ppxscal/embedding_network huggingface dataset:
Modelling Event Communication to Enable Adaptive Behaviour in Resource- Constrained Distributed Virtual Environments
Authors: Stephen Workman Gerard Parr Philip Morrow Darryl Charles
Venue: Proceedings of the International Conference on Autonomic and Autonomous Systems (2006)

In this paper we propose a model of event communication to be used in an adaptive, resourceaware mobile multimedia application. Distributed virtual environments (DVEs) must employ application layer adaptation to deal with the variable resource availability of wireless networks and client devices. To enable such adaptation, we propose a model of typical DVE event traffic which is based on the available and required resources as seen at the application level. Building upon existing research which takes overall traffic characteristics into consideration, our model introduces the individual event streams and their effect on the overall network resource requirements (bandwidth, delay and packet loss). The model is evaluated using traffic analysis from a typical multiplayer game (Quake II). We conclude by discussing the importance of the proposed model within the framework of a resource-aware, adaptive DVE system, highlighting the implications for wireless communication.
Time Series Prediction Using Nonlinear Support Vector Regression Based on Classification
Authors: MAO XueMin, YANG Jie
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)

In this paper, an introduction of traditional time series prediction model using SVM has been first given, and then followed by description of a new network training algorithm and a nonlinear regression algorithm of support vector machine which are based on classification. Compared with traditional SVM regression algorithm, CSVR algorithm is less sensitive and more robust. It is another advantage that the value of the parameters can be set according to individual situation. More importantly, this method can also escape from over-fitting. Finally, an analysis of this new method has been given to demonstrate the validity of this method.
Buffered asynchronous communication mechanisms
Authors: Fei Xia, Fei Hao, Ian Clark, Alex Yakovlev, E. Graeme Chester
Venue: Fundamenta Informaticae (2005)

Previous work on asynchronous communication mechanisms (ACMs) has not dealt with buffered forms (with the number of data cells n>1). This paper describes a systematic design/synthesis process for ACMs with arbitrary buffer size, a series of resulting buffered ACM algorithms, and the modelling and simulation of these ACMs using Matlab, putting ACMs (esp. buffered ones) in the context of complex engineering systems.
Memory Fault Simulator for Static-Linked Faults
Authors: A. Benso, A. Bosio, S. Di Carlo, G. Di Natale, P. Prinetto
Venue: Proceedings of the 15th Asian Test Symposium (2006)

Static Linked Faults are considered an interesting class of memory faults. Their capability of influencing the behavior of other faults causes the hiding of the fault effect and makes test algorithm design and validation a very complex task. This paper presents a Memory Fault Simulator architecture targeting the full set of linked faults.
Palisade Corporation
Authors: Abigail Holley
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Using data for your advantage. Palisade Corporation, the leader in analysis and simulation software tools, is pleased to announce the release of NeuralTools, the Neural Networks add-in for Microsoft Excel. NeuralTools has a broad range of applications where sets of data can be used to predict future outcomes. In this session, attendees will discover how to analyze and use existing data to solve problems and identify opportunities. This seminar will include the use of NeuralTools in prediction applications. Statistical analysis with Palisade's StatTools and analysis under uncertainty using @RISK will also be covered. 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
An Extensible Service Development Toolkit to Support Earth Science Grids
Authors: Jason Cope, Henry M. Tufo, Matthew Woitaszek
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

This paper describes the development and use of an extensible service provider toolkit (ESP) for an Earth Science service-oriented architecture (SOA). Grid-enabled Earth Science applications and tools are beginning to use web services to integrate distributed resources and legacy applications. Unfortunately, each application requires substantial effort often repeated to implement base Grid functionality before addressing application-specific requirements. In an effort to help Earth Science application developers more rapidly develop these web services, we have created an extensible service provider toolkit. The toolkit provides the foundation to develop specialized services for Earth Science Grids, including legacy application and computational resource services. To demonstrate the functionality of ESP, we redeveloped several existing web services and illustrate ESP's benefits, including reduced software development time and software reuse.
Brain Potentials Reflect Behavioral Differences in True and False Recognition
Authors: Tim Curran, Daniel L. Schacter, Marcia K. Johnson, Ruth Spinks
Venue: Journal of Cognitive Neuroscience (2001)

People often falsely recognize nonstudied lures that are semantically similar to previously studied words. Behavioral research suggests that such false recognition is based on high semantic overlap between studied items and lures that yield a feeling of familiarity, whereas true recognition is more often associated with the recollection of details. Despite this behavioral evidence for differences between true and false recognition, research measuring brain activity (PET, fMRI, ERP) has not clearly differentiated corresponding differences in brain activity. A median split was used to separate subjects into Good and Poor performers based on their discrimination of studied targets from similar lures. Only Good performers showed late (1000&ndash;1500 msec), right frontal event-related brain potentials (ERPs) that were more positive for targets and lures compared with new items. The right frontal differences are interpreted as reflecting postretrieval evaluation processes that were more likely to be engaged by Good than Poor performers. Both Good and Poor performers showed a parietal ERP old/new effect (400&ndash;800 msec), but only Poor performers showed a parietal old/lure difference. These results are consistent with the view that the parietal and frontal ERP old/new effects reflect dissociable processes related to recollection.
Accelerating Newton Optimization for Log-Linear Models through Feature Redundancy
Authors: Arpit Mathur, Soumen Chakrabarti
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Log-linear models are widely used for labeling feature vectors and graphical models, typically to estimate robust conditional distributions in presence of a large number of potentially redundant features. Limited-memory quasi-Newton methods like LBFGS or BLMVM are optimization workhorses for such applications, and most of the training time is spent computing the objective and gradient for the optimizer. We propose a simple technique to speed up the training optimization by clustering features dynamically, and interleaving the standard optimizer with another, coarse-grained, faster optimizer that uses far fewer variables. Experiments with logistic regression training for text classification and conditional random field (CRF) training for information extraction show promising speed-ups between 2× and 9× without any systematic or significant degradation in the quality of the estimated models.
Assessment on Undetectable Burst Errors in Tandem CRCs
Authors: Meng-Lai Yin, Bruce Orenstein
Venue: Proceedings of the 12th Pacific Rim International Symposium on Dependable Computing (2006)

This paper addresses the conditional probability for undetectable burst errors when using two CRC (Cyclic Redundancy Check) codes in tandem, given that nonguaranteed- detectable burst errors have occurred. Three distinctive cases are dsicussed based on the error positions and the conditional probability of undetectable errors under each case is derived. Because this probability depends on the exact CRC polynomials selected, an upper-bound assessment is provided to address general cases.
Can distributed software development be agile?
Authors: Balasubramaniam Ramesh, Lan Cao, Kannan Mohan, Peng Xu
Venue: Communications of the ACM (2006)

Three organizations studied here suggest the answer is "yes," when the unique characteristics of both environments are successfully blended.
Towards dynamic adaptation of i/o scheduling in commodity operating systems
Authors: Patricia J. Teller
Venue:  (2006)

Disk scheduling algorithms in operating systems often are designed to satisfy a primary application data delivery requirement. Multiple concurrent and conflicting requirements need to be satisfied to support concurrently executing applications. Accordingly, a disk scheduling algorithm that is designed to concurrently satisfy multiple data delivery requirements is crucial to the support of diverse architectures, disk systems, and workloads. To concurrently satisfy multiple data delivery requirements, we implement and evaluate a mechanism that dynamically switches between two policies in order to enforce two performance requirements. This two-policy adaptation strives to provide latency guarantees for requests at all times and, when all requests meet their latency requirements, it strives to simultaneously provide fairness in terms of number of requests. This dissertation presents a description of the two-policy adaptation and demonstrates why, in some cases, it cannot simultaneously satisfy both performance requirements. Also, the fairness of the number of requests metric is disputed. Accordingly, we next leverage a fair queuing discipline and implement a fair scheduling algorithm that can be extended to satisfy multiple data delivery requirements concurrently. Our new scheduling strategy uses compensated disk-time as the resource-sharing metric and achieves fairness and predictable application performance. To the best of our knowledge, ours is the only I/O scheduling algorithm that provides predictability in application performance, one of the most important system requirements. In addition, this algorithm and the underlying queuing system is flexible enough to implement the enforcement of a number of other performance requirements such as request latencies, anticipation of requests, and service level objectives, while concurrently providing fairness. In this dissertation we describes the impact of different resource-sharing metrics of conventional fair scheduling on application performance predictability. We present the fairness properties, analytical and experimental evaluations of various fair scheduling algorithms.
Catalan and Apéry numbers in residue classes
Authors: Moubariz Z. Garaev, Florian Luca, Igor E. Shparlinski
Venue: Journal of Combinatorial Theory Series A (2006)

We estimate character sums with Catalan numbers and middle binomial coefficients modulo a prime p. We use this bound to show that the first at most p13/2(log p)6 elements of each sequence already fall in all residue classes modulo every sufficiently large p, which improves the previously known result requiring pO(p) elements. We also study, using a different technique, similar questions for sequences satisfying polynomial recurrence relations like the Apéry numbers. We show that such sequences form a finite additive basis modulo p for every sufficiently large prime p.
A Novel Bargaining Based Dynamic Spectrum Management Scheme in Reconfigurable Systems
Authors: Miao Pan, Shuo Liang, Haozhi Xiong, Jie Chen, Guangyi Li
Venue: Proceedings of the International Conference on Systems and Networks Communication (2006)

B3G wireless networks are expected to be characterized by the pouring of diversified services supported by different operators. In parallel with this, how to efficiently utilize the limited radio spectrum and guarantee the operator's profits has become a joint economical and technical problem. As a possible solution, in this paper, we set forth a novel bargaining approach for dynamic spectrum management (DSM) based on alternating-offer bargaining games in microeconomics. In the context of distributed reconfigurable networks in the charge of different operators, bargaining based dynamic spectrum management (BDSM) scheme introduces trading agent (TA), changing bargaining ability as well as revenue-sharing mechanism to facilitate the spectrum trading. Related technologies, bargaining games and proposed algorithm are also described in details. Simulation results show that with imperfect load predicting, BDSM is effective in improving the utilization of spectrum, expanding the individual operator's profits and enhancing the fairness among different RANs (radio access networks).
DR-Prolog: A System for Defeasible Reasoning with Rules and Ontologies on the Semantic Web
Authors: Grigoris Antoniou, Antonis Bikakis
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

Nonmonotonic rule systems are expected to play an important role in the layered development of the Semantic Web. Defeasible reasoning is a direction in nonmonotonic reasoning that is based on the use of rules that may be defeated by other rules. It is a simple, but often more efficient approach than other nonmonotonic rule systems for reasoning with incomplete and inconsistent information. This paper reports on the implementation of a system for defeasible reasoning on the Web. The system 1) is syntactically compatible with RuleML, 2) features strict and defeasible rules, priorities, and two kinds of negation, 3) is based on a translation to logic programming with declarative semantics, 4) is flexible and adaptable to different intuitions within defeasible reasoning, and 5) can reason with rules, RDF, RDF Schema, and (parts of) OWL ontologies.
An Emprical Evaluation of Memory Management Alternatives for Real-Time Java
Authors: Filip Pizlo, Jan Vitek
Venue: Proceedings of the 27th IEEE International Real-Time Systems Symposium (2006)

Memory management is a critical issue for correctness and performance of hard-real time systems. Java environments usually incorporate high-throughput garbage collection algorithms, but these algorithms can induce pause times in excess of 100 milliseconds. This is not acceptable for a real-time system. Two approaches for remedying this problem are being investigated. The pause times can be bounded with a real-time garbage collector; or a means to program around the collector entirely can be provided, as is done in the Real-time Specification for Java with its Scoped Memory interface. This paper presents the first side-by-side empirical evaluation of the impact of memory management regimes on realistic realtime applications. We present usability arguments as well as a detailed performance comparison of scoped memory and real-time garbage collection. Experience with medium sized systems suggests that while programming with Scoped Memory is error prone, it provides substantially better throughput. We have observed a throughput reduction of up to 37% and, in the worst-case, an 80% latency penalty for real-time garbage collection.
Impact of paging channel overloads or attacks on a cellular network
Authors: Jérémy Serror, Hui Zang, Jean C. Bolot
Venue: Proceedings of the 5th ACM workshop on Wireless security (2006)

IP and cellular phone networks used to be isolated from each other. In recent years however, the two networks have started to overlap with the emergence of devices that access the Internet using cellular infrastructures. One important question then, given this overlap, is whether actions or threats on the Internet side can impact the telecom or cellular side. We address this problem in the paper and specifically consider threats on the paging channel, which is a key conduit shared by both Internet and cellular traffic.Our contributions are as follows: we illustrate through experiments on a CDMA2000 cellular network that overloads or attacks launched from the Internet can significantly increase the paging load and increase the delay of paging messages, including cellular call setup requests, which in turn could lead to non-completed calls; we derive a simple but accurate queuing model for the paging system in a CDMA2000 network and use this model to demonstrate that the paging channel exhibits sharp rather than graceful degradation under load; and through this model, we identify critical parameters that impact paging performance. Although our study is focused on CDMA2000 networks, we believe that similar problems exist in other types of cellular networks that employ a single control channel with limited bandwidth for both voice and data services.
A Novel Predictive Control and Its Application on Water Level System of Ship Boiler
Authors: Sheng Liu, Yanyan Li
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

Water level is an important index to ensure the safety and stable operation of the ship boiler. Because of the nonlinear and time lag of the water level system, normal PID control can't obtain the satisfactory effect. So the improved neural network predictive control based on support vector machine (SVM) was presented. This method used SVM to identify the predictive model of the system, and used BP network based on simulated annealing (SA) algorithm to make receding optimization. Finally, this method was applied to the water level control system of ship boiler. The simulation results show that this method has high precision, and it's also suit for the engineering application.
Propagation of in-plane waves in an isotropic panel with a crack
Authors: Arkadiusz Zak, Marek Krawczuk, Wieslaw Ostachowicz
Venue: Finite Elements in Analysis and Design (2006)

The paper presents certain results of the analysis of wave propagation in an isotropic panel with damage in the form of a fatigue crack. This problem is solved by the use of the spectral element method. In the current approach the panel is modelled by a number of 36-node spectral membrane finite elements with nodes defined at appropriate Gauss-Lobatto-Legendre points. As approximation polynomials the 5th order orthogonal Lagrange polynomials have been used. In order to calculate the element characteristic stiffness and mass matrices the Gauss-Lobatto quadrature has been applied. The crack can be of an arbitrary length, depth, and location. The elastic behaviour of the panel at the crack location is simulated as a line spring with a varying stiffness along the crack length. Numerical calculations are carried out for various locations of the crack in the panel as well as for the panel with stiffeners. The problem of the identification of the crack from the transmitted and reflected waves is also considered in the paper.
Answering XML Queries Using Path-Based Indexes: A Survey
Authors: Kam-Fai Wong, Jeffrey Xu Yu, Nan Tang
Venue: World Wide Web (2006)

The problem of answering XML queries using path-based indexes is to find efficient methods for accelerating the XML query with pre-designed index structures over the XML database. This problem received increasing interests and have been lucubrated in recent years. Regular path expression is the core of the XML query languages e.g., XPath and XQuery. Most of the state-of-the-art path-based XML indexes, therefore, hammer at how to efficiently answer the path-based XML queries. This paper surveys various approaches to indexing XML data proposed in the literature. We give a step by step analysis to show the evolution of index structures for XML path information, based on tree structures or more commonly, directed labeled graphs. For each approach, we first present the specific issue it aims to tackle, and then the proposed solution presented. Furthermore, construction, physical data storage and maintenance costs, are analyzed.
Clustering-Based Source Selection for Efficient Image Retrieval in Peer-to-Peer Networks
Authors: Martin Eisenhardt, Wolfgang Muller, Andreas Henrich, Daniel Blank, Soufyane El Allali
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

In peer-to-peer (P2P) networks, computers with equal rights form a logical (overlay) network in order to provide a common service that lies beyond the ca- pacity of every single participant. Efficient similarity search is generally recognized as a frontier in research about P2P systems. One way to address it is using data source selection based approaches where peers summa- rize the data they contribute to the network, generat- ing typically one summary per peer. When process- ing queries, these summaries are used to choose the peers (data sources) that are most likely to contribute to the query result. Only those data sources are con- tacted. There are two main contributions of this paper. We extend earlier work, adding a data source selec- tion method for high-dimensional vector data, compar- ing different peer ranking schemes. More importantly, we present a method that uses progressive stepwise data exchange between peers to better each peer's summary and therefore improve the system's performance.
Towards robust indexing for ranked queries
Authors: Dong Xin, Chen Chen, Jiawei Han
Venue: Proceedings of the 32nd international conference on Very large data bases (2006)

Top-k query asks for k tuples ordered according to a specific ranking function that combines the values from multiple participating attributes. The combined score function is usually linear. To efficiently answer top-k queries, preprocessing and indexing the data have been used to speed up the run time performance. Many indexing methods allow the online query algorithms progressively retrieve the data and stop at a certain point. However, in many cases, the number of data accesses is sensitive to the query parameters (i.e., linear weights in the score functions).In this paper, we study the sequentially layered indexing problem where tuples are put into multiple consecutive layers and any top-k query can be answered by at most k layers of tuples. We propose a new criterion for building the layered index. A layered index is robust if for any k, the number of tuples in the top k layers is minimal in comparison with all the other alternatives. The robust index guarantees the worst case performance for arbitrary query parameters. We derive a necessary and sufficient condition for robust index. The problem is shown solvable within O(ndlog n) (where d is the number of dimensions, and n is the number of tuples). To reduce the high complexity of the exact solution, we develop an approximate approach, which has time complexity O(2d n(log n)r(d)-1), where r(d) = ⌈d/2⌉ + ⌊d/2⌋ ⌈d/2⌉. Our experimental results show that our proposed method outperforms the best known previous methods.