ppxscal/embedding_network huggingface dataset:
Methodology for Supporting Novel Model of E-Learning Platform in Grid Architecture
Authors: Tianding Chen
Venue: Proceedings of the 7th international conference on Advances in Web Based Learning (2008)

It combines grid technology with E-Learning, present an E-Learning architecture based on grid technology to support learning novel mode. By using Grid Computing technology, this method aims to integrate those unrelated computers in schools to replace high level server as the teaching platforms of E-Learning. Thus, not only the computer sources in schools can be fully used and applied, and moreover, constantly sharing the computer sources from other schools or associations as well as the computing capacities. In this paper, a prototype of E-Learning platform using grid environment is proposed, built up using a number of open source E-Learning software in a heterogeneous environment. In the future, using grid technology on E-Learning might be a new scheme. We also expect the outcome and experiences of this research can provide reference to the schools that wish to develop E-Learning environment for saving the cost and time in developing a similar system. 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
A probabilistic multi-class strategy of one-vs.-rest support vector machines for cancer classification
Authors: Jin-Hyuk Hong, Sung-Bae Cho
Venue: Neurocomputing (2008)

Support vector machines (SVMs), originally designed for binary classification, have been applied for multi-class classification with effective decomposition and reconstruction schemes. Decomposition schemes such as one-vs.-rest (OVR) and pair-wise partition a dataset into several subsets of two classes so as to produce multiple outputs that should be combined. Majority voting or winner-takes-all is a representative reconstruction scheme to combine those outputs, but it often causes some problems to consider tie-breaks and tune the weights of individual classifiers. In this paper, we propose a novel method in which SVMs are generated with the OVR scheme and probabilistically ordered by using the naive Bayes classifiers (NBs). This method is able to break ties that frequently occur when working with multi-class classification systems with OVR SVMs. More specifically, we use the Pearson correlation to select informative genes and reduce the dimensionality of gene expression profiles when constructing the NBs. The proposed method has been validated on several popular multi-class cancer datasets and produced higher accuracy than conventional methods.
Agent-Based User Personalization Using Context-Aware Semantic Reasoning
Authors: Fran Frkovic, Vedran Podobnik, Krunoslav Trzec, Gordan Jezic
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

The future of mobile telecommunications is aimed at creating a user-centric wireless world which takes into account user's preferences, as well as communication context (e.g., network and terminal heterogeneity or user location). In order to enable context-aware personalization of communication services offered by next-generation mobile networks, we propose an agent-based approach in combination with semantic reasoning techniques from the Semantic Web. In particular, we use ontology-based user profiles to create an agent-based context-aware service which supports personalization according to user's preferences. An ontology is created which contains knowledge regarding terminal capabilities and user preferences, as well as a software agent which manages user personalization according to the context extracted from the user profile.
The Impact of Clustering on Token-Based Mutual Exclusion Algorithms
Authors: Julien Sopena, Luciana Arantes, Fabrice Legond-Aubry, Pierre Sens
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

We present in this article a theoretical study and performance results about the impact of the Grid architecture on token-based mutual exclusion algorithms. To this end, both the original token-based Naimi-Tréhel's algorithm and a hierarchical approach, suitable to cope with the intrinsic heterogeneity of communication latencies of Grid environments, are studied and evaluated.
Web-Based Multi-Observer Segmentation Evaluation Tool
Authors: Yaoyao Zhu, Xiaolei Huang, Daniel Lopresti, Rodeny Long, Sameer Antani, Zhiyun Xue, George Thoma
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

Multi-observer segmentation evaluation is useful in the imaging community. We have developed web-based software for automatic performance evaluation of multiple image segmentations which is based on the Baysian Decision framework. It computes a probabilistic estimate of the true segmentation (ground truth map) and performance measures for the individual segmentations (sensitivity and specificity). The strength of the tool is that it integrates the two kinds of prior knowledge of segmentations: the truth prior (the prior probability) and the observer prior (the performance measures of observers), which can generate more accurate evaluations.
Coupled Meshfree-BEM Platform for Electrocardiographic Simulation: Modeling and Validations
Authors: Linwei Wang, Heye Zhang, Ken C. Wong, Pengcheng Shi
Venue: Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality (2008)

The foremost premise for the success of noninvasive volumetric myocardial transmembrane (TMP) imaging from body surface potential (BSP) recordings is a realistic yet efficient electrocardiographic model which relates volumetric myocardial TMP distributions to BSP distributions. With a view towards the inverse problem, appropriate model simplifications should be emphasized to balance the accuracy of the model with the feasibility of the inversion. In this paper, we present a novel coupled meshfree-BEM platform to represent the combined heart-torso structure and derive the associated TMP-to-BSP models. The numerical accuracy and convergency of the presented approach is verified against analytic solutions on a synthetic geometry. The associated simplifications are justified by comparing models at different level of complexity, which further demonstrates the benefits of homogeneous torso assumption in the inverse problem. Initial simulation experiments on a realistic heart-torso structure further show the physiological plausibility of the presented approach.
Approximation Algorithms for Scheduling Parallel Jobs: Breaking the Approximation Ratio of 2
Authors: Klaus Jansen, Ralf Thöle
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

In this paper we study variants of the non-preemptive parallel job scheduling problem where the number of machines is polynomially bounded in the number of jobs. For this problem we show that a schedule with length at most (1 + &epsilon;)OPT can be calculated in polynomial time, which is the best possible result (in the sense of approximation ratio), since the problem is strongly NP-hard. For the case when all jobs must be allotted to a subset of machines with consecutive indices a schedule with length at most (1.5 + &epsilon;)OPT can be calculated in polynomial time. The previously best known results are algorithms with absolute approximation ratio 2.
An intelligent proactive security system for cyber centres using Cognitive Agents
Authors: P. Venkataram, Jeremy Pitt, B. Sathish Babu, E. Mamdani
Venue: International Journal of Information and Computer Security (2008)

The computers at cyber centres are vulnerable. They can be used for various illegal activities. Only the system-level security solutions are not sufficient to prevent these activities completely. There is a need for an intelligent scheme which identifies culprits based on behaviours and actions. This paper proposes an intelligent and environment based proactive security system for cyber centres, using cognitive agents. The agents are used for belief generation, belief analysis and to execute suitable security actions and pro-actions. This method of controlling the cyber crime at usage level, will be the requisite step towards preventing Internet abuse.
A Method for Modulo Operation by Use of Spatial Parallelism
Authors: Kouichi Nitta, Nobuto Katsuta, Osamu Matoba
Venue: Proceedings of the 1st international workshop on Optical SuperComputing (2008)

An optical method for modulo operations has been proposed. This method utilizes phase modulation of light wave. This method can be applied to modulo multiplication which is an important operation in an algorithm for prime factorization. Optical parallel processing based on the method is implemented with a Michelson interferometer. This report shows that this method is effective in prime factorization. Especially, we study on suitability between large scale data processing for the prime factorization and the proposed method.
Mining Multidimensional Sequential Patterns over Data Streams
Authors: Chedy Raïssi, Marc Plantevit
Venue: Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery (2008)

Sequential pattern mining is an active field in the domain of knowledge discovery and has been widely studied for over a decade by data mining researchers. More and more, with the constant progress in hardware and software technologies, real-world applications like network monitoring systems or sensor grids generate huge amount of streaming data. This new data model, seen as a potentially infinite and unbounded flow, calls for new real-time sequence mining algorithms that can handle large volume of information with minimal scans. However, current sequence mining approaches fail to take into account the inherent multidimensionality of the streams and all algorithms merely mine correlations between events among only one dimension. Therefore, in this paper, we propose to take multidimensional framework into account in order to detect high-level changes like trends. We show that multidimensional sequential pattern mining over data streams can help detecting interesting high-level variations. We demonstrate with empirical results that our approach is able to extract multidimensional sequential patterns with an approximate support guarantee over data streams.
Application of Artificial Neural Networks (ANNs) to Predict Air Quality Classes in Big Cities
Authors: W. Kaminski, J. Skrzypski, E. Jach-Szakiel
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

The aim of the study was to examine the possibilities of the development of a prognostic instrument for the air quality management in big cities. The models ANNs were tested (MLP and RBF type). The study was focused on the development of the neural network models for prediction of the classes of the air quality state in relation to mean daily PM10 concentration. The air quality class was predicted for the next day in relation to mean daily concentrations. The tests were carried out in the city of Lodz in central Poland. The results of the modelling were very satisfactory. In the optimally constructed models false prognosis were only 1.9% in testing series and 1.4% in training series. A low level of error prediction confirmed the fact that the neural network models are an effective instrument of the air quality management in big cities.
3D Shape Recovery with Registration Assisted Stereo Matching
Authors: Huei-Yung Lin, Sung-Chung Liang, Jing-Ren Wu
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

A novel method for simultaneously acquiring and registering range data of a real object from different viewpoints is presented. Currently, most 3D model reconstruction techniques do not cooperate with the existing range data for shape recovery of future viewpoints. In this work, a stereo vision system is developed for 3D model acquisition. To reduce the computation and increase the accuracy of stereo matching algorithms, the recovered range data from previous viewpoints are registered and then used to provide additional constraints for 3D acquisition of the next viewpoint. Experiments have shown that our approach gives better performance on both execution time and stereo matching results.
Computer Vision and Pattern Recognition in Homeland Security Applications
Authors: Giovanni B. Garibotto
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

The tutorial will summarize the status of research and innovation in the field of Security of Computer Vision and Pattern Recognition Technology. Two main research areas are considered: intelligent scene analysis in video-surveillance, and mobile Automatic Number Plate recognition ANPR, for investigation and crime prevention. The lecture will refer the most recent advances of mobile ANPR solutions on board of patrol car as well as portable hand-held devices to improve mobility and flexibility. From the patrol car it is possible to collect vehicle information within the traffic flow with a performance that far exceeds human detection and recognition capabilities in all weather conditions and 24 h operation. Such a solution is currently used by most advanced police departments in the world.
ReCombinatorics: Combinatorial Algorithms for Studying the History of Recombination in Populations
Authors: Dan Gusfield
Venue: Proceedings of the 19th annual symposium on Combinatorial Pattern Matching (2008)

The work discussed in this talk falls into the emerging area of Population Genomics. I will first introduce the area and then talk about specific problems and combinatorial algorithms involved in the inference of recombination from population data.A phylogenetic network (or Ancestral Recombination Graph) is a generalization of a tree, allowing structural properties that are not tree-like. With the growth of genomic and population data (coming for example from the HAPMAP project) much of which does not fit ideal tree models, and the increasing appreciation of the genomic role of such phenomena as recombination (crossing-over and gene-conversion), recurrent and back mutation, horizontal gene transfer, and mobile genetic elements, there is greater need to understand the algorithmics and combinatorics of phylogenetic networks.In this talk I will survey a range of our recent algorithmic, mathematical and practical results on phylogenetic networks with recombination and show applications of these results to several issues in Population Genomics.Various parts of this work are joint work with Satish Eddhu, Chuck Langley, Dean Hickerson, Yun S. Song, Yufeng Wu, V. Bansal, V. Bafna and Z. Ding. All the papers and associated software can be accessed at http://wwwcsif.cs.ucdavis.edu/~gusfield/
Mining Software Aging Patterns by Artificial Neural Networks
Authors: Hisham El-Shishiny, Sally Deraz, Omar Bahy
Venue: Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition (2008)

This paper investigates the use of Artificial Neural Networks (ANN) to mine and predict patterns in software aging phenomenon. We analyze resource usage data collected on a typical long-running software system: a web server. A Multi-Layer Perceptron feed forward Artificial Neural Network was trained on an Apache web server dataset to predict future server swap space and physical free memory resource exhaustion through ANN univariate time series forecasting and ANN nonlinear multivariate time series empirical modeling. The results were benchmarked against those obtained from non-parametric statistical techniques, parametric time series models and other empirical modeling techniques reported in the literature.
Adoption of Mobile TV Services Among Early Users: Convergence of Familiar Technologies and Emergence of Technology Induced Paradoxes
Authors: Claudia Loebbecke, Claudio Huyskens, Sirkka L. Jarvenpaa
Venue: Proceedings of the 2008 7th International Conference on Mobile Business (2008)

With the convergence of telecommunication infrastructures, computer technology, and media content services, mobile TV offerings have become feasible. Mobile TV offerings are defined as real-time broadcast transmissions of content to mobile devices. Research on early adopters suggests that 3Italia's Mobile TV offerings, the world's first nationwide DVBH Mobile TV offerings, are experiencing increasing use, user preferences for time sensitive content, and user satisfaction with content. Our analysis suggests that from a user perspective, Mobile TV offerings represent a convergence of familiar technologies. The familiar nature of offerings may lead to emergence of fewer technology induced paradoxes than what has been found with other mobile services. We find that only two paradoxes appear relevant to Mobile TV use: empowerment / enslavement and engagement /disengagement. Future research must wait for a richer set of paradoxes emerging from a stronger consideration of broadcast technology and services. This paper contributes to innovation research on mobile services.
Taylor-G&ouml;rtler Vortices in the Flow Driven by a Rotating Magnetic Field in a Cylindrical Container
Authors: K. Fraňa, J. Stiller, R. Grundmann
Venue: Journal of Visualization (2005)

Taylor-G&ouml;rtler vortices play an important role in the flow driven by rotating magnetic field in a closed cylindrical container. The visualization of these structures is essential to understand their physics and their impact on the dynamics of the flow. We present a study of various methods for identifying vortex cores, including the so-called &lambda;$_2$ and Q criteria. While &lambda;$_2$ is, probably, the better indicator it is more sensitive to numerical noise and thus less effective in devising 3D vortex structures. Here, the Q criterion proved particularly useful when applied to the fluctuation velocity field.
Queueing network analysis on dynamic lot streaming
Authors: Taofeng Ye
Venue: Computers and Operations Research (2009)

Lot streaming is a technique used to split a production lot into several smaller transfer batches. In this way, processing a product in a multistage serial production system by overlapping production between stages is available. As a result, production can be accelerated. In this paper, a modified N-policyM/G/1 queueing system with a non-reliable server is proposed. With the relevant parameters of this queueing system, the problem of lot streaming in dynamic situations can be solved. To obtain the optimal transfer batch size, a cost objective function including transport cost, repair cost, turning cost, and holding cost is formulated. Further, in order to illustrate the usefulness of the proposed methods, numerical examples are solved. On the basis of the results of these examples, some important conclusions are drawn.
The ImmApp: A Digital Application for Immersive Interaction with Sound Art Archives
Authors: J. Milo Taylor
Venue: Computer Music Modeling and Retrieval. Sense of Sounds: 4th International Symposium, CMMR 2007, Copenhagen, Denmark, August 27-31, 2007. Revised Papers (2008)

This paper introduces a doctoral research project which is developing an innovative digital research methodology based around a MySql [2] database. The project's aim is to deliver an innovative re-presentation of sound art discourse from a digitized, post-modern, post-Cageian perspective.
Managing Branch Versioning in Versioned/Temporal XML Documents
Authors: Luis J. Arévalo Rosado, Antonio Polo Márquez, Jorge Martínez Gil
Venue: Proceedings of the 5th international Symposium on XML Database: Database and XMLTechnologies (2007)

Due to the linear nature of time, XML timestamped solutions for the management of XML versions have difficulty in supporting non-lineal versioning. Following up on our previous work, which dealt with a new technique for the management of non-lineal versions of XML graph documents, called versionstamp, we have gone a step forward by adding temporal information to each version included in the document. Not only does it allow us to query the vDocuments on a temporal and version level but also we can manage branch versioning in the temporal axis. Moreover, to check its functionality, we have compared our technique to a timestamped XML solution and a set of Web services has been developed. The easy management of multiple versioning, the large number of queries in different XML standard query languages and its implementation by using only XML technology, are some of the advantages of the proposed technique.
Mobile Robots and Intelligent Environments
Authors: Francesco Capezio, Fulvio Mastrogiovanni, Antonio Sgorbissa, Renato Zaccaria
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

This paper deals with a knowledge representation architecture for distributed systems. The aim is to adopt a common framework to deal with an "intelligent space", i.e., an ecosystem composed by artificial entities which cooperate to perform an intelligent multi-source data fusion. This information is used to coordinate the behavior of mobile robots and intelligent appliances. The experimental results discuss this interaction with respect to the fulfillment of complex service tasks.
A Simple Model for Sequences of Relational State Descriptions
Authors: Ingo Thon, Niels Landwehr, Luc Raedt
Venue: Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II (2008)

Artificial intelligence aims at developing agents that learn and act in complex environments. Realistic environments typically feature a variable number of objects, relations amongst them, and non-deterministic transition behavior. Standard probabilistic sequence models provide efficient inference and learning techniques, but typically cannot fully capture the relational complexity. On the other hand, statistical relational learning techniques are often too inefficient. In this paper, we present a simple model that occupies an intermediate position in this expressiveness/efficiency trade-off. It is based on CP-logic, an expressive probabilistic logic for modeling causality. However, by specializing CP-logic to represent a probability distribution over sequences of relational state descriptions, and employing a Markov assumption, inference and learning become more tractable and effective. We show that the resulting model is able to handle probabilistic relational domains with a substantial number of objects and relations.
Foundations of C++/CLI: The Visual C++ Language for .NET 3.5, 2 edition
Authors: Gordon Hogenson
Venue: Expert'S Voice In .Net (2008)

Foundations of C++/CLI: The Visual C++ Language for .NET 3.5 introduces C++/CLI, Microsofts extensions to the C++ syntax that allow you to target the common language runtime, the key to the heart of the .NET Framework 3.5. This book gives you a small, fastpaced primer that will kickstart your journey into the world of C++/CLI. In 13 nofluff chapters, Microsoft insiders take readers into the core of the C++/CLI language and explain both how the language elements work and how Microsoft intends them to be used. This book is a beginners guide, but it assumes a familiarity with programming basics. And it concentrates on explaining the aspects of C++/CLI that make it the most powerful and fun language of the .NET Framework. As such, this book is ideal if youre thinking of migrating to C++/CLI from another language. By the end of this book, youll have a thorough grounding in the core language elements together with the confidence to explore further that comes from a solid understanding of a languages syntax and grammar. What youll learn The basics of C++/CLI The objectoriented features of C++/CLI How C++/CLI sits within the .NET Framework 3.5 How to create C++/CLI programs Using STL/CLR Who is this book for Developers wanting to learn C++/CLI