ppxscal/embedding_network huggingface dataset:
Exploring Robustness Enhancements for Logic-Based Passage Filtering
Authors: Ingo Glöckner, Björn Pelzer
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I (2008)

The use of logic in question answering (QA) promises better accuracy of results, better utilization of the document collection, and a straightforward solution for integrating background knowledge. However, the brittleness of the logical approach still hinders its breakthrough into applications. Several proposals exist for making logic-based QA more robust against erroneous results of linguistic analysis and against gaps in the background knowledge: Extracting useful information from failed proofs, embedding the prover in a relaxation loop, and fusion of logic-based and shallow features using machine learning (ML). In the paper, we explore the effectiveness of these techniques for logic-based passage filtering in the LogAnswer question answering system. An evaluation on factual question of QA@CLEF07 reveals a precision of 54.8% and recall of 44.9% when relaxation results for two distinct provers are combined.
Classification and Diagnosis of Heart Sounds and Murmurs Using Artificial Neural Networks
Authors: Juan Martínez-Alajarín, José López-Candel, Ramón Ruiz-Merino
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

Cardiac auscultation still remains today as the basic technique to easily achieve a cardiac valvular diagnosis. Nowadays, auscultation can be powered with automated computer-aided analysis systems to provide objective, accurate, documented and cost-effective diagnosis. This is particulary useful when such systems offer remote diagnosis capabilities. ASEPTIC is a telediagnosis system for cardiac sounds that allows the analysis of remote phonocardiographic signals. The pattern recognition stage of ASEPTIC is presented in this paper. It is based in feature selection from the cardiac events, and classification using a multilayer perceptron artificial neural network trained with Levenberg-Marquardt algorithm for fast convergence. Three categories of records have been considered: normal, with holosystolic murmur, and with midsystolic murmur. Experimental results show high correct classification rates for the three categories: 100%, 92.69%, and 97.57%, respectively.
MagentaToolkit: A Set of Multi-agent Tools for Developing Adaptive Real-Time Applications
Authors: George Rzevski, Petr Skobelev, Vyacheslav Andreev
Venue: Proceedings of the 3rd international conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing (2007)

MagentaToolkit is a set of multi-agent tools based on the adaptive problem solving method, which is capable of solving complex problems characterized by a large number of variables of high variety and dynamics caused by the occurrence of unpredictable events.The Toolkit comprises a Multi-Agent Engine, Virtual Market and Ontology Editor. The Toolkit speeds up substantially the application development process and can be used by programmers without expertise in multi-agent technology. The paper contains the description of MagentaToolkit, outlines principles of application design and operation and presents examples of adaptive applications developed for clients.
Griwes: Generic Model and Preliminary Specifications for a Graph-Based Knowledge Representation Toolkit
Authors: Jean-François Baget, Olivier Corby, Rose Dieng-Kuntz, Catherine Faron-Zucker, Fabien Gandon, Alain Giboin, Alain Gutierrez, Michel Leclère, Marie-Laure Mugnier, Rallou Thomopoulos
Venue: Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning (2008)

Griwes is an initiative to develop a common model and an open-source freeware platform shared by different graph-based frameworks. We provide an overview of its objectives, architecture and specifications. We detail some of the basic mathematical structures that are used to characterize the primitives for graph-based knowledge representation. We then propose to factorize recurrent knowledge representation primitives that can be shared across specific graph-based languages and we provide a proof of concept by showing how two languages (Simple Conceptual Graphs and RDF) can be described in this framework.
On a Graphics Hardware-Based Vortex Detection and Visualization System
Authors: S. Stegmaier, T. Ertl
Venue: Journal of Visualization (2005)

We present a graphics hardware-based system for interactive denoising, vortex detection, and visualization of vector data. No intermediate results need to be read back by the application once the vector field has been loaded onto the graphics adapter. Due to modern GPUs' parallel processing capabilities, our system significantly outperforms software implementations and thus provides a valuable tool for the interactive exploration of vector fields and the understanding of flow structures.
Domain Decomposition Techniques for Parallel Generation of Tetrahedral Meshes
Authors: Barbara Głut, Tomasz Jurczyk
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

We present solutions for dealing with the problem of parallel generation of unstructured meshes for 3D domains. The selected approach is based on a geometric decomposition of the domain where the input data is given in the form of a surface mesh. The difference between the two presented decomposition techniques lies in the step where the actual partitioning takes place. In the first method the partitioning is obtained using solely the surface mesh while in the latter one a coarse tetrahedral mesh is used. After the decomposition and creation of an interface mesh (which is a surface mesh in both approaches) the final volume meshes are generated independently for each subdomain. The interface mesh and the subdomain meshes are constructed using a Riemannian metric combined with a control space structure which allows to generate meshes with varied density and anisotropy [1].
Bayesian System Identification of Molecular Cascades
Authors: Junichiro Yoshimoto, Kenji Doya
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

We present a Bayesian method for the system identification of molecular cascades in biological systems. The contribution of this study is to provide a theoretical framework for unifying three issues: 1) estimating the most likely parameters; 2) evaluating and visualizing the confidence of the estimated parameters; and 3) selecting the most likely structure of the molecular cascades from two or more alternatives. The usefulness of our method is demonstrated in several benchmark tests.
CLEAR'07 Evaluation of USC Human Tracking System for Surveillance Videos
Authors: B. Wu, V. K. Singh, C. -H. Kuo, L. Zhang, S. C. Lee, R. Nevatia
Venue: Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers (2008)

This paper presents the evaluation results of a system for tracking humans in surveillance videos. Moving blobs are detected based on adaptive background modeling. A shape based multi-view human detection system is used to find humans in moving regions. The detected responses are associated to infer the human trajectories. The shaped based human detection and tracking is further enhanced by a blob tracker to boost the performance on persons at a long distance from the camera. Multi-threading techniques are used to speedup the process. Results are given on the video test set of the CLEAR-VACE surveillance human tracking evaluation task.
Visualization of health-subject analysis based on query term co-occurrences
Authors: Jin Zhang, Dietmar Wolfram, Peiling Wang, Yi Hong, Rick Gillis
Venue: Journal of the American Society for Information Science and Technology (2008)

A multidimensional-scaling approach is used to analyze frequently used medical-topic terms in queries submitted to a Web-based consumer health information system. Based on a year-long transaction log file, five medical focus keywords (stomach, hip, stroke, depression, and cholesterol) and their co-occurring query terms are analyzed. An overlap-coefficient similarity measure and a conversion measure are used to calculate the proximity of terms to one another based on their co-occurrences in queries. The impact of the dimensionality of the visual configuration, the cutoff point of term co-occurrence for inclusion in the analysis, and the Minkowski metric power k on the stress value are discussed. A visual clustering of groups of terms based on the proximity within each focus-keyword group is also conducted. Term distributions within each visual configuration are characterized and are compared with formal medical vocabulary. This investigation reveals that there are significant differences between consumer health query-term usage and more formal medical terminology used by medical professionals when describing the same medical subject. Future directions are discussed. &copy; 2008 Wiley Periodicals, Inc.
A Vibrotactile Device for Display of Virtual Ground Materials in Walking
Authors: Yon Visell, Jeremy R. Cooperstock, Bruno L. Giordano, Karmen Franinovic, Alvin Law, Stephen Mcadams, Kunal Jathal, Federico Fontana
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

We present a floor tile designed to provide the impression of walking on different ground materials, such as gravel, carpet, or stone. The device uses affordable and commercially available vibrotactile actuators and force sensors, and as such might one day be cost-effectively used in everyday environments. The control software is based on a lumped model of physical interactions between the foot and the ground surface. We have prototyped a measurement scheme for calibrating the device to match real-world ground materials.
Graph Analysis with High-Performance Computing
Authors: Bruce Hendrickson, Jonathan W. Berry
Venue: Computing in Science and Engineering (2008)

Large, complex graphs arise in many settings including the Internet, social networks, and communication networks. To study such data sets, the authors explored the use of high-performance computing (HPC) for graph algorithms. They found that the challenges in these applications are quite different from those arising in traditional HPC applications and that massively multithreaded machines are well suited for graph problems.
Stereo Saliency Map Considering Affective Factors in a Dynamic Environment
Authors: Young-Min Jang, Sang-Woo Ban, Minho Lee
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

We propose a new integrated saliency map model, which reflects more human-like visual attention mechanism. The proposed model considers not only the binocular stereopsis to construct a final attention area so that the closer attention area can be easily made to pop-out as in human binocular vision, based on the single eye alignment hypothesis, but also both static and dynamic features of an input scene. Moreover, the proposed saliency map model includes an affective computing process to skip an unwanted area and/or to pay attention to a desired area, mimicking the pulvinar's function in the human preference and refusal mechanism in subsequent visual search processes. In addition, we show the effectiveness of using the symmetry feature implemented by a neural network and independent component analysis (ICA) filter to construct more object preferable attention model. The experimental results show that the proposed model can generate more plausible scan paths for natural input scenes.
Analyzing Learners' Self-organization in Terms of Co-construction, Co-operation and Co-ordination
Authors: Patrice Moguel, Pierre Tchounikine, André Tricot
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

We define a pedagogic collective challenge as a CSCL learning situation where: (1) the problem is designed to make learners practice some target domain-related and/or meta-cognitive competencies; (2) a group of learners is involved, as a team, in the solving of the problem; (3) the solving requires the learners to join their forces; (4) the problem and the setting are designed to create a positive tension that motivates learners. Such chall- enges aim at enhancing learners' motivation in involving themselves in the collective solving and, within this process, in knowledge generative interactions such as conflict resolution, explanation or mutual regulation [1].
Online Monitoring: Security or Social Control?
Authors: Michael A. Caloyannides
Venue: IEEE Security and Privacy (2004)

Claims of security not withstanding, governmental Internet monitoring does little to protect ordinary citizens from real online threats. The technology and know-how are freely available for determined users to hide their tracks and protect their legitimate need for and right to privacy while exploring the Internet.
Linear Bandwidth Naccache-Stern Encryption
Authors: Benoît Chevallier-Mames, David Naccache, Jacques Stern
Venue: Proceedings of the 6th international conference on Security and Cryptography for Networks (2008)

The Naccache-Stern (ns) knapsack cryptosystem is an original yet little-known public-key encryption scheme. In this scheme, the ciphertext is obtained by multiplying public-keys indexed by the message bits modulo a prime p. The cleartext is recovered by factoring the ciphertext raised to a secret power modulo p.ns encryption requires a multiplication per two plaintext bits on the average. Decryption is roughly as costly as an rsa decryption. However, ns features a bandwidth sublinear in log p, namely log p/ log log p. As an example, for a 2048-bit prime p, ns encryption features a 233-bit bandwidth for a 59-kilobyte public key size.This paper presents new ns variants achieving bandwidths linear in log p. As linear bandwidth claims a public-key of size log3 p/ log log p, we recommend to combine our scheme with other bandwidth optimization techniques presented here.For a 2048-bit prime p, we obtain figures such as 169-bit plaintext for a 10-kilobyte public key, 255-bit plaintext for a 20-kilobyte public key or a 781-bit plaintext for a 512-kilobyte public key. Encryption and decryption remain unaffected by our optimizations: As an example, the 781-bit variant requires 152 multiplications per encryption.
Existence and Stability of Periodic Solution of Non-autonomous Neural Networks with Delay
Authors: Minghui Jiang, Xiaohong Wang, Yi Shen
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

The paper investigates the existence and global stability of periodic solution of non-autonomous neural networks with delay. Then the existence and uniqueness of periodic solutions of the neural networks are discussed in the paper. Moreover, criterion on stability of periodic solutions of the neural networks is obtained by using matrix function inequality, and algorithm for the criterion on the neural networks is provided. Result in the paper generalizes and improves the result in the existing references. In the end, an illustrate example is given to verify our results.
Robust Speaker Modeling Based on Constrained Nonnegative Tensor Factorization
Authors: Qiang Wu, Liqing Zhang, Guangchuan Shi
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

Nonnegative tensor factorization is an extension of nonnegative matrix factorization(NMF) to a multilinear case, where nonnegative constraints are imposed on the PARAFAC/Tucker model. In this paper, to identify speaker from a noisy environment, we propose a new method based on PARAFAC model called constrained Nonnegative Tensor Factorization (cNTF). Speech signal is encoded as a general higher order tensor in order to learn the basis functions from multiple interrelated feature subspaces. We simulate a cochlear-like peripheral auditory stage which is motivated by the auditory perception mechanism of human being. A sparse speech feature representation is extracted by cNTF which is used for robust speaker modeling. Orthogonal and nonsmooth sparse control constraints are further imposed on the PARAFAC model in order to preserve the useful information of each feature subspace in the higher order tensor. Alternating projection algorithm is applied to obtain a stable solution. Experiments results demonstrate that our method can improve the recognition accuracy specifically in noise environment.
Locally planar graphs are 5-choosable
Authors: Matt DeVos, Ken-ichi Kawarabayashi, Bojan Mohar
Venue: Journal of Combinatorial Theory Series B (2008)

It is proved that every graph embedded in a fixed surface with sufficiently large edge-width is 5-choosable.
Take a ride on the gentoo train
Authors: Mike Diehl
Venue: Linux Journal (2008)

Gentoo, power and flexibility, but not for the faint of heart.
A Formal Approach to Aggregated Belief Formation
Authors: Annerieke Heuvelink, Michel C. Klein, Jan Treur
Venue: Proceedings of the 12th international workshop on Cooperative Information Agents XII (2008)

This paper introduces a formal method to aggregate over basic beliefs, in order to deduce aggregated or complex beliefs as often used in applications. Complex beliefs can represent several things, such as a belief about a period in which other beliefs held or the minimal or maximal certainty with which a belief held. As such they contain richer information than the basic beliefs they are aggregated from and can be used to optimize an agent's search through its memory and its reasoning processes. The developed method can also aggregate over aggregated beliefs, hence nested aggregations are possible. An implementation in Prolog demonstrates its operationality.
Echo State Networks for Real-Time Audio Applications
Authors: Stefano Squartini, Stefania Cecchi, Michele Rossini, Francesco Piazza
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

This paper deals with the employment of Echo State Networks for identification of nonlinear dynamical systems in the digital audio field. The real contribution of the work is that such networks have been implemented and run in real-time on a specific PC based software platform for the first time, up to the authors' knowledge. The nonlinear dynamical systems to be identified in the audio applications here addressed are the mathematical model of a commercial Valve Amplifier and the low-frequency response of a loud-speaker. Experimental results have shown that, at a certain frequency sampling rate, the ESNs considered (after the training procedure performed off-line) are able to tackle the real-time tasks successfully.
Four-Dimensional Processing Tools for Cardiovascular Data
Authors: Steven Wixson
Venue: IEEE Computer Graphics and Applications (1983)

A system capable of displaying animated, interactive, 3-D images of the human cardiovascular system is nearing completion¿a system that uses only well-established technologies.
Markov model of a digital stochastic generator
Authors: V. M. Kuznetsov, V. A. Pesoshin, E. L. Stolov
Venue: Automation and Remote Control (2008)

A stochastic process generator based on a chain of modulo-two adders with asynchronous feedback loops is investigated. The generator dynamics is described by the Erlang equations. A mathematical model of the generated stochastic process is proposed. The implementation of the generator using modern electronic devices is considered.
A Human-Machine Cooperative Approach for Time Series Data Interpretation
Authors: Thomas Guyet, Catherine Garbay, Michel Dojat
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

This paper deals with the interpretation of biomedical multivariate time series for extracting typical scenarios. This task is known to be difficult, due to the temporal nature of the data at hand, and to the context-sensitive aspect of data interpretation, which hamper the formulation of a priori knowledge about the kind of patterns to detect and their interrelations. A new way to tackle this problem is proposed, based on a collaborative approach between a human and a machine by means of specific annotations. Two grounding principles, namely autonomy and knowledge discovery, support the co-construction of successive abstraction levels for data interpretation. A multi-agent system is proposed to implement effectively these two principles. Respiratory time series data (Flow, Paw) have been explored with our system for patient/ventilator asynchronies characterization studies.
Modeling Workflows, Interaction Patterns, Web Services and Business Processes: The ASM-Based Approach
Authors: Egon Börger, Bernhard Thalheim
Venue: Proceedings of the 1st international conference on Abstract State Machines, B and Z (2008)

We survey the use of the Abstract State Machines (ASM) method for a rigorous foundation of modeling and validating web services, workflows, interaction patterns and business processes. We show in particular that one can tailor business process definitions in application-domain yet rigorous terms in such a way that the resulting ASM models can be used as basis for binding contracts between domain experts and IT technologists. The method combines the expressive power and accuracy of rule-based modeling with the intuition provided by visual graph-based descriptions. We illustrate this by an ASM-based semantical framework for the OMG standard for BPMN (Business Process Modeling Notation). The framework supports true concurrency, heterogeneous state and modularity (compositional design and verification techniques). As validation example we report some experiments, carried out with a special-purpose ASM simulator, to evaluate various definitions proposed in the literature for the critical OR-join construct of BPMN.
Microstrip patch antenna for a retinal prosthesis
Authors: S. Raghavan, G. Anantha Kumar
Venue: Proceedings of the 7th WSEAS International Conference on Instrumentation, Measurement, Circuits and Systems (2008)

This paper is about the investigation of a novel approach for establishing a data telemetry link in a dual-unit retinal prosthesis at microwave frequencies (1.4GHz and 2.35GHz) using a pair of Microstrip patch antennas. Approximately sized extraocular (25mm × 25 mm) and intraocular (6mm × 6mm) antennas are simulated using IE3D and compared with reference experimental results which was designed and fabricated using the Finite Difference Time Domain Method.
Boltzmann Machine Incorporated Hybrid Neural Fuzzy System for Hardware/Software Partitioning in Embedded System Design
Authors: Yue Huang, Yong-Soo Kim
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

Nowadays one of the most vital problems in embedded system co-design is Hardware/Software (HW/SW) partitioning. Due to roughly assumed parameters in design specification and imprecise benchmarks for judging the solution's quality, embedded system designers have been working on finding a more efficient method for HW/SW partitioning for years. We propose an application of a hybrid neural fuzzy system incorporating Boltzmann machine to the HW/SW partitioning problem. Its architecture and performance estimation against other popular algorithm are evaluated. The simulation result shows the proposed system outperforms other algorithm both in cost and performance.