ppxscal/embedding_network huggingface dataset:
Time-Space FE-PDAS Method for Dynamic Unilateral Contact Problem in Viscoelasticity
Authors: Jiří Nedoma, Josef Daněk
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

The paper deals with numerical analysis of a class of multibody dynamic unilateral contact problems. The presented problem describes the seismological model problem, representing a new approach in this branch and of studying propagation of seismic waves through broken up upper parts of the Earth. The semi-implicit finite element and the primal-dual active set strategy methods will be discussed.
Applications of AR*-GRNN model for financial time series forecasting
Authors: Weimin Li, Yishu Luo, Qin Zhu, Jianwei Liu, Jiajin Le
Venue: Neural Computing and Applications (2008)

AR* models contain Autoregressive Moving Average and Generalized Autoregressive Conditional Heteroscedastic class model which are widely used in time series. Recent researches in forecasting with Generalized Regression Neural Network (GRNN) suggest that GRNN can be a promising alternative to the linear and nonlinear time series models. In this paper, a model composed of AR* and GRNN is proposed to take advantage of their feathers in linear and nonlinear modeling. In the AR*-GRNN model, AR* modeling improves the forecasting performance of the combined model by capturing statistical and volatility information from the time series. The relative experiments testify that the combined model provides an effective way to improve forecasting performance which can be achieved by either of the models used separately.
Digit-Serial Structures for the Shifted Polynomial Basis Multiplication over Binary Extension Fields
Authors: Arash Hariri, Arash Reyhani-Masoleh
Venue: Proceedings of the 2nd international workshop on Arithmetic of Finite Fields (2008)

Finite field multiplication is one of the most important operations in the finite field arithmetic. Recently, a variation of the polynomial basis, which is known as the shifted polynomial basis, has been introduced. Current research shows that this new basis provides better performance in designing bit-parallel and subquadratic space complexity multipliers over binary extension fields. In this paper, we study digit-serial multiplication algorithms using the shifted polynomial basis. They include a Most Significant Digit (MSD)-first digit-serial multiplication algorithm and a hybrid digit-serial multiplication algorithm, which includes parallel computations. Then, we explain the hardware architectures of the proposed algorithms and compare them to their existing counterparts. We show that our MSD-first digit-serial shifted polynomial basis multiplier has the same complexity of the Least Significant Digit (LSD)-first polynomial basis multiplier. Also, we present the results for the hybrid digit-serial multiplier which offers almost the half of the latency of the best known digit-serial polynomial basis multipliers.
Singularity Detection Using AWT with Application to Fault Diagnosis
Authors: Mao Pang, Chen-long Yang, Xiao-jun Zhou
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Singularity analysis of vibration signal is an effective method for mechanical fault diagnosis. Signal singularities can be characterized by its wavelet transforms modulus. Real wavelets are generally adopted in analysis. In fact, analytic wavelet transform (AWT) only reflects positive frequencies of signal and its modulus oscillation is weaker than real wavelet transform (RWT), so signal singularities can be detected more accurately. Singularities detection and de-noise based AWT are applied to vibration signals of running machines. Signals are analyzed by this method sampled under several conditions in a main reducer performance test bed developed by us. Experiment results show that singularity detection using the modulus maximum of an analytic wavelet is better than that of a real wavelet. The fault feature can be distinguished from the reconstructing signals more easily, which makes for fault features extraction.
Outlier Detection with Kernel Density Functions
Authors: Longin Jan Latecki, Aleksandar Lazarevic, Dragoljub Pokrajac
Venue: Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition (2007)

Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel unsupervised algorithm for outlier detection with a solid statistical foundation is proposed. First we modify a nonparametric density estimate with a variable kernel to yield a robust local density estimation. Outliers are then detected by comparing the local density of each point to the local density of its neighbors. Our experiments performed on several simulated data sets have demonstrated that the proposed approach can outperform two widely used outlier detection algorithms (LOF and LOCI).
A Prediction Algorithm Based on Time Series Analysis
Authors: Jianping Qiu, Lichao Chen, Yingjun Zhang
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II (2008)

In the context of the Semantic Web, it may be beneficial for a user to receive a forecast regarding the reliability of an information source. We offer an algorithm for building more effective social networks of trust by using CLRM (classic linear regression models). For managing uncertainty, we introduce some random variables which neither the consumer nor the provider can control its value. Such random variables that can be successively accumulated from each stage of multi-stage forecasts are reduced through the use of analytical tools that combine statistical methods with advances in time series analysis. Time series analysis can relate 'current' values of a critical variable to its past values and to the values of current. Moreover, to model real world scenario, VAR-GARCH (Vector Auto Regression Generalized Autoregressive Conditional Heteroskedasticity) model is used to represent forecasting results which are generally influenced by interactions between decision makers.
A New Cable-Actuated Haptic Interface Design
Authors: Fabien Ferlay, Florian Gosselin
Venue: Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios (2008)

Cable robots or wire driven robots possess many advantages that make them well suited to be used as haptic interfaces. They present very low inertia and very low friction because of their very light mechanical structure. However, a bulky structure is needed to carry the motor units all around the handle. To avoid this problem, we previously proposed to replace one of the pulling cables with a pushing cylinder. Nevertheless, the actuation lines tend to be less regularly distributed in space, resulting in anisotropic and inhomogeneous static and dynamic performances. In this paper, we introduce a new architecture allowing better performances all over the workspace. This upgrade is validated with a precise cartography of the robot's most important haptic characteristics.
Formal interaction specification in public health surveillance systems using π-calculus
Authors: Dibyendu Baksi
Venue: Computer Methods and Programs in Biomedicine (2008)

This paper provides formal specification of interactions in typical public health surveillance systems involving healthcare agencies at local, state and federal levels. Although few standards exist for exchange of healthcare information, there is a general lack of formal models of the protocols involved in the interactions between the agencies. The quality of medical care provided is an end result of a well designed choreography of diverse services provided by different healthcare entities. One of the major challenges in this field appears to be explicit formal specification of such interactions. Such formal specification work is the first step leading to both design and verification of important properties of public healthcare systems. @p-calculus is a formal modeling technique for precise specification of semantics in interacting concurrent systems where mobility is involved. Two different configurations of public health surveillance systems are modelled using @p-calculus in this paper.
On the consistency of ensemble classification algorithms
Authors: Peter L. Bartlett
Venue:  (2007)

The fields of machine learning and statistics experienced fast growth in the past 25 years. A lot of theoretical and empirical research was done in the area of classification and a lot of new algorithms were proposed. Not all of them survived the scrutiny of tests of their effectiveness, but some were shown to be very effective and are widely used in practice even if their theoretical foundations are unclear. In this work we study two of the most successful classification and regression algorithms that were introduced in the past 15 years&mdash;AdaBoost and Random Forests. In both cases we are interested in the consistency of these algorithms in the classification setting. In the case of the AdaBoost algorithm we investigate the risk, or probability of error, of the classifier produced by the algorithm. In particular, we consider the stopping strategy to be used in AdaBoost to achieve universal consistency. We show that provided AdaBoost is stopped after n 1-&egr; iterations&mdash;for sample size n and &egr; &isin; (0, 1)&mdash;the sequence of risks of the classifiers it produces approaches the Bayes risk. This answers the long-standing question of whether the AdaBoost algorithm in its original formulation is consistent or not. For the Random Forests algorithm the goal was also to establish consistency or show the lack of it since there seems to exist some confusion about the algorithm: Breiman's words [17] "the generalization error for forests converges a.s. to a limit as the number of trees in the forest becomes large" are interpreted, at least sometimes, as a statement on the consistency of the algorithm. We consider a classification setting and provide a simple proof that in the one-dimensional case Random Forests, as formulated in [17] and implemented in the randomForests R package, is nothing but a 1-nearest neighbour classifier, hence it is not consistent. The proof also reveals that the algorithm can be made consistent by choosing the bootstrap sample size sublinear in the training sample size. A simulation study suggests that the same might be true in higher dimensions.
Fatigue life assessment using signal processing techniques
Authors: S. Abdullah, M. Z. Nuawi, C. K. E. Nizwan, A. Zaharim, Z. M. Nopiah
Venue: Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation (2008)

This paper presents the fatigue life assessment using signal processing approaches which study on the characteristics of the fatigue signal in frequency and time-frequency domain. The signals used in this research were variable amplitude fatigue signal which consisted of a synthetic data and experimentally measured data. As frequency domain method is one of the techniques to analyse random signal, it can be applied to observe strain characteristic of the signal in frequency domain. Thus, Power Spectral Density (PSD) algorithm was used to gain the power distribution of the input signals. The short-time Fourier transform (STFT) method was then used to transform the input signal into the time-frequency domain. The transformation of time domain signal into time-frequency domain provides the power distribution display with respect to the particular time and frequency information. From the power distribution gained, the fatigue damage features can be identified. Finally, the life estimation of the components was calculated in order to study its durability.
C Versus Fortran-77 for Scientific Programming
Authors: Tom MacDonald
Venue: Scientific Programming (1992)

The predominant programming language for numeric and scientific applications is Fortran-77 and supercomputers are primarily used to run large-scale numeric and scientific applications. Standard C* is not widely used for numerical and scientific programming, yet Standard C provides many desirable linguistic features not present in Fortran-77. Furthermore, the existence of a standard library and preprocessor eliminates the worst portability problems. A comparison of Standard C and Fortran-77 shows several key deficiencies in C that reduce its ability to adequately solve some numerical problems. Some of these problems have already been addressed by the C standard but others remain. Standard C with a few extensions and modifications could be suitable for all numerical applications and could become more popular in supercomputing environments.
Perceptually Motivated Sub-band Decomposition for FDLP Audio Coding
Authors: Petr Motlíček, Sriram Ganapathy, Hynek Hermansky, Harinath Garudadri, Marios Athineos
Venue: Proceedings of the 11th international conference on Text, Speech and Dialogue (2008)

This paper describes employment of non-uniform QMF decomposition to increase the efficiency of a generic wide-band audio coding system based on Frequency Domain Linear Prediction (FDLP). The base line FDLP codec, operating at high bit-rates (~136 kbps), exploits a uniform QMF decomposition into 64 sub-bands followed by sub-band processing based on FDLP. Here, we propose a non-uniform QMF decomposition into 32 frequency sub-bands obtained by merging 64 uniform QMF bands. The merging operation is performed in such a way that bandwidths of the resulting critically sampled sub-bands emulate the characteristics of the critical band filters in the human auditory system. Such frequency decomposition, when employed in the FDLP audio codec, results in a bit-rate reduction of 40% over the base line. We also describe the complete audio codec, which provides high-fidelity audio compression at ~66 kbps. In subjective listening tests, the FDLP codec outperforms MPEG-1 Layer 3 (MP3) and achieves similar qualities as MPEG-4 HE-AAC codec.
Proteus: Visuospatial analogy in problem-solving
Authors: Jim Davies, Ashok K. Goel, Patrick W. Yaner
Venue: Knowledge-Based Systems (2008)

We hypothesize that visuospatial knowledge alone is sufficient for analogical transfer of problem-solving procedures. We developed a theory of visuospatial analogical problem-solving. Proteus, our implemented program, provides a content account, with vocabulary and data structures, and a process account, with methods and algorithms. Proteus addresses all major subtasks of analogy, and identifies a new subtask: dynamic mapping generation between the intermediate knowledge states in the source and the target, when a step in the transferred procedure creates a new object. Examining the limitations of use of visuospatial knowledge alone, we help identify the functional roles of non-visuospatial knowledge.
Reliability of electrolytic capacitors in computers
Authors: Mark VanBuskirk
Venue: Papers and discussions presented at the Dec. 8-10, 1953, eastern joint AIEE-IRE computer conference: information processing systems---reliability and requirements (1953)

If any person would ask ten different electronic manufacturers whose equipments cover a wide variety of electronic circuits for their opinions of electrolytic capacitors, it is possible there would be ten different answers. These answers might range from: "We use them all the time, and never have any trouble," to the extreme: "We wouldn't use them under any circumstance. They are not reliable." 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
Dynamic processing windows for mobile robotic real-time systems
Authors: Steve Goddard
Venue:  (2008)

Mobile real-time systems must sense constraints imposed by a dynamically changing environment and predictably react to those changes in real-time. Mobile real-time systems add yet one more level of complexity in that the computing platform travels through the environment with which the system is interacting. These systems have spatio-temporal requirements in the sense that correct behavior is defined in terms of both space and time. We present a design and analysis methodology for these platforms that integrates spatio-temporal attributes with fixed priority real-time scheduling. To support dynamic environments, we divide the path the mobile platform traverses into zones and associate with each zone a processing window. We also present an algorithmic framework for adjusting platform speed, performance parameters or processing windows such that the maximum speed less than or equal to the desired speed (or performance) is maintained or maximized while adjusting the processing window to maintain schedulability of the platform's real-time tasks. We test our theory and methodology on two different case studies representing two different mobile robotic applications.
The Effectiveness of T-Way Test Data Generation
Authors: Michael Ellims, Darrel Ince, Marian Petre
Venue: Proceedings of the 27th international conference on Computer Safety, Reliability, and Security (2008)

This paper reports the results of a study comparing the effectiveness of automatically generated tests constructed using random and t-way combinatorial techniques on safety related industrial code using mutation adequacy criteria. A reference point is provided by hand generated test vectors constructed during development to establish minimum acceptance criteria. The study shows that 2-way testing is not adequate measured by mutants kill rate compared with hand generated test set of similar size, but that higher factor t-way test sets can perform at least as well. To reduce the computation overhead of testing large numbers of vectors over large numbers of mutants a staged optimising approach to applying t-way tests is proposed and evaluated which shows improvements in execution time and final test set size.
Resource conflict detection in simulation of function unit pipelines
Authors: Pekka Jääskeläinen, Vladimír Guzma, Viljami Korhonen
Venue: Journal of Systems Architecture: the EUROMICRO Journal (2008)

Processor simulators are important parts of processor design toolsets in which they are used to verify and evaluate the properties of the designed processors. While simulating architectures with independent function unit pipelines using simulation techniques that avoid the overhead of instruction bit-string interpretation, such as compiled simulation, the simulation of function unit pipelines can become one of the new bottlenecks for simulation speed. This paper evaluates several resource conflict detection models, commonly used in compiler instruction scheduling, in the context of function unit pipeline simulation. The evaluated models include the conventional reservation table based-model, the dynamic collision matrix model, and an finite state automata (FSA) based model. In addition, an improvement to the simulation initialization time by means of lazy initialization of states in the FSA-based approach is proposed. The resulting model is faster to initialize and provides comparable simulation speed to the actively initialized FSA.
Incorporating Gene Functions into Regression Analysis of DNA-Protein Binding Data and Gene Expression Data to Construct Transcriptional Networks
Authors: Peng Wei, Wei Pan
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2008)

Useful information on transcriptional networks has been extracted by regression analyses of gene expression data and DNA-protein binding data. However, a potential limitation of these approaches is their assumption on the common and constant activity level of a transcription factor (TF) on all the genes in any given experimental condition; for example, any TF is assumed to be either an activator or a repressor, but not both, while it is known that some TFs can be dual regulators. Rather than assuming a common linear regression model for all the genes, we propose using separate regression models for various gene groups; the genes can be grouped based on their functions or some clustering results. Furthermore, to take advantage of the hierarchical structure of many existing gene function annotation systems, such as Gene Ontology (GO), we propose a shrinkage method that borrows information from relevant gene groups. Applications to a yeast dataset and simulations lend support for our proposed methods. In particular, we find that the shrinkage method consistently works well under various scenarios. We recommend the use of the shrinkage method as a useful alternative to the existing methods.
SINAI at CLEF Ad-Hoc Robust Track 2007: Applying Google Search Engine for Robust Cross-Lingual Retrieval
Authors: F. Martínez-Santiago, A. Montejo-Ráez, M. A. García-Cumbreras
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

We report our web-based query generation experiments for English and French collections in the Robust task of the CLEF Ad-Hoc track. We continued with the approach adopted in the previous year, although the model has been modified. Last year we used Google to expand the original query. This year we create a new expanded query in addition to the original one. Thus, we retrieve two lists of relevant documents, one for each query (the original and the expanded one). In order to integrate the two lists of documents, we apply a logistic regression merging solution. The results obtained are discouraging but the failure analysis shows that very difficult queries are improved by using both queries instead of the original query. The problem is to decide when a query is very difficult.
Protecting Agent from Attack in Grid ComputingIII
Authors: Byungryong Kim
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

P2P network has been emerging as a very attractive content distribution mechanism. Nevertheless flooding based applications and systems with distribution hash tables based model, which are already developed, are having difficulty in the development and the application because they do not satisfy many issues such as privacy protection of end-user. In this study we propose neighbor-set based privacy protection model. The proposed technique is based on the typical distributed hash tables model, chord, and was designed to be protected from attack by securing anonymity to participating nodes. Proposed protecting scheme and how to solve the problem of load balancing caused in the process will be explained. 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
Particle Swarm Optimization for the Multidimensional Knapsack Problem
Authors: Fernanda Hembecker, Heitor S. Lopes, Walter Godoy,  Jr.
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I (2007)

The multidimensional 0/1 knapsack problem is a classical problem of discrete optimization. There are several approaches for solving the different variations of such problem, including mathematical programming and stochastic heuristic methods. This paper presents the application of Particle Swarm Optimization (PSO) for the problem, using selected instances of ORLib. For the instances tested, results were very close or equal to the optimal solution known, even considering that the parameters of PSO were not optimized. The analysis of the results suggests the potential of a simple PSO for this class of combinatorial problems.