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Overcoming Bandwidth and Satellite Communications Limitations to Accelerate Applications of Remote Sensing and High Performance Computing for Sustainable African Development: Contributions from Egypt, Nigeria and South Africa

Overcoming Bandwidth and Satellite Communications Limitation...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Gilbert L. Rochon Magdy Wahab Gamal El Afandi Ado Dan-Isa Happy Sithole Khomotso Kganyago Souleymane Fall Joseph Quansah Akilah Martin Bereket Araya Chetan Maringanti Cliff Robinson Kaiem L. Frink Jean Pierre Antelo Rosen Center for Advanced Computing Purdue Terrestrial Observatory Purdue University-Information Technology IN USA Department of Astronomy & Meteorology Faculty of Science Cairo University Cairo Egypt Department of Meteorology & Astronomy Al-Azhar University Cairo Egypt Department of Computer Engineering Bayero University Kano Nigeria Center for High Performance Computing CHCP-CSIRO Cape Town South Africa Department of Agricultural & Biological Engineering Purdue University West Lafayette IN USA School for New Learning De Paul University Chicago IL USA Purdue Research Opportunities Program West Lafayette IN USA

Sixty-two years after the first photos of earth taken by a camera aboard a V-2 rocket in October, 1946, and forty-eight years since the first CORONA satellite images were captured, the status of remote sensing research and applications within the African continent has made dramatic progress. Many African countries now have remote sensing research centers, within government agencies, research institutes and universities. Some countries in Africa currently have earth observing and/or telecommunications satellites in orbit and/or have such assets in various planning stages. The authors document such progress, in addition to the constraints to further applications of remote sensing for sustainable development in Africa, with special reference to data distribution constraints. Moreover, the authors address the urgency for bandwidth improvements within the African continent, so as to enable sustainable development initiatives to benefit from advances in high performance computing, required for ab initio near-real-time analysis of satellite-data. Such capabilities, it is argued, are propaedeutic for time-critical initiatives, such as vulnerability assessment, disaster preparedness and mitigation, emergency response, humanitarian assistance and post-calamity reconstruction, associated with a wide array of biogenic and anthropogenic disasters. Case studies of advances in infrastructure for satellite remote sensing and high performance computing, with implications for sustainable development in Africa, are provided from Egypt, Nigeria and South Africa.

关键词： Bandwidth Satellite communication Acceleration Remote sensing High performance computing Africa Sustainable development Earth Continents Cameras

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Perceptual-based region extraction from hand drawn sketches

Perceptual-based region extraction from hand drawn sketches

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3rd IASTED International Conference on Advances in computer science and technology, ACST 2007

作者： Waranusast, Rattapoom Computer Science and Information Management Program Asian Institute of Technology P.O. Box 4 Khlong Luang Pathumthani 12120 Thailand

ISBN: (纸本)9780889866560

Pen-based computing devices have become more popular and more important, because it facilitates a natural way of input to users. To develop pen-based systems, automatic interpretation of sketches is crucial. However, this task is sensitive to drawing styles. This paper proposes a stroke grouping method based on Gestalt theory. The proposed algorithm group strokes into regions, each stroke is split into smaller stroke segments according to its corners and junctions. Then, for every stroke segments that can form closed loops, all possible regions are searched. Applying the notion of law of continuity in Gestalt theory to a set of all possible regions, scores of good continuity and convexity of all regions can be computed. The region with the best score is stored and extracted from the sketch. This iterative process is repeated until no stroke segments are left in the set of closed-loop segments. The algorithm implemented and tested on a tablet PC showed good results.

关键词： Iterative methods

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A Decision Support System for Evaluating International Student Applications

A Decision Support System for Evaluating International Stude...

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37th Annual Frontiers in Education Conference (FIE 2007), vol.2

作者： Nguyen Thi Ngoc Hien Peter Haddawy Computer Science and Information Management Program Asian Institute of Technology Thailand

In today's transnational admission environment, evaluating applicant qualifications is becoming increasingly challenging. While standardized tests can be helpful, studies have shown that they are rather noisy predictors of performance. Predicting educational outcome is a viable alternative in such heterogeneous environments. Performance prediction models can be built by applying data mining techniques to enrollment data. In this paper we present an approach to using Bayesian networks to predict graduating cumulative Grade Point Average based on applicant background at the time of admission. While such prediction models can be helpful, their recommendations may not be followed by departmental faculty members making admission decisions if they are presented as black boxes. We thus present a novel approach to deriving a case-based retrieval mechanism from the Bayesian network prediction model in such a way that the similarity measure used by the case-based system is consistent with the predictive model. The case-based component retrieves the past student most similar to the applicant being evaluated. The Bayesian network model is evaluated using stratified ten-fold cross validation.

关键词： Bayesian networks Case-based retrieval Student evaluation

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Deriving financial aid optimization models from admissions data

Deriving financial aid optimization models from admissions d...

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Frontiers in Education (FIE) Conference

作者： Le Van Thanh Peter Haddawy Computer Science and Information Management Program Asian Institute of Technology Thailand

This paper presents a novel approach to deriving probabilistic models that predict enrollment given applicant background and the amount of financial aid offered. Our Bayesian network models can be used to optimize various enrollment objectives. We present a novel efficient optimization algorithm that uses the models to maximize expected tuition revenue under capacity constraints including student-faculty ratio and accommodation. We demonstrate and evaluate our approach using four years of graduate admissions data from the Asian Institute of technology, consisting of 7,788 applicants from 84 different countries. This data set is particularly challenging since reliable family income data is not available for students from most of these countries. Evaluating the Bayesian network model with 10-fold cross validation yields an ROC Az value of 0.8451, with a predictive accuracy of 82.70% at a threshold of 0.5. Comparing the results of the tuition revenue optimization model to the institute's current financial aid allocation practice shows that if single-term tuition revenue is the sole optimization criterion, the institute can achieve its current enrollment numbers while realizing significant savings in its financial aid budget. The prediction and optimization software is currently being incorporated into the institute's online admissions processing system.

关键词： Predictive models Bayesian methods Logistics Accuracy Resource management Probability Error analysis Neural networks Regression tree analysis computer science

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A deliberate integration of information technology into the classroom

A deliberate integration of information technology into the ...

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114th Annual ASEE Conference and Exposition, 2007

作者： Fairfax, Duane Huggins, Kevin Goda, Bryan USMA United States Computer Science Program US Military Academy United States IEEE Department of Electrical Engineering and Computer Science US Military Academy at West Point United States Association for Computing Machinery Institute of Electrical and Electronic Engineers Information Technology Program US Military Academy United States

The information Age has revolutionized the way students learn in the classroom. The United States Military Academy (USMA) emphasizes the importance of information technology (IT) through an academy-wide IT specific goal. This goal supports the USMA's mission of producing Army Officers who can respond effectively to technological changes in the defense of our nation. Courses augmented with IT can be daunting for cadets who lack the experience and confidence level to succeed in the course. As a result, these types of courses are avoided by cadets if at all possible. This is not an option for an aspiring officer who will lead the soldiers of tomorrow on a digitized battlefield. Since 1990, cadets have been issued a computer which has played a central role in bringing the power of IT to all graduates of the Military Academy. Integration of IT in the curriculum begins early with every cadet receiving a laptop computer. An integrated software package is included to support any course of instruction. Cadets receive two courses in IT, one in their freshman year and one in their junior year. The freshman course teaches the cadet the basic functionality of the laptop, a basic programming language, and creating a basic website. The junior course builds on the freshman course by teaching the cadets to create an advanced website, design and build a network, manage a database, and create an information system. IT plays a central role in several overlap courses between engineering and the humanities in such areas as information warfare, terrorism, and the legal aspects of intellectual property rights. What makes this approach unique is the methodical diffusion of IT into course design which removes the barrier between learning and the implementation of IT as an academic multiplier. An academy-wide committee consisting of 12 members is responsible for examining collected data to see how well the Military Academy is meeting its LT goal. This data comes from a variety of sources such

关键词： information technology

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A comparative analysis of techniques for predicting academic performance

A comparative analysis of techniques for predicting academic...

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Frontiers in Education (FIE) Conference

作者： Nguyen Thai Nghe Paul Janecek Peter Haddawy Computer Science and Information Management Program Asian Institute of Technology Thailand Cantho University Vietnam

This paper compares the accuracy of decision tree and Bayesian network algorithms for predicting the academic performance of undergraduate and postgraduate students at two very different academic institutes: Can Tho University (CTU), a large national university in Viet Nam; and the Asian Institute of technology (AIT), a small international postgraduate institute in Thailand that draws students from 86 different countries. Although the diversity of these two student populations is very different, the data-mining tools were able to achieve similar levels of accuracy for predicting student performance: 73/71% for {fail, fair, good, very good} and 94/93% for {fail, pass} at the CTU/AIT respectively. These predictions are most useful for identifying and assisting failing students at CTU (64% accurate), and for selecting very good students for scholarships at the AIT (82% accurate). In this analysis, the decision tree was consistently 3-12% more accurate than the Bayesian network. The results of these case studies give insight into techniques for accurately predicting student performance, compare the accuracy of data mining algorithms, and demonstrate the maturity of open source tools.

关键词： Performance analysis Data mining Decision trees Bayesian methods Prediction algorithms Accuracy Scholarships Predictive models information analysis Algorithm design and analysis

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Implementing and Improving a method for non-invasive elicitation of probabilities for bayesian networks 07

Implementing and Improving a method for non-invasive elicita...

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International Conference on computer Systems and Technologies and Workshop for PhD Students in Computing, CompSysTech '07

作者： De Jongh, Martinus Druzdzel, Marek Rothkrantz, Leon Faculty of Electrical Engineering Mathematics and Computer Science Man-Machine Interaction Group Delft University of Technology Delft Netherlands Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA United States

ISBN: (纸本)9789549641509

Knowledge elicitation is difficult for expert systems that are based on probability theory. The elicitation of probabilities for a probabilistic model requires a lot of time and interaction between the knowledge engineer and the expert. Druzdzel and van der Gaag [5] have proposed a theoretical framework that would allow the use of multiple types of probabilistic information for elicitation of Bayesian networks. This framework has been used as a starting point for the implementation of a non-invasive elication method. © 2007 ACM.

关键词： Linear programming

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Interpreting cabinet approval ratings by neural networks

Interpreting cabinet approval ratings by neural networks

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IASTED International Conference on Artificial Intelligence and Applications, AIA 2007

作者： Kamimura, Ryotaro Yoshida, Fumihiko Kitajima, Ryozo Information Science Laboratory Information Technology Center Tokai University 1117 Kitakaname Hiratsuka Kanagawa 259-1292 Japan Department of Media Studies Tokai University 1117 Kitakaname Hiratsuka Kanagawa 259-1292 Japan Graduate Program in Computer Sciences Tokai University 1117 Kitakaname Hiratsuka Kanagawa 259-1292 Japan

ISBN: (纸本)9780889866317

In this paper, we try to estimate Japan's cabinet approval ratings by using neural networks. In addition, we try to extract the important features in input patterns. This is the first attempt to use neural networks and to interpret the mechanism of inference for approval estimation in a comprehensive way. Experimental results show that neural networks have much better performance than that obtained by the standard regression analysis in terms of training and testing errors. The information loss analysis reveals that the first variable, that is, the previous ratings should play the most important role in inference. Though the experimental result here shown is a preliminary one, it certainly suggests a possibility of the automatic inference of cabinet approval ratings.

关键词： Feature extraction

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information-Theoretic Variable Selection in Neural Networks

Information-Theoretic Variable Selection in Neural Networks

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IEEE Symposium on Foundations of Computational Intelligence, FOCI

作者： Ryotaro Kamimura Fumihiko Yoshida Yamashita Toshie Ryozo Kitajima Information Technology Center Information Science Laboratory Japan Department of Media Studies Tokai University Hiratsuka Kanagawa Japan Graduate Program in Computer Sciences Tokai University Hiratsuka Kanagawa Japan

In this paper, we propose a new type of information-theoretic approach to variable selection. Many approaches have been proposed in estimating the importance of input variables. The majority of these approaches have focused upon output errors. We here introduce an approach concerning internal representations. First, we delete an input unit with corresponding connection weights. Then, by examining some change in hidden unit activation with and without a input variable, we can extract an important variable. We apply this method to an artificial data in which the number of hidden units is redundantly increased so as to clearly show improved performance and the stability of our method. Then, we apply the method to the cabinet approval ratings in which better interpretation of input variables can be given

关键词： Input variables Neural networks Computational intelligence computer networks information theory Data mining Standards development Measurement units information science Laboratories

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Delivering Context-aware Learning Guidance in the Mobile Learning Environment based on information Theory

Delivering Context-aware Learning Guidance in the Mobile Lea...

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International Conference on Advanced Learning Technologies (ICALT)

作者： Rita Kuo Min-Chang Wu Alex Chang Maiga Chang Jia-Sheng Heh Department of Electronic Engineer Chung Yuan Christian University Taiwan Department of Information and Computer Engineering Chung Yuan Christian University Taiwan Program Office of National Science and Technology Program for Learning in Taiwan Taiwan

Mobile Learning makes students get the advantages of both traditional learning and e-learning. How to give students learning sequence suggestions in the mobile learning environment is a big issue and is also the goal of this paper. This research uses knowledge map to store the characteristics of each learning object and designs a situated map to represent spatial knowledge in the mobile learning environment. By using these two knowledge structures, knowledge map and situated map, the system created by this research can generate various navigation sentences and ask students to observe the characteristics of learning objects. This research also takes information theory into consideration in order to decide which navigation sentence should deliver to the student first. The system calculates the entropy for each generated sentence and finds the most appropriate one to deliver to the student. At the end of this paper, an experiment system is implemented for the 5th year biology course, Plant Observation.

关键词： information theory Navigation Electronic learning Mobile computing Knowledge representation Humans Cognition Personal digital assistants US Department of Transportation Sequences

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