ppxscal/embedding_network huggingface dataset:
A highly modular normalized adaptive lattice algorithm for multichannel least squares filtering
Authors: G.-O. Glentis, C. H. Slump
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

A highly modular normalized adaptive lattice algorithm for multichannel least squares FIR filtering and multivariable system identification, is presented. Multichannel filters with different numbers of delay elements per input channel are allowed. The main features of the proposed multichannel adaptive lattice least squares algorithm are the use of scalar only operations, multiplications/divisions and square roots, and the local communication which enables the development of a fully pipelinable architecture.
Technology as a Tool for Fighting Poverty: How Culture in the Developing World Affect the Security of Information Systems
Authors: Job Asheri Chaula, Louise Yngstrom, Stewart Kowalski
Venue: Proceedings of the Fourth IEEE International Workshop on Technology for Education in Developing Countries (2006)

Many developing nations are looking to IT infrastructure investments as means to reach sustainable economic growth. They strive to automate various processes in anticipation to improve production and quality of service to meet millennium development goals and cope with globalization needs. This has led to the automation of critical systems. It is therefore imperative that the security of such critical systems is one of the central issues to be addressed as developing nations plan, acquire and use information systems. The purpose of this paper is to examine the role of culture in systems security problems. We argue that insecure systems undermine economic growth and that culture defines how people plan, acquire and use information systems in a secure way. We also present some findings of culture evaluation case study that was carried out in Tanzania to determine the role of culture in the process of securing electricity power utility systems.
Interoperable Adaptive Educational Hypermedia: A Web Service Definition
Authors: Maram Meccawy, Ilknur Celik, Alexandra Cristea, Craig Stewart, Helen Ashman
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

This paper presents an approach to resolve the problem of authoring and interchanging educational material, based on web services. Here we describe the ultimate goal, of reusing and interchanging freely adaptive elearning material, shortly sketch previous solutions, showing their benefits but also limitations and then introduce our webservice based approach. Finally, we discuss the gains brought by our proposed solution.
Automated benchmarking and analysis tool
Authors: Tomas Kalibera, Jakub Lehotsky, David Majda, Branislav Repcek, Michal Tomcanyi, Antonin Tomecek, Petr Tuma, Jaroslav Urban
Venue: Proceedings of the 1st international conference on Performance evaluation methodolgies and tools (2006)

Benchmarking is an important performance evaluation technique that provides performance data representative of real systems. Such data can be used to verify the results of performance modeling and simulation, or to detect performance changes. Automated benchmarking is an increasingly popular approach to tracking performance changes during software development, which gives developers a timely feedback on their work. In contrast with the advances in modeling and simulation tools, the tools for automated benchmarking are usually being implemented ad-hoc for each project, wasting resources and limiting functionality.We present the result of project BEEN, a generic tool for automated benchmarking in a heterogeneous distributed environment. BEEN automates all steps of a benchmark experiment from software building and deployment through measurement and load monitoring to the evaluation of results. The notable features include separation of measurement from the evaluation and ability to adaptively scale the benchmark experiment based on the evaluation. BEEN has been designed to facilitate automated detection of performance changes during software development (regression benchmarking).
A New Wavelet Fitting Method for Geometric Correction
Authors: Shuang-Bo Fei, Rui-Zhen Zhao
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

Since the trend is to integrate remote sensing images and other spatial data in geographic information systems, geometric correction is an indispensable preprocessing in various applications. The purpose of geometric correction is to compensate for the distortions caused by the earth's curvature and rotation, the spacecraft's speed, altitude and attitude, and the scan skew etc. Today polynomial fitting (PF) is a commonly used method for geometric correction. However, the correction accuracy in some cases is not very satisfactory. A new wavelet fitting (WF) method is presented in this paper. By introducing a rotation factor to the wavelet function, we get an improved wavelet basis which is more appropriate for describing the geometric distortion. The experimental results show that the presented method is very efficient and can greatly improve the correction results.
Scientific visualization and data mining for massive scientific datasets
Authors: Aiichiro Nakano
Venue:  (2005)

Beowulf clusters and Grid computing have commoditized computing and one of the largest users of this commodity simulate large physical and biological systems involving billions of entities. Success of such ultrascale simulations depends essentially on the visualization and analysis of massive multivariate data sets. However with increasing system size, researchers are being overwhelmed with data and information. Scientific visualization and data mining are two powerful tools that can help a researcher explore and understand their data. However, exploratory and hence interactive visualization and mining of billion entity datasets pose enormous computational challenges. To address this issue, we are have developed scalable and parallel scientific visualization and data mining algorithms, to aid computational scientists performing billion-particle simulations of materials. We introduce novel algorithms that use hierarchical data abstraction for data culling, probabilities for occlusion culling, multiple levels-of-detail, and parallel and distributed variations of our techniques. These algorithms have been successfully implemented in a scientific visualization application that has been disseminated into the community and to visualize some of the largest systems in the world. We also present graph based clustering and feature detection algorithms to identify and track topological and structural anomalies of chemical bond networks in materials.
Organization of Virtual Communities
Authors: Asif Akram, Rob J. Allan
Venue: Proceedings of the Second International Conference on Semantics, Knowledge, and Grid (2006)

Locating suitable resources within a Grid system is a computationally intensive process, with no guarantee of quality and suitability of the discovered resources. An alternative approach is to categorize resources based on the services they provide -- leading to the interaction of peers with common goals to form societies/communities. Organization of resources in different communities is suggested to be useful for efficient resource discovery. We have implemented JXTA prototype to illustrate the concepts of community formation in which Peers offering different services can be grouped together based on different criteria.
Essays on improving software development productivity and economic and operational analysis of content distribution networks
Authors: Vijay S. Mookerjee
Venue:  (2006)

The first essay on improving software development productivity addresses issues related to a new software development approach called pair programming. The remaining two essays in this dissertation focus on economic and operational issues in content distribution networks. Each essay uses methodologies such as integer programming, numerical simulation, and game theory to tackle these Information Systems issues. Recently there has been considerable interest in pair programming---a novel development approach in which a pair of developers jointly works on the same piece of code. The purpose of the first study is to compare the performance of pair development with that of solo development under two separate objectives---effort minimization and time minimization. In both cases, we develop analytical models to calculate optimal module to developer assignments (for both the pair and solo approaches) so as to minimize the objective being served. In the second essay, we develop an economic model to investigate the impact peer-to-peer (P2P) networks on the providers of content distribution services (such as Akamai). Our finding is that the eventual impact of a P2P network could either benefit or hurt the profits of a content distribution provider (CDP). Our model considers the incentives of the producer (or content provider, e.g., CNN) together with the incentives of the consumer (who derives some positive utility from consuming the content) to derive the optimal extent of content distribution, with and without the existence of a P2P network. In the third essay, we present and analyze a simple, structured model of peer-to-peer (P2P) networks to gain insights. The primary objective of this study is to examine whether sharing in P2P networks can result purely from self-interest. Another goal is to understand the conditions under which free-riding can occur. We find that congested external common resources, such an external link through which all traffic enters and leaves the P2P community, play a key role in determining the sharing profile of a P2P community. Finally, free-riding can be shown to occur if the participants are heterogeneous with respect to the resources they possess.
Improving the Preciseness of Dependence Analysis Using Exception Analysis
Authors: Shujuan Jiang, Shengwu Zhou, Yuqin Shi, Yuanpeng Jiang
Venue: Proceedings of the 15th International Conference on Computing (2006)

Program dependence analysis is an analysis technique to identify and determine various program dependences in program source codes. It is an important approach for testing, understanding, maintaining programs. Exception handling mechanism in modern programming languages is a technology that can improve software robustness, but failures to account for the effects of exception handling mechanism in dependence analysis can result in incorrect analysis result. In this paper, we extend previous work on dependences analysis using exception analysis to analyze the dependences of C++ programs with exception handling constructs. The Improved Exception Control Flow Graph we propose, IECFG, is a novel representation of C++ program's intra-functional control flow. The IECFG is more precise than traditional CFG in representing the programs with exception handling constructs. We introduce how to construct the Program Dependence Graph(PDG) and the System Dependence Graph(SDG) based on the IECFG. With the help of this representation, we can obtain more precise information than most previous methods we know.
Electrophysiological Measures of Language Processing in Bilinguals
Authors: Alice Mado Proverbio
Venue: Journal of Cognitive Neuroscience (2002)

The aim of the present study was to investigate how multiple languages are represented in the human brain. Event-related brain potentials (ERPs) were recorded from right-handed polyglots and monolinguals during a task involving silent reading. The participants in the experiment were nine Italian monolinguals and nine Italian/Slovenian bilinguals of a Slovenian minority in Trieste; the bilinguals, highly fluent in both languages, had spoken both languages since birth. The stimuli were terminal words that would correctly complete a short, meaningful, previously shown sentence, or else were semantically or syntactically incorrect. The task consisted in deciding whether the sentences were well formed or not, giving the response by pressing a button. Both groups read the same set of 200 Italian sentences to compare the linguistic processing, while the bilinguals also received a set of 200 Slovenian sentences, comparable in complexity and length, to compare the processing of the two languages within the group. For the bilinguals, the ERP results revealed a strong, left-sided activation, reflected by the N1 component, of the occipitotemporal regions dedicated to orthographic processing, with a latency of about 150 msec for Slovenian words, but bilateral activation of the same areas for Italian words, which was also displayed by topographical mapping. In monolinguals, semantic error produced a long-lasting negative response (N2 and N4) that was greater over the right hemisphere, whereas syntactic error activated mostly the left hemisphere. Conversely, in the bilinguals, semantic incongruence resulted in greater response over the left hemisphere than over the right. In this group, the P615 syntactical error responses were of equal amplitude on both hemispheres for Italian words and greater on the right side for Slovenian words.The present findings support the view that there are interand intrahemispheric brain activation asymmetries when monolingual and bilingual speakers comprehend written language. The fact that the bilingual speakers in the present study were highly fluent and had acquired both languages in early infancy suggests that the brain activation patterns do not depend on the age of acquisition or the fluency level, as in the case of late, not-so-proficient L2 language learners, but on the functional organization of the bilinguals' brain due to polyglotism and based on brain plasticity.
Neural network prediction of peptide separation in strong anion exchange chromatography
Authors: Cheolhwan Oh, Stanislaw H. Żak, Hamid Mirzaei, Charles Buck, Fred E. Regnier, Xiang Zhang
Venue: Bioinformatics (2007)

Motivation: The still emerging combination of technologies that enable description and characterization of all expressed proteins in a biological system is known as proteomics. Although many separation and analysis technologies have been employed in proteomics, it remains a challenge to predict peptide behavior during separation processes. New informatics tools are needed to model the experimental analysis method that will allow scientists to predict peptide separation and assist with required data mining steps, such as protein identification. Results: We developed a software package to predict the separation of peptides in strong anion exchange (SAX) chromatography using artificial neural network based pattern classification techniques. A multi-layer perceptron is used as a pattern classifier and it is designed with feature vectors extracted from the peptides so that the classification error is minimized. A genetic algorithm is employed to train the neural network. The developed system was tested using 14 protein digests, and the sensitivity analysis was carried out to investigate the significance of each feature. Availability: The software and testing results can be downloaded from ftp://ftp.bbc.purdue.edu. Contact: zhang100@purdue.edu
Solution of the stochastic H∞-optimization problem for discrete time linear systems under parametric uncertainty
Authors: A. P. Kurdyukov, E. A. Maximov
Venue: Automation and Remote Control (2006)

The stochastic H ¿-optimization problem for a linear discrete time system with uncertain parameters is formulated and solved. The system operates in the presence of Gaussian random disturbances. The original problem with parametric uncertainty is reduced to the stochastic H ¿-optimization problem without uncertainty and having one extra input, which is essentially the mixed H 2/H ¿-optimization problem. In a sense, the problem considered in this paper incorporates the classical H 2/H ¿-and H ¿-optimization problems as limiting cases.
Modeling waiting systems from domain expert specifications
Authors: Maâmar El-Amine Hamri, Claudia Frydman, Lucile Torres
Venue: Proceedings of the 37th conference on Winter simulation (2005)

This paper proposes an application that consists in allocating services by managing waiting queues. The chosen example is the Jaspar bank described by Banks et al. The specification is based on the task type, named dynamic assignment, of the methodology CommonKADS. Then, the task type is transformed into an DEVS atomic model based on rules defined to facilitate this passage for the experts which are not familiarized with formal specifications. The operational model is verified and validated by simulation.
Austrian Grid: Overview on the Project with Focus on Parallel Applications
Authors: Jens Volkert
Venue: Proceedings of the Proceedings of The Fifth International Symposium on Parallel and Distributed Computing (2006)

GRIDs are large-scale distributed computing infrastructures that enable the integrated and collaborative use of high-end computers, networks, databases, and scientific instruments owned and managed by multiple organizations. Currently, a lot of national and international grid projects aim in building and using grids. One of them is the Austrian Grid. This project targets different areas of applications, including medical sciences, high-energy physics, applied numerical simulations, astrophysical simulations and solar observations, as well as meteorology and geophysics. Corresponding to the previous experience of the initiators of the project a lot of the applications are parallele ones. In the first part of the talk an overview on Austrian Grid will be presented. We will speak about the goals and the results in general. In the second part of the lecture the focus will be on parallel applications. We will discuss some answers given by the research of Austrian Grid to questions like: how to map parallel applications onto a grid, which kind of tools are necessary, which extensions of standard middleware are desirable.
A Comparative Analysis of Data Distribution Methods in an Agent-Based Neural System for Classification Tasks
Authors: Laura Emmanuella A. Santana, Anne M. P. Canuto, Joao Carlos Xavier Junior, Andre M. C. Campos
Venue: Proceedings of the Sixth International Conference on Hybrid Intelligent Systems (2006)

The NeurAge (Neural agents) system has been proposed as an alternative to transform the centralized decision making process of a multi-classifier system into a distributed, flexible and incremental one. This system has presented good results in some conventional (centralized) classification tasks. Nevertheless, in some classification tasks, relevant features might be distributed over a set of agent. These applications can be classified as distributed classification tasks. In this paper, a comparative investigation of the NeurAge system using some methods for data distribution will be performed. In addition, the performance of the NeurAge system will be compared with some existing multi-classifier systems.
Low-power hybrid structure of digital matched filters for direct sequence spread spectrum systems
Authors: Sung-Won Lee, In-Cheol Park
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

This paper presents a low-power structure of digital matched filters (DMFs), which is proposed for direct sequence spread spectrum systems. Traditionally, low-power approaches for DMFs are based on either the transposed-form structure or the direct-form one. A new hybrid structure that employs the direct-form structure for local addition and the transposed-form structure for global addition is used to take advantages of both structures. For a 128-tap DMF, the proposed DMF that processes 32 addends a cycle consumes 46 % less power at the expense of 6 % area overhead as compared to the state-of-the-art low-power DMF [M. Liou et al., 2001].
Volume Rendering Using Tiny Particles
Authors: Naohisa Sakamoto, Jorji Nonaka, Koji Koyamada, Satoshi Tanaka
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

In the present paper, we introduce a novel point-based volume rendering technique based on particle generation from user-specified transfer function. In the proposed technique, a set of tiny particles is generated from a given 3D scalar field. This particle generation process is based on a user-specified transfer function and rejection method. These particles are then projected onto the image plane to generate the final image. The main characteristic of the proposed technique is that the particle projection order is independent and unfixed because the transparency values of the particles are not taken into account. Therefore, only the depth-order comparison between the particles is required during the projection stage, which can greatly facilitate the distributed processing. When the quantity of projected particles is small, for instance, a maximum of one per pixel area, it becomes difficult to achieve semi-transparency, which is the main characteristic of volume rendering. To overcome this problem, sub-pixel processing is applied in order to allow the projection of multiple particles onto each of the pixel areas. The final pixel value is then obtained by averaging the contribution from each of these projected particles. The use of the Metropolis method for particle generation is also investigated as an alternative method for further improving the image quality.
The Partitioned Multiprocessor Scheduling of Deadline-Constrained Sporadic Task Systems
Authors: Sanjoy Baruah, Nathan Fisher
Venue: IEEE Transactions on Computers (2006)

A polynomial-time algorithm is presented for partitioning a collection of sporadic tasks, each constrained to have its relative-deadline parameter be no larger than its period parameter, among the processors of an identical multiprocessor platform. Since the partitioning problem is easily seen to be NP--hard in the strong sense, this algorithm is unlikely to be optimal. A quantitative characterization of its worst-case performance is provided in terms of resource augmentation: It is shown that any set of sporadic tasks that can be partitioned among the processors of an m{\hbox{-}}{\rm processor} identical multiprocessor platform will be partitioned by this algorithm on an m{\hbox{-}}{\rm processor} platform in which each processor is (3-1/m) times as fast.
Gossip Based Streaming with Incentives for Peer Collaboration
Authors: Sachin Agarwal, Shruti Dube
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

Peer-to-peer (P2P) systems are becoming a popular means of streaming audio and video content but they are prone to bandwidth starvation if selfish peers do not contribute bandwidth to other peers. We prove that an incentive mechanism can be created for a live streaming P2P protocol while preserving the asymptotic properties of randomized gossip based streaming without any incentives. In order to show the utility of our result, we adopt a distributed incentive scheme from P2P file storage literature to the live streaming scenario.We provide simulation results that confirm the ability to achieve a constant download rate (in time, per peer) that is needed for streaming applications on peers. The incentive scheme fairly differentiates peers' download rates according to how much useful bandwidth they contribute back to the P2P system, thus creating a powerful quality of service incentive for peers to contribute bandwidth to other peers. In addition we provide preliminary data from a real implementation of a gossip based streaming application.