ppxscal/embedding_network huggingface dataset:
Simulation and Verification of Asynchronous Systems by means of a Synchronous Model
Authors: Nicolas Halbwachs, Louis Mandel
Venue: Proceedings of the Sixth International Conference on Application of Concurrency to System Design (2006)

Synchrony and asynchrony are commonly opposed to each other. Now, in embedded applications, actual solutions are often situated in between, with synchronous processes composed in a partially asynchronous way. Examples of such intermediate solutions are GALS, quasi-synchronous periodic processes, deadline-driven task scheduling. . . In this paper, we illustrate the use of the synchronous paradigm to model and validate such partially asynchronous applications. We show that, through the use of sporadic activation of processes and simulation of nondeterminism by the way of auxiliary inputs, the synchronous paradigm allows a precise control of asynchrony. The approach is illustrated on a real case study, proposed in the framework of the European Integrated project "Assert".
MILLE-XTERM and LTSP
Authors: Francis Giraldeau, Jean-Michel Dault, Benoit des Ligneris
Venue: Linux Journal (2006)

If you thought Network Computing was dead, wait until you read this.
Multi-Criterion Active Learning in Conditional Random Fields
Authors: Christopher T. Symons, Nagiza F. Samatova, Ramya Krishnamurthy, Byung H. Park, Tarik Umar, David Buttler, Terence Critchlow, David Hysom
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

Conditional Random Fields (CRFs), which are popular supervised learning models for many Natural Language Processing (NLP) tasks, typically require a large collection of labeled data for training. In practice, however, manual annotation of text documents is quite costly. Furthermore, even large labeled training sets can have arbitrarily limited performance peaks if they are not chosen with care. This paper considers the use of multi-criterion active learning for identification of a small but sufficient set of text samples for training CRFs. Our empirical results demonstrate that our method is capable of reducing the manual annotation costs, while also limiting the retraining costs that are often associated with active learning. In addition, we show that the generalization performance of CRFs can be enhanced through judicious selection of training examples.
Short- and Long-Delay Intracranial ERP Repetition Effects Dissociate Memory Systems in the Human Brain
Authors: François Guillem, Alain Rougier, Bernard Claverie
Venue: Journal of Cognitive Neuroscience (1999)

Prior exposure to a stimulus can facilitate the performance to subsequent presentations of that stimulus. ERP studies have shown that this facilitation is associated with the modulation of two components (N400 and P600). Investigation of the time course of both behavioral and ERP repetition effects have led to the assumption that it is subserved by the combination of at least two mechanisms operating at different time-points: a short-delay semantic activation and a long-lasting episodic mechanism. The present experiment recorded intracranial ERPs from various structures during a continuous recognition memory task to investigate the respective contribution of the different brain regions to short- and long-delay ERP repetition effects. The results are in good agreement with both the classical neuropsychological literature and the more recent data obtained with functional imagery techniques. They provide electrophysiological evidence of multiple anatomo-functional memory systems in the human brain: a short-term semantic activation system and a long-term episodic memory system, with interface structures that coordinate the functioning of these two systems.
Sequential homotopy-based computation of multiple solutions to nonlinear equations
Authors: F. M. Coetzee, V. L. Stonick
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

Homotopy methods have achieved significant success in solving systems of nonlinear equations for which the number of solutions are known and the homotopy paths are bounded. We present a two-stage homotopy process which does not require a-priori knowledge of the number of solutions to a system of nonlinear equations. This approach makes use of compact manifolds to find solutions sequentially along disconnected homotopy paths. The procedure is tested on two standard optimization and neural network benchmark problems.
Neurophysiological Indexes of Speech Processing Deficits in Children with Specific Language Impairment
Authors: Valerie L. Shafer, Mara L. Morr, Hia Datta, Diane Kurtzberg, Richard G. Schwartz
Venue: Journal of Cognitive Neuroscience (2005)

We used neurophysiological and behavioral measures to examine whether children with specific language impairment (SLI ) have deficits in automatic processing of brief, phonetically similar vowels, and whether attention plays a role in such deficits. The neurophysiological measure mismatch negativity (MMN ) was used as an index of discrimination in two tasks; one in which children ignored the auditory stimuli and watched a silent video and a second in which they attended to the auditory modality. Children with SLI showed good behavioral discrimination, but significantly poorer behavioral identification of the brief vowels than the children with typical language development (TLD). For the TLD children, two neurophysiological measures (MMN and a later negativity, LN ) indexed discrimination of the vowels in both tasks. In contrast, only the LN was elicited in either task for the SLI group. We did not see a direct correspondence between the absence of MMN and poor behavioral performance in the children with SLI. This pattern of findings indicates that children with SLI have speech perception deficiencies, although the underlying cause may vary.
Fair Queuing Memory Systems
Authors: Kyle J. Nesbit, Nidhi Aggarwal, James Laudon, James E. Smith
Venue: Proceedings of the 39th Annual IEEE/ACM International Symposium on Microarchitecture (2006)

We propose and evaluate a multi-thread memory scheduler that targets high performance CMPs. The proposed memory scheduler is based on concepts originally developed for network fair queuing scheduling algorithms. The memory scheduler is fair and provides Quality of Service (QoS) while improving system performance. On a four processor CMP running workloads containing a mix of applications with a range of memory bandwidth demands, the proposed memory scheduler provides QoS to all of the threads in all of the workloads, improves system performance by an average of 14% (41% in the best case), and reduces the variance in the threads' target memory bandwidth utilization from .2 to .0058.
Processor architecture: too much parallelism?
Authors: David B. Kirk
Venue: Proceedings of the 15th international conference on Parallel architectures and compilation techniques (2006)

CPUs and GPUs have evolved considerably in the past few years, and the pace of change and evolution in processor architecture is likely to increase. Constraints of excess heat dissipation and power consumption have forced a radical rethinking of microprocessor architecture, from the headlong pursuit of GHz clock rates to multicore and multithreaded approaches. The demands of graphics vertex and pixel processing as well as more general non-graphics applications have driven GPUs to be powerful data-parallel floating point processing engines. Research and development in programming languages and environments has not kept pace with the changes in processors. Consequently, computer science and computer engineering research and education is not addressing important problems, or preparing students well for today's computer industr.This talk will provide some historical and architectural perspective on data-parallel GPU architectures, and will attempt to make some trend predictions for the future of GPUs. We will then provide some examples of successes and failures in mapping parallel algorithms to these architectures. Finally, we will conclude with some calls to action in research and education, to improve the utilization of these ubiquitous and powerful parallel machines.
Using discrete-element simulation to evaluate laboratory instrumentation needs
Authors: Valerie G. Caryer Cook
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Strategic planning for laboratory operations capital investment involves predicting the usage of equipment used in daily operations. Development laboratories are particularly difficult to model equipment usage, due to the large variation in the types of projects or tests conducted and complex equipment needs. Discrete-element simulation can be used to effectively model the use of equipment inventory in this highly variable environment. This presentation demonstrates the use of a WITNESS discrete-element simulation model to optimize capital investment in data acquisition equipment for an NVH laboratory. The model is used to evaluate the effect of increasing investment in data acquisition chassis units versus component cards to maximize the efficiency of the instrumentation process. The model was also adjusted to reflect future laboratory demand conditions to increase the accuracy of the prediction. The study resulted in a recommendation of the most cost-efficient combination of chassis units and component cards for the laboratory. 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
A Fuzzy Model for Selection of QoS-Aware Web Services
Authors: Ping Wang, Kuo-Ming Chao, Chi-Chun Lo, Chun-Lung Huang, Yinsheng Li
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2006)

With the increasing popularity of employing web services, quality of service (QoS) measure of service becomes a significant concern for service consumers and providers. However, current technologies are poor to identify the relative importance of nonfunctional QoS criteria for web services and they are not fitting well for selecting the appropriate service. In this paper, a new scheme for right selection of QoSaware of web services which exploits fuzzy logic to locate and select the right service based on customer's preference or satisfaction degree. The aim is to compute both functional and non-functional weightings of QoS criteria and to assist customers to make the right choice for web services.
A High Performance ASIC for Cellular Automata (CA) Applications
Authors: Cheryl A. Kincaid, Saraju P. Mohanty, Armin R. Mikler, Elias Kougianos, Brandon Parker
Venue: Proceedings of the 9th International Conference on Information Technology (2006)

CA are useful tools in modeling and simulation. However, the more complex a CA is, the longer it takes to run in typical environments. A dedicated CA machine solves this problem by allowing all cells to be computed in parallel. In this paper we present simple yet useful hardware that can perform the required computations in constant time complexity, O(1).
Challenges in Visual Data Analysis
Authors: Daniel A. Keim, Florian Mansmann, Jorn Schneidewind, Hartmut Ziegler
Venue: Proceedings of the conference on Information Visualization (2006)

In today's applications data is produced at unprecedented rates. While the capacity to collect and store new data grows rapidly, the ability to analyze these data volumes increases at much lower pace. This gap leads to new challenges in the analysis process, since analysts, decision makers, engineers, or emergency response teams depend on information "concealed" in the data. The emerging field of visual analytics focuses on handling massive, heterogenous, and dynamic volumes of information through integration of human judgement by means of visual representations and interaction techniques in the analysis process. Furthermore, it is the combination of related research areas including visualization, data mining, and statistics that turns visual analytics into a promising field of research. This paper aims at providing an overview of visual analytics, its scope and concepts, and details the most important technical research challenges in the field.
BaseVISor: A Triples-Based Inference Engine Outfitted to Process RuleML and R-Entailment Rules
Authors: Christopher J. Matheus, Ken Baclawski, Mieczyslaw M. Kokar
Venue: Proceedings of the Second International Conference on Rules and Rule Markup Languages for the Semantic Web (2006)

BaseVISor is a forward-chaining inference engine based on a Rete network optimized for the processing of RDF triples. A clause within the body and head of a rule either represents an RDF triple or invokes a procedural attachment (either built-in or user defined). This paper describes how BaseVISor has been outfitted to process RuleML and R-Entailment rules. In the case of RuleML, n-ary predicates are automatically translated into binary predicates and reified statements that encapsulate the n-ary predicates' arguments. For R-Entailment rules, the appropriate R-Entailment axioms, axiomatic triples and consistency rules are automatically imported into the engine and then used to derive all triples entailed by any set of triples asserted into the fact base. Operation of the system is illustrated using sample rule sets for both RuleML and R-Entailment and instructions are provided on how to obtain the BaseVISor beta release and process the examples.
Personal Health Record Systems and Their Security Protection
Authors: Khin Than Win, Willy Susilo, Yi Mu
Venue: Journal of Medical Systems (2006)

The objective of this study is to analyze the security protection of personal health record systems. To achieve this we have investigated different personal health record systems, their security functions, and security issues. We have noted that current security mechanisms are not adequate and we have proposed some security mechanisms to tackle these problems.
Solution Path for Semi-Supervised Classification with Manifold Regularization
Authors: Gang Wang, Tao Chen, Dit-Yan Yeung, Frederick H. Lochovsky
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

With very low extra computational cost, the entire solution path can be computed for various learning algorithms like support vector classification (SVC) and support vector regression (SVR). In this paper, we extend this promising approach to semi-supervised learning algorithms. In particular, we consider finding the solution path for the Laplacian support vector machine (LapSVM) which is a semi-supervised classification model based on manifold regularization. One advantage of the this algorithm is that the coefficient path is piecewise linear with respect to the regularization parameter, hence its computational complexity is quadratic in the number of labeled examples.
Scheduling with QoS in parallel I/O systems
Authors: Ajay Gulati, Peter Varman
Venue: Proceedings of the international workshop on Storage network architecture and parallel I/Os (2004)

Parallel I/O architectures are increasingly deployed for high performance computing and in shared data centers. In these environments it is desirable to provide QoS-based allocation of disk bandwidth to different applications sharing the I/O system. In this paper, we introduce a model of disk bandwidth allocation, and provide efficient scheduling algorithms to assign the bandwidth among the concurrent applications.
Visual Data Mining of Application Services Data
Authors: Ronald Knoetze, Charmain Cilliers, Janet Wesson
Venue: Proceedings of the conference on Information Visualization (2006)

Many network monitoring tools do not provide sufficiently in-depth and useful reports on network usage, particularly in the domain of application services data. Application services form an integral part of organizational networks. The optimization of the performance of these networks is only possible if the networks are effectively monitored. Techniques that identify patterns of network usage can assist in the successful monitoring of network performance. The focus of this paper is on the development of a visual data mining prototype, called NetPatterns, which facilitates the effective visualization of network performance data.
Batch implementation of Growing Self-Organizing Map
Authors: Yaohua Yu, Damminda Alahakoon
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

The Growing Self-organizing map algorithm (GSOM) has been developed based on SOM. With its dynamic structure, GSOM can generate feature maps without pre-determining their size. It has shown many significant advantages when processing very large data sets. These advantages could be further enhanced if the processing speed of the algorithm could be increased. This paper presents a modified version of GSOM, which implements the batch processing principle to shorten the processing time. The algorithm and experimental results showing the improved performance are presented in this paper.
Distributing the Sloan Digital Sky Survey Using UDT and Sector
Authors: Yunhong Gu, Robert L. Grossman, Alex Szalay, Ani Thakar
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

In this paper, we describe a peer-to-peer storage system called Sector that is designed to access and transport large data sets over wide area high performance networks. We also describe our recent experience using Sector to distribute the Sloan Digital Sky Survey BESTDR4 catalog data.
A Method for Fetal Heart Rate Extraction Based on Time-Frequency Analysis
Authors: E. C. Karvounis, M. G. Tsipouras, D. I. Fotiadis, K. K. Naka
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

A three-stage method for fetal heart rate extraction, from abdominal ECG recordings, is proposed. In the first stage the maternal R-peaks and fiducial points (QRS onset and offset) are detected, using time-frequency analysis, and the maternal QRS complexes are eliminated. The second stage locates the positions of the candidate fetal R-peaks, using complex wavelets and pattern matching theory techniques. In the third stage, the fetal R-peaks that overlap with the maternal QRS complexes are found. The method is validated using a dataset of 4 long duration recordings and the obtained results indicate high detection ability of the method (96% accuracy).
Learning Foveal Sensing Strategies in Unconstrained Surveillance Environments
Authors: Andrew D. Bagdanov, Alberto Del Bimbo, Walter Nunziati, Federico Pernici
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

In this paper we report on techniques for automatically learning foveal sensing strategies for an active pan-tiltzoom camera. The approach uses reinforcement learning to discover foveal actions maximizing the performance of visual detectors, that are in turn assumed to be highly correlated with the task at hand. In our case, the main goal is to recognize people, hence a frontal face detection module is employed. The system uses reinforcement learning to learn if, when and how to foveate on a subject, based on its previous experience in terms or successful actions in similar situations. An action is successful if it leads to a correct face detection in the high resolution images obtained when the subject is zoomed in. In contrast with existing methods, the proposed approach obviates the need for camera calibration and camera performance modeling. Also, the method does not rely on active tracking of targets. Experimental results show how the system is capable of learning foveation strategies without requiring extensive a priori information or environmental models. Results also illustrate how the system effectively learns a strategy that allows the camera to foveate only in situations where successful detection is highly likely.
Congestion due to Rate Variations in cdma2000 Data Networks
Authors: Vikas Paliwal, Parsa Larijani, Ioannis Lambadaris, Biswajit Nandy
Venue: Wireless Personal Communications: An International Journal (2006)

In order to support high data rate requirements and effectively manage the scarce wireless resources, additional bandwidth channels are allocated and taken away from mobile stations in 3G wireless data networks quite frequently. A TCP sender connected to the mobile, on seeing ACKs coming at a faster pace after additional bandwidth allocation, turns overtly optimistic and injects data into the network at a rate that might be excessive for an intermediate router, thereby leading to loss of multiple packets and subsequent prolonged recovery and periods of underutilization. In this work, we characterize this problem using an analytical model for losses based on continuous flow approximation as well as an extensive simulation setup. We also illustrate how bandwidth oscillations create more severe congestion than an increase in number of users to the extent that even RED algorithm is unable to check the sharp growth of queues. As a result, multiple packets are lost in a droptail fashion. We further demonstrate the dependence of congestion due to bandwidth allocation on the time during which mobiles' rates are increased and observe the degradation in performance for typical load scenarios. We also try to identify the boundary for stable operation of RED and finally present some possible methods for improving the performance.
Report from the 4th International Workshop on Net-Centric Computing (NCC 2005)
Authors: Scott Tilley, Kostas Kontogiannis
Venue: Proceedings of the 13th IEEE International Workshop on Software Technology and Engineering Practice (2005)

This paper reports on the activities and results from the 4th International Workshop on Net-Centric Computing (NCC 2005) that was held on September 25, 2005 in Budapest, Hungary as part of the 13th Software Technology and Engineering Practice conference (STEP 2005). The theme of NCC 2005 was "Middleware: The Next Generation." The workshop focused on issues related to emerging middleware technologies in an NCC environment. Representative topics included gap analysis of current middleware offerings, empirical studies of middleware as an enabling technology for NCC applications, and forecasts for new directions in middleware in the coming years.
Individual differences in sense of classroom community
Authors: Fengfeng Ke
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

The paper proposed reports a causal-comparative study that were conducted to examine whether the sense of community development differs by students' characteristics in both traditional and online course setting. Subjects comprise 171 undergraduate students enrolled in a major American university. Specifically, the researchers investigate whether students' learning preference, gender, and peer-acquaintance level influence their sense of community after controlling for initial differences, and whether their sense of community correlates with course grades.
A Novel RF Test Scheme Based on a DFT Method
Authors: Jee-Youl Ryu, Bruce C. Kim, Iboun Sylla
Venue: Journal of Electronic Testing: Theory and Applications (2006)

This paper presents a new RF testing scheme based on a design-for-testability (DFT) method for measuring functional specifications of RF integrated circuits (IC). The proposed method provides the input impedance, gain, noise figure, voltage standing wave ratio (VSWR) and output signal-to-noise ratio (SNR) of a low noise amplifier (LNA). The RF test scheme is based on theoretical expressions that produce the actual RF device specifications by utilizing the output DC voltages from the DFT chip. This technique can save marginally failing chips in production testing as well as in the system, hence saving a tremendous amount of revenue from unnecessary device replacements.