CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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_id ecaade2015_237
id ecaade2015_237
authors Vrouwe, Ivo; Luyten, Laurens and Pak, Burak
year 2015
title Teaching and Learning CAAD and CAM in a Fluid Era - Tools and Strategies for the Analysis and Synthesis of Ill-Defined Construction Problems
source Martens, B, Wurzer, G, Grasl T, Lorenz, WE and Schaffranek, R (eds.), Real Time - Proceedings of the 33rd eCAADe Conference - Volume 2, Vienna University of Technology, Vienna, Austria, 16-18 September 2015, pp. 119-126
doi https://doi.org/10.52842/conf.ecaade.2015.2.119
wos WOS:000372316000015
summary In this paper we discuss a series of tools and strategies to support learner-centred construction education in the complexity of the era today (Bauman, 2000). By using these tools in the education of CAD and CAM in construction education at universities for the arts, design and architecture, we aim to support the student in the abstract aspects of Bloom's (1956) cognitive learning domain. In order to present a coherent spectrum of educational tools and strategies, we start with the introduction of a tool for problem-analysis. The tool is explained by applying it to the context of spatial design construction, digital design and fabrication. Then we shortly discuss the process of design-evaluation. Next we introduce three models for design-synthesis. Afterwards, a test case is used to elaborate on the different tools and strategies which are tested and evaluated.
series eCAADe
email
more https://mh-engage.ltcc.tuwien.ac.at/engage/ui/watch.html?id=d75a9f02-6f80-11e5-bc83-9bf4aa35f970
last changed 2022/06/07 07:58

_id 2720
authors Magyar, Peter and Temkin, Aron
year 2000
title Developing an Algorithm for Topological Transformation
source SIGraDi’2000 - Construindo (n)o espacio digital (constructing the digital Space) [4th SIGRADI Conference Proceedings / ISBN 85-88027-02-X] Rio de Janeiro (Brazil) 25-28 september 2000, pp. 203-205
summary This research intends to test the architectural application of Jean Piaget’s clinical observations, described in the book: The Child’s Conception of Space (Piaget, 1956), according to which topology is an ordering discipline, active in the human psyche. Earlier attempts, based on the principles of graph-theory, were able to cover only a narrow aspect of spatial relations, i.e. connectivity, and were mostly a-perceptional, visually mute. The “Spaceprint” method, explained and illustrated in co-author’s book: Thought Palaces (Magyar, 1999), through dimensional reduction, investigates volumetric, 3D characteristics and relationships with planar 2D configurations. These configurations, however, represent dual values: they are simultaneously the formal descriptors of both finite matter and (fragments of) infinite space. The so- called “Particular Spaceprint”, as a tool of design development in building, object, or urban scales, with the help of digital technology, could express - again simultaneously - qualities of an idea-gram and the visual, even tactile aspects of material reality. With topological surface-transformations, the “General Spaceprints”, these abstract yet visually active spatial formulas can be obtained.
series SIGRADI
email
last changed 2016/03/10 09:55

_id 435a
authors Mitchell, William J.
year 1990
title Afterword: The Design Studio of The Future
source The Electronic Design Studio: Architectural Knowledge and Media in the Computer Era [CAAD Futures ‘89 Conference Proceedings / ISBN 0-262-13254-0] Cambridge (Massachusetts / USA), 1989, pp. 479-494
summary Things began to change in the mid-1940s, though architects hardly noticed. Scientists and engineers started to speculate that the new electronic technologies which had emerged in the wartime years would profoundly change the character of intellectual work. Vannevar Bush (1945) imagined a device called the Memex, which would function as a personal information server. By the 1950s computers were becoming a commercial reality, and in 1956 Fortune magazine published a remarkably prescient depiction of a machine that we can now recognize as a computer-aided design workstation complete with graphic input devices and a multi-window display showing different views of a three-dimensional object. These wonderful machines were never built, much less put to any practical use, but they established a powerful idea.
series CAAD Futures
email
last changed 2003/05/16 20:58

_id acadia08_256
id acadia08_256
authors Ostwald, Michael J.; Josephine Vaughan; Stephan Chalup
year 2008
title A Computational Analysis of Fractal Dimensions in the Architecture of Eileen Gray
source Silicon + Skin: Biological Processes and Computation, [Proceedings of the 28th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) / ISBN 978-0-9789463-4-0] Minneapolis 16-19 October 2008, 256-263
doi https://doi.org/10.52842/conf.acadia.2008.256
summary This paper is the first investigation of the fractal dimensions of five of the house designs of Eileen Gray; a prominent architect working mainly in France between 1922 and 1956. In this paper, a computational variation of the “box-counting approach” (used to determine fractal dimension) is applied to a multi-dimensional review of the houses of Gray. As a contemporary of Le Corbusier, Gray is a significant architect for such an analysis. This research is important because it expands the set of examples of early Twentieth Century architects who have been analyzed using the method. This paper provides a computer-assisted mathematical analysis of characteristic visual complexity in five houses designs by Eileen Gray.
keywords Algorithm; Analysis; Computation; Design; Environment
series ACADIA
last changed 2022/06/07 08:00

_id 1bb0
authors Russell, S. and Norvig, P.
year 1995
title Artificial Intelligence: A Modern Approach
source Prentice Hall, Englewood Cliffs, NJ
summary Humankind has given itself the scientific name homo sapiens--man the wise--because our mental capacities are so important to our everyday lives and our sense of self. The field of artificial intelligence, or AI, attempts to understand intelligent entities. Thus, one reason to study it is to learn more about ourselves. But unlike philosophy and psychology, which are also concerned with AI strives to build intelligent entities as well as understand them. Another reason to study AI is that these constructed intelligent entities are interesting and useful in their own right. AI has produced many significant and impressive products even at this early stage in its development. Although no one can predict the future in detail, it is clear that computers with human-level intelligence (or better) would have a huge impact on our everyday lives and on the future course of civilization. AI addresses one of the ultimate puzzles. How is it possible for a slow, tiny brain{brain}, whether biological or electronic, to perceive, understand, predict, and manipulate a world far larger and more complicated than itself? How do we go about making something with those properties? These are hard questions, but unlike the search for faster-than-light travel or an antigravity device, the researcher in AI has solid evidence that the quest is possible. All the researcher has to do is look in the mirror to see an example of an intelligent system. AI is one of the newest disciplines. It was formally initiated in 1956, when the name was coined, although at that point work had been under way for about five years. Along with modern genetics, it is regularly cited as the ``field I would most like to be in'' by scientists in other disciplines. A student in physics might reasonably feel that all the good ideas have already been taken by Galileo, Newton, Einstein, and the rest, and that it takes many years of study before one can contribute new ideas. AI, on the other hand, still has openings for a full-time Einstein. The study of intelligence is also one of the oldest disciplines. For over 2000 years, philosophers have tried to understand how seeing, learning, remembering, and reasoning could, or should, be done. The advent of usable computers in the early 1950s turned the learned but armchair speculation concerning these mental faculties into a real experimental and theoretical discipline. Many felt that the new ``Electronic Super-Brains'' had unlimited potential for intelligence. ``Faster Than Einstein'' was a typical headline. But as well as providing a vehicle for creating artificially intelligent entities, the computer provides a tool for testing theories of intelligence, and many theories failed to withstand the test--a case of ``out of the armchair, into the fire.'' AI has turned out to be more difficult than many at first imagined, and modern ideas are much richer, more subtle, and more interesting as a result. AI currently encompasses a huge variety of subfields, from general-purpose areas such as perception and logical reasoning, to specific tasks such as playing chess, proving mathematical theorems, writing poetry{poetry}, and diagnosing diseases. Often, scientists in other fields move gradually into artificial intelligence, where they find the tools and vocabulary to systematize and automate the intellectual tasks on which they have been working all their lives. Similarly, workers in AI can choose to apply their methods to any area of human intellectual endeavor. In this sense, it is truly a universal field.
series other
last changed 2003/04/23 15:14

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