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113th Annual ASEE Conference and Exposition, 2006

作者： Eschenbach, Elizabeth Johnson, James H. Brus, Chris Carlson, Patricia Giammar, Dan Grauer, Bette Hotaling, Liesl Oguntimein, Gbekeloluwa Safferman, Steven Wentling, Tim Humboldt State University United States Department of Environmental Resources Engineering Humboldt State University United States Howard University United States Department of Environmental Engineering College of Engineering Architecture and Computer Sciences Howard University United States Board of Scientific Counselors Executive Committee U.S. Environmental Protection Agency Office of Research and Development United States EPA's Science Advisory Board Department of Energy-sponsored HBCU/MI Environmental Technology Consortium Board Environmental Studies and Toxicology and the Engineering Council of the American Society for Engineering Education United States University of Iowa United States Program University of Iowa United States Rose-Hulman Institute of Technology United States Department of Rhetoric Rose-Hulman Institute ot Technology U.S. Air Forcer United States Army's Aberdeen Proving Ground NASA's Classroom of the Future Wheeling WV United States Washington University United States Department of Civil Engineering Washington University St. Louis United States Environmental Engineering Science Program Center for Materials Innovation United States McPherson High School United States McPherson High School McPherson KS United States Stevens Institute of Technology United States Stevens Institute of Technology United States Morgan State University United States Michigan State University United States Biosystems and Agricultural Engineering Department Michigan State University United States University of Dayton United States U.S. EPA Office of Research and Development United States National Center for Supercomputing Applications United States Department of Information Science Graduate School of Library and Information Science National Center for Supercomputing Applications University of Illinois United States

The Collaborative Large-scale Engineering Analysis Network for Environmental Research (CLEANER) Project Office has been established with funding from the National science Foundation (NSF) to the University of Illinois Urbana-Champaign (UIUC) and a coalition of 11 other institutions. The project office is coordinating the creation of a strategic plan consisting of research, cyberinfrastructure, and education plans that set forth a roadmap for the collaborative engineering analysis network for the study of environmental problems. This report will be completed by July 2007 and requires input from K-12 educators, administrators and other stakeholders in K-12 education. This paper describes the CLEANER project, provides an example of the CLEANER Education Committee's vision for the K-12 area and lists contacts for further information. The intention of this paper is to elicit input from the K-12 engineering education community, including K-12 educators, on how the CLEANER Education Plan could better meet the future needs of K-12 students and educators © American Society for Engineering Education, 2006.

关键词： Engineering education

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Examining design threads: Issues in Web design across student populations

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Proceedings of the Association for Information science and technology 2006年第1期42卷

作者： Joette Stefl-Mabry Allison Druin Dania Bilal Michael Radlick Thomas Mackey Carol Doll Diane Nahl Department of Information Studies of the College of Computing and Information and School of Education University at Albany State University of New York University of Maryland College of Information Studies and Institute for Advanced Computer Studies School of Information Sciences The University of Tennessee 1345 Circle Park Knoxville TN 37996 The Not for Profit Institute for Research on Learning Technology Visions Department of Information Studies of the College of Computing and Information University at Albany State University of New York Department of Information and Computer Sciences Library and Information Science Program University of Hawai'I at Manoa

This session relates directly to this year's conference theme Sparking Synergies: Bringing Research and Practice Together as it brings together researchers from different disciplines (information science and educational technology) to discuss current issues and trends related to Web usage across student populations. “Complex design problems require more knowledge than any single person possesses” (Arias, Eden, Fischer, Gorman, and Scharff, 2000, p. 84), thus each panelist will contribute highlights of his or her current research regarding the design, information, and pedagogical, needs of specific student populations (K-12 to higher education). After the panelists have presented their findings Diane Nahl will intertwine the threads of the panelists' conversations and, with the audience's assistance, begin to weave a fabric to uncover common usability issues.

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A segmentation method using compound Markov random fields based on a general boundary model

A segmentation method using compound Markov random fields ba...

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IEEE International Conference on Image Processing

作者： Jue Wu A.C.S. Chung Bioengineering Program and Department of Computer Science School of Engineering Hong Kong University of Science and Technology Hong Kong China

Markov random field (MRF) theory has widely been applied to segmentation in noisy images. This paper proposes a new MRF method. First, it couples the original labeling MRF with a boundary MRF that can help improve the performance of segmentation. Second, the boundary model is general and does not need prior training. Third, unlike existing related work, our model offers more compact interaction between the two MRFs. Experiments on synthetic images and real clinical datasets show that the proposed approach is able to produce good segmentation results, especially removing noise in low signal-to-noise ratio regions.

关键词： Markov random fields Image segmentation Labeling Signal to noise ratio Image restoration Lattices Biomedical engineering computer science Image analysis Surface reconstruction

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Metabolic visualization and intelligent shape analysis of the hippocampus

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International Conference on Computational Intelligence and Security, CIS 2005

作者： Choi, Yoo-Joo Kim, Jeong-Sik Kim, Min-Jeong Choi, Soo-Mi Kim, Myoung-Hee Institute for Graphic Interfaces Ewha-SK Telecom Building 11-1 Daehyun-Dong Seodaemun-Ku Seoul Korea Republic of Department of Computer Science and Engineering Ewha Womans University Daehyun-Dong Seodaemun-Ku Seoul Korea Republic of Center for Computer Graphics and Virtual Reality Ewha Womans University Daehyun-Dong Seodaemun-Ku Seoul Korea Republic of School of Computer Engineering Sejong University Seoul Korea Republic of Department of Computer Application Technology Seoul University of Venture and Information Seoul Korea Republic of

ISBN: (纸本)3540308199

This paper suggests a prototype system for visualization and analysis of anatomic shape and functional features of the hippocampus. Based on the result of MR-SPECT multi-modality image registration, anatomical and functional features of hippocampus are extracted from MR and registered SPECT images, respectively. The hippocampus is visualized in 3D by applying volume rendering to hippocampus volume data extracted from the MR image with color coded by registered SPECT image. In order to offer the objective and quantitative data concerning to the anatomic shape and functional features of the hippocampus, the geometric volume and the SPECT intensity histogram of hippocampus regions are automatically measured based on the MR and the registered SPECT image, respectively. We also propose a new method for the analysis of hippocampal shape using an integrated Octree-based representation, consisting of meshes, voxels, and skeletons. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Image analysis

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Elementary science classroom learning with wireless response devices implementing active and experiential learning

Elementary science classroom learning with wireless response...

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IEEE International Workshop on Wireless, mobile and Ubiquitous technology in Education (WMUTE)

作者： Yu-Fen Chen Chen-Chung Liu Ming-Hung Yu Sung-Bin Chang Yun-Chen Lu Tak-Wai Chan Department of Computer Science Information Engineering National Central University Taiwan Graduate Institute of Network Learning Technology National Central University Taiwan Degree Program of E-Learning College of Science National Chiao Tung University Taiwan Chu-Wei Elementary School Taiwan

Active learning enables learners to actively engage in learning. Learning not only transfers material to students for learning, but also encourages greater mental engagement and more extensive student-student and student-instructor interaction than does a typical lecture class. Peer instruction (PI) engages students in active learning by achieving continuous instructor-student interaction in a physics lecture. However, the methodologies and the effectiveness of implementing PI for elementary school students have seldom been clarified. This study explores the possibility of adopting PI in an elementary science classroom. The research considerations of the study are as follows: (1) how wireless technology can enhance PI in elementary science classroom; (2) how a teacher can engage students in pre-class reading, and (3) whether elementary school students have sufficient social skills to perform a PI discussion? These questions are examined by observing how the PI pedagogical model worked with a wireless response system in elementary science classroom. Based on the observation, this study also proposes a way of improving the PI learning experience of elementary school students by adding experiments and observations during peer discussion to explain concepts and phenomena in physics.

关键词： Educational institutions Physics Chemical elements computer science Materials science and technology Electronic learning Probes Astrochemistry Physiology Astronomy

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Journal of Information science and Engineering: Editorial notice

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Journal of Information science and Engineering 2005年第5期21卷 i-ii页

作者： Lee, Der-Tsai Amato, Nancy M. Chang, Shih-Fu Chen, Homer H. Chen, Tsuhan Hsu, Tsan-Sheng Hwang, Jenq-Neng Kuo, Sy-Yen Kuo, Tei-Wei Li, Chung-Sheng Tokuyama, Takeshi Wing, Jeannette Wu, Tzong-Chen Yen, John Computer Science at Texas A and M University United States Parasol Laboratory United States IEEE Transactions on Parallel and Distributed Systems Computing Research Association's Committee on the Status of Women in Computing Research CRA-W's Distributed Mentor Program United States Department of Electrical Engineering Columbia University United States Lab. United States College of Electrical Engineering and Computer Science National Taiwan University Taiwan IEEE Transactions on Circuits and Systems for Video Technology IEEE Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States ACM ACM SIGACT IEEE Computer Society IICM Austria Research and Development of the Department Multimedia Signal Processing Technical Committee IEEE Signal Processing Society United States IEEE Transactions on Circuits and systems for Video Technology College of Electrical Engineering and Computer Science National Taiwan Ocean University Keelung Taiwan Department of Electrical Engineering National Taiwan University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan IEEE Technical Committee on Real-Time Systems Computer Science Division IBM T.J. Watson Research Center United States IBM Research Division Graduate School of Information Sciences Tohoku University Japan ACM IPSJ Mathematical Society of Japan Japan Department of Computer Science Computer Science Department Carnegie Mellon University United States National Academies of Science's Computer Science and Telecommunications Board United States Microsoft's Trustworthy Academic Advisory Board Intel Research Pittsburgh's Advisory Board United States Dartmouth's Institute for Security Technology Studies Advisory Committee Canada Sloan Research Fellowships Program Committee United States ACM Taiwan China Information Sciences and Technology Pennsylvania State University United States Laboratory for Intelligent Agents Penn State's School of Info

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System dynamics of supply chain network organization structure

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Information Systems and e-Business Management 2004年第2期2卷 187-206页

作者： Zhang, Yong Dilts, David Management of Technology Program Vanderbilt University Electrical Engineering & Computer Science Department School of Engineering Nashville USA Owen Graduate School of Management Vanderbilt University Nashville USA

Information technology is providing manufacturers with additional flexibility with regard to their supply chain network choices. Our research studies supply chain network organization structures categorized by the organic and mechanistic management control structures. The structural impacts on cost and fill rate performance are studied in two-echelon and two-supply-chain network organization models under different market coordination conditions using system dynamic simulations. Our results show significant effects of demand and network structural factors, and their interactions, on these measures. As demand becomes dynamic, the cooperative interaction model, where supply chains cooperate to satisfy customer demand, is found to have better system performance than the competitive supply chain model. The analysis also suggests that increasing the responsiveness at the downstream plant is particularly important to the overall system performance improvement.

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Multiresolution image registration based on kullback-leibler distance

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7th International Conference on Medical Imaging and computer Assisted Intervention, MICCAI 2004

作者： Gan, Rui Wu, Jue Chung, Albert C.S. Yu, Simon C.H. Wells, William M. Department of Computer Science Hong Kong University of Science and Technology Hong Kong Bioengineering Program School of Engineering Hong Kong University of Science and Technology Hong Kong Dept of Diagnostic Radiology and Organ Imaging Prince of Wales Hospital Hong Kong Brigham and Women’s Hospital Harvard Medical School BostonMA United States MIT CSAI Laboratory CambridgeMA United States

ISBN: (纸本)3540229760

This paper extends our prior work on multi-modal image registration based on the a priori knowledge of the joint intensity distribution that we expect to obtain, and Kullback-Leibler distance. This expected joint distribution can be estimated from pre-aligned training images. Experimental results show that, as compared with the Mutual Information and Approximate Maximum Likelihood based registration methods, the new method has longer capture range at different image resolutions, which can lead to a more robust image registration method. Moreover, with a simple interpolation algorithm based on non-grid point random sampling, the proposed method can avoid interpolation artifacts at the low resolution registration. Finally, it is experimentally demonstrated that our method is applicable to a variety of imaging modalities. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Image resolution

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Multiresolution image registration based on Kullback-Leibler distance

Multiresolution image registration based on Kullback-Leibler...

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Medical Image Computing and computer-Assisted Intervention, MICCAI 2004 - 7th International Conference, Proceedings

作者： Gan, Rui Wu, Jue Chung, Albert C.S. Yu, Simon C.H. Wells III, William M. Department of Computer Science Hong Kong University of Science and Technology Hong Kong Hong Kong Bioengineering Program School of Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong Dept. of Diagnostic Radiology and Organ Imaging Prince of Wales Hospital Hong Kong Hong Kong Brigham and Women's Hospital Harvard Medical School Boston MA United States MIT CSAI Laboratory Cambridge MA United States

关键词： Medical imaging

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Generalized Associative Memory Models: Their Memory Capacities and Potential application

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Journal of Advanced Computational Intelligence and Intelligent Informatics 2004年第1期8卷 56-64页

作者： Yap, Tfcddy N. Azcarraga, Arnulfo E. Software Technology Department College of Computer Studies De La Salle University Professional Schools Inc. 2401 Taft Avenue Manila1004 Philippines Program for Research into Intelligent Systems School of Computing Department of Computer Science 3 Science Drive 2 Singapore117543 Singapore De La Salle University Canlubang Laguna Philippines

The Hopfield and bi-directional associative memory (TJAM) models are well developed and carefully studied models tor associative memory that are patterned after the memory structure of the animal brain. Their basic limitation is that they can only perform associations between at most two sets of patterns. Several different models for generalized associative memory are proposed. These models are all extensions or generalizations of the Hopfield and RAM models that can perform multiple associations. Extensive software simulations are conducted to evaluate the different models, using the memory capacity as basis tor comparing their performance. Lastly, potential application of these models as data fusion systems is explored. © 2004 Fuji technology Press. All rights reserved.

关键词： Data fusion

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