge Corpus: Design Technique." Alma mater. Vestnik Vysshey Shkoly, no. 12 (December 2021): 69–76. http://dx.doi.org/10.20339/am.12-21.069.

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The article presents the results of a pilot study for the structural transformation of 18 Bachelor’s Degree Programs for e-learning using Consolidated Knowledge Corpus. Consolidated Knowledge Corpus is a multidimensional object-oriented structure of educational content objects and their connections. All academic topics from 224 disciplines were combined into a Consolidated Knowledge Corpus to unify similarities and eliminate duplication. A unified matrix of educational content for the first year of study for 18 bachelor’s programs was compiled and an optimized modular structure of the curriculum was built. As a result, the necessary production volume of digital educational products and subsequently the necessary volume of investments were reduced by 55 percent.
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43

Gillam, April. "Vehicles knowledge-based design environment." Journal of Spacecraft and Rockets 30, no. 3 (May 1993): 342–47. http://dx.doi.org/10.2514/3.25521.

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44

Wood, Richard M., and Steven X. S. Bauer. "Discussion of Knowledge-Based Design." Journal of Aircraft 39, no. 6 (November 2002): 1053–60. http://dx.doi.org/10.2514/2.3034.

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45

Houe, Raymond, and Bernard Grabot. "Knowledge Modeling for Eco-design." Concurrent Engineering 15, no. 1 (March 2007): 7–20. http://dx.doi.org/10.1177/1063293x07076272.

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46

Mark, William. "Knowledge-Based User Interface Design." Human–Computer Interaction 1, no. 4 (December 1985): 339–57. http://dx.doi.org/10.1207/s15327051hci0104_3.

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47

Li, Q., and W. J. Zhang. "Computer comparison of design knowledge." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 212, no. 8 (August 1, 1998): 635–45. http://dx.doi.org/10.1243/0954405981515905.

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Automatic comparison of design knowledge generated and consumed during a design process is very useful. Basically, design knowledge can be classified into four categories: (a) artefact (product) structures, (b) artefact behaviours, (c) artefact functions and (d) causalities among structures, behaviours and functions. This paper proposes an intelligent hybrid graph approach to represent design knowledge associated with these categories. Comparison of design knowledge thus turns out to be the comparison of hybrid graphs. A general algorithm is developed for the graph comparison purpose. In this general algorithm, comparison of line graphs is an important task, which is realized by using the Hopfield—Tank neural network algorithm. An initial implementation of this algorithm proves to be promising.
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48

WU, HENG LI XINDONG. "LEARNING DESIGN KNOWLEDGE AS GENERALIZATION." Cybernetics and Systems 29, no. 2 (March 1998): 181–207. http://dx.doi.org/10.1080/019697298125786.

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49

Carlisle, Ysanne, and Alison Dean. "Design As Knowledge Integration Capability." Creativity and Innovation Management 8, no. 2 (June 1999): 112–21. http://dx.doi.org/10.1111/1467-8691.00125.

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50

Westphal, Christopher. "Knowledge engineering for software design." ACM SIGSOFT Software Engineering Notes 13, no. 1 (January 3, 1988): 57–58. http://dx.doi.org/10.1145/43857.43865.

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