ppxscal/embedding_network huggingface dataset:
Moving overlapping grids with adaptive mesh refinement for high-speed reactive and non-reactive flow
Authors: William D. Henshaw, Donald W. Schwendeman
Venue: Journal of Computational Physics (2006)

We consider the solution of the reactive and non-reactive Euler equations on two-dimensional domains that evolve in time. The domains are discretized using moving overlapping grids. In a typical grid construction, boundary-fitted grids are used to represent moving boundaries, and these grids overlap with stationary background Cartesian grids. Block-structured adaptive mesh refinement (AMR) is used to resolve fine-scale features in the flow such as shocks and detonations. Refinement grids are added to base-level grids according to an estimate of the error, and these refinement grids move with their corresponding base-level grids. The numerical approximation of the governing equations takes place in the parameter space of each component grid which is defined by a mapping from (fixed) parameter space to (moving) physical space. The mapped equations are solved numerically using a second-order extension of Godunov's method. The stiff source term in the reactive case is handled using a Runge-Kutta error-control scheme. We consider cases when the boundaries move according to a prescribed function of time and when the boundaries of embedded bodies move according to the surface stress exerted by the fluid. In the latter case, the Newton-Euler equations describe the motion of the center of mass of the each body and the rotation about it, and these equations are integrated numerically using a second-order predictor-corrector scheme. Numerical boundary conditions at slip walls are described, and numerical results are presented for both reactive and non-reactive flows that demonstrate the use and accuracy of the numerical approach.
Professional development that considers teachers' attitudes toward an innovation
Authors: Jeannine E. Turner, ChanMin Kim
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

This study investigated the extent to which teachers' motivation and attitudes for professional development training facilitated their willingness to implement reform strategies. Teachers completed surveys prior to training and after receiving training. Analysis compared the responses of beginning teachers (new to the process) and advanced teachers (receiving advanced training). Advanced teachers showed that their instructional strategies and goals corresponded to the innovations at the start. At the end of the training, Beginning teachers gave positive ratings for the training and their emotions toward implementing the training.
Introducing TDD on a free libre open source software project: a simulation experiment
Authors: Ivana Turnu, Marco Melis, Alessandra Cau, Michele Marchesi, Alessio Setzu
Venue: Proceedings of the 2004 workshop on Quantitative techniques for software agile process (2004)

This paper describes a simulation model that represents the first step to modeling open source software development processes. The model has been tuned using data from a real FLOSS project: Apache. The goal of our research is to show the effects of adopting TDD (Test Driven Development) on our open source simulation model. In order to introduce the TDD practice, we have only changed some parameter values in the FLOSS simulation model. In particular, the average time required to write a line of production code increases because now automated tests are also coded, the number of defects injected during coding decreases as does the debugging time to fix a single defect. The two FLOSS development models (nonTDD and TDD) have been compared, the one incorporating the agile practice of Test Driven Development yielding better results in terms of code quality (defects/Kloc).
Learning to cooperate in multi-agent social dilemmas
Authors: Enrique Munoz de Cote, Alessandro Lazaric, Marcello Restelli
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

In many Multi-Agent Systems (MAS), self-interested agents need to cooperate in order to maximize their own utilities in time. The goal of this work is to improve cooperation among agents that use best-response Reinforcement Learning (RL) algorithms (Q-Learning), by the introduction of two new principles (Change or Learn Fast and Change and Keep) that foster the reaching of Pareto efficient stable outcomes.
Testing and inspecting reusable product line components: first empirical results
Authors: Christian Denger, Ronny Kolb
Venue: Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering (2006)

In recent years, product line development has increasingly received attention in industry as it enables software-developing organizations to reduce both cost and time of developing and maintaining increasingly complex systems as well as to address the demands for individually customized products. Successful product line development requires high quality of reusable artifacts in order to achieve the promised benefits. The unique issues of quality assurance in the context of systematic reuse, however, have not been quantitatively investigated so far. This paper describes a first empirical study comparing the two defect detection techniques, code inspections and functional testing, in the context of product line development. The primary goal of the study was to initially investigate the defect finding potential of the techniques on reusable software components with common and variant features. The major findings of the study are that the two techniques identified different types of defects on variants of a reusable component. Inspections are on average 66.39% more effective and need on average 36.84% less effort to detect a defect We found that both the testing and inspection techniques applied in the experiment were ineffective in identifying variant-specific defects. Overall, the results indicate that the standard quality assurance techniques seem to be insufficient to address special characteristics of reusable components.
Treemap: An O(log n) algorithm for indoor simultaneous localization and mapping
Authors: Udo Frese
Venue: Autonomous Robots (2006)

This article presents a very efficient SLAM algorithm that works by hierarchically dividing a map into local regions and subregions. At each level of the hierarchy each region stores a matrix representing some of the landmarks contained in this region. To keep those matrices small, only those landmarks are represented that are observable from outside the region.A measurement is integrated into a local subregion using O(k2) computation time for k landmarks in a subregion. When the robot moves to a different subregion a full least-square estimate for that region is computed in only O(k3 log n) computation time for n landmarks. A global least square estimate needs O(kn) computation time with a very small constant (12.37 ms for n = 11300).The algorithm is evaluated for map quality, storage space and computation time using simulated and real experiments in an office environment.
Estimation of Internal and External Parameters for Camera Calibration Using 1D Pattern
Authors: Xiangjian He, Huaifeng Zhang, Namho Hur, Jinwoong Kim, Qiang Wu, Taeone Kim
Venue: Proceedings of the IEEE International Conference on Video and Signal Based Surveillance (2006)

Camera calibration is to estimate the intrinsic and extrinsic parameters of a camera. Most of object-based calibration methods used 3D or 2D pattern. A novel and more flexible 1D object-based calibration was introduced only a couple of years ago, but merely for estimation of intrinsic parameters. The estimation of extrinsic papers is essential when multiple cameras are involved for simultaneously taking images from different view angles and when the knowledge of relative locations between the cameras is required. Though it is relatively simple using 2D or 3D calibration pattern, the estimation of extrinsic parameters is not obvious using 1D pattern. In this paper, we will perform a 1D camera calibration involving both intrinsic and extrinsic parameters.
Multicommodity network design with discrete node costs
Authors: P. Belotti, F. Malucelli, L. Brunetta
Venue: Networks (2007)

Although there is an extensive literature dealing with network design, little attention has been devoted to networks with complicated node costs. Although node costs, depending linearly on the total passing flow, can be easily embedded into the more usual framework of networks with link costs, when the node costs are, for instance, a stepwise function of the facilities installed into the nodes, this is no longer possible. This feature seems to be crucial in modern telecommunications networks, but has also applications in other fields, where a limited set of technologies is available with discrete values of capacities and costs. In our specific application, we propose a mathematical programming model that explicitly accounts for node costs that are stepwise with nonlinear increments. Two families of valid inequalities are then introduced, one of which is an extension of those presented in a previous work by Stoer and Dahl for multifacility network models. As the separation problem for these inequalities is difficult, we develop a heuristic separation procedure. We devise a branch-and-cut method and test it on a set of real-world instances found in the network design literature. This new method proves to be efficient when compared to a commercial general purpose MIP algorithm. &copy; 2006 Wiley Periodicals, Inc. NETWORKS, Vol. 49(1), 90&ndash;99 2007
The global warming visualizer: a scientific visualization environment for education
Authors: Daniel C. Edelson, Douglas N. Gordin, Brian A. Clark
Venue: Proceedings of the 1996 international conference on Learning sciences (1996)

The new technologies of scientific visualization have had a dramatic impact on the way science is conducted in a wide variety of disciplines. The SciVEE (Scientific Visualization Environments for Education) Project at Northwestern University is engaged in developing scientific visualization environments designed to bring the advantages that scientific visualization provides for scientists to science students. Through its use of color, shape, and motion to represent quantities and processes in nature, scientific visualization enables individuals to capitalize their natural visual processing capabilities to identify patterns in complex data. In addition, it provides a representational medium to facilitate scientific dialogue. Using scientific visualization as a technology to support science learning by students, as opposed to scientists, presents significant challenges. These challenges include the adaptation of complex software for learners and the development of learning activities that take advantage of scientific visualizations unique features. The Global Warming Visualizer and its accompanying Global Warming Learning Activities are being developed to respond to these challenges. The Global Warming Visualizer is a software environment that provides students with access to a portion of the data sets that the scientific community is using to investigate global climatic issues, including global warming. The Global Warming Learning Activities introduce students to the scientific and policy issues associated with the controversies over the possibility of significant, near-term global warming.
Identification of non-measurable parameters of ferroelectrics by optimization method
Authors: S. A. Kukushkin, A. V. Osipov, P. Tu. Guzenko, V. V. Spirin
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 3 (2003)

All approach to define certain constants for ferroelectric crystals with respect to analysis of evolution of the switching current, is proposed. Algorithms for separate identification of such nonmeasurable parameters of ferroelectrics as the surface tension and the kinetic coefficients are given.
Pedestrian Detection via Periodic Motion Analysis
Authors: Yang Ran, Isaac Weiss, Qinfen Zheng, Larry S. Davis
Venue: International Journal of Computer Vision (2007)

We describe algorithms for detecting pedestrians in videos acquired by infrared (and color) sensors. Two approaches are proposed based on gait. The first employs computationally efficient periodicity measurements. Unlike other methods, it estimates a periodic motion frequency using two cascading hypothesis testing steps to filter out non-cyclic pixels so that it works well for both radial and lateral walking directions. The extraction of the period is efficient and robust with respect to sensor noise and cluttered background. In order to integrate shape and motion, we convert the cyclic pattern into a binary sequence by Maximal Principal Gait Angle (MPGA) fitting in the second method. It does not require alignment and continuously estimates the period using a Phase-locked Loop. Both methods are evaluated by experimental results that measure performance as a function of size, movement direction, frame rate and sequence length.
When response variability increases neural network robustness to synaptic noise
Authors: Gleb Basalyga, Emilio Salinas
Venue: Neural Computation (2006)

Cortical sensory neurons are known to be highly variable, in the sense that responses evoked by identical stimuli often change dramatically from trial to trial. The origin of this variability is uncertain, but it is usually interpreted as detrimental noise that reduces the computational accuracy of neural circuits. Here we investigate the possibility that such response variability might in fact be beneficial, because it may partially compensate for a decrease in accuracy due to stochastic changes in the synaptic strengths of a network. We study the interplay between two kinds of noise, response (or neuronal) noise and synaptic noise, by analyzing their joint influence on the accuracy of neural networks trained to perform various tasks. We find an interesting, generic interaction: when fluctuations in the synaptic connections are proportional to their strengths (multiplicative noise), a certain amount of response noise in the input neurons can significantly improve network performance, compared to the same network without response noise. Performance is enhanced because response noise and multiplicative synaptic noise are in some ways equivalent. So if the algorithm used to find the optimal synaptic weights can take into account the variability of the model neurons, it can also take into account the variability of the synapses. Thus, the connection patterns generated with response noise are typically more resistant to synaptic degradation than those obtained without response noise. As a consequence of this interplay, if multiplicative synaptic noise is present, it is better to have response noise in the network than not to have it. These results are demonstrated analytically for the most basic network consisting of two input neurons and one output neuron performing a simple classification task, but computer simulations show that the phenomenon persists in a wide range of architectures, including recurrent (attractor) networks and sensorimotor networks that perform coordinate transformations. The results suggest that response variability could play an important dynamic role in networks that continuously learn.
Piecewise quartic polynomial curves with a local shape parameter
Authors: Xuli Han
Venue: Journal of Computational and Applied Mathematics (2006)

Piecewise quartic polynomial curves with a local shape parameter are presented in this paper. The given blending function is an extension of the cubic uniform B-splines. The changes of a local shape parameter will only change two curve segments. With the increase of the value of a shape parameter, the curves approach a corresponding control point. The given curves possess satisfying shape-preserving properties. The given curve can also be used to interpolate locally the control points with GC2 continuity. Thus, the given curves unify the representation of the curves for interpolating and approximating the control polygon. As an application, the piecewise polynomial curves can intersect an ellipse at different knot values by choosing the value of the shape parameter. The given curve can approximate an ellipse from the both sides and can then yield a tight envelope for an ellipse. Some computing examples for curve design are given.
Achieving Reliable Broadcasting in Ad Hoc Wireless Networks with Directional Antennas
Authors: Wei Kuang Lai, Chin-Shiuh Shieh, Yi-Cheng Kuo
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

Aimed at higher reliability in broadcasting for ad hoc wireless networks, an innovative broadcasting scheme is developed and presented in this article. Featuring mini-slots at the MAC layer and directional antennas for NACK signal forwarding and transmission, the proposed scheme outperforms previous approaches in terms of packet loss recovery time, overhead, and throughput, as reported in the simulations.
A European Legal Approach to Grid Computing
Authors: Nikolaos Volanis, Jos Dumortier
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

This paper presents a European legal approach to grid computing. In the absence of specific legislation regulating its legal status, we attempt to classify the different layers of grid computing (grid fabric, grid middleware and grid applications) by applying the relevant legal terminology to the nature (hardwaresoftware) and function (provision of services) of each layer. We suggest that grid services should be holistically considered as information society services for the purposes of applying the relevant regulatory framework.
Frequency evaluation for exponentially fitted Runge-Kutta methods
Authors: Hans Van de Vyver
Venue: Journal of Computational and Applied Mathematics (2005)

This paper can be seen as a further investigation of the frequency evaluation techniques which are very recently proposed by Ixaru et al. for exponentially fitted multistep algorithms for first-order ordinary differential equations (ODEs). The question answered was how the frequencies should be tuned in order to have a maximal benefit from exponentially fitted methods. In a previous paper, this frequency evaluation algorithm was successfully applied in a direct way to a second-order exponentially fitted Runge-Kutta (EFRK) method of collocation type but such a direct application is impossible for higher-order EFRK methods. To overcome this difficulty we develop an efficient extension of Ixaru's frequency evaluation algorithm for the exponentially fitted RadauIIA method of third order. It is an adaption of Ixaru's algorithm in the sense that instead being applied globally, it is applied stagewise. Numerical experiments illustrate the properties of the developed algorithm.
Resolution-Based Policy Search for Imperfect Information Differential Games
Authors: Minh Nguyen-Duc, Brahim Chaib-draa
Venue: Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology (2006)

Differential games (DGs), considered as a typical model of game with continuous states and non-linear dynamics, play an important role in control and optimization. Finding optimal/approximate solutions for these game in the imperfect information setting is currently a challenge for mathematicians and computer scientists. This article presents a multi-agent learning approach to this problem. We hence propose a method called resolution-based policy search, which uses a limited non-uniform discretization of a perfect information game version to parameterize policies to learn. We then study the application of this method to an imperfect information zero-sum pursuit-evasion game (PEG). Experimental results demonstrate strong performance of our method and show that it gives better solutions than those given by traditional analytical methods.
Domain cloning for a particle-in-cell (PIC) code on a cluster of symmetric-multiprocessor (SMP) computers
Authors: R. Hatzky
Venue: Parallel Computing (2006)

In 2000, a new approach to parallelization, domain cloning, was presented by [C.C. Kim, S.E. Parker, Massively parallel three-dimensional toroidal gyrokinetic flux-tube turbulence simulation, Journal of Computational Physics 161 (2000) 589-604]. Domain cloning is an additional layer of parallelization, a supplement to one-dimensional domain decomposition which gives the opportunity to optimize the scaling properties of certain particle-in-cell codes. A further adaptation to a cluster of symmetric-multiprocessor computers is presented in this work. Hence, very good scaling properties up to 2048 processors could be achieved for a particle-in-cell code surpassing the Tflop/s performance threshold.
Evaluation Framework for Open Source Software Maintenance
Authors: Timo Koponen
Venue: Proceedings of the International Conference on Software Engineering Advances (2006)

Open Source Software is becoming evermore important and widespread these days, so its maintenance has become important issue. In this paper, we presented an evaluation framework for Open Source Software maintenance. The framework was evaluated with five well known case studies. The results showed that our framework was suitable for evaluating scale of the project and activity, efficiency, traceability and quickness of the defect management and maintenance processes. The case studies showed that quality of the defect reports was low and therefore many of them were ignored as duplicate or invalid. In addition, most of the software changes were not connected to defects, which may express lack of management.
Linkability of Two Blind Signature Schemes
Authors: Jianhong Zhang, Wei Zou
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

Blind signature allows a user to obtain signatures from an authority on any document, in such a way that the authority learns nothing about the message that is being signed. The blindness is an important property in blind signature scheme. In this work, we analyze security of two ID-based blind signature schemes [3][8], and show that the two schemes don't satisfy blindness, in other words, the signer is able to link a valid message-signature pair obtained by some user. It means that the two blind signature schemes are insecure.
Multi-Dimensional Model-based Genericity in Omega+
Authors: Jacques Lonchamp
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

Future CSCL technologies are described by the community as flexible, tailorable, and appropriate for various collaborative settings, conditions and contexts. This paper describes the key design issues of a generic synchronous collaborative learning environment. In this approach, model-based genericity is applied to the four dimensions of collaborative learning: the situation, the interaction, the process, and the effects.
Lossless data compression using adaptive filters
Authors: N. Magotra, W. McCoy, F. Livingston, S. Stearns
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

The paper describes the application of adaptive filters in a two stage lossless data compression algorithm. The term lossless implies that the original data can be recovered exactly. The first stage of the scheme consists of a lossless adaptive predictor while the second stage performs arithmetic coding. The unique aspects of the paper are: (a) defining the concept of a reversible filter as opposed to an invertible filter; (b) performing lossless data compression using primarily floating-point operations; (c) designing lossless adaptive predictors; (d) using a modified arithmetic coding algorithm that can readily handle inputs consisting of more than 14 bits.