ppxscal/embedding_network huggingface dataset:
Relational Databases as Semantic Web Endpoints
Authors: Matthias Hert
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

This proposal explores the promotion of existing relational databases to Semantic Web Endpoints. It presents the benefits of ontology-based read and write access to existing relational data as well as the need for specialized, scalable reasoning over that data. We introduce our approach for translating SPARQL/Update operations to SQL, describe how scalable reasoning can be realized by using the power of the database system, and outline two case studies for evaluating our approach. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Split Bregman Algorithm, Douglas-Rachford Splitting and Frame Shrinkage
Authors: Simon Setzer
Venue: Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision (2009)

We examine relations between popular variational methods in image processing and classical operator splitting methods in convex analysis. We focus on a gradient descent reprojection algorithm for image denoising and the recently proposed Split Bregman and alternating Split Bregman methods. By identifying the latter with the so-called Douglas-Rachford splitting algorithm we can guarantee its convergence. We show that for a special setting based on Parseval frames the gradient descent reprojection and the alternating Split Bregman algorithm are equivalent and turn out to be a frame shrinkage method.
Goal-directed shortest-path queries using precomputed cluster distances
Authors: Jens Maue, Peter Sanders, Domagoj Matijevic
Venue: Journal of Experimental Algorithmics (JEA) (2009)

We demonstrate how Dijkstra's algorithm for shortest path queries can be accelerated by using precomputed shortest path distances. Our approach allows a completely flexible tradeoff between query time and space consumption for precomputed distances. In particular, sublinear space is sufficient to give the search a strong &ldquo;sense of direction&rdquo;. We evaluate our approach experimentally using large, real-world road networks.
Improving the mental models held by novice programmers using cognitive conflict and jeliot visualisations
Authors: Linxiao Ma, John Ferguson, Marc Roper, Isla Ross, Murray Wood
Venue: ACM SIGCSE Bulletin (2009)

Recent research has found that many novice programmers often hold non-viable mental models of basic programming concepts which can limit their potential to develop appropriate programming skills. Previous work by the authors suggests that a teaching model that integrates cognitive conflict and program visualisation can help novices formulate appropriate mental models. This paper first outlines a 'concepts roadmap' that provides an ordered approach to learning programming concepts allowing students to build on fundamental base knowledge. It then reports the results of a series of studies investigating the use of the Jeliot visualisation tool as the visualisation component of the proposed learning model when applied to these concepts. The findings include: the ease with which Jeliot can be tailored to visualise a range of concepts using a variety of examples; the Jeliot visualisation of object reference was too complex for CS1 students; further evidence that CS1 students struggle to develop appropriate understanding of a range of key programming concepts; and, further evidence that an integrated cognitive conflict/visualisation strategy can help students develop an appropriate understanding of key programming concepts.
The Research of Negative Correlation Learning Based on Artificial Neural Network
Authors: Yi Ding, Xufu Peng, Xian Fu
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

The integrated technology of the artificial neural network is a research focus of the neural computing technology, which possesses ripe applications in a lot of fields. The neural network ensemble studies the same question with limited neural networks. The output of the ensemble under some input example is determined by all the output of the neural network forming the ensemble under the same input example. The negative correlation learning, which encourages different individual network to study and train different parts of the ensemble in order to make the whole ensemble study the whole training data better, is a training method for the neural network ensemble in this paper. Using a BP algorithm with impulse in the error function is an improvement of the method of negative correlation learning in the paper. The method is an algorithm in batches with more powerful generalization ability and studying of speed, because it combines primitive correlation learning with BP algorithm of impulse.
Automated and hand-coded measurement of deliberative quality in online policy discussions
Authors: Peter Muhlberger, Jennifer Stromer-Galley
Venue: Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government (2009)

A number of research projects are now underway to assess how IT tools and deliberative techniques could enhance public input into government at all levels. The success of such projects depends to an important degree on objective measurement of the quality of discussion under different utilizations of tools and techniques. This paper explores the value of two techniques for determining the quality of policy discussion in the context of federal agency rulemaking: a human-coded technique and a technique involving statistical bootstrapping of natural language processing data. The hand-coded technique utilizes counts of verbal behaviors that are indicative of intellectual engagement. This includes such behaviors as raising questions, disagreeing, and introducing new topics. The automated technique develops a measure of sophistication of reasoning based on significant co-occurrence of concepts in participants' speech. Such co-occurrence clarifies the network of conceptual relations utilized by participants. The more connections participants make between policy-relevant concepts, the more sophisticated their speech should be. Data consist of discussion of the federal rulemaking issue of network neutrality regulation by a sample of 53 volunteers. Correlations and ordinary least squares regression find that the conceptual connection and hand-coded measures, despite being qualitatively quite different, significantly predict each other and several other measures of sophistication, including two indicators of network neutrality knowledge and sophistication of views of government.
The constitutive and the instrumental in social design
Authors: Murali Venkatesh
Venue: Proceedings of the 4th International Conference on Design Science Research in Information Systems and Technology (2009)

Simon's <u>The Sciences of the Artificial</u> is rightly influential as a founding text in design research in the information systems field (IS). Simon's contributions in the same volume to what he calls social planning and human design - practices associated with the development of societal scale artifacts that foster a "humane society" - are much less visible in IS design research. I develop and expand on some of Simon's insights here using social design projects such as IT-based civic networks as my context, drawing on a civic network development project called the Urban-net that I have tracked since its inception in 1996. I define some distinctive features of such projects and advance an institutionalist conception of actors (designers) and action. Despite noting that "nothing is more fundamental in setting our research agenda and informing our research methods than our view of the nature of the human beings whose behavior we are studying" (Simon 1985; emphasis added), and despite his recognition that social planning projects often are quite different from other types of technical projects in the demands they make on actors, Simon's (1996) discussion is not moved by a sufficiently nuanced view of the designer. Apropos, and drawing on a sociological institutionalist view of social actors and action, I outline a model of two inter-related design activities: constitutive design - targeting design of the normative or institutional foundation and governance mechanisms - and instrumental design, where designers specify the system to be built within the agreed-upon normative constraints. I conclude with a brief account of the Urban-net case.
Cell Breathing Techniques for Load Balancing in Wireless LANs
Authors: Yigal Bejerano, Seung-Jae Han
Venue: IEEE Transactions on Mobile Computing (2009)

Maximizing network throughput while providing fairness is one of the key challenges in wireless LANs (WLANs). This goal is typically achieved when the load of access points (APs) is balanced. Recent studies on operational WLANs, however, have shown that AP load is often substantially uneven. To alleviate such imbalance of load, several load balancing schemes have been proposed. These schemes commonly require proprietary software or hardware at the user side for controlling the user-AP association. In this paper we present a new load balancing technique by controlling the size of WLAN cells (i.e., AP's coverage range), which is conceptually similar to cell breathing in cellular networks. The proposed scheme does not require any modification to the users neither the IEEE 802.11 standard. It only requires the ability of dynamically changing the transmission power of the AP beacon messages. We develop a set of polynomial time algorithms that find the optimal beacon power settings which minimize the load of the most congested AP. We also consider the problem of network-wide min-max load balancing. Simulation results show that the performance of the proposed method is comparable with or superior to the best existing association-based methods.
Actor-agent application for train driver rescheduling
Authors: Erwin J. W. Abbink, David G. A. Mobach, Pieter J. Fioole, Leo G. Kroon, Eddy H. T. van der Heijden, Niek J. E. Wijngaards
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

This paper describes the design, implementation, visualizations, results and lessons learned of a novel real-world socio-technical research system for the purpose of rescheduling train drivers in the event of disruptions. The research system is structured according to the Actor-Agent paradigm: here agents assist in rescheduling tasks of train drivers. Coordination between agents is based on a team formation process in which possible rescheduling alternatives can be evaluated, based on constraints and preferences of involved human train drivers and dispatchers. The research system is the result of cooperation on decentralised multi-agent crew rescheduling between Netherlands Railways (NS) and the D-CIS Lab. The implementation is realized using the Cougaar framework and includes actual timetable and rolling stock schedule data and driver duty data.
A Modern Tower of Babel
Authors: Norman Chonacky
Venue: Computing in Science and Engineering (2009)

Former editor in chief Norman Chonacky waxes lyrical about the trials and tribulations involved in—along with the importance of—learning a new computer language.
Evaluating the Vulnerability of Network Traffic Using Joint Security and Routing Analysis
Authors: Patrick Tague, David Slater, Jason Rogers, Radha Poovendran
Venue: IEEE Transactions on Dependable and Secure Computing (2009)

Joint analysis of security and routing protocols in wireless networks reveals vulnerabilities of secure network traffic that remain undetected when security and routing protocols are analyzed independently. We formulate a class of continuous metrics to evaluate the vulnerability of network traffic as a function of security and routing protocols used in wireless networks. We develop two complementary vulnerability definitions using set theoretic and circuit theoretic interpretations of the security of network traffic, allowing a network analyst or an adversary to determine weaknesses in the secure network. We formalize node capture attacks using the vulnerability metric as a nonlinear integer programming minimization problem and propose the GNAVE algorithm, a Greedy Node capture Approximation using Vulnerability Evaluation. We discuss the availability of security parameters to the adversary and show that unknown parameters can be estimated using probabilistic analysis. We demonstrate vulnerability evaluation using the proposed metrics and node capture attacks using the GNAVE algorithm through detailed examples and simulation.
Multi-criteria optimization approach for the deployment planning problem of multi-hop wireless networks
Authors: D. Benyamina, N. Hallam
Venue: Proceedings of the international conference on Computational and information science 2009 (2009)

The few studies carried out so far on planning Wireless Mesh Networks (WMNs) tend all to be monoobjective optimization models. We propose a different approach to address the planning of WMN problem that reflects as much as possible the real-life problem. Basically, an optimal (or rather a good and realistic) planning solution has to be simultaneously cheap (minimizing the deployment cost) and efficient (maximizing the throughput). To achieve this, we devise a novel generic multi-objective optimization model where the two objectives of network cost deployment and network throughput are simultaneously optimized under obvious network constraints. We then derive two instance models differing mainly in how the second objective is defined: maximizing the culmination of the flows over the entire network or minimizing the aggregation of network interferences. Obviously, a new network metric is proposed to handle this task. A comparative experimental study with different key-parameter settings on the two instance models is conducted to help network planner decide which planning optimization model to choose given their specific requirements and/or scenarios.
A New Instance-Based Label Ranking Approach Using the Mallows Model
Authors: Weiwei Cheng, Eyke Hüllermeier
Venue: Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks (2009)

In this paper, we introduce a new instance-based approach to the label ranking problem. This approach is based on a probability model on rankings which is known as the Mallows model in statistics. Probabilistic modeling provides the basis for a theoretically sound prediction procedure in the form of maximum likelihood estimation. Moreover, it allows for complementing predictions by diverse types of statistical information, for example regarding the reliability of an estimation. Empirical experiments show that our approach is competitive to start-of-the-art methods for label ranking and performs quite well even in the case of incomplete ranking information.
Epipolar geometry of catadioptric stereo systems with planar mirrors
Authors: Hsien-Huang P. Wu, Meng-Tu Lee, Ping-Kuo Weng, Soon-Lin Chen
Venue: Image and Vision Computing (2009)

In order to simplify the design and implementation of a stereo vision system, catadioptric instruments have been used to capture stereo images with a single camera. These catadioptric stereo systems not only provide radiometric advantages over traditional two-camera stereo, but also reduce the complexity and cost of acquiring stereoscopic video. Although much research has been done on the design of the catadioptric stereo system, little attention has been paid to analyze the planar catadioptric stereo (PCS) system based on the epipolar geometry. In this paper, we investigated characteristics of a selected PCS system and proved that it can be approximated by affine epipolar geometry. This affine model reduces the number of parameters in the fundamental matrix from seven in the conventional stereo system to only four in the PCS system. Experimental results verify that estimation of the fundamental matrix for a PCS system can be more robust, precise, and much easier to implement with the affine model. Furthermore, rectification of the image pair based on the affine fundamental matrix can achieve better performance with much less geometric distortion. These significant advantages confirm the usefulness of an affine fundamental matrix model for the selected PCS system.
QUASI-ORTHOGONAL SPACE-TIME BLOCK
Authors: Chau Yuen
Venue:  (2007)

Quasi-Orthogonal Space-Time Block Code presents an up-to-date, comprehensive and in-depth discussion of an important emerging class of space-time codes, called the Quasi-Orthogonal STBC (QO-STBC). Used in Multiple-Input Multiple-Output (MIMO) communication systems, they provide transmit diversity with higher code rates than the well-known orthogonal STBC (O-STBC), yet at lower decoding complexity than non-orthogonal STBC. This book will help readers gain a broad understanding of the fundamental principles as well as the state-of-the-art work in QO-STBC, thus enabling them to appreciate the roles of QO-STBC in future broadband wireless systems and to inspire further research. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Incorporating Prior Knowledge into Task Decomposition for Large-Scale Patent Classification
Authors: Chao Ma, Bao-Liang Lu, Masao Utiyama
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

With the adoption of min-max-modular support vector machines (SVMs) to solve large-scale patent classification problems, a novel, simple method for incorporating prior knowledge into task decomposition is proposed and investigated. Two kinds of prior knowledge described in patent texts are considered: time information, and hierarchical structure information. Through experiments using the NTCIR-5 Japanese patent database, patents are found to have time-varying features that considerably affect classification. The experimental results demonstrate that applying min-max modular SVMs with the proposed method gives performance superior to that of conventional SVMs in terms of training time, generalization accuracy, and scalability.
Case-Based Reasoning on Images and Signals, 1st edition
Authors: Petra Perner, Petra Perner
Venue: Studies In Computational Intelligence (2007)

This book is the first edited book that deals with the special topic of signals and images within Case-Based Reasoning (CBR). Signal-interpreting systems are becoming increasingly popular in medical, industrial, ecological, biotechnological and many other applications. Existing statistical and knowledge-based techniques lack robustness, accuracy and flexibility. New strategies are needed that can adapt to changing environmental conditions, signal variation, user needs and process requirements. Introducing CBR strategies into signal-interpreting systems can satisfy these requirements. CBR can be used to control the signal-processing process in all phases of a signal-interpreting system to derive information of the highest possible quality. Beyond this CBR offers different learning capabilities, for all phases of a signal-interpreting system, that satisfy different needs during the development process of a signal-interpreting system. The structure of the book is divided into a theoretical part and into an application-oriented part. Scientists and computer science experts from industry, medicine and biotechnology who like to work on the special topics of CBR for signals and images will find this work useful. Although case-based reasoning is often not a standard lecture at universities we hope we to also inspire PhD students to deal with this topic.
Extracting Opinions Relating to Consumer Electronic Goods from Web Pages
Authors: Taichi Nakamura, Hiroshi Maruyama
Venue: Proceeding of the 2006 conference on Knowledge-Based Software Engineering: Proceedings of the Seventh Joint Conference on Knowledge-Based Software Engineering (2006)

This paper describes a means of extracting the highly credible opinion ratings from Web pages. The principle behind our proposal is based on extracting the co-occurrence relation between a word representing a feature in the specification of a product or service produced by a company and a word showing a consumer's evaluation and then enlarging the dictionaries by registering additional words or phrases that appear in the co-occurrence relation.
From Association to Causation via a Potential Outcomes Approach
Authors: Sunil Mithas, M. S. Krishnan
Venue: Information Systems Research (2009)

Despite the importance of causal analysis in building a valid knowledge base and in answering managerial questions, the issue of causality rarely receives the attention it deserves in information systems (IS) and management research that uses observational data. In this paper, we discuss a potential outcomes framework for estimating causal effects and illustrate the application of the framework in the context of a phenomenon that is also of substantive interest to IS researchers. We use a matching technique based on propensity scores to estimate the causal effect of an MBA on information technology (IT) professionals' salary in the United States. We demonstrate the utility of this counterfactual or potential outcomes--based framework in providing an estimate of the sensitivity of the estimated causal effects because of selection on unobservables. We also discuss issues related to the heterogeneity of treatment effects that typically do not receive as much attention in alternative methods of estimation, and show how the potential outcomes approach can provide several new insights into who benefits the most from the interventions and treatments that are likely to be of interest to IS researchers. We discuss the usefulness of the matching technique in IS and management research and provide directions to move from establishing association to assessing causation.
Automated plaque diagnosis utilizing Levenberg Marquardt & radial basis function with supervised training of chromatic colors
Authors: Hadzli Hashim, Fairul Nazmie Osman, Norkhairiane Khairudin
Venue: Proceedings of the 10th WSEAS international conference on Neural networks (2009)

This paper presents the application of Artificial Neural Network (ANN) in development of an automated diagnosis system for selected psoriasis skin disease. Previous work has shown that analyzing psoriasis lesion digital images using YCbCr color model is feasible. Furthermore, human skin images if digitally quantified operates better on the chrominance plane rather than the normal RGB. YCbCr mean gradation color indices representing cropped images of psoriasis lesion are used to train multi layer ANN model using Levenberg Marquardt (LM) and Radial Basis Function (RBF) algorithm. The supervised training of these models layer are then evaluated, tested and validated through analysis of the performance indicators regularly applied in medical research.