ppxscal/embedding_network huggingface dataset:
A stochastic model for solitons
Authors: Yoshiaki Itoh, Hosam M. Mahmoud, Daisuke Takahashi
Venue: Random Structures Algorithms (2004)

The soliton physics for the propagation of waves is represented by a stochastic model in which the particles of the wave can jump ahead according to some probability distribution. We demonstrate the presence of a steady state (stationary distribution) for the wavelength. It is shown that the stationary distribution is a convolution of geometric random variables. Approximations to the stationary distribution are investigated for a large number of particles. The model is rich and includes Gaussian cases as limit distribution for the wavelength (when suitably normalized). A sufficient Lindeberg-like condition identifies a class of solitons with normal behavior. Our general model includes, among many other reasonable alternatives, an exponential aging soliton, of which the uniform soliton is one special subcase (with Gumbel's stationary distribution). With the proper interpretation, our model also includes the deterministic model proposed in Takahashi and Satsuma [A soliton cellular automaton, J Phys Soc Japan 59 (1990), 3514-3519].
Cryptanalysis of a pay-as-you-watch system
Authors: Marc Joye
Venue: Information Processing Letters (2003)

In this paper, we exhibit security flaws in the MICROCAST pay-as-you-watch system. From the sole knowledge of public parameters, we show how any intruder is able to forge a coin and so to freely get access to the service.
String Quartets in Binary
Authors: Noga Alon, János Körner, Angelo Monti
Venue: Combinatorics, Probability and Computing (2000)

Let M(n, A) denote the maximum possible cardinality of a family of binary strings of length n, such that for every four distinct members of the family there is a coordinate in which exactly two of them have a 1. We prove that M(n, A) &le; 20.78n for all sufficiently large n. Let M(n, C) denote the maximum possible cardinality of a family of binary strings of length n, such that for every four distinct members of the family there is a coordinate in which exactly one of them has a 1. We show that there is an absolute constant c < 1&#x002F;2 such that M(n, C) &le; 2cn for all sufficiently large n. Some related questions are discussed as well.
VLSI Architecture of Centroid Tracking Algorithms for Video Tracker
Authors: Manvendra Singh, B. S. Chauhan, N. K. Sharma
Venue: Proceedings of the 17th International Conference on VLSI Design (2004)

Selection of tracking algorithm is a critical aspectrelated to performance of video tracker. With theadvancement in reconfigurable technology such asFPGAs, it is possible to analyse algorithms on hardwareplatform for real time implementation. A centroid basedtracker has been developed using standard CCIR-B videofrom either CCD or IR camera. In the present workscheme for implementation of centroid tracker and VLSIarchitecture for various types of centroid based trackingalgorithms has been analyzed. Xilinx FPGA has beenused as a target device for performance evaluation ofvarious centroid tracking algorithms and comparison ofresource & timing requirements associated with thesealgorithms have been done.
Machine learning and data mining via mathematical programming-based support vector machines
Authors: Glenn Martin Fung
Venue:  (2003)

Several issues that arise in machine learning and data mining are addressed using mathematical programming based support vector machines (SVMs). We address the following important problems. Instead of a standard SVM that classifies points by assigning them to one of two disjoint halfspaces, points are classified by assigning them to the closest of two parallel planes (in input or feature space) that are pushed apart as far as possible. This formulation leads to an extremely fast and simple algorithm for generating a linear or nonlinear classifier that merely requires the solution of a single system of nonsingular linear equations. Multiclass and incremental extensions of this proximal formulation are also presented. Prior knowledge, in the form of multiple polyhedral sets each belonging to one of two categories, is introduced into a reformulation of a linear SVM classifier. The resulting formulation is solved efficiently by a linear program and results in enhanced testing set correctness. A finite concave minimization algorithm is proposed for constructing classifiers that use a minimal number of data points both in generating and characterizing classifiers. The algorithm is theoretically justified by linear programming perturbation theory and a leave-one-out error bound, as well as by effective computational results on several real world datasets. Another very fast Newton based stand-alone algorithm to solve this problem is also presented. The problem of incorporating unlabeled data into a support vector machine is formulated as a concave minimization problem on a polyhedral set for which a stationary point is quickly obtained by solving a few (5 to 7) linear programs. We also propose an implicit Lagrangian formulation of a support vector machine classifier that results in a highly effective iterative scheme and that is solved here by a finite Newton method. The proposed method, which is extremely fast and terminates in 6 or 7 iterations, can handle classification problems in very high dimensional spaces, e.g. over 28,000, in a few seconds on a 400 MHz Pentium II machine. The method can also handle problems with large datasets and requires no specialized software other than a commonly available solver for a system of linear equations. Finite termination of the proposed method is established. To sum up, we present several mathematical programming based algorithms that address various important SVM related issues such as: speed, scalability, data dependence and sparse representation, use of unlabeled data and knowledge incorporation.
Dynamic Load Balancing in PC Clusters: An Application to a Multi-Physics Model
Authors: Ricardo Vargas Dorneles, Rogério Luis Rizzi, Tiaraju A. Diverio, Philippe O. A. Navaux
Venue: Proceedings of the 15th Symposium on Computer Architecture and High Performance Computing (2003)

This work describes the use of dynamic load balancing in a PC cluster, applied to a multi-physics model that combines the parallel solution for three-dimensional (3D) PDEs of shallow water bodies flow and the parallel solution for the three-dimensional PDEs of scalartransportation of substances. The dynamic load balancing is obtained via diffusion algorithms. The numerical mesh is partitioned using RCB algorithm, in order to minimize communication and balance the load. Parallelism is obtained through Schwarz's additive Domain Decomposition Method (DDM), so that the sub-problems are solved concurrently. SPMD is the programming model used and the message passing between processes in the PC cluster is done with MPICH library.
A Nonoverlapping Domain Decomposition Method for Maxwell's Equations in Three Dimensions
Authors: Qiya Hu, Jun Zou
Venue: SIAM Journal on Numerical Analysis (2003)

In this paper, we propose a nonoverlapping domain decomposition method for solving the three-dimensional Maxwell equations, based on the edge element discretization. For the Schur complement system on the interface, we construct an efficient preconditioner by introducing two special coarse subspaces defined on the nonoverlapping subdomains. It is shown that the condition number of the preconditioned system grows only polylogarithmically with the ratio between the subdomain diameter and the finite element mesh size but possibly depends on the jumps of the coefficients.
Creating dome animations with the Digital Pueblo Project
Authors: Ed Angel, Hue Walker Baumgarner-Kirby, David Beining
Venue: ACM SIGGRAPH 2003 Sketches Applications (2003)

The Digital Pueblo Project at the University of New Mexico is building the infrastructure for a digital arts and animation industry in a largely rural state with many diverse cultural groups. Key to this effort is project-based training of an "eight to eighty" workforce drawn from the community. This presentation shows a successful effort to create fulldome animations for the LodeStar Astronomy Center using a collection of local artists, students, and computer scientists.
Efficient Multidimensional Quantitative Hypotheses Generation
Authors: Amihood Amir, Reuven Kashi, Nathan S. Netanyahu
Venue: Proceedings of the Third IEEE International Conference on Data Mining (2003)

Finding local interrelations (hypotheses) among attributeswithin very large databases of high dimensionalityis an acute problem for many databases and data miningapplications. These include, dependency modeling, clusteringlarge databases, correlation and link analysis.Traditional statistical methods are concerned with the corroborationof (a set of) hypotheses on a given body ofdata. Testing all of the hypotheses that can be generatedfrom a database with millions of records and dozens offields is clearly infeasible. Generating, on the other hand,a set of the most "promising" hypotheses (to be corroborated)requires much intuition and ingenuity.In this paper we present an efficient method for rankingthe multidimensional hypotheses using image processingof data visualization. In the heart of the method lies theuse of visualization techniques and image processing ideasto rank subsets of attributes according to the relation betweenthem in the databases. Some of the scalability issuesare solved by concise generalized histograms and by usingan efficient on-line computation of clustering around amedian with only five additional memory words. In additionto presenting our algorithmic methodology, we demonstrateits efficiency and performance by applying it to realcensus data sets, as well as synthetic data sets.
A Definition for Information System Survivability
Authors: Vickie R. Westmark
Venue: Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 9 - Volume 9 (2004)

Society has become dependent on information systems. As networks develop into large-scale systems, often critical to personal and business operations, survivability of these systems is imperative. While these systems continue to emerge and grow, answers to questions like: "What does survivability mean?", "How is survivability being measured?", and "How is survivability computed?" become very important.This paper summarizes the standard or lack of standard methods for defining and computing survivability while providing an easy to reference baseline of the current state. It also provides a template for defining survivability to facilitate subsequent research into computational quality attributes by using standard definitions. Where there are gaps or inconsistencies in current research and practice, assessments can be made to continue research and development in the areas most needed to develop taxonomy of survivability.
Efficient Kernel Density Estimation Using the Fast Gauss Transform with Applications to Color Modeling and Tracking
Authors: Ahmed Elgammal, Ramani Duraiswami, Larry S. Davis
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2003)

Many vision algorithms depend on the estimation of a probability density function from observations. Kernel density estimation techniques are quite general and powerful methods for this problem, but have a significant disadvantage in that they are computationally intensive. In this paper, we explore the use of kernel density estimation with the fast Gauss transform (FGT) for problems in vision. The FGT allows the summation of a mixture of M Gaussians at N evaluation points in O(M+N) time, as opposed to O(MN) time for a naive evaluation and can be used to considerably speed up kernel density estimation. We present applications of the technique to problems from image segmentation and tracking and show that the algorithm allows application of advanced statistical techniques to solve practical vision problems in real-time with today's computers.
Mining the Web to Discover the Meanings of an Ambiguous Word
Authors: Raz Tamir, Reinhard Rapp
Venue: Proceedings of the Third IEEE International Conference on Data Mining (2003)

In information retrieval and text mining, informationon word senses is usually taken from dictionaries or lexicaldatabases that have been prepared by lexicographers.In this paper we propose an automatic method for wordsense induction, i.e. for the discovery of a set of sensedescriptors to a given ambiguous word. The approach isbased on the statistics of word co-occurrence as derivedfrom web pages. The underlying assumption is that thesenses of an ambiguous word are best described by termsthat, although bearing a strong association to this word,are mutually exclusive, i.e. whose association strengthwithin the retrieved web pages is as weak as possible.Measuring association strength is based upon a novelConfidence Gain approach that relates the observed co-occurrencefrequency for two sense descriptor candidatesto an average co-occurrence frequency for pairs of arbitrarywords. The proposed approach is fully unsupervisedand takes into account the contemporary meanings ofwords, as reflected in texts from the internet. Our resultsare evaluated using a list of ambiguous words commonlyreferred to in the literature.
Routing permutations in partitioned optical passive stars networks
Authors: Alessandro Mei, Romeo Rizzi
Venue: Journal of Parallel and Distributed Computing (2003)

It is shown that a Partitioned Optical Passive Stars (POPS) network with g groups and d processors per group can route any permutation among the n = dg processors in one slot when d = 1 and 2 ⌈d/g⌉ slots when d > 1. The number of slots used is optimal in the worst case, and is at most the double of the optimum for all permutations π such that π(i) ≠ i, for all i.
OF-FMEA: an approach to safety analysis of object-oriented software intensive systems
Authors: Tadeusz Cichocki, Janusz Górski
Venue: Artificial intelligence and security in computing systems (2003)

The paper presents an extension to the common FMEA method in such a way that it can be applied to safety analysis of systems (hardware and software) that are developed using a recently popular object oriented approach. The method makes use of the object and collaboration models of UML. It assumes that the system components are specified formally using the CSP notation. The method supports systematic way of failure mode identification and validation. Selected failure modes are injected to the specification of "normal' behaviour and their consequences are analysed with the help of an automatic tool. The verification process provides hints for possible redesign of components. Experiences of using the method for a railway signalling case study are also reported.
Delay Analysis of IEEE 802.11 in Single-Hop Networks
Authors: Marcelo M. Carvalho, J. J. Garcia-Luna-Aceves
Venue: Proceedings of the 11th IEEE International Conference on Network Protocols (2003)

This paper presents an analytical model to compute the average service time and jitter experienced by a packet when transmitted in a saturated IEEE 802.11 ad hoc network. In contrast to traditional work in the literature, in which a distribution is usually fitted or assumed, we use a bottom-up approach and build the first two moments of the service time based on the IEEE 802.11 binary exponential backoff algorithm and the events underneath its operation. Our model is general enough to be applied to any type of IEEE 802.11 wireless ad hoc network where the channel state probabilities driving a node's backoff operation are known. We apply our model to saturated single-hop ad hoc networks under ideal channel conditions. We validate our model through extensive simulations and conduct a performanceevaluation of a node's average service time and jitter for both direct sequence and frequency-hopping spread spectrum physical layers.
A Multiobjective Model for QoS Multicast Routing Based on Genetic Algorithm
Authors: Xunxue Cui, Chuang Lin, Yaya Wei
Venue: Proceedings of the 2003 International Conference on Computer Networks and Mobile Computing (2003)

Usually multiple quality of service (QoS) guarantees are required in most of multicast applications. In this paper, it is formulated as a multiobjective constrained combinatorial optimization problem for a protocol to determine multicast routes satisfying different QoS requirements. We use a multiobjective model and routing approach based on genetic algorithm that optimizes multiple QoS parameters simultaneously. The corresponding results demonstrate that the proposed approach is capable of discovering a set of nondominated routes within a finite evolutionary generation. Its feasibility and performance has been verified.
Use of amorphous carbon as a gate insulator for GaAs and related compounds
Authors: S. Paul, F. J. Clough
Venue: Microelectronic Engineering (2003)

Deposition of gate insulator in the arsenic-based compound semiconductors (such as GaAs, AlGaAs), always causes stoichiometric changes in these materials. The deposition of any materials above 350 °C results in the segregation of As at the surface of the semiconductor, which deteriorates the metal-insulator field effect transistor properties. a-C:H can be deposited at room temperature and hence the effect of temperature on arsenic segregation can be eliminated. This work investigates the use of a-C:H as a gate insulator in arsenic-based compound semiconductors.
Query optimization using fuzzy set theory for multidatabase systems
Authors: Qiang Zhu, P. Å. Larson
Venue: Proceedings of the 1993 conference of the Centre for Advanced Studies on Collaborative research: distributed computing - Volume 2 (1993)

One of the challenges for global query optimization in a multidatabase system (MDBS) is that some local optimization information may not be accurately known at the global level because of local autonomy. In this paper, we introduce a fuzzy query optimization approach that is based on fuzzy set theory, introduced by Zadeh in the 1960s, to tackle the challenge. We describe the problem of fuzzy query optimization and compare the fuzzy optimization approach with the traditional (crisp) optimization approach. We show that the fuzzy approach has a better chance to find a good execution strategy for a query than the crisp approach in an MDBS environment, but the complexity of the former may grow exponentially as the complexity of the later. To reduce the complexity, we use a weighted k-approximate fuzzy value to approximate every fuzzy value during fuzzy query optimization. It is proven that the improved fuzzy approach has the same order of complexity as the crisp approach.
Closest point query among the union of convex polytopes using rasterization hardware
Authors: Young J. Kim, Kenneth Hoff, Ming C. Lin, Dinesh Manocha
Venue: Journal of Graphics Tools (2002)

We present a novel approach using rasterization hardware to perform the following query: Given a collection of convex polytopes in 3D, find the closest point from some given point inside the polytopes to the surface of the union of the polytopes. The algorithm takes advantage of multipass rendering, clipping, and depth tests. We also demonstrate its application to penetration depth computation.
Properly colored subgraphs and rainbow subgraphs in edge-colorings with local constraints
Authors: Noga Alon, Tao Jiang, Zevi Miller, Dan Pritikin
Venue: Random Structures Algorithms (2003)

We consider a canonical Ramsey type problem. An edge-coloring of a graph is called m-good if each color appears at most m times at each vertex. Fixing a graph G and a positive integer m, let f(m, G) denote the smallest n such that every m-good edge-coloring of Kn, yields a properly edge-colored copy of G, and let g(m, G) denote the smallest n such that every m-good edge-coloring of Kn yields a rainbow copy of G. We give bounds on f(m, G) and g(m, G). For complete graphs G = Kt, we have c1mt2/ln t ≤ f(m, Kt) ≤ c2mt2, and c'1mt3/ln t ≤ g(m, Kt) ≤ c'2mt3/ln t, where c1, c2, c'1, c'2 are absolute constants. We also give bounds on f(m, G) and g(m, G) for general graphs G in terms of degrees in G. In particular, we show that for fixed m and d, and all sufficiently large n compared to m and d, f(m, G) = n for all graphs G with n vertices and maximum degree at most d.
Integration of COTS software products ARENA & CPLEX for an inventory/logistics problem
Authors: Mayur Vamanan, Qian Wang, Rajan Batta, Robert J. Szczerba
Venue: Computers and Operations Research (2004)

This paper describes the integration of two commercially available, highly specialized, off-the-shelf software packages--CPLEX and ARENA. We present the need for such integration and the ways in which it differs from the more traditional methods of problem solving. The two products are described in detail followed by an example that requires this integration. A detailed account of the integration is also presented together with drawbacks of this approach.
Bayesian marginal inference via candidate's formula
Authors: Chuhsing Kate Hsiao, Su-Yun Huang, Ching-Wei Chang
Venue: Statistics and Computing (2004)

Computing marginal probabilities is an important and fundamental issue in Bayesian inference. We present a simple method which arises from a likelihood identity for computation. The likelihood identity, called Candidate's formula, sets the marginal probability as a ratio of the prior likelihood to the posterior density. Based on Markov chain Monte Carlo output simulated from the posterior distribution, a nonparametric kernel estimate is used to estimate the posterior density contained in that ratio. This derived nonparametric Candidate's estimate requires only one evaluation of the posterior density estimate at a point. The optimal point for such evaluation can be chosen to minimize the expected mean square relative error. The results show that the best point is not necessarily the posterior mode, but rather a point compromising between high density and low Hessian. For high dimensional problems, we introduce a variance reduction approach to ease the tension caused by data sparseness. A simulation study is presented.
A queueing control model for retail services having back room operations and cross-trained workers
Authors: Oded Berman, Richard C. Larson
Venue: Computers and Operations Research (2004)

Many retail service facilities have both front room and back room operations. The front room deals with serving customers, perhaps from a queue. The back room focuses typically on restocking of shelves and sorting and/or processing of paperwork. We model such a facility having workers who are cross-trained to do both jobs. We assume that back room work is interruptible. A manager can bring a worker from the back room to the front room when the customer checkout queue becomes "too long". A reverse assignment occurs when the number of customers is sufficiently small.We assume that the retail facility contains two customer-counting technologies. The first counts the number of shoppers in the store who are not already in checkout queues and the second counts the number of customers at checkout. The goal is to find the minimum number of workers to staff the facility subject to two performance constraints. The mean queue delay in the front room must be less than a pre-specified value, and the time-average number of workers in the back room must be greater than a pre-specified value. Once the minimum complement of workers is found, a secondary goal is to minimize mean queueing delay subject to retaining back room feasibility. The system is a continuous time Markov process having a three-dimensional state space. The (heuristic) optimization process includes state-dependent rules for switching workers between rooms.