ppxscal/embedding_network huggingface dataset:
MP3 Players and Audio Games: An Alternative to Portable Video Games Console for Visually Impaired Players
Authors: Alexis Sepchat, Simon Descarpentries, Nicolas Monmarché, Mohamed Slimane
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

Both the evolutions of technologies and the increase of the Web download market have led to a democratisation of digital audio players throughout the world. Smaller and lighter, this media has become the best companion to listen his (her) favorite music everywhere. Indeed, thanks to the improvement of their performances, currently, they can be used to watch videos, to store data, etc. Among these new applications, it is imaginable to use them as a portable audio games console. Audio games are still the main solution for visually impaired players to play computer games. This paper introduces our contribution to elaborate an audio games console, accessible for visually impaired players, based on digital audio players.
Mining Unexpected Web Usage Behaviors
Authors: Dong (Haoyuan) Li, Anne Laurent, Pascal Poncelet
Venue: Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects (2008)

Recently, the applications of Web usage mining are more and more concentrated on finding valuable user behaviors from Web navigation record data, where the sequential pattern model has been well adapted. However with the growth of the explored user behaviors, the decision makers will be more and more interested in unexpected behaviors, but not only in those already confirmed. In this paper, we present our approach USER, that finds unexpected sequences and implication rules from sequential data with user defined beliefs, for mining unexpected behaviors from Web access logs. Our experiments with the belief bases constructed from explored user behaviors show that our approach is useful to extract unexpected behaviors for improving the Web site structures and user experiences.
Ball Mill Load Measurement Using Self-adaptive Feature Extraction Method and LS-SVM Model
Authors: Gangquan Si, Hui Cao, Yanbin Zhang, Lixin Jia
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Ball mill load is the most important parameter optimized in the Ball Mill Pulverizing System (BMPS) in Thermal Power Plant. The accurate measurement of ball mill load is imperative and difficult. The approach based on self-adaptive feature extraction algorithm for noise signal and LS-SVM model is proposed to achieve this purpose. By analyzing the sensitivity distributions of working condition transitions, the characteristic power spectrum (CPS) is obtained. Then the self-adaptive weights can be calculated based on the CPS and the centroid frequency. The extracted features of the mill noise using this method show good adaptability to working condition transitions. Further more, softsensing models are built by combining a LS-SVM model and various feature extraction methods so as to estimate the mill load. Experimental results show that the performance of the model combined with the proposed extraction method is better than that with other methods.
Introduction to Advances in Geosensor Networks
Authors: Silvia Nittel, Alexandros Labrinidis, Anthony Stefanidis
Venue: GeoSensor Networks: Second International Conference, GSN 2006, Boston, MA, USA, October 1-3, 2006, Revised Selected and Invited Papers (2008)

Advances in microsensor technology as well as the development of miniaturized computing platforms enable us to scatter numerous untethered sensing devices in hard to reach terrains, and continuously collect geospatial information in never before seen spatial and temporal scales. These geosensor network technologies are revolutionizing the way that geospatial information is collected, analyzed and integrated, with the geospatial content of the information being of fundamental importance. Analysis and event detection in a geosensor network may be performed in real-time by sensor nodes, or off-line in several distributed, in-situ or centralized base stations.
Secure Forwarding in DHTs - Is Redundancy the Key to Robustness?
Authors: Marc Sànchez-Artigas, Pedro García-López, Antonio G. Skarmeta
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

The provisioning of techniques for secure message forwarding over Distributed Hash Tables has been a research concern for a long time. Several techniques have been developed and evaluated, but typically each based on the increase of redundancy as a defense against data forwarding attacks. Although the security vigor of these solutions, they have left the scalability aspect largely unaddressed, as the weak peers may not support the congestion caused by the increase on redundancy. In this article, we take the opposite tack and discuss why improving the quality of delivery paths can achieve a resilience comparable to redundant routing. To prove our intuition, we confront the two strategies and develop a representative algorithm of each category. Further, we validate our work using two other existing protocols that increase redundancy (more independent paths) to fortify routing. Our results reveal that improving the quality of paths can be as effective as increasing redundancy but with minimum overhead.
Abstract Geometrical Computation and the Linear Blum, Shub and Smale Model
Authors: Jérôme Durand-Lose
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

Abstract geometrical computation naturally arises as a continuous counterpart of cellular automata. It relies on signals (dimensionless points) traveling at constant speed in a continuous space in continuous time. When signals collide, they are replaced by new signals according to some collision rules. This simple dynamics relies on real numbers with exact precision and is already known to be able to carry out any (discrete) Turing-computation. The Blum, Shub and Small (BSS) model is famous for computing over ℝ (considered here as a ℝ unlimited register machine) by performing algebraic computations. We prove that signal machines (set of signals and corresponding rules) and the infinite-dimension linear (multiplications are only by constants) BSS machines can simulate one another.
Multilevel algorithms for linear ordering problems
Authors: Ilya Safro, Dorit Ron, Achi Brandt
Venue: Journal of Experimental Algorithmics (JEA) (2009)

Linear ordering problems are combinatorial optimization problems that deal with the minimization of different functionals by finding a suitable permutation of the graph vertices. These problems are widely used and studied in many practical and theoretical applications. In this paper, we present a variety of linear--time algorithms for these problems inspired by the Algebraic Multigrid approach, which is based on weighted-edge contraction. The experimental result for four such problems turned out to be better than every known result in almost all cases, while the short (linear) running time of the algorithms enables testing very large graphs.
Invariants for Parameterised Boolean Equation Systems
Authors: Simona Orzan, Tim A. Willemse
Venue: Proceedings of the 19th international conference on Concurrency Theory (2008)

The concept of invariance for Parameterised Boolean Equation Systems (PBESs) is studied in greater detail. We identify a weakness with the associated theory and fix this problem by proposing a stronger notion of invariance called global invariance. A precise correspondence is proven between the solution of a PBES and the solution of its invariant-strengthened version; this enables one to exploit global invariants when solving PBESs. Furthermore, we show that global invariants are robust w.r.t. all common PBES transformations and that the existing encodings of verification problems into PBESs preserve the invariants of the processes involved. These traits provide additional support for our notion of global invariants, and, moreover, provide an easy manner for transferring (e.g. automatically discovered) process invariants to PBESs. Several examples are provided that illustrate the advantages of using global invariants in various verification problems.
Application of Cross-Language Criteria for the Automatic Distinction of Expert and Non Expert Online Health Documents
Authors: Natalia Grabar, Sonia Krivine
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

Distinction between expert and non expert documents is an important issue in the medical area, for instance in the context of information retrieval. In our work we address this issue through stylistic corpus analysis and application of machine learning algorithms. Our hypothesis is that this distinction can be observed on the basis of a little number of criteria and that such criteria can be language and domain independent. The used criteria have been acquired in source corpus (Russian) and then tested on source and target (French) corpora. The method shows up to 90% precision and 93% recall, and 85% precision and 74% recall in source and target corpora.
A Modified RBF Neural Network and Its Application in Radar
Authors: Yang Jun, Ma Xiaoyan, Lu Qianhong, Liu Bin, Deng Bin
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

Aiming at the problem of parameter estimation in radar detection, a modified RBF neural network is proposed to estimate parameter accurately because of its good approximation ability to random nonlinear function and quick convergence speed. Two classical detection methods, which widely used in radar field, are listed in this paper, and their corresponding parameters are estimated with modified RBF neural network. Theoretical analysis and numerical results both show that the proposed method has good parameter estimation accuracy and quick convergence speed.
Transformations in Reconfigurable Place/Transition Systems
Authors: Ulrike Prange, Hartmut Ehrig, Kathrin Hoffmann, Julia Padberg
Venue: Concurrency, Graphs and Models: Essays Dedicated to Ugo Montanari on the Occasion of His 65th Birthday (2008)

Reconfigurable place/transition systems are Petri nets with initial markings and a set of rules which allow the modification of the net during runtime in order to adapt the net to new requirements. For the transformation of Petri nets in the double pushout approach, the categorical framework of adhesive high-level replacement systems has been instantiated to Petri nets. In this paper, we show that also place/transition systems form a weak adhesive high-level replacement category. This allows us to apply the developed theory also to tranformations within reconfigurable place/transition systems.
Designing an information system for Grids: Comparing hierarchical, decentralized P2P and super-peer models
Authors: Carlo Mastroianni, Domenico Talia, Oreste Verta
Venue: Parallel Computing (2008)

As deployed Grids increase from 10s to 1000s of nodes, the construction of an efficient and scalable information system is a key issue, as it is vital for providing querying and discovery services. Today most Grids adopt a centralized or hierarchical model for their information system, but this model is characterized by poor scalability, resiliency and load-balancing features. Nowadays the research and development community is heading towards the use of scalable information systems based on distributed models such as the decentralized peer-to-peer (P2P) model and the super-peer model. If the former is adopted, each node can act both as a client and a server as it can generate discovery requests and also respond to requests issued by other peers. Requests and responses are forwarded with a hop-by-hop mechanism by ad hoc Grid Services hosted by Grid nodes. The super-peer model is a recently proposed approach that combines features of centralized and P2P models. A super-peer acts as a server for a single Grid organization, and publishes metadata describing the resources provided by the nodes of that organization. At the same time, super-peers connect to each other to form a P2P network at a higher level. This paper analyzes information systems based on three alternative models: the hierarchical, the decentralized P2P, and the super-peer model. A performance evaluation of such models is reported, and afterwards a performance comparison is discussed in order to analyze the pros and cons of each solution.
Assembly Code Analysis Using Stochastic Process Algebra
Authors: Lamia Djoudi, Leïla Kloul
Venue: Proceedings of the 5th European Performance Engineering Workshop on Computer Performance Engineering (2008)

Currently compilers contain a large number of optimisations which are based on a set of heuristics that are not guaranteed to be effective to improve the performance metrics. In this paper, we propose a strategy which allows us the analysis and the choice of the best optimisation, by focusing on the hot part of an assembly code. In our approach, for each optimisation applied, the code of the hot loop is extracted and its dependency graph generated. Finally, and in order to select the best optimisation, the generated graphs are analytically analysed using stochastic process algebra.
Voice Browser for Groupware Systems: VoBG - A Simple Groupware Client for Visually Impaired Students
Authors: Makoto Kobayashi
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

A dedicated browser application named Voice Browser for Groupware systems (VoBG) was developed. The target users are visually impaired persons who are computer novices. This browser is a client application for a specified groupware system named Garoon 2, which is one of the most popular groupware system packages in Japan. The groupware is Web-based system and basically accessible for the visually impaired users. However, the structure of each Web page generated by the groupware server is too complicated to get information exactly for beginners with visual impairment. To solve this problem, VoBG reduces information of these pages using information of HTML tags, and reconstructs each page to understandable format for the target users.
Geometric construction of quintic parametric B-splines
Authors: Isabella Cravero, Carla Manni, M. Lucia Sampoli
Venue: Journal of Computational and Applied Mathematics (2008)

The aim of this paper is to present a new class of B-spline-like functions with tension properties. The main feature of these basis functions consists in possessing C^3 or even C^4 continuity and, at the same time, being endowed by shape parameters that can be easily handled. Therefore they constitute a useful tool for the construction of curves satisfying some prescribed shape constraints. The construction is based on a geometric approach which uses parametric curves with piecewise quintic components.
Clustering Analysis Using Data Range Aware Seeding and Agglomerative Expectation Maximization
Authors: Hongwei Zhu, Honglei Zhu
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

Expectation maximization (EM) is a local maximization method of the mixture model. When applied to clustering analysis, it generates good results only with reasonably good initialization, which can be produced by hierarchical agglomeration. However, hierarchical agglomeration has poor scalability due to its computational complexity. This paper presents a novel method, called ISOEM, to overcome this limitation. It uses a data range aware seeding algorithm to create an initial classification to initialize an iterative selforganizing process. The process alternates betweenEM and agglomeration coupled with classification EM. Evaluation using two imagery datasets showedthe method had very good performance. The paperalso presents the results of using a skewness measureand a separation-cohesion index as indicators for determiningthe number of clusters in the data.
Time, Wavelet and Hilbert-Huang Domain Analysis of Signals from Ultrasonic Based Equipment for the Non Destructive Evaluation of Concrete and Brick Masonry Walls
Authors: Antonino Musolino, Marco Raugi, Mauro Tucci, Florin Turcu
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

In this paper we compare the effectiveness of the time, wavelet and Hilbert-Huang domain analysis of waveforms from a Non Destructive Test (NDT) equipment. The analysis of the signals from NDT systems is one of the most important activities in the recognition of the presence of possible defects that are usually associated with the presence of echoes from the defects themselves. Very often the echoes traveling back to the sensors are superimposed with the signal from the transducer. We analyze the waveforms obtained by couples of sensors in order to extract the echoes and to recognize the points were they originate. Data are obtained by a measurement campaign on a concrete wall and on masonry specimens of different texture and thickness.
The SSEC in Historical Perspective
Authors: Charles J. Bashe
Venue: IEEE Annals of the History of Computing (1982)

The Selective Sequence Electronic Calculator (SSEC) was the first machine to combine electronic computation with a stored program, and the first machine capable of operating on its own instructions as data. When placed in operation in 1948, and for some time thereafter, it was the most flexible and powerful computer in existence. IBM published relatively little about it, and the SSEC has been largely overlooked by computer historians. This paper provides a historical setting for the SSEC.
A Gradient BYY Harmony Learning Algorithm for Straight Line Detection
Authors: Gang Chen, Lei Li, Jinwen Ma
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

Straight line detection is a basic problem in image processing and has been extensively studied from different aspects, but most of the existing algorithms need to know the number of straight lines in an image in advance. However, the Bayesian Ying-Yang (BYY) harmony learning can make model selection automatically during parameter learning for the Gaussian mixture modeling, which can be further applied to detecting the correct number of straight lines automatically by representing the straight lines with Gaussians or Gaussian functions. In this paper, a gradient BYY harmony learning algorithm is proposed to detect the straight lines automatically from an image as long as the pre-assumed number of straight lines is larger than the true one. It is demonstrated by the simulation and real image experiments that this gradient BYY harmony learning algorithm can not only determine the number of straight lines automatically, but also detect the straight lines accurately against noise.
Efficient Incremental Learning Using Self-Organizing Neural Grove
Authors: Hirotaka Inoue, Hiroyuki Narihisa
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

Multiple classifier systems (MCS) have become popular during the last decade. Self-generating neural tree (SGNT) is one of the suitable base-classifiers for MCS because of the simple setting and fast learning. In an earlier paper, we proposed a pruning method for the structure of the SGNT in the MCS to reduce the computational cost and we called this model as self-organizing neural grove (SONG). In this paper, we investigate a performance of incremental learning using SONG for a large scale classification problem. The results show that the SONG can ensure rapid and efficient incremental learning.
Robust Impedance Control of a Delayed Telemanipulator Considering Hysteresis Nonlinearity of the Piezo-actuated Slave Robot
Authors: Reza Seifabadi, Seyed Mehdi Rezaei, Saeed Shiry, Mozafar Saadat, Mohammad Zarei-Nejad, Kamran Razi, Hossein Habibollahi
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

The slave robot in this research is a 1-DOF piezo actuatorwhich includes hysteresis nonlinearity. Nonlinear hysteresis behavior makes robot control a complex task. In this research, the nonlinear and uncertain dynamics of the slave robot has been considered through the teleoperation control loop. LuGre friction model is used as the estimator of the hysteresis loop. An impedance controller for the master side and a sliding-mode-based impedance controller for the slave side have been proposed. The latter is a sliding mode controller, because the plant is nonlinear and uncertain. Also, it is an impedance controller providing both high performances during contact and excellent tracking in free space motion. These controllers make teleoperator robustly stable against uncertainties and bounded constant time delay. Meanwhile, scaling factors, known as sources of instability, have no disturbing effect. After canceling the nonlinear term out of the teleoperator by the controllers, stability of the entire system will be guaranteed by Llewellyn's absolute stability criterion. Performance of the proposed controllers is investigated through simulation.
A Local Search Based Evolutionary Multi-objective Optimization Approach for Fast and Accurate Convergence
Authors: Karthik Sindhya, Kalyanmoy Deb, Kaisa Miettinen
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

A local search method is often introduced in an evolutionary optimization technique to enhance its speed and accuracy of convergence to true optimal solutions. In multi-objective optimization problems, the implementation of a local search is a non-trivial task, as determining a goal for the local search in presence of multiple conflicting objectives becomes a difficult proposition. In this paper, we borrow a multiple criteria decision making concept of employing a reference point based approach of minimizing an achievement scalarizing function and include it as a search operator of an EMO algorithm. Simulation results with NSGA-II on a number of two to four-objective problems with and without the local search approach clearly show the importance of local search in aiding a computationally faster and more accurate convergence to Pareto-optimal solutions. The concept is now ready to be coupled with a faster and more accurate diversity-preserving procedure to make the overall procedure a competitive algorithm for multi-objective optimization.
Parallel Implementation of Complexity Reduction Approach to Fourth Order Approximation on 2D Free Space Wave Propagation
Authors: Mohammad Khatim Hasan, Mohamed Othman, Zulkifly Abbas, Jumat Sulaiman, Fatimah Ahmad
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

Recently, a new variant of FDTD method known as High Speed Low Order FDTD (HSLO-FDTD) shows to solve 1D electromagnetic problem faster than the standard FDTD method by 67%. Application of parallel strategy to the method for 2D electromagnetic problem gain better saving in computational time to the parallel FDTD method by 85.2%. This method is called Ultra High Speed Low Order FDTD (UHSLO-FDTD). Both method applies the second order discretization with complexity reduction approach. In this paper, fourth order discretization with complexity reduction approach have succeeds to improve the accuracy of UHSLO-FDTD method. However, the fourth order scheme need higher computational time than UHSLO-FDTD method, but still faster than the FDTD method. This fourth order scheme is called Ultra High Speed High Order Finite Difference Time Domain (UHSHO-FDTD) method. In this paper we solve 2D wave propagation problems on a Symmetrical Multiprocessor machine using message-passing interface. We examine the parallelism efficiency of the algorithm by analyzing the simulation time and speedup.