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Inaugural IEEE-IES Digital EcoSystems and Technologies Conference, DEST

作者： Pathom Pumpuang Anongnart Srivihok Prasong Praneetpolgrang Somchai Numprasertchai Department of Computer Science Faculty of Science Kasetsart University Bangkok Thailand Master of Science Program in Information Technology Graduate School Sripatum University Bangkok Thailand Department of Computer Engineering Faculty of Engineer Kasetsart University Bangkok Thailand

ISBN: (纸本)9781424414895

The objective of this study is to propose a model for planning course registration by using a data mining technique: Bayesian network. The proposed model can be used to predict the sequences of courses to be registered by undergraduate students whose majors are computer science or engineering. The data set was obtained from student enrollments and include GPA and grades in each subject for first and second year students from a private university in Thailand. Evaluations show that the predictive power of this model is acceptable. The implications from this studypsilas findings suggest that the model can be applied for advising students in planning courses to be registered in each semester. Further, the model appears to be useful for improving curriculum development in order to fit both studentspsila and university requirements.

关键词： Bayesian methods Biological system modeling computers Education Computational modeling Brain modeling Brain models

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Recommending mobile content using content diffusion and user preference transition

Recommending mobile content using content diffusion and user...

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2008 International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government, EEE 2008

作者： Lee, Tong Queue Lee, Eunchang Park, Young Park, Yongtae Department of Mobile Internet Dongyang Technical College Seoul Korea Republic of Graduate Program in Technology and Management Seoul National University Seoul Korea Republic of Department of Computer Science and Information Systems Bradley University Peoria IL United States Department of Industrial Engineering Seoul National University Seoul Korea Republic of

ISBN: (纸本)1601320639

Recommendation accuracy is especially important in mobile e-commerce environments due to the limited screen size of mobile devices and relatively expensive connection costs. Mobile content tends to be fashionable and are geared for young users. This paper presents a novel method of building a more accurate recommender system for mobile content in a mobile ecommerce environment. The method is based on collaborative filtering, and models content diffusion and user preference transition and incorporates them in constructing pseudo ratings from implicit feedback data. In a variety of experiments, recommender systems based on the method showed significantly better recommendation accuracy than a pure collaborative filtering-based recommender system.

关键词： Collaborative filtering

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Discovering Flow Anomalies: A SWEET Approach

Discovering Flow Anomalies: A SWEET Approach

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IEEE International Conference on Data Mining (ICDM)

作者： James M. Kang Shashi Shekhar Christine Wennen Paige Novak Department of Computer Science University of Minnesota MN USA Graduate Program in Water Resources Science University of Minnesota MN USA Department of Civil Engineering University of Minnesota MN USA

Given a percentage-threshold and readings from a pair of consecutive upstream and downstream sensors, flow anomaly discovery identifies dominant time intervals where the fraction of time instants of significantly mis-matched sensor readings exceed the given percentage-threshold. Discovering flow anomalies (FA) is an important problem in environmental flow monitoring networks and early warning detection systems for water quality problems. However, mining FAs is computationally expensive because of the large (potentially infinite) number of time instants of measurement and potentially long delays due to stagnant (e.g. lakes) or slow moving (e.g. wetland) water bodies between consecutive sensors. Traditional outlier detection methods (e.g. t-test) are suited for detecting transient FAs (i.e., time instants of significant mis-matches across consecutive sensors) and cannot detect persistent FAs (i.e., long variable time-windows with a high fraction of time instant transient FAs) due to a lack of a pre-defined window size. In contrast, we propose a Smart Window Enumeration and Evaluation of persistence-Thresholds (SWEET) method to efficiently explore the search space of all possible window lengths. Computation overhead is brought down significantly by restricting the start and end points of a window to coincide with transient FAs, using a smart counter and efficient pruning techniques. Experimental evaluation using a real dataset shows our proposed approach outperforms Nainodotve alternatives.

关键词： Birth disorders Pollution measurement Water pollution Sensor phenomena and characterization Rivers Water resources Lakes Condition monitoring Contamination Petroleum

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Nanoscale porous silicon waveguides for biosensing applications

Nanoscale porous silicon waveguides for biosensing applicati...

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21st Annual Meeting of the IEEE Lasers and Electro-Optics Society, LEOS 2008

作者： Rong, G. Wei, X. Kang, C. Liscidini, M. Sipe, J.E. Mernaugh, R.L. Weiss, S.M. Department of Electrical Engineering and Computer Science Vanderbilt University Nashville TN 37235 United States Interdisciplinary Graduate Program in Materials Science Vanderbilt University Nashville TN 37235 United States Department of Physics Institute for Optical Sciences University of Toronto Toronto ON M5S 1A7 Canada Department of Biochemistry Vanderbilt University Nashville TN 37235 United States

Nanoscale porous silicon waveguides, both on silicon substrates and free-standing membranes, are explored for biosensing applications. Measured detection limits in the nanomolar range are reported for DNA sensing. ... 详细信息

ISBN: (纸本)9781424419326

关键词： Porous silicon

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A study on phase noise characteristics of oscillation circuits focused signal output position

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2008年第8期128卷 1377-1378页

作者： Imaike, Takeshi Sakuta, Yukinori Sekine, Yoshifumi Program in Electronic Engineering Graduate School of Science and Technology Nihon University 7-24-1 Narashinodai Funabashi Chiba 274-8501 Japan Department of Electronics and Computer Science College of Science and Technology Nihon University 7-24-1 Narashinodai Funabashi Chiba 274-8501 Japan

This paper discusses phase noise characteristics of an Fr oscillator focusing on a signal output position. Oscillation circuits can be divided into an amplifier and a feedback circuit. We compared that phase noise characteristics before passing through a feedback circuit or a after. As a result, it turned out that the slope of the phase noise characteristic does not relate to the signal output position. © 2008 The Institute of Electrical Engineers of Japan.

关键词： Phase noise

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Using a literature-based NMF model for discovering gene functional relationships

Using a literature-based NMF model for discovering gene func...

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IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

作者： Elina Tjioe Michael Berry Ramin Homayouni Genome Science and Technology Graduate School University of Tennessee Knoxville TN USA Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA Bioinformatics Program Department of Biology University of Memphis Memphis TN USA

The rapid growth of the biomedical literature and genomic information presents a major challenge for determining the functional relationships among genes. In this study, we develop a Web-based bioinformatics software environment called FAUN or feature annotation using nonnegative matrix factorization (NMF) to facilitate both the discovery and classification of functional relationships among genes. Both the computational complexity and parameterization of NMF for processing gene sets are discussed. We tested FAUN on three manually constructed gene document collections, and then used it to analyze several microarray-derived gene sets obtained from studies of the developing cerebellum in normal and mutant mice. FAUN provides utilities for collaborative knowledge discovery and identification of new gene relationships from text streams and repositories (e.g., MEDLINE). It is particularly useful for the validation and analysis of gene associations suggested by microarray experimentation.

关键词： Bioinformatics Genomics Data mining Matrix decomposition Large scale integration Feature extraction Iterative methods Biological system modeling computer science Computational biology

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DLM: A distributed Large Memory System using remote memory swapping over cluster nodes

DLM: A distributed Large Memory System using remote memory s...

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IEEE International Conference on Cluster Computing

作者： Hiroko Midorikawa Motoyoshi Kurokawa Ryutaro Himeno Mitsuhisa Sato Department of Computer and Information Science Seikei University Musashino Tokyo Japan Graduate School of Systems and Information Engineering University of Tsukuba Tennodai Tsukuba Ibaraki Japan Advanced Center of Computing and Communication Wako Saitama Japan Research Program for Computational Science RIKEN Wako Saitama Japan

Emerging 64 bitOSpsilas supply a huge amount of memory address space that is essential for new applications using very large data. It is expected that the memory in connected nodes can be used to store swapped pages efficiently, especially in a dedicated cluster which has a high-speed network such as 10 GbE and Infiniband. In this paper, we propose the distributed large memory system (DLM), which provides very large virtual memory by using remote memory distributed over the nodes in a cluster. The performance of DLM programs using remote memory is compared to ordinary programs using local memory. The results of STREAM, NPB and Himeno benchmarks show that the DLM achieves better performance than other remote paging schemes using a block swap device to access remote memory. In addition to performance, DLM offers the advantages of easy availability and high portability, because it is a user-level software without the need for special hardware. To obtain high performance, the DLM can tune its parameters independently from kernel swap parameters. We also found that DLMpsilas independence of kernel swapping provides more stable behavior.

关键词： Kernel Arrays Memory management Servers Bandwidth Performance evaluation Benchmark testing

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Nanoscale porous silicon waveguides for biosensing applications

Nanoscale porous silicon waveguides for biosensing applicati...

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IEEE Photonics Conference (IPC)

作者： G. Rong X. Wei C. Kang M. Liscidini J. E. Sipe R. L. Mernaugh S. M. Weiss Department of Electrical Engineering and Computer Science Vanderbilt University Nashville TN USA Interdisciplinary Graduate Program in Materials Science Vanderbilt University Nashville TN USA Department of Physics and Institute for Optical Sciences University of Toronto Toronto ONT Canada Department of Biochemistry Vanderbilt University Nashville TN USA

关键词： Silicon Biosensors Optical waveguides Gratings Biomembranes Resonance DNA Biological materials Optical materials Optical surface waves

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Finding cancer-related gene combinations using a molecular evolutionary algorithm

Finding cancer-related gene combinations using a molecular e...

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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Park, Chan-Hoon Kim, Soo-Jin Kim, Sun Cho, Dong-Yeon Zhang, Byoung-Tak School of Computer Science and Engineering Seoul National University Seoul 151-742 Korea Republic of Graduate Program in Bioinformatics Seoul National University Seoul 151-742 Korea Republic of

ISBN: (纸本)1424415098

High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray analysis by managing large and complex data systematically. However, combinatorial interactions among genes have not been considered as a unit of the analysis since previous methods mainly focus on a whole gene or a single isolated gene. Here, we introduce a molecular evolutionary algorithm called probabilistic library model (PLM). In the PLM, library elements are generated from gene combinations. An evolutionary procedure is adopted to learn the probabilistic distribution of training samples. We apply the PLM to prostate cancer microarray data. The experimental results show that the PLM classifiers perform better than conventional methods such as neural networks and decision trees in accuracy. We also examine the evolved library to find cancer-related gene combinations. ©2007 IEEE.

关键词： Microarrays

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Rich learning experiences for minority undergraduate students through inquiry-based project activities in the field and laboratory settings

Rich learning experiences for minority undergraduate student...

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114th Annual ASEE Conference and Exposition, 2007

作者： Nagchaudhuri, Abhijit Mitra, Madhumi Stoakley, Rose Turner, Tiara Cherinet, Suraf Ladd, Gabriel Chalyam, Harsha Hartman, Christopher Burrows-Mcelwain, James B. University of Maryland-Eastern Shore United States Department of Engineering and Aviation Sciences University of Maryland Eastern Shore United States ASME SME ASEE Department of Biology and Environmental Science University of Maryland Eastern Shore United States Biology Education Program UMES France Mathematics Program University of Maryland Eastern Shore Department of Mathemtics and Computer Sciences United States Aviation Science Program University of Maryland Eastern Shore United States Graduate Program UMES United States Department of Mathematics and Computer Science University of Maryland Eastern Shore United States Aviation Science Program Department of Engineering and Aviation Science University of Maryland Eastern Shore United States Aviation Program Department of Engineering and Aviation Sciences Aviation Program

With support from HBCU-UP (Historically Black College and University Undergraduate program) at National science Foundation (NSF), the ACTION (Advanced Curriculum and Technology-Based Instructional Opportunities Network) program at University of Maryland Eastern Shore (UMES) is promoting inquiry based active learning and research projects among undergraduate STEM (science, Technology, engineering and Mathematics) majors. Field based experiential learning efforts titled (i) AIRSPACES: Aerial Imaging and Remote Sensing for Precision Agriculture and Environmental Stewardship and (ii) ECPA: Environmentally Conscious Precision Agriculture, provided a perfect setting for STEM undergraduates to interact with UMES farm personnel, graduate students, NASA and USDA researchers collaborating with the faculty members in the project. In the summer of 2006 ACTION program supported three undergraduate students to work with the principal author to work on a chosen aspect of the ongoing effort. For this ACTION project students decided to focus on aspects of yield monitoring and remote sensing for the precision agriculture project at UMES. This paper will highlight the student efforts related to the ACTION project for 2006 summer and discuss how the out of classroom, field, and laboratory based activities enhanced learning. © American Society for engineering Education, 2007.

关键词： Learning systems

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