ppxscal/embedding_network huggingface dataset:
Hessian-Based Model Reduction for Large-Scale Data Assimilation Problems
Authors: Omar Bashir, Omar Ghattas, Judith Hill, Bart Bloemen Waanders, Karen Willcox
Venue: Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007 (2007)

Assimilation of spatially- and temporally-distributed state observations into simulations of dynamical systems stemming from discretized PDEs leads to inverse problems with high-dimensional control spaces in the form of discretized initial conditions. Solution of such inverse problems in "real-time" is often intractable. This motivates the construction of reduced-order models that can be used as surrogates of the high-fidelity simulations during inverse solution. For the surrogates to be useful, they must be able to approximate the observable quantities over a wide range of initial conditions. Construction of the reduced models entails sampling the initial condition space to generate an appropriate training set, which is an intractable proposition for high dimensional initial condition spaces unless the problem structure can be exploited. Here, we present a method that extracts the dominant spectrum of the input-output map (i.e. the Hessian of the least squares optimization problem) at low cost, and uses the principal eigenvectors as sample points. We demonstrate the efficacy of the reduction methodology on a large-scale contaminant transport problem.
Algorithmic performance studies on graphics processing units
Authors: Olaf Schenk, Matthias Christen, Helmar Burkhart
Venue: Journal of Parallel and Distributed Computing (2008)

We report on our experience with integrating and using graphics processing units (GPUs) as fast parallel floating-point co-processors to accelerate two fundamental computational scientific kernels on the GPU: sparse direct factorization and nonlinear interior-point optimization. Since a full re-implementation of these complex kernels is typically not feasible, we identify the matrix-matrix multiplication as a first natural entry-point for a minimally invasive integration of GPUs. We investigate the performance on the NVIDIA GeForce 8800 multicore chip initially architectured for intensive gaming applications. We exploit the architectural features of the GeForce 8800 GPU to design an efficient GPU-parallel sparse matrix solver. A prototype approach to leverage the bandwidth and computing power of GPUs for these matrix kernel operation is demonstrated resulting in an overall performance of over 110 GFlops/s on the desktop for large matrices and over 38 GFlops/s for sparse matrices arising in real applications. We use our GPU algorithm for PDE-constrained optimization problems and demonstrate that the commodity GPU is a useful co-processor for scientific applications.
Prediction of Protein Homo-oligomer Types with a Novel Approach of Glide Zoom Window Feature Extraction
Authors: Qi-Peng Li, Shao-Wu Zhang, Quan Pan
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

A novel approach of glide zoom window feature extraction based on protein sequence was proposed for predicting protein homo-oligomers. Based on the concept of glide zoom window, three feature vectors of amino acids distance sum, amino acids mean distance and amino acids distribution, were extracted. A series of feature sets were constructed by combing these feature vectors with amino acids composition to form pseudo amino acid compositions (PseAAC). The support vector machine (SVM) was used as base classifier. The 73.19% total accuracy is arrived in jackknife test, which is 7.87% higher than that of conventional amino acid composition method. The results show that the novel feature extraction method of glide zoom window is effective and feasible, and the feature vectors extracted with this method may contain more protein structure information.
Dynamic Scheduling and Control System Based on Multi-layer Mixed Construction of Manufacturing Resource Agents
Authors: Yan Cao, Yanli Yang, Lina Yang
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

Faced with processing time uncertainties, equipment reliability/availability, demand changes, manpower fluctuation and so on in a dynamic manufacturing environment, an organization structure for agile production scheduling and control based on MAS is put forward to achieve effective and efficient production. A hybrid multi-layer agent structure is put forward to facilitate constructing various agents. Bidding mechanism is adopted to decompose and assign manufacturing tasks that determine the cooperative relationship among agents at different levels. The integration of task assignment and scheduling is realized through capability matching and dynamic scheduling. Agent granularity and MAS model are determined dynamically according to production demands. Consequently, all resources in a manufacturing system are reorganized into an agile manufacturing network of agents to collaboratively plan, control and manage distributed production by exploiting the autonomous and cooperative characteristics of various agents.
Estimation of Force Motor Command to Control Robot by NIRS-Based BCI
Authors: Tadashi Tsubone, Kiyotaka Tsutsui, Takeo Muroga, Yasuhiro Wada
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

We consider a possibility for estimating force amplitude and start and end timing of movements based on hemoglobin density by using near-infrared spectroscopy (NIRS). In first experiments, subjects carried out isometric movements of three levels of force amplitude in order to measure EMG, force amplitude and hemoglobin density, and these relationships were investigated. We confirmed strong correlations between these measurements. From these relationships we propose two estimation models; one is to estimate the EMG from hemoglobin density and the other is to estimate the force amplitude from the estimated EMG. We can construct estimation models with high performance by minimizing AIC. Second, we examines the estimation of start and end timing of tapping movement by using NIRS signal around pyramidal area. We show the analysis of regional cerebral blood flow during maximum tapping effort movement and the method to quantitatively estimate start and end timing of movement. Finally, we show an example of a BMI system applying estimation models to control an arm robot.
Mechanism design for abstract argumentation
Authors: Iyad Rahwan, Kate Larson
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

Since their introduction by Dung over a decade ago, abstract argumentation frameworks have received increasing interest in artificial intelligence as a convenient model for reasoning about general characteristics of argument. Such a framework consists of a set of arguments and a binary defeat relation among them. Various semantic and computational approaches have been developed to characterise the acceptability of individual arguments in a given argumentation framework. However, little work exists on understanding the strategic aspects of abstract argumentation among self-interested agents. In this paper, we introduce (game-theoretic) argumentation mechanism design (ArgMD), which enables the design and analysis of argumentation mechanisms for self-interested agents. We define the notion of a direct-revelation argumentation mechanism, in which agents must decide which arguments to reveal simultaneously. We then design a particular direct argumentation mechanism and prove that it is strategy proof under specific conditions; that is, the strategy profile in which each agent reveals its arguments truthfully is a dominant strategy equilibrium.
Modeling Interactions between Biochemical Reactions
Authors: A. Ehrenfeucht, G. Rozenberg
Venue: Proceedings of the 29th international conference on Applications and Theory of Petri Nets (2008)

From the information processing point of view a living cell consists of a (huge) number of biochemical reactions that interact with each other. Two main mechanisms through which biochemical reactions influence each other are facilitation and inhibition. Therefore it is reasonable to base a formal model of interactions between biochemical reactions on a suitable formalization of these two mechanisms. Recently introduction reaction systems is a formal model following this way of reasoning.We have made a number of assumptions that hold for a great number of biochemical reactions and therefore underlie the model of reaction systems. The assumptions are:Reactions are primary, while structures are secondary.There is a "threshold supply" of elements: either an element is present and then there is "enough" of it, or an element is not present. Thus there is no counting in the basic model.There is no "permanency" of elements: if "nothing" happens to an element, then it ceases to exist. Sustaining an element requires an effort ("life/existence must be sustained").We will argue that assumptions underlying the functioning of biochemical reactions are very different to the underlying axioms of standard models in theoretical computer science (including the model of Petri nets).
Fair(er) and (Almost) Serene Committee Meetings with Logical and Formal Concept Analysis
Authors: Mireille Ducassé, Sébastien Ferré
Venue: Proceedings of the 16th international conference on Conceptual Structures: Knowledge Visualization and Reasoning (2008)

In academia, many decisions are taken in committee, for example to hire people or to allocate resources. Genuine people often leave such meetings quite frustrated. Indeed, it is intrinsically hard to make multi-criteria decisions, selection criteria are hard to express and the global picture is too large for participants to embrace it fully. In this article, we describe a recruiting process where logical concept analysis and formal concept analysis are used to address the above problems. We do not pretend to totally eliminate the arbitrary side of the decision. We claim, however, that, thanks to concept analysis, genuine people have the possibility to 1) be fair with the candidates, 2) make a decision adapted to the circumstances, 3) smoothly express the rationales of decisions, 4) be consistent in their judgements during the whole meeting, 5) vote (or be arbitrary) only when all possibilities for consensus have been exhausted, and 6) make sure that the result, in general a total order, is consistent with the partial orders resulting from the multiple criteria.
A Robust Regression Model for Simultaneous Localization and Mapping in Autonomous Mobile Robot
Authors: Xinzheng Zhang, Ahmad B. Rad, Yiu-Kwong Wong
Venue: Journal of Intelligent and Robotic Systems (2008)

Segment-based maps as sub-class of feature-based mapping have been widely applied in simultaneous localization and map building (SLAM) in autonomous mobile robots. In this paper, a robust regression model is proposed for segment extraction in static and dynamic environments. We adopt the MM-estimate to consider the noise of sensor data and the outliers that correspond to dynamic objects such as the people in motion. MM-estimates are interesting as they combine high efficiency and high breakdown point in a simple and intuitive way. Under the usual regularity conditions, including symmetric distribution of the errors, these estimates are strongly consistent and asymptotically normal. This robust regression technique is integrated with the extended Kalman filter (EKF) to build a consistent and globally accurate map. The EKF is used to estimate the pose of the robot and state of the segment feature. The underpinning experimental results that have been carried out in static and dynamic environments illustrate the performance of the proposed segment extraction method.
Towards Efficient Evolutionary Design of Autonomous Robots
Authors: Peter Krčah
Venue: Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware (2008)

Recent works explored the possibility of designing physical robots using evolutionary algorithms. We propose a novel algorithm for the evolution of morphology and control of autonomous robots controlled by artificial neural networks. The proposed algorithm is inspired by NeuroEvolution of Augmenting Topologies (NEAT) which efficiently evolves artificial neural networks. All three main components of NEAT algorithm (protecting evolutionary innovation through speciation, effective crossover of neural networks with different topologies and incremental growth from minimal structure) are applied to the evolution of both morphology and control system of a robot. Large-scale experiments with simulated robots have shown that the proposed algorithm uses significantly less fitness evaluations than a standard genetic algorithm on all four tested fitness functions. Positive contribution of each component of the proposed algorithm has been confirmed with a series of supplementary ablation experiments. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Dynamic Cooperative Coevolutionary Sensor Deployment Via Localized Fitness Evaluation
Authors: Xingyan Jiang, Yuanzhu Peter Chen, Tina Yu
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

We propose an innovative cooperative co-evolutionary computation framework, Dynamic Cooperative Coevolution (DCC), which provides dynamic coupling of neighboring species for the fitness evaluation of individuals. One feature of DCC is the utilization of local fitness to achieve a global optimum, which makes it possible for co-evolutionary algorithms to be applied in localized distributed environments, such as network computing. This work is motivated by our interest in autonomous sensor deployment, where a sensor can only communicate with those within a limited range. Our experiments show that DCC is effective in obtaining good solutions under such distributed and localized conditions.
A Novel ID-Based Threshold Ring Signature Scheme Competent for Anonymity and Anti-forgery
Authors: Yu Fang Chung, Zhen Yu Wu, Feipei Lai, Tzer Shyong Chen
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

This study presents an approach to improving the (t, n) ring signature, which permits a signer to sign anonymously. Using fair partitioning to design a new (t, n) threshold ring signature based on bilinear pairing, the study develops a threshold signature method. The proposed method not only permits total signer anonymity, but also resist the signature of an anonymous signer from being forged even in a random oracle mode. Besides, the method is competent for protecting the identity and signature of a signer in regard to the anonymity property of ring signature. Therefore, this method trends suitable for those application complex, such as electronic voting and electronic cash, as well as for democratic management in which members with specific threshold value voice their opinion.
An Approximation Algorithm for Binary Searching in Trees
Authors: Eduardo Laber, Marco Molinaro
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

In this work we consider the problem of computing efficient strategies for searching in trees. As a generalization of the classical binary search for ordered lists, suppose one wishes to find a (unknown) specific node of a tree by asking queries to its arcs, where each query indicates the endpoint closer to the desired node. Given the likelihood of each node being the one searched, the objective is to compute a search strategy that minimizes the expected number of queries. Practical applications of this problem include file system synchronization and software testing. Here we present a linear time algorithm which is the first constant factor approximation for this problem. This represents a significant improvement over previous O(logn)-approximation.
Matching XML documents in highly dynamic applications
Authors: Adrovane M. Kade, Carlos A. Heuser
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

Highly dynamic applications like the Web and peer-to-peer systems require a great deal of effort in document management. Documents from different sources may contain parts that, although having different structure or different contents, may be considered as representing the same conceptual information. One essential task in this scenario is the identification of complementary or overlapping documents that need to be integrated. In this paper, we deal specifically with documents represented in the XML format. XML document integration is an important process in highly dynamic applications, for the volume of data available in this format is constantly growing. XML integration is also a challenging task, due to the flexible nature of XML, which may lead to structure divergences and content conflicts between the documents. In this work, we present a novel approach to the matching problem, i.e., the problem of defining which parts of two documents contain the same information. Matching is usually the first step of an integration process. Our approach is novel in the sense it combines similarity information from the content of the elements with information from the structure of the documents. This feature, as our experiments confirm, makes our approach capable of dealing with content as well as structural divergences.
Information Leakage Caused by Hidden Data in Published Documents
Authors: Simon Byers
Venue: IEEE Security and Privacy (2004)

Inconsidering theleakage ofinformationthrough hidden text mechanismsin commonlyused information interchangeformats, the author demonstrates how to automate and scale the search for hidden data in Microsoft Word documents. The combination of this scaling with typical behavior patterns of Word users and the default settings of the Word program leads to an uncomfortable state of affairs for Word users concerned about information security. The author discusses some countermeasures employable by users and notes more general consequences of these effects.
Combining weights with fuzziness for intelligent semantic web search
Authors: Hai Jin, Xiaomin Ning, Weijia Jia, Hao Wu, Guilin Lu
Venue: Knowledge-Based Systems (2008)

Intelligent retrieval for best satisfying users search intensions still remains a challenging problem due to the inherent complexity of real-world semantic web applications. Usually, a search request contains not only vagueness or imprecision, but also personalized information goals. This paper presents a novel approach which formulates one's search request through tightly combining fuzziness together with the user's subjective weighting importance over multiple search properties. A special ranking mechanism based on the weighed fuzzy query representation is proposed. The ranking method generates a set of ''degree of relevance'' - an overall score which reflects both fuzzy predicates and the user's personalized preferences in the search request. Moreover, the ranking method is general and unique rather than arbitrary. Hence, search results shall be properly ordered in terms of their relevance with respect to best matching the search intension. The experimental results show that our approach can effectively capture users information goals and produce much better search results than existing approaches.
Exploring the potential effects of emoticons
Authors: Albert H. Huang, David C. Yen, Xiaoni Zhang
Venue: Information and Management (2008)

Instant messaging (IM) has shown signs of becoming one of the main stream communication applications for users, like e-mail. Many people maintain constant contacts with multiple friends and relations via IM simultaneously whenever they are online, whether working on other applications or not. In addition to allowing instant exchange of text information, a unique feature of IM is its use of graphical icons that express emotions, known as emotional icons or emoticons. We explored their potential effects. Our model, based on prior theory and research, was tested using data collected from student users; it was analyzed to reveal potential effects of emoticons on various factors related to the use of IM. Our study used structural equation modeling (SEM) analysis; the results showed that the user of emoticons felt a positive effect on enjoyment, personal interaction, perceived information richness, and perceived usefulness. Our results suggested, however, that emoticons were not just enjoyable to use, but also a valuable addition to communication methods.
Answering what-if deployment and configuration questions with wise
Authors: Mukarram Tariq, Amgad Zeitoun, Vytautas Valancius, Nick Feamster, Mostafa Ammar
Venue: Proceedings of the ACM SIGCOMM 2008 conference on Data communication (2008)

Designers of content distribution networks often need to determine how changes to infrastructure deployment and configuration affect service response times when they deploy a new data center, change ISP peering, or change the mapping of clients to servers. Today, the designers use coarse, back-of-the-envelope calculations, or costly field deployments; they need better ways to evaluate the effects of such hypothetical "what-if" questions before the actual deployments. This paper presents What-If Scenario Evaluator (WISE), a tool that predicts the effects of possible configuration and deployment changes in content distribution networks. WISE makes three contributions: (1) an algorithm that uses traces from existing deployments to learn causality among factors that affect service response-time distributions; (2) an algorithm that uses the learned causal structure to estimate a dataset that is representative of the hypothetical scenario that a designer may wish to evaluate, and uses these datasets to predict future response-time distributions; (3) a scenario specification language that allows a network designer to easily express hypothetical deployment scenarios without being cognizant of the dependencies between variables that affect service response times. Our evaluation, both in a controlled setting and in a real-world field deployment at a large, global CDN, shows that WISE can quickly and accurately predict service response-time distributions for many practical What-If scenarios.
Dynamic PIV Measurement of a High-Speed Flow Issuing from Vent-Holes of a Curtain-Type Airbag
Authors: S. J. Lee, Y. G. Jang, Y. S. Choi, W. P. Ha
Venue: Journal of Visualization (2008)

A curtain-type airbag is a safety device designed to protect passengers from the side collisions of a car. The curtain-type airbag system consists of an inflator, a fill-hose, and a curtain-airbag. The fill-hose is a passageway and distributor of the exploded gases from the inflator to the airbag through vent-holes. Although the design of vent-holes is important for proper deployment of the airbag, it is very difficult to measure the exceedingly high speed flow issuing from the vent-holes by using conventional measurement methods. In this study, we employed a dynamic PIV technique to measure the temporal evolution of instantaneous velocity fields of the flow ejecting from the vent-holes. From the velocity field data measured at a frame rate of 2000 fps, the temporal variation of the volume flux from vent-holes was also evaluated for the diagnosis of airbag performance. The flows ejecting from the vent-holes showed high velocity fluctuations, and the maximum velocity was about 480 m/s. The instantaneous velocity fields in the initial stage showed a swaying motion of a high-speed jet. The accumulated volume flux from the vent-holes was also compared at each vent-hole region.