ppxscal/embedding_network huggingface dataset:
A push-based prefetching for cooperative caching RAM Grid
Authors: Rui Chu, Nong Xiao, Lei Chen, Xicheng Lu
Venue: Proceedings of the 13th International Conference on Parallel and Distributed Systems - Volume 01 (2007)

As an innovative distributed computing technique for sharing the memory resources in high-speed network, RAM Grid exploits the distributed free nodes, and provides remote memory for the nodes which are short of memory. One of the RAM Grid systems named DRACO, tries to provide cooperative caching to improve the performance of the user node which has mass disk I/O but lacks local memory. However, the performance of DRACO is constrained with the network communication cost. In order to hide the latency of remote memory access and improve the caching performance, we proposed using push- based prefetching to enable the caching providers to push the potential useful memory pages to the user nodes. Specifically, for each caching provider, it employs sequential pattern mining techniques, which adapts to the characteristics of memory page access sequences, on locating useful memory pages for prefetching. We have verified the effectiveness of the proposed method through system analysis and trace-driven simulations.
Recommendation systems for decision support: An editorial introduction
Authors: Ting-Peng Liang
Venue: Decision Support Systems (2008)

This special section is focused on recommendation systems, computer-based information systems that provide suggestions based on previous usage behavior. The papers included in this section were selected from the Pacific Asia Conference on Information Systems (PACIS) and Workshop on Electronic Business (WEB). The application domains include website browsing aids, knowledge recommendation, document clustering, and team staff selection. They provide a snapshot of current development in using recommendation systems for decision support.
Integer frequency offset detection methods for OFDM-based WLAN systems
Authors: Sanghun Kim, Sangho Ahn, Seung Hwan Yoo, Sun Yong Kim, Seokho Yoon
Venue: Proceedings of the 2nd international conference on Ubiquitous information management and communication (2008)

Recently, a frequency offset estimation method for orthogonal frequency division multiplexing (OFDM) has been proposed by Ren et al. (REA) [9]. The method can estimate an frequency offset for any training symbol structure. In the REA method, however, the integer frequency offset detection probability is rapidly varying according to the fractional frequency offset. In this paper, we first analyze the REA frequency offset estimation method, and define new detection criteria suitable for integer frequency offset detection. Then, we propose two efficient integer frequency offset estimation methods based on maximum likelihood method. The proposed methods overcome the drawback of the REA method, maintaining its advantage. The numerical results demonstrate that the proposed methods outperform the REA method in terms of the integer frequency offset detection probability.
Analysing georeferenced population genetics data with Geneland
Authors: Gilles Guillot, Filipe Santos, Arnaud Estoup
Venue: Bioinformatics (2008)

Summary: We introduce a new algorithm to account for the presence of null alleles in inferences of populations clusters from individual multilocus genetic data. We show by simulations that the presence of null alleles can affect the accuracy of inferences if not properly accounted for and that our algorithm improve signficantly their accuracy. Availability: This new algorithm is implemented in the program Geneland. It is freely available under GNU public license as an R package on the Comprehensive R Archive Network. It now includes a fully clickable graphical interface. Informations on how to get the software are available on folk.uio.no/gillesg/Geneland.html Contact: gilles.guillot@bio.uio.no Supplementary information: Details on the simulation study are available from folk.uio.no/gillesg/BioInformatics_Geneland
Editorial
Authors: Pedro j. Sanz
Venue: Robotica (2007)

The idea underlying this Special Issue arises from previous successfully international events organized in this robotics context. Thus, during 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, hosted in Edmonton, Canada, a Workshop, with the same title was successfully organized by this guest editor. Moreover, this editor was involved in this research area, as co-Chair of the “Manipulation and Grasping Interest Group”, within the European Robotics Research Network (i.e. EURON), from 2001, organizing also a couple of International Summer Schools, supported by EURON, on these topics (Spain, 2001 and 2004). On the other hand, as time goes by, more and more robotics applications are oriented towards working in all kind of service domains, such as hospitals, museums, etc. Hence, the interest on those robotic systems, integrating manipulation and navigation capabilities, namely mobile manipulators, is drastically increasing around the entire world. Therefore, this special issue is trying to face this new scenario providing a comprehensive overview of some key topics, foundations and applications within the Mobile Manipulators context, including human-robot interaction aspects and critical issues related with navigation and manipulation performance, among others.
Analysis of ENVISAT ASAR data for forest parameter retrieval and forest type classification-a case study over deciduous forests of central India
Authors: T. R. K. Chand, K. V. S. Badarinath
Venue: International Journal of Remote Sensing (2007)

The present paper gives an account of potential of Environment Satellite-Advanced Synthetic Aperture Radar (ENVISAT-ASAR) C-band data in forest parameter retrieval and forest type classification over deciduous forests of Tadoba Andhari Tiger Reserve (TATR), central India. Ground data on phyto-sociology and Leaf Area Index (LAI) over the study area was collected in 23 sampling points (20m×20m) over the study area. Phyto-sociological data collected over the study area was used to compute plot-wise biometric parameters like basal area, volume, stem density and dominant height. ENVISAT ASAR data covering the study area, pertaining to 24 November 2005, has been geo-referenced and digital number (DN) values were converted to radar backscatter values. Regression analysis between backscatter and the retrieved biometric variables has been done to explain the relationships between SAR backscatter and forest parameters. Analysis showed a significant correlation between backscatter and biometric parameters and backscatter values typically increased with increase in basal area, volume, stem density and dominant height. The scatter observed between ASAR backscatter and stem density, basal area and dominant height suggested limitation of C-band data in estimating biometric variables in heterogeneous forest systems. Further, ASAR data was used in conjunction with Indian Remote sensing Satellite (IRS-P6)-Linear Imaging Self Scanner (LISS) III data of 16 October 2004 to classify the study area into different land use/land cover (LU/LC) classes. Various texture and adaptive filters were applied on ASAR image to reduce speckle noise and enhance image features. An attempt is made to merge ASAR image with LISS-III to enhance feature discrimination. Training sets corresponding to the ground data have been used to derive confusion matrices for the ASAR and LISS-III images. Results suggested better discrimination of vegetation types in the merged data suggesting the possible use of ASAR data in forest type discrimination.
Highly efficient asynchronous execution of large-grained parallel programs
Authors: Y. Aumann
Venue: Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science (1993)

An n-thread parallel program p is large-grained if in every parallel step the computations on each of the threads are complex procedures requiring numerous processor instructions. This practically relevant style of programs differs from PRAM programs in its large granularity and the possibility that within a parallel step the computations on different threads may considerably vary in size. Let M be an n-processor asynchronous parallel system, with no restriction on the degree of asynchrony and without any specialized synchronization mechanisms. It is a challenging theoretical as well as practically important problem to ensure correct execution of P on such a parallel machine. Let P be a large-grained program requiring total work W for its execution on a synchronous a-processor parallel system. We present a transformation (compilation) of P into a program C(P) which correctly and efficiently effects the computation of P on the asynchronous machine M. Under moderate assumptions on the granularity of threads and the size of the program variables, execution of C(P) requires just O(Wlog* n) expected total work, and the memory space overhead is a small multiplicative constant.
Using mental rotation as a methodology to evaluate shape perception in computer graphics
Authors: Tina R. Ziemek, Sarah H. Creem-Regehr, William B. Thompson
Venue: Proceedings of the 5th symposium on Applied perception in graphics and visualization (2008)

Understanding the shape of 3D objects is particularly significant in scientific visualization and CAD/CAM applications, however objective measurements of how various rendering techniques affect object perception has not received enough attention. We propose a methodology which uses the Vandenberg and Kuse [1978] mental rotation paradigm as a mechanism for evaluating how well viewers are able to encode and match novel shapes presented in a computer graphics display. The established methodology and body of research on mental rotation provides a basis for its use to probe the influence of rendering on 3D shape perception. Our approach is complementary to techniques that evaluate perception of local shape properties and the adjustment of gauge figures to match local surface orientation [Koenderink et al. 1992]. We demonstrate the methodology with an experiment showing that at least in some circumstances, subjects are more accurate at shape perception with Blinn-style rendering than with Lambertian-style rendering.
Numerical solution to steady and transient problems in thermohydrodynamic lubrication using a combination of finite element, finite volume and boundary element methods
Authors: J. Durany, J. Pereira, F. Varas
Venue: Finite Elements in Analysis and Design (2008)

A coupled model for pressure and temperature computations in a plain journal bearing which includes shaft and bushing thermal exchange with the external environment is presented and numerically solved here, both for the steady and the time-dependent case. The numerical solution to the global problem includes a combination of ad hoc techniques for the solution to each submodel. A finite element method for the hydrodynamic Reynolds equation with a cavitation model of Elrod-Adams is applied; the energy equation in the lubricating film is solved by a second order cell-vertex volume method, and the bushing temperature distribution is computed by using a (collocation) boundary element-dual reciprocity method.
Parameterization construction of integer wavelet transforms for embedded image coding
Authors: Zaide Liu, Nanning Zheng
Venue: International Journal of Computer Mathematics (2007)

The Integer Wavelet Transform (IWT) has proved particularly successful in the area of embedded lossy-to-lossless image coding. One of the possible methods to realize the IWT is the lifting scheme. Here we construct a new class of IWTs parameterized simply by one free parameter, which are obtained by introducing a free variable to the lifting-based factorization of a Deslauriers-Dubuc interpolating filter. The exact one-parameter expressions for this class of IWTs are deduced and different IWTs can be easily obtained by adjusting the free parameter. In particular, several IWTs with their lifting filters all having binary coefficients are constructed. Extensive experiments show that our transforms have superior compression performance for both lossless and lossy image coding than the state-of-the-art IWTs, and yet require only comparable computational complexity. In addition, a quantization method that improves the rate-distortion performance of the IWT remarkably is also discussed.
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Authors: Ruslan Salakhutdinov, Andriy Mnih
Venue: Proceedings of the 25th international conference on Machine learning (2008)

Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP estimate of the model parameters, a procedure that can be performed efficiently even on very large datasets. However, unless the regularization parameters are tuned carefully, this approach is prone to overfitting because it finds a single point estimate of the parameters. In this paper we present a fully Bayesian treatment of the Probabilistic Matrix Factorization (PMF) model in which model capacity is controlled automatically by integrating over all model parameters and hyperparameters. We show that Bayesian PMF models can be efficiently trained using Markov chain Monte Carlo methods by applying them to the Netflix dataset, which consists of over 100 million movie ratings. The resulting models achieve significantly higher prediction accuracy than PMF models trained using MAP estimation.
Nursing risk management by focusing on critical words or phrases in nurses' conversations
Authors: Akinori Abe, Hiromi Itoh Ozaku, Kaoru Sagara, Noriaki Kuwahara, Kiyoshi Kogure
Venue: International Journal of Knowledge-based and Intelligent Engineering Systems (2007)

This paper proposes a dynamic prediction procedure that observes nurses' conversations to determine critical points in nursing accidents or incidents. Our previous proposal for this task adopted abduction to logically determine the accident or incident point. However, in this paper we propose a different type of nursing accident or incident determination method. Here, the point is suggested by words or phrases that have certain features. We regard such words or phrases that might cause accidents or incidents as "chances." This paper analyzes the features of nurses' dialogue and conversation during nursing activities. Based on this analysis, we propose a prototype system that dynamically determines the point where an accident or incident occurs. Accordingly, we aim to deploy this system to achieve better nursing risk management.
Loss-aware network coding for unicast wireless sessions: design, implementation, and performance evaluation
Authors: Shravan Rayanchu, Sayandeep Sen, Jianming Wu, Suman Banerjee, Sudipta Sengupta
Venue: ACM SIGMETRICS Performance Evaluation Review (2008)

Local network coding is growing in prominence as a technique to facilitate greater capacity utilization in multi-hop wireless networks. A specific objective of such local network coding techniques has been to explicitly minimize the total number of transmissions needed to carry packets across each wireless hop. While such a strategy is certainly useful, we argue that in lossy wireless environments, a better use of local network coding is to provide higher levels of redundancy even at the cost of increasing the number of transmissions required to communicate the same information. In this paper we show that the design space for effective redundancy in local network coding is quite large, which makes optimal formulations of the problem hard to realize in practice. We present a detailed exploration of this design space and propose a suite of algorithms, called CLONE, that can lead to further throughput gains in multi-hop wireless scenarios. Through careful analysis, simulations, and detailed implementation on a real testbed, we show that some of our simplest CLONE algorithms can be efficiently implemented in today's wireless hardware to provide a factor of two improvement in throughput for example scenarios, while other, more effective, CLONE algorithms require additional advances in hardware processing speeds to be deployable in practice.
A, B> 0 IRn×nassures(tr(A)/n)p/(n-1) + (tr(B)/n)p/(n-1)≤ (tr(A+pB)/n)p/(n-1)≤ (tr(Ap+Bp)/n)1/(n-1)for 1 ≤p< ∞
Authors: Poramate Pranayanuntana, Praiboon Pantaragphong
Venue: Proceedings of the 10th WSEAS International Conference on APPLIED MATHEMATICS (2006)

We discuss the use of the matrix analog of Firey's extension of Brunn-Minkowski inequality and the use of an operator concave map f : A ↦ A1/p, p ≥ 1 in conjunction with a unital positive linear map Φ : A ↦ D(I, n - 1; A, 1)I to obtain the inequality (tr(A)/n)p/(n-1) + (tr(B)/n)p/(n-1) ≤ (tr(A + pB)/n)p/(n-1) ≤ (tr(Ap + Bp)/n)1/(n-1) for 1 ≤ p < ∞.
Error estimates for approximate solutions to Bellman equations associated with controlled jump-diffusions
Authors: Espen R. Jakobsen, Kenneth H. Karlsen, Claudia La Chioma
Venue: Numerische Mathematik (2008)

We derive error estimates for approximate (viscosity) solutions of Bellman equations associated to controlled jump-diffusion processes, which are fully nonlinear integro-partial differential equations. Two main results are obtained: (i) error bounds for a class of monotone approximation schemes, which under some assumptions includes finite difference schemes, and (ii) bounds on the error induced when the original L&#x00e9;vy measure is replaced by a finite measure with compact support, an approximation process that is commonly used when designing numerical schemes for integro-partial differential equations. Our proofs use and extend techniques introduced by Krylov and Barles-Jakobsen.
Drawing the line: teaching the semantics of binary class associations
Authors: James H. Paterson, John Haddow, Ka Fai Cheng
Venue: ACM SIGCSE Bulletin (2008)

This poster presents the use of a customizable code pattern tool to provide support for teaching of binary class associations in object-oriented design and programming based on recent research on the semantics of associations.
Multitarget identification and localization using bistatic MIMO radar systems
Authors: Haidong Yan, Jun Li, Guisheng Liao
Venue: EURASIP Journal on Advances in Signal Processing (2008)

A scheme for multitarget identification and localization using bistatic MIMO radar systems is proposed. Multitarget can be distinguished by Capon method, as well as the targets angles with respect to transmitter and receiver can be synthesized using the received signals. Thus, the locations of the multiple targets are obtained and spatial synchronization problem in traditional bistatic radars is avoided. The maximum number of targets that can be uniquely identified by proposed method is also analyzed. It is indicated that the product of the numbers of receive and transmit elements minus-one targets can be identified by exploiting the fluctuating of the radar cross section (RCS) of the targets. Cramer-Rao bounds (CRB) are derived to obtain more insights of this scheme. Simulation results demonstrate the performances of the proposed method using Swerling II target model in various scenarios.
Notes on “On the restudy of fuzzy complex analysis: Part I and Part II”
Authors: Dong Qiu, Lan Shu
Venue: Fuzzy Sets and Systems (2008)

In this note, we show by counterexamples that some results of Qiu and colleagues [On the restudy of fuzzy complex analysis: Part I. The sequence and series of fuzzy complex numbers and their convergences, Fuzzy Sets and Systems 115 (2000) 445-450; On the restudy of fuzzy complex analysis: Part II. The continuity and differentiation of fuzzy complex functions, Fuzzy Sets and Systems 120 (2001) 517-521.] concerning the convergence of the series of fuzzy complex numbers and the differentiation of fuzzy complex functions are incorrect, and offer some of their modified versions. We also show that the derivative introduced by them is inappropriate for the functions mapping complex numbers into fuzzy complex numbers.
A pedestrian detection system using applied log-Gabor
Authors: J. Janta, P. Kumsawat, K. Attakitmongkol, A. Srikaew
Venue: Proceedings of the 7th WSEAS International Conference on Signal, Speech and Image Processing (2007)

Pedestrian detection is one of the most important research contents of road safety. The crucial idea behind such pedestrian safety systems is to protect the driver and pedestrian from any accident. In this paper, a pedestrian feature extraction based on applied log-Gabor filters is presented. The resulting filtered images show desirable segmentation performance which allows support vector machines to be able to efficiently classify and recognize the pedestrian. The proposed system is capable of detecting multiple pedestrians from complex background and providing size and position information of pedestrians within the image. Pedestrians with different sizes, shapes, postures, and clothes can be detected effectively. Results and discussions are presented.
Protecting Users' Anonymity in Pervasive Computing Environments
Authors: Linda Pareschi, Daniele Riboni, Claudio Bettini
Venue: Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications (2008)

The large scale adoption of adaptive services in pervasive and mobile computing is likely to be conditioned to the availability of reliable privacy-preserving technologies. Unfortunately, the research in this field can still be considered in its infancy. This paper considers a specific pervasive computing scenario, and shows that the application of state-of-the-art techniques for the anonymization of service requests is insufficient to protect the privacy of users. A specific class of attacks, called shadow attacks, is formally defined and a set of defense techniques is proposed. These techniques are validated through the use of a simulator and an extensive set of experiments.
An Efficient Solution for Model Checking Graph Transformation Systems
Authors: Luciano Baresi, Vahid Rafe, Adel T. Rahmani, Paola Spoletini
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2008)

This paper presents an efficient solution for modeling checking graph transformation systems. The approach transforms AGG specifications into Bogor models and supports both attributed typed graphs and layered transformations. Resulting models are amenable to check interesting properties expressed as combinations of LTL (Linear Temporal Logic) and graph transformation rules. The first experimental results are encouraging and show that in most cases our proposal improves existing approaches, both in terms of performance and expressiveness.
A BCD-based architecture for fast coordinate rotation
Authors: Antonio Jimeno, Higinio Mora, Jose L. Sanchez, Francisco Pujol
Venue: Journal of Systems Architecture: the EUROMICRO Journal (2008)

Although radix 10 based arithmetic has been gaining renewed importance over the last few years, decimal systems are not efficient enough and techniques are still under development. In this paper, an improvement of the CORDIC (coordinate rotation digital computer) method for decimal representation is proposed and applied to produce fast rotations. The algorithm uses BCD operands as inputs, combining the advantages of both decimal and binary systems. The result is a reduction of 50% in the number of iterations if compared with the original Decimal CORDIC method. Finally, we present a hardware architecture useful to produce BCD coordinates rotations accurately and fast, and different experiments demonstrating the advantages of the new method are shown. A reduction of 75% in a single stage delay is obtained, whereas the circuit area just increases in about 5%.