ppxscal/embedding_network huggingface dataset:
Control of frictional dynamics of a one-dimensional particle array
Authors: Yi Guo, Zhihua Qu
Venue: Automatica (Journal of IFAC) (2008)

Control of frictional forces is required in many applications of tribology. While the problem is approached by chemical means traditionally, a recent approach was proposed to control the system mechanically to tune frictional responses. We design feedback control laws for a one-dimensional particle array sliding on a surface subject to friction. The Frenkel-Kontorova model describing the dynamics is a nonlinear interconnected system and the accessible control elements are average quantities only. We prove local stability of equilibrium points of the un-controlled system in the presence of linear and nonlinear particle interactions, respectively. We then formulate a tracking control problem, whose control objective is for the average system to reach a designated targeted velocity using accessible elements. Sufficient stabilization conditions are explicitly derived for the closed-loop error systems using the Lyapunov theory based methods. Simulation results show satisfactory performances. The results can be applied to other physical systems whose dynamics is described by the Frenkel-Kontorova model.
Pure Iteration and Periodicity
Authors: Mathias Barra
Venue: Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms (2008)

We define a hierarchy of small sub-recursive classes, based on the schema of pure iteration. is compared with a similar hierarchy, based on primitive recursion, for which a collapse is equivalent to a collapse of the small Grzegorczyk-classes. Our hierarchy does collapse, and the induced relational class is shown to have a highly periodic structure; indeed a unary predicate is decidable in iff it is definable in Presburger Arithmetic. The concluding discussion contrasts our findings to those of Kutyłowski [12].
AttributeTrust A Framework for Evaluating Trust in Aggregated Attributes via a Reputation System
Authors: Apurva Mohan, Douglas M. Blough
Venue: Proceedings of the 2008 Sixth Annual Conference on Privacy, Security and Trust (2008)

To enable a rich attribute-based authorization system, it is desirable that a large number of user attributes are available, possibly provided by multiple entities. The user may be required to aggregate his attributes and present them to a service provider to prove he has the right to access some service. In this paper, we present Attribute Trust – a policy-based privacy enhanced framework for aggregating user attributes and evaluating confidence in these attributes. We envision a future where attribute providers will be commonplace and service providers will face the problem of choosing one among multiple attribute providers that can provide the same user attribute. In Attribute Trust, we address this problem by means of a reputation system model based on transitive trust. Entities express confidence in other entities to supply trusted attributes, forming chains from a service provider to different attribute providers. A service provider uses this transitive reputation to decide whether to accept a particular attribute from a specific attribute provider.We discuss how the Attribute Trust model prevents common attacks on reputation systems. Attribute Trust differs from the current approaches by deriving its attack resistance from its specific context of attribute provisioning, its voting mechanism formulation, and unique properties of its confidence relationships.
Minimal Feedback During Tutorial Dialogue
Authors: Pamela Jordan, Diane Litman
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

We analyzed unexpected student responses to a natural language (NL) ITS to determine if improved feedback could be beneficial. Our analysis of a corpus of ITS-student dialogues suggests that unexpected responses represent learning opportunities. We outline our plans for testing feedback appropriate to subclassifications of these responses.
PowerUp: an accessible virtual world
Authors: Shari Trewin, Vicki L. Hanson, Mark R. Laff, Anna Cavender
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

PowerUp is a multi-player virtual world educational game with a broad set of accessibility features built in. This paper considers what features are necessary to make virtual worlds usable by individuals with a range of perceptual, physical, and cognitive disabilities. The accessibility features were included in the PowerUp game and validated, to date, with blind and partially sighted users. These features include in-world navigation and orientation tools, font customization, self-voicing text-to-speech output, and keyboard-only and mouse-only navigation. We discuss user requirements gathering, the validation study, and further work needed.
Novel results in short-range visualization and vision systems based on gated imaging
Authors: Andrzej Sluzek, Tan Ching Seong
Venue: Proceedings of the 6th WSEAS International Conference on Applied Electromagnetics, Wireless and Optical (2008)

Visibility enhancement using gated images has been known for at least 20 years. The majority of gated imaging systems are used to enhance human vision under extremely difficult conditions (fog, turbid water, strong ambient light, etc.). In most of the reported applications the intended ranges of gated-imaging systems are rather long so that a simplified model of gated imaging can be used. Moreover, no attempts have been reported on methods more sophisticated than just capturing images using gated imaging. In this paper, we present selected results expanding areas of typical applications. First, we briefly discuss and explain the theory of short-range gated imaging. In vision-related applications, short-range gated imaging is needed only in high turbidity conditions so that we focus on gated imaging in highly turbid media. Secondly, we propose a technique for automatic image fusion using a sequence of gated images captured by a precisely controlled pulsed laser. The fusion of several images can provide good quality of visualization over a wide range of depths. A feasibility-study system build using this principle will be briefly discussed. We believe that the proposed methods are a significant step towards system capable of providing visibility in extremely difficult scenarios (e.g. inspecting areas of turbulent liquids, seeing through almost non-transparent liquids, etc.).
Stabilized finite element methods with anisotropic mesh refinement for the Oseen problem
Authors: Thomas Apel, Tobias Knopp, Gert Lube
Venue: Applied Numerical Mathematics (2008)

Nonstationary incompressible flow problems can be split into auxiliary problems of Oseen type. We present the analysis of conforming stabilized Galerkin methods of SUPG/PSPG-type with equal-order interpolation of velocity/pressure and with emphasis on structured anisotropic mesh refinement in boundary layers. We prove a modified inf-sup condition with a constant independent of the viscosity and of critical parameters of the mesh. Numerical tests support the results.
Multilayered visuo-haptic hair simulation
Authors: Ugo Bonanni, Melanie Montagnol, Nadia Magnenat-Thalmann
Venue: The Visual Computer: International Journal of Computer Graphics (2008)

Over the last fifteen years, research on hair simulation has made great advances in the domains of modeling, animation and rendering, and is now moving towards more innovative interaction modalities. The combination of visual and haptic interaction within a virtual hairstyling simulation framework represents an important concept evolving in this direction. Our visuo-haptic hair interaction framework consists of two layers which handle the response to the user&#x2019;s interaction at a local level (around the contact area), and at a global level (on the full hairstyle). Two distinct simulation models compute individual and collective hair behavior. Our multilayered approach can be used to efficiently address the specific requirements of haptics and vision. Haptic interaction with both models has been tested with virtual hairstyling tools.
Brief paper: Efficient computation of l1 uncertainty model from an impulse response set
Authors: Marco Casini, Andrea Garulli, Antonio Vicino
Venue: Automatica (Journal of IFAC) (2008)

In this paper the problem of constructing the minimum @?"1 uncertainty model containing a finite set of assigned models is addressed. This problem is relevant to @?"1 robust control design techniques, in order to minimize the size of the uncertainty set associated to the nominal plant. The problem is formulated as a (conditional) Chebyshev center problem and an algorithm for its solution is proposed. The algorithm converges in a finite number of steps showing computational efficiency for large size problems.
Mean q-Ball Strings Obtained by Constrained Procrustes Analysis with Point Sliding
Authors: Irina Kezele, Cyril Poupon, Muriel Perrin, Yann Cointepas, Vincent Kouby, Fabrice Poupon, Jean-François Mangin
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

The idea underpinning the work we present herein is to design robust and objective tools for brain white matter (WM) morphometry. We focus on WM tracts, and propose to represent them by their mean lines, to which we associate the attributes derived from high-angular resolution diffusion imaging (HARDI). The definition of the tract mean line derives directly from the geometry of the tract fibres. We determine the fibre point correspondences and impact factors of individual fibres, upon which we estimate average HARDI models along the tract mean lines. This way we obtain a compact tract representation that exploits all the available information, and is at the same time free of the outlier influence and undesired tract edge effects.
Modeling Aceto-White Temporal Patterns to Segment Colposcopic Images
Authors: Héctor-Gabriel Acosta-Mesa, Nicandro Cruz-Ramírez, Rodolfo Hernández-Jiménez, Daniel-Alejandro García-López
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

Colposcopy test is the second most used technique to diagnose cervical cancer disease. Some researchers have proposed to use temporal changes intrinsic to the colposcopic image sequences to automatically characterize cervical lesion. Under this approach, every single pixel on the image is represented as a Time Series of length equal to the sampling frequency times acquisition points. Although this approach seems to show promising results, the data analysis procedures have to deal with huge data set that rapidly increase with the number of cases (patients) considered in the analysis. In the present work, we perform principal component analysis (PCA) to reduce the dimensionality of the data in order to facilitate similarity measures for classification and clustering. The importance of this work is that we propose a model to parameterize the dynamics of the system using an efficient representation getting a 1.11% data compression ratio and similarity on clustering of 0.78. The feasibility of the proposed model is shown testing the similarity of the clusters generated using the k-means algorithm over the raw data and the compressed representation of real data.
Discussing Redundancy Issues in Intelligent Agent-Based Non-traditional Grids
Authors: Versavia Ancusa, Razvan Bogdan, Mircea Vladutiu
Venue: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II (2008)

In this paper is presented an improved model of ambient intelligent based on non-traditional Grids. It is studied the fault tolerance of the proposed model taking into account the redundancy at link level.
A Parallel Monte-Carlo Tree Search Algorithm
Authors: Tristan Cazenave, Nicolas Jouandeau
Venue: Proceedings of the 6th international conference on Computers and Games (2008)

Monte-Carlo Tree Search is a powerful paradigm for the game of Go. In this contribution we present a parallel Master-Slave algorithm for Monte-Carlo Tree Search and test it on a network of computers using various configurations: from 12,500 to 100,000 playouts, from 1 to 64 slaves, and from 1 to 16 computers. On our own architecture we obtain a speedup of 14 for 16 slaves. With a single slave and five seconds per move our algorithm scores 40.5% against GNU Go, with sixteen slaves and five seconds per move it scores 70.5%. At the end we give the potential speedups of our algorithm for various playout times.
A Software-Based Trusted Platform Module Emulator
Authors: Mario Strasser, Heiko Stamer
Venue: Proceedings of the 1st international conference on Trusted Computing and Trust in Information Technologies: Trusted Computing - Challenges and Applications (2008)

When developing and researching new trusted computing technologies, appropriate tools to investigate their behavior and to evaluate their performance are of paramount importance. In this paper, we present an efficient and portable TPM emulator for Unix. Our emulator enables not only the implementation of flexible and low-cost test-beds and simulators but, in addition, provides programmers of trusted systems with a powerful testing and debugging tool that can also be used for educational purposes. Thanks to its portability and interoperability, the TPM emulator runs on a variety of platforms and is compatible with the most relevant software packages and interfaces.
PCPs with small soundness error
Authors: Irit Dinur
Venue: ACM SIGACT News (2008)

The soundness error of a PCP verifier is the probability (usually denoted ε) that the verifier accepts an incorrect input. We are interested in the smallest possible values of ε for which the PCP theorem holds, and in particular whether the theorem holds when ε is an inverse polynomial function of the input length. We discuss the 'sliding scale conjecture' of [BGLR93, LY94] and related questions. We then sketch some of the existing approaches and constructions of PCPs with sub-constant soundness error.
Easy Efficiency-Enhancement Technique for the ECGA
Authors: Vinícius V. de Melo, Alexandre C. B. Delbem
Venue: Proceedings of the 2008 10th Brazilian Symposium on Neural Networks (2008)

Several works have shown that population size affects the performance and efficiency of evolutionary optimization algorithms. There are works in the literature proposing techniques for the determination of the best size of a population using complex equations or synthetic benchmarks. Nevertheless, higher population size usually lead to more function evaluations and higher running time. On the other hand, lower population size in general implies a poor sampling of the search space and premature convergence of the algorithm. This paper investigates the influence of the first population on estimation of distribution algorithms. The basic idea is that the first population has a very larger effect on the estimation of distribution than the remaining populations. We analyzed the effects produced on an ECGA by different population sizes and distribution functions in the first population. We verified that the running population size can be smaller than the one estimated by the authors of the ECGA, if a larger initial population is used. Thus, it is possible the development of ECGAs requiring relatively lower running time and evaluations without decreasing the success rate. Therefore, the knowledge provided by this work can largely contribute for the improvement of general estimation of distribution algorithms.
Learning Block-Preserving Outerplanar Graph Patterns and Its Application to Data Mining
Authors: Hitoshi Yamasaki, Yosuke Sasaki, Takayoshi Shoudai, Tomoyuki Uchida, Yusuke Suzuki
Venue: Proceedings of the 18th international conference on Inductive Logic Programming (2008)

An outerplanar graph is a planar graph which can be embedded in the plane in such a way that all of vertices lie on the outer boundary. Many chemical compounds are known to be expressed by outerplanar graphs. We proposed a block preserving outerplanar graph pattern (bpo- graph pattern, for short) as a graph pattern common to a set of outerplanar graphs like a dataset of chemical compounds. In this paper, firstly we give a polynomial time algorithm for finding a minimally generalized bpo- graph pattern explaining a given set of outerplanar graphs. Secondly we give a pattern mining algorithm for enumerating all maximal frequent bpo- graph patterns in a set of outerplanar graphs. Finally, in order to show the performance of the pattern mining algorithm, we report experimental results on chemical datasets.
CoCoME - The Common Component Modeling Example
Authors: Sebastian Herold, Holger Klus, Yannick Welsch, Constanze Deiters, Andreas Rausch, Ralf Reussner, Klaus Krogmann, Heiko Koziolek, Raffaela Mirandola, Benjamin Hummel, Michael Meisinger, Christian Pfaller
Venue: The Common Component Modeling Example: Comparing Software Component Models (2007)

The example of use which was chosen as the Common Component Modeling Example (CoCoME) and on which the several methods presented in this book should be applied was designed according to the example described by Larman in [1]. The description of this example and its use cases in the current chapter shall be considered under the assumption that this information was delivered by a business company as it could be in the reality. Therefore the specified requirements are potentially incomplete or imprecise.
KCK-Means: A Clustering Method Based on Kernel Canonical Correlation Analysis
Authors: Chuan-Liang Chen, Yun-Chao Gong, Ying-Jie Tian
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Kernel Canonical Correlation Analysis (KCCA) is a technique that can extract common features from a pair of multivariate data, which may assist in mining the ground truth hidden in the data. In this paper, a novel partitioning clustering method called KCK-means is proposed based on KCCA. We also show that KCK-means can not only be run on two-view data sets, but also it performs excellently on single-view data sets. KCK-means can deal with both binary-class and multi-class clustering tasks very well. Experiments with three evaluation metrics are also presented, the results of which reflect the promising performance of KCK-means.
Weights and Topology: A Study of the Effects of Graph Construction on 3D Image Segmentation
Authors: Leo Grady, Marie-Pierre Jolly
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Graph-based algorithms have become increasingly popular for medical image segmentation. The fundamental process for each of these algorithms is to use the image content to generate a set of weights for the graph and then set conditions for an optimal partition of the graph with respect to these weights. To date, the heuristics used for generating the weighted graphs from image intensities have largely been ignored, while the primary focus of attention has been on the details of providing the partitioning conditions. In this paper we empirically study the effects of graph connectivity and weighting function on the quality of the segmentation results. To control for algorithm-specific effects, we employ both the Graph Cuts and Random Walker algorithms in our experiments.
Speech Emotion Recognition System Based on BP Neural Network in Matlab Environment
Authors: Guobao Zhang, Qinghua Song, Shumin Fei
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

An emotion recognition system based on BP neural network to recognize special human affective states existed in the speech signal is presented in this paper. About 600 short sentences with different contents in different emotional speeches from 4 speakers are collected for training and testing the feasibility of the system. The energy, pitch and speech rate characteristics are extracted from these speech signals. angry, calm, happy, sad, and surprise as the 5 typical emotions are classified with BP Neural network. In order to update automatically the emotion recognition system with time, an additional study step, just as the feed-back control, is adopted to train the finished network again according to the output. The experiments show that the system is of satisfactory emotion detection performance for some emotions.
Application-Layer Traffic Analysis of a Peer-to-Peer System
Authors: Dietmar Tutsch, Gilbert Babin, Peter Kropf
Venue: IEEE Internet Computing (2008)

Characterizing traffic behavior helps to optimize the network architecture for improved performance. Using a modified LimeWire servent (for both the server and client) and a variance-time plot for traffic characterization, the authors analyze the Gnutella protocol's traffic shape and find that the messages exhibit a self-similar shape. This result shows network designers that they need to consider the self-similar traffic shape in their set-up — for instance, by introducing appropriate buffer sizes.
The SRI-ICSI Spring 2007 Meeting and Lecture Recognition System
Authors: Andreas Stolcke, Xavier Anguera, Kofi Boakye, Özgür Çetin, Adam Janin, Mathew Magimai-Doss, Chuck Wooters, Jing Zheng
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)

We describe the latest version of the SRI-ICSI meeting and lecture recognition system, as was used in the NIST RT-07 evaluations, highlighting improvements made over the last year. Changes in the acoustic preprocessing include updated beamforming software for processing of multiple distant microphones, and various adjustments to the speech segmenter for close-talking microphones. Acoustic models were improved by the combined use of neural-net-estimated phone posterior features, discriminative feature transforms trained with fMPE-MAP, and discriminative Gaussian estimation using MPE-MAP, as well as model adaptation specifically to nonnative and non-American speakers. The net effect of these enhancements was a 14-16% relative error reduction on distant microphones, and a 16-17% error reduction on close-talking microphones. Also, for the first time, we report results on a new "coffee break" meeting genre, and on a new NIST metric designed to evaluate combined speech diarization and recognition.
A Splitting Scheme for Large-Scale Atmosphere Dynamics Models
Authors: Andrei Bourchtein, Ludmila Bourchtein
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

Splitting techniques are applied in the context of the semi-Lagrangian semi-implicit approach in order to design computationally efficient and accurate numerical scheme for large-scale atmosphere dynamics. Description of the constructed numerical algorithm is provided and its properties of accuracy and stability are discussed. Performed numerical experiments with daily gridded atmospheric data showed that the developed scheme is efficient and supplies accurate forecast fields using time steps up to one hour.
The Analysis of Technology Progress and Production of Chinese Citrus Fruit
Authors: Xiaoyin Wang, Yuhong Li, Chunjie Qi
Venue: Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology (2008)

This paper has figured out the output elasticity values of input factors of Chinese production using the model of widespread C-D production function and the input-output data of Chinese citrus fruit in recent 20 years. They are the output elasticity of capital, that of labor and that of planting land. And their values are respectively 0.31, 0.27 and 1.52. Furthermore, this paper has figured out the average rate 4.165% of science and technology and the contribution rate 49.73% of science and technology through the formula deduced by total factor production and used to figure out the progress of science and technology. According to the research, this paper has ended up with some constructive recommendations.