ppxscal/embedding_network huggingface dataset:
A model for real-time on-surface flows
Authors: Jean-Fran&#x00e7;ois El Hajjar, Vincent Jolivet, Djamchid Ghazanfarpour, Xavier Pueyo
Venue: The Visual Computer: International Journal of Computer Graphics (2009)

Simulating fluid flows for visualization purposes is known to be one of the most challenging fields of the computer graphics domain. While rendering vast liquid areas has been widely addressed this last decade, few papers have tackled the problematic of on-surface flows, even though real-time applications such as drive simulators or video games could greatly benefit from such methods. We present a novel empirical method for the animation of liquid droplets lying on a flat surface, the core of our technique being a simulation operating on a 2D grid which is implementable on GPU. The wetted surface can freely be oriented in space and is not limited to translucent materials, the liquid flow being governed by external forces, the viscosity parameter and the presence of obstacles. Furthermore, we show how to simply incorporate in our simulation scheme two enriching visual effects, namely absorption and ink transport. Rendering can be achieved from an arbitrary view point using a GPU image based raycasting approach and takes into account the refraction and reflection of light. Even though our method doesn&#x2019;t benefit from the literature of fluid mechanics, we show that convincing animations in terms of realism can be achieved in real-time.
A Linear-Time Algorithm for Hamming Distance with&#x00a0;Shifts
Authors: Minghui Jiang
Venue: Theory of Computing Systems (2009)

The Hamming distance with shifts was introduced by Bookstein et&#x00a0;al. as a generalization of the traditional Hamming distance to allow a tunable degree of fuzziness when comparing two binary sequences of the same length. We present a linear-time algorithm for computing this distance. The previous best time bound was quadratic.
Generalized Picard singular integrals
Authors: George A. Anastassiou, Ali Aral
Venue: Computers Mathematics with Applications (2009)

In this article, we introduce and study a new type of Picard singular integral operators on R^n constructed by means of the concept of the nonisotropic @b-distance and the q-exponential functions. The central role here is played by the concept of nonisotropic @b-distance, which allows one to improve and generalize the results given for classical Picard and q-Picard singular integral operators. In order to obtain the rate of convergence we introduce a new type of modulus of continuity depending on the nonisotropic @b-distance with respect to the uniform norm. Then we give the definition of @b-Lebesque points depending on nonisotropic @b-distance and a pointwise approximation result shown at these points. Furthermore, we study the global smoothness preservation property of these new type Picard singular integral operators and prove a sharp inequality.
Supervised Inductive Learning with Lotka-Volterra Derived Models
Authors: Karen Hovsepian, Peter Anselmo, Subhasish Mazumdar
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

We present a classification algorithm built on our adaptation of the Generalized Lotka-Volterra model, well-known in mathematical ecology. The training algorithm itself consists only of computing several scalars, per each training vector, using a single global user parameter and then solving a linear system of equations. Construction of the system matrix is driven by our model and based on kernel functions. The model allows an interesting point of view of kernels' role in the inductive learning process. We describe the model through axiomatic postulates. Finally, we present the results of the preliminary validation experiments.
ESA&rsquo;s activities towards a short-range laser communications terminal
Authors: Hanspeter Lutz
Venue: Space Communications (1998)

An overview is given of the intersatellite laser communication activities of the European Space Agency (ESA), focusing on the most recent systems and hardware technology efforts aimed at realizing small and compact laser terminals for worldwide mobile communication systems and satellite-based data networks.
Exploiting Cache in Multimedia
Authors: Rita Cucchiara, Andrea Prati, Massimo Piccardi
Venue: Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2 (1999)

The paper explores cache strategies for multimedia. Although many architectural improvements have been designed for multimedia, the cache structure and the standard caching policies of general-purpose processors exhibit poor performance in exploiting the 2D spatial locality typical of programs handling and processing images. In this paper we propose a novel caching approach suitably tailored to the requirement of multimedia programs. Our proposal exploits hardware pre-fetching for allocating in cache blocks of data that satisfy the 2D spatial locality requirements. Results refer to a benchmark suite of multimedia program including MPEG decoding and image processing programs with different data dependency and access scheme to image data.
Cancelling ECG artifacts in EEG using a modified independent component analysis approach
Authors: Stéphanie Devuyst, Thierry Dutoit, Patricia Stenuit, Myriam Kerkhofs, Etienne Stanus
Venue: EURASIP Journal on Advances in Signal Processing (2008)

We introduce a new automatic method to eliminate electrocardiogram (ECG) noise in an electroencephalogram (EEG) or electrooculogram (EOG). It is based on a modification of the independent component analysis (ICA) algorithm which gives promising results while using only a single-channel electroencephalogram (or electrooculogram) and the ECG. To check the effectiveness of our approach, we compared it with other methods, that is, ensemble average subtraction (EAS) and adaptive filtering (AF). Tests were carried out on simulated data obtained by addition of a filtered ECG on a visually clean original EEG and on real data made up of 10 excerpts of polysomnographic (PSG) sleep recordings containing ECG artifacts and other typical artifacts (e.g., movement, sweat, respiration, etc.). We found that our modified ICA algorithm had the most promising performance on simulated data since it presented the minimal root mean-squared error. Furthermore, using real data, we noted that this algorithm was the most robust to various waveforms of cardiac interference and to the presence of other artifacts, with a correction rate of 91.0%, against 83.5% for EAS and 83.1% for AF.
Collaborative feed reading in a community
Authors: Netta Aizenbud-Reshef, Ido Guy, Michal Jacovi
Venue: Proceedings of the ACM 2009 international conference on Supporting group work (2009)

Feed readers have emerged as one of the salient applications that characterize Web 2.0. Lately, some of the available readers introduced social features, analogously to other Web 2.0 applications, such as recommendations and tagging. Yet, most of the readers lack collaborative features, such as the ability to share feeds in a community or divide the reading task among community members. In this paper we describe CoffeeReader, a web-based feed reader, which combines social and collaborative features, and is deployed in a small community within our company. CoffeeReader provides awareness of other users' feed lists and read status; it enables information sharing such as tags and recommendations; and aims to support coordination of filtering through feeds to locate important items. We compare these group collaboration features of CoffeeReader with emerging features in publicly available feed readers; present the outcomes of using CoffeeReader within our community; and discuss our findings and their implications on making feed readers more collaborative.
Steganalytic Measures for the Steganography Using Pixel-Value Differencing and Modulus Function
Authors: Jeong-Chun Joo, Hae-Yeoun Lee, Cong Nguyen Bui, Won-Young Yoo, Heung-Kyu Lee
Venue: Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing (2008)

The steganalytic measures are proposed to destroy the steganographic method using pixel-value differencing(PVD) and modulus function. The modulus PVD steganography method utilizes the remainder of the two consecutive pixels to embed the secret data, which gains more flexibility and is capable of deriving the optimal remainder of the two pixels at the least distortion. However, there exist unavoidable weaknesses: fluctuation of the histogram, asymmetry of the 1 and -1 histogram values, and abnormal increasing of the 0 histogram value. The steganalytic measures are designed using these weaknesses of the modulus PVD steganography method. Through experiments, we prove that the proposed steganalytic measures successfully defeat the modulus PVD steganography method.
Adaptive filter length selection for acoustic echo cancellation
Authors: Christian Schüldt, Fredric Lindstrom, Haibo Li, Ingvar Claesson
Venue: Signal Processing (2009)

The number of coefficients in an adaptive finite impulse response filter-based acoustic echo cancellation setup is an important parameter, affecting the overall performance of the echo cancellation. Too few coefficients give undermodelling and too many cause slow convergence and an additional echo due to the mismatch of the extra coefficients. This paper proposes a method to adaptively determine the filter length, based on estimation of the mean square deviation. The method is primarily intended for identifying long non-sparse systems, such as a typical impulse response from an acoustic setup. Simulations with band limited flat spectrum signals are used for verification, showing the behavior and benefits of the proposed algorithm. Furthermore, off-line calculation using recorded speech signals show the behavior in real situations and comparison with another state-of-the-art variable filter length algorithm shows the advantages of the proposed method.
Identification of ARX systems with non-stationary inputs - asymptotic analysis with application to adaptive input design
Authors: László Gerencsér, Håkan Hjalmarsson, Jonas Mårtensson
Venue: Automatica (Journal of IFAC) (2009)

A key problem in optimal input design is that the solution depends on system parameters to be identified. In this contribution we provide formal results for convergence and asymptotic optimality of an adaptive input design method based on the certainty equivalence principle, i.e. for each time step an optimal input design problem is solved exactly using the present parameter estimate and one sample of this input is applied to the system. The results apply to stable ARX systems with the input restricted to be generated by white noise filtered through a finite impulse response filter, or a binary signal obtained from the latter by a static nonlinearity.
Advances in Computational Astrophysics
Authors: Alan C. Calder, Richard T. Kouzes
Venue: Computing in Science and Engineering (2009)

This special astrophysics issue presents three case studies on modeling supernovae, which are spectacular stellar explosions. A fourth paper presents a set of parallel analytical tools being developed to analyze the complex results of such simulations. Many astrophysics problems include multiple interacting physical processes and involve disparate length and time scales. Such multiphysics, multiscale applications are challenging to model and require the largest extant computers to simulate.
Spectral difference method for compressible flow on unstructured grids with mixed elements
Authors: Chunlei Liang, Antony Jameson, Z. J. Wang
Venue: Journal of Computational Physics (2009)

This paper presents the development of a 2D solver for inviscid and viscous compressible flows using the spectral difference (SD) method for unstructured grids with mixed elements. A mixed quadrilateral and triangular grid is first refined using one-level h-refinement to generate a quadrilateral grid while keeping the curvature of boundary edges. The SD method designed for quadrilateral meshes can subsequently be applied for the refined unstructured grid. Results obtained with the SD method for both inviscid and viscous compressible flows compare well with analytical solutions and other published results.
Personal Workspace for Large-Scale Data-Driven Computational Experiment
Authors: Yiming Sun, Scott Jensen, Sangmi Pallickara, Beth Plale
Venue: Proceedings of the 7th IEEE/ACM International Conference on Grid Computing (2006)

As the scale and complexity of data-driven computational science grows, so grows the burden on the scientists and students in managing the data products used and generated during experiments. Products must be moved and directories created. Search support in traditional file systems is arcane. While storage management tools can store rich metadata, these tools do not satisfy the nuances of the individual computational science researcher working alone or cooperatively. We have developed a personal workspace tool, myLEAD, that actively manages metadata and data products for users. Inspired by the Globus MCS metadata catalog and layered on top of the UK e-Science OGSA-DAI tool, myLEAD provides capture, storage and search tools to the computational scientist. In this paper we experimentally evaluate the performance of the myLEAD metadata catalog.
Physical models for electron transport in graphene nanoribbons and their junctions
Authors: Azad Naeemi, James D. Meindl
Venue: Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design (2008)

Physics-based equivalent circuit models are presented for armchair and zigzag graphene nanoribbons (GNRs), and their conductances have been benchmarked against those of carbon nanotubes and copper wires. It is demonstrated that GNRs that have large coherence length behave like waveguides for electrons. This poses both challenges and opportunities for designing graphene nanoelectronic circuits.
Self-adaptive software: Landscape and research challenges
Authors: Mazeiar Salehie, Ladan Tahvildari
Venue: ACM Transactions on Autonomous and Adaptive Systems (TAAS) (2009)

Software systems dealing with distributed applications in changing environments normally require human supervision to continue operation in all conditions. These (re-)configuring, troubleshooting, and in general maintenance tasks lead to costly and time-consuming procedures during the operating phase. These problems are primarily due to the open-loop structure often followed in software development. Therefore, there is a high demand for management complexity reduction, management automation, robustness, and achieving all of the desired quality requirements within a reasonable cost and time range during operation. Self-adaptive software is a response to these demands; it is a closed-loop system with a feedback loop aiming to adjust itself to changes during its operation. These changes may stem from the software system's self (internal causes, e.g., failure) or context (external events, e.g., increasing requests from users). Such a system is required to monitor itself and its context, detect significant changes, decide how to react, and act to execute such decisions. These processes depend on adaptation properties (called self-&ast; properties), domain characteristics (context information or models), and preferences of stakeholders. Noting these requirements, it is widely believed that new models and frameworks are needed to design self-adaptive software. This survey article presents a taxonomy, based on concerns of adaptation, that is, how, what, when and where, towards providing a unified view of this emerging area. Moreover, as adaptive systems are encountered in many disciplines, it is imperative to learn from the theories and models developed in these other areas. This survey article presents a landscape of research in self-adaptive software by highlighting relevant disciplines and some prominent research projects. This landscape helps to identify the underlying research gaps and elaborates on the corresponding challenges.
A Randomized Approach for Approximating the Number of Frequent Sets
Authors: Mario Boley, Henrik Grosskreutz
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

We investigate the problem of counting the number of frequent (item)sets---a problem known to be intractable in terms of an exact polynomial time computation. In this paper, we show that it is in general also hard to approximate. Subsequently, a randomized counting algorithm is developed using the Markov chain Monte Carlo method. While for general inputs an exponential running time is needed in order to guarantee a certain approximation bound, we empirically show that the algorithm still has the desired accuracy on real-world datasets when its running time is capped polynomially.
Solving Very Difficult Japanese Puzzles with a Hybrid Evolutionary-Logic Algorithm
Authors: Emilio G. Ortiz-García, Sancho Salcedo-Sanz, Ángel M. Pérez-Bellido, Antonio Portilla-Figueras, Xin Yao
Venue: Proceedings of the 7th International Conference on Simulated Evolution and Learning (2008)

In this paper we present a hybrid evolutionary algorithm to solve a popular logic-type puzzle, the so called Japanese puzzle. We propose to use the evolutionary algorithm in order to initialize a logic ad-hoc algorithm, which works as a local search and implicitly defines the fitness function of the problem. Two novel operators, one for initializing the evolutionary algorithm and a second one providing a novel type of mutation adapted to Japanese puzzles are described in the paper.
Information technology approach in computer science
Authors: Bijan Mashaw
Venue: Journal of Computing Sciences in Colleges (2009)

Computer Science programs are facing a decline in enrollment while the workforce demand for Information Technology professionals is growing. This paper presents a multidisciplinary approach for a computing program to accommodate the employers' hiring requirements in the 21st century. The proposed program integrates the technical and professional requirements with general education requirements and electives to prepare students for an Information Technology Career. The program also allows computing education to cross over to other fields in order to provide a wider market for the computer science.
Study on personalized recommendation based on collaborative filtering
Authors: Taowei Wang, Aimin Yang, Yibo Ren
Venue: Proceedings of the 3rd WSEAS international conference on Computer engineering and applications (2009)

Collaborative filtering is the most successful technology for building personalized recommendation system and is extensively used in many fields. In the paper, a system architecture of personalized recommendation using collaborative filtering based on web log is proposed and data preparation process is detailedly described. The paper also gives an improved k-means algorithm for clustering user transactions. Experimental results show that our proposed algorithm could increase recommendation precision.
On the approximability of the Maximum Agreement SubTree and Maximum Compatible Tree problems
Authors: Sylvain Guillemot, François Nicolas, Vincent Berry, Christophe Paul
Venue: Discrete Applied Mathematics (2009)

The aim of this paper is to give a complete picture of approximability for two tree consensus problems which are of particular interest in computational biology: Maximum Agreement SubTree (MAST) and Maximum Compatible Tree (MCT). Both problems take as input a label set and a collection of trees whose leaf sets are each bijectively labeled with the label set. Define the size of a tree as the number of its leaves. The well-known MAST problem consists of finding a maximum-sized tree that is topologically embedded in each input tree, under label-preserving embeddings. Its variant MCT is less stringent, as it allows the input trees to be arbitrarily refined. Our results are as follows. We show that MCT is NP-hard to approximate within bound n^1^-^@e on rooted trees, where n denotes the size of each input tree; the same approximation lower bound was already known for MAST [J. Jansson, Consensus algorithms for trees and strings, Ph. D. Thesis, Lund University, 2003]. Furthermore, we prove that MCT on two rooted trees is not approximable within bound 2^l^o^g^^^1^^^-^^^@e^n, unless all problems in NP are solvable in quasi-polynomial time; the same result was previously established for MAST on three rooted trees [J. Hein, T. Jiang, L. Wang, K. Zhang, On the complexity of comparing evolutionary trees, Discrete Applied Mathematics 71 (1-3) (1996) 153-169] (note that MAST on two trees is solvable in polynomial time [M.A. Steel, T.J. Warnow, Kaikoura tree theorems: Computing the maximum agreement subtree, Information Processing Letters 48 (2) (1993) 77-82]). Let CMAST, resp. CMCT, denote the complement version of MAST, resp. MCT: CMAST, resp. CMCT, consists of finding a tree that is a feasible solution of MAST, resp. MCT, and whose leaf label set excludes a smallest subset of the input labels. The approximation threshold for CMAST, resp. CMCT, on rooted trees is shown to be the same as the approximation threshold for CMAST, resp. CMCT, on unrooted trees; it was already known that both CMAST and CMCT are approximable within ratio three on rooted and unrooted trees [V. Berry, F. Nicolas, Maximum agreement and compatible supertrees, in: S.C. Sahinalp, S. Muthukrishnan, U. Dogrusoz (Eds.), Proceedings of the 15th Annual Symposium on Combinatorial Pattern Matching, CPM'04, in: LNCS, vol. 3109, Springer-Verlag, 2004, pp. 205-219; G. Ganapathy, T.J. Warnow, Approximating the complement of the maximum compatible subset of leaves of k trees, in: K. Jansen, S. Leonardi, V. V. Vazirani (Eds.), Proceedings of the 5th International Workshop on Approximation Algorithms for Combinatorial Optimization, APPROX'02, in: LNCS, vol. 2462, Springer-Verlag, 2002, pp. 122-134]. The latter results are completed by showing that CMAST is APX-hard on three rooted trees and that CMCT is APX-hard on two rooted trees.
The Higher-Order Aggregate Update Problem
Authors: Christos Dimoulas, Mitchell Wand
Venue: Proceedings of the 10th International Conference on Verification, Model Checking, and Abstract Interpretation (2008)

We present a multi-pass interprocedural analysis and transformation for the functional aggregate update problem. Our solution handles untyped programs, including unrestricted closures and nested arrays. Also, it can handle programs that contain a mix of functional and destructive updates. Correctness of all the analyses and of the transformation itself is proved.
Partial conflict-relieving programmable address shuffler for parallel memories in multi-core processor
Authors: Young-Su Kwon, Bon-Tae Koo, Nak-Woong Eum
Venue: Proceedings of the 2009 Asia and South Pacific Design Automation Conference (2009)

The advancement of process technology enables the integration of multiple cores featuring parallel processing. The requirement of extensive memory bandwidth puts a major performance bottleneck in multi-core architectures for media applications. While the parallel memory system is a viable solution to account for a large amount of memory transactions required by multiple cores, memory access conflicts caused by simultaneous accesses to an identical memory page by two or more cores limit the performance of multi-core architectures. We propose and evaluate the programmable memory address shuffler associated with the novel memory shuffling algorithm integrated in multi-core architectures with parallel memory system. The address shuffler efficiently translates the requested memory addresses into the shuffled addresses such that access conflicts diminish by analyzing the access pattern of the application. We demonstrate that the shuffling of sub-pages is represented by cyclic linked list which enables partial address shuffling with the minimal number of shuffling table entries. The programmable address shuffler reduces the amount of access conflicts by 83% for pitch-shifting audio decompression.