ppxscal/embedding_network huggingface dataset:
Generalized characteristic interface conditions for high-order multi-block computation
Authors: Takahiro Sumi, Takuji Kurotaki, Jun Hiyama
Venue: International Journal of Computational Fluid Dynamics (2007)

In practical fluid computation with structured grids around complex geometries, singular points with metric discontinuity can frequently be found. Generally, the grid singularities may cause numerical oscillations when some high-order finite difference scheme is applied. Recently, an excellent theory has been proposed which solves the above singular problem by block decomposition along the singular surface and by imposition of the characteristic interface conditions (CIC) on the block interface. However, the original theory has constraints on the mathematical treatment of the block interface, and therefore prevents numerical flexibility from a practical point of view. In this article, in order to extend the functions of the original CIC, we propose the generalized characteristic interface conditions (GCIC). Proper numerical test analysis is conducted to validate the performance of the GCIC, and as a practical application, multi-block computation is performed with the GCIC applied to complex geometry.
An algorithm for semi-infinite transportation problems
Authors: Shen-Yu Chen, Soon-Yi Wu
Venue: Journal of Computational and Applied Mathematics (2008)

In this paper we consider a class of semi-infinite transportation problems. We develop an algorithm for this class of semi-infinite transportation problems. The algorithm is a primal dual method which is a generalization of the classical algorithm for finite transportation problems. The most important aspect of our paper is that we can prove the convergence result for the algorithm. Finally, we implement some examples to illustrate our algorithm.
A rate-distortion one-class model and its applications to clustering
Authors: Koby Crammer, Partha Pratim Talukdar, Fernando Pereira
Venue: Proceedings of the 25th international conference on Machine learning (2008)

In one-class classification we seek a rule to find a coherent subset of instances similar to a few positive examples in a large pool of instances. The problem can be formulated and analyzed naturally in a rate-distortion framework, leading to an efficient algorithm that compares well with two previous one-class methods. The model can be also be extended to remove background clutter in clustering to improve cluster purity.
Towards decentralized self-adaptive component-based systems
Authors: Luciano Baresi, Sam Guinea, Giordano Tamburrelli
Venue: Proceedings of the 2008 international workshop on Software engineering for adaptive and self-managing systems (2008)

Modern software systems are challenging challenge software engineers since they must adapt effectively and efficiently with respect to the environment in which they are deployed. To this end, the paper outlines an architecture, supported by special-purpose languages and aspect oriented techniques, for the design of component-based of distributed self-adaptive systems. Software artifacts are dynamically grouped, and constantly supervised by a network of ad-hoc components. The supervision mechanism exploits special-purpose languages that define data collection, correlation, aggregation, and analysis, to reason on properties defined at different levels of pervasiveness (from component-wide to system-wide). Its goal is to identify situations that trigger adaptations. Our approach is characterized by a decentralized architecture in which there is no single point of failure or bottleneck, and a clear separation of concerns between business logic and adaptation mechanisms. These concepts are demonstrated by a fantasy example that offers a general abstraction for distributed load balancing problems.
Image shape representation using curve fitting
Authors: Pornchai Mongkolnam, Thanee Dechsakulthorn Chakarida Nukoolkit
Venue: Proceedings of the 6th WSEAS International Conference on Signal, Speech and Image Processing (2006)

We present an approach for representing digital image by using B-spline curve fittings to the segmented digital image. The image is first segmented to form isolated contours and regions. Each region's boundary (contour) is thereafter approximated by a B-spline curve. A cubic B-spline curve is used instead of a far higher degree Bezier curve to approximate the boundary because it has a local control property and is less wiggly. The obtained B-spline curves are collectively composed and used to represent the original image. One of the many practical applications lies in image retrieval, clustering and classification where general shapes, arrangement and composition of control points of those obtained B-spline curves are used to compare and find similarity between images in a collection.
Service and Utility Oriented Distributed Computing Systems: Challenges and Opportunities for Modeling and Simulation Communities
Authors: Rajkumar Buyya, Anthony Sulistio
Venue: Proceedings of the 41st Annual Simulation Symposium (anss-41 2008) (2008)

Grids and peer-to-peer (P2P) networks have emerged as popular platforms for the next generation parallel and distributed computing. In these environments, resources are geographically distributed, managed and owned by various organizations with different policies, and interconnected by wide-area networks or the Internet. This introduces a number of resource management and application scheduling challenges in the domain of security, resource and policy heterogeneity, fault tolerance, and dynamic resource conditions. In these dynamic distributed computing environments, it is hard and challenging to carry out resource management design studies in a repeatable and controlled manner as resources and users are autonomous and distributed across multiple organizations with their own policies. Therefore, simulations have emerged as the most feasible technique for analyzing policies for resource allocation. This paper presents emerging trends in distributed computing and their promises for revolutionizing the computing field, and identifies distinct characteristics and challenges in building them. We motivate opportunities for modeling and simulation communities and present our discrete-event grid simulation toolkit, called GridSim, used by researchers world-wide for investigating the design of utility-oriented computing systems such as Data Centers and Grids. We present various case studies on the use of GridSim in modeling and simulation of Business Grids, parallel applications scheduling, workflow scheduling, and service pricing and revenue management.
Search for Steady States of Piecewise-Linear Differential Equation Models of Genetic Regulatory Networks
Authors: Hidde de Jong, Michel Page
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2008)

Analysis of the attractors of a genetic regulatory network gives a good indication of the possible functional modes of the system. In this paper we are concerned with the problem of finding all steady states of genetic regulatory networks described by piecewise-linear differential equation (PLDE) models. We show that the problem is NP-hard and translate it into a propositional satisfiability (SAT) problem. This allows the use of existing, efficient SAT solvers and has enabled the development of a steady state search module of the computer tool Genetic Network Analyzer (GNA). The practical use of this module is demonstrated by means of the analysis of a number of relatively small bacterial regulatory networks as well as randomly generated networks of several hundreds of genes.
The effect of direct PAG incorporation into the polymer main chain on reactive ion etch resistance of 193nm and EUV chemically amplified resists
Authors: Cheng-Tsung Lee, Clifford L. Henderson, Mingxing Wang, Kenneth E. Gonsalves, Wang Yueh, Jeanette M. Roberts
Venue: Microelectronic Engineering (2008)

The incorporation of photoacid generator (PAG) functional groups directly into the resist resin polymer backbone has shown improved lithographic performance in achieving high resolution, high sensitivity, and low line edge roughness (LER) simultaneously in chemically amplified resists. However, the effect of direct PAG incorporation into the resist polymer on the reactive ion etch (RIE) performance in such materials was not previously studied. This paper discusses the dependence of the etch performance of such polymer-bound PAG materials on PAG structure and composition. Increased PAG loadings in both 193nm and EUV polymer-bound PAG resist platforms shows significant improvement in polymer etch resistance. Current polymer etch rate correlations and models were not able to accurately predict the trend of etch behavior within each polymer-bound PAG resist family.
Identification of Low-Level Point Radiation Sources Using a Sensor Network
Authors: Nageswara S. V. Rao, Mallikarjun Shankar, Jren-Chit Chin, David K. Y. Yau, Srinivasagopalan Srivathsan, S. Sitharama Iyengar, Yong Yang, Jennifer C. Hou
Venue: Proceedings of the 7th international conference on Information processing in sensor networks (2008)

Identification of a low-level point radiation source amidst background radiation is achieved by a network of radiation sensors using a two-step approach. Based on measurements from three sensors, the geometric difference triangulation method is used to estimate the location and strength of the source. Then a sequential probability ratio test based on current measurements and estimated parameters is employed to finally decide: (1) the presence of a source with the estimated parameters, or (2) the absence of the source, or (3) the insufficiency of measurements to make a decision. This method achieves specified levels of false alarm and missed detection probabilities, while ensuring a close-to-minimal number of measurements for reaching a decision. This method minimizes the ghost-source problem of current estimation methods, and achieves a lower false alarm rate compared with current detection methods. This method is tested and demonstrated using: (1) simulations, and (2) a test-bed that utilizes the scaling properties of point radiation sources to emulate high intensity ones that cannot be easily and safely handled in laboratory experiments.
Mobile Telephones Used as Boarding Passes: Enabling Technologies and Experimental Results
Authors: Tommy Bouchard, Mathieu Hémon, François Gagnon, Vivianne Gravel, Olivier Munger
Venue: Proceedings of the Fourth International Conference on Autonomic and Autonomous Systems (2008)

As IATA is adopting new boarding media for airplanes, cell phones are considered as the first candidate to replace traditional tickets. This will improve the efficiency of delivery, flight time update and boarding process. This evolution is made possible by displaying two-dimensional barcodes on the mobile device screen. The boarding process involves many steps and participants before one can access the plane. First, the traveler has to check-in to his flight, get his boarding pass. Then, he/she goes through the security gate, which leads to the boarding gate. Finally, the passenger accesses the plane. At every step of the process, he/she needs to show his/her paper boarding pass, which could be replaced by a more convenient media, like cell phones. Also, more than 500 different models of cell phones are available on the North American market, each having different characteristics. These characteristics must be known in order to achieve proper barcode delivery. This paper discusses the main challenge underlying the replacement of paper with barcodes over cell phones. It also proposes an experimental base to evaluate the adaptive models needed to fit the barcodes into every screen.The present work proved that it is possible to go through the entire boarding process using a mobile device as a boarding pass, if the barcode is specifically created to fit the user's cell phone screen. The information needed to create the barcode depends on the adaptive model. Simple models require more information, which takes a long time to collect. The proposed experimentation can be used to evaluate different models.
Optimal precomputation for mapping service level agreements in grid computing
Authors: Qin Liu, Xiaohua Jia, Chanle Wu
Venue: Future Generation Computer Systems (2008)

A complicated task running on the grid system is usually made up of many services, each of which typically offers a better service quality at a higher cost. Mapping service level agreements (SLAs) optimally is to find the most appropriate quality level for each service such that the overall SLA of a task is achieved at the minimum cost. This paper considers mapping the execution time SLA in the case of the discrete cost function, which is an NP-hard problem. Due to the high computation of mapping SLAs, we propose a precomputation scheme that makes the selection of each individual service level in advance for every possible SLA requirement, which can reduce the request response time greatly. We use a (1+@e)-approximation method, whose solution for any time bound is at most (1+@e) times of the optimal cost. Simulation results demonstrate the superiority of our method compared with others.
Depth control of remotely operated underwater vehicles using an adaptive fuzzy sliding mode controller
Authors: Wallace M. Bessa, Max S. Dutra, Edwin Kreuzer
Venue: Robotics and Autonomous Systems (2008)

Sliding mode control, due to its robustness against modelling imprecisions and external disturbances, has been successfully employed to the dynamic positioning of remotely operated underwater vehicles. In order to improve the performance of the complete system, the discontinuity in the control law must be smoothed out to avoid the undesirable chattering effects. The adoption of a properly designed thin boundary layer has proven effective in completely eliminating chattering, however, leading to an inferior tracking performance. This paper describes the development of a depth control system for remotely operated underwater vehicles. The adopted approach is based on the sliding mode control strategy and enhanced by an adaptive fuzzy algorithm for uncertainty/disturbance compensation. The stability and convergence properties of the closed-loop system are analytically proved using Lyapunov stability theory and Barbalat's lemma. Numerical results are presented in order to demonstrate the control system performance.
Stochastic model for cell movement in a knockout switch in computer networks
Authors: Diwakar Shukla Surendra Gadewar
Venue: Journal of High Speed Networks (2007)

In computer networks, switching is used as a juncture to provide a path to a message to pass on. The knockout switch is a specially designed architecture having equal number of input and output lines. An input cell, in this switch, passes through several stages like filters, concentrators and shifters (or queue). The cell may be under unicasting or multicasting depending upon the number of tokens of output lines allotted. This paper considers the random movement of a cell, inside the design of knockout switch, up to the output line. A Markov chain model is proposed to explain the transitions on various states of filter, concentrator and shifter. The outgoing probability is computed using the number of transitions performed by the cell. Several theorems and corollaries are derived for explaining the behavior of the cell movement. The expected number of transitions are computed keeping various situational constraints. A simulation study is performed to support the derived theorems under the model.
Antenna array synthesis with clusters of unmanned aerial vehicles
Authors: Ramu S. Chandra, Sean H. Breheny, Raffaello D'Andrea
Venue: Automatica (Journal of IFAC) (2008)

In this paper, we investigate the use of formations of Unmanned Aerial Vehicles (UAVs) as phased antenna arrays. This will help to improve communications with clusters of small unmanned aerial vehicles which are currently constrained by on-board power limitations. The problem of maximizing the power output from the array in the direction of the receiver is posed as an optimization problem which happens to be non-convex; a relaxation of this problem is then solved as a computationally tractable (convex) Second-Order Conic Program (SOCP). The performance obtained by the simplified approach is then tested against rigorous numerical bounds obtained using Semidefinite Programming (SDP) duality theory; these bounds are of independent interest in antenna theory. In order to maintain the objective value close to the optimal when the vehicles deviate from their positions (due to wind gusts, for example), a simple linear control law is proposed. Simulation results are given to show the effectiveness of the proposed approaches.
An efficient ghost fluid method for compressible multifluids in Lagrangian coordinate
Authors: Li Cai, Jian-Hu Feng, Wen-Xian Xie
Venue: Applied Numerical Mathematics (2008)

In this paper, we present an extended ghost fluid method (GFM) for computations of inviscid compressible multifluids in Lagrangian coordinate. That is, we capture the appropriate interface conditions by defining a fluid that has the velocity and the pressure of the real fluid at each point, but the entropy or the internal energy of some other fluid. Meanwhile, a single-fluid solver, CWENO-type central-upwind scheme, is developed in Lagrangian coordinate. The high resolution and the non-oscillatory quality of the scheme can be verified by solving several numerical experiments.
Discriminative structure and parameter learning for Markov logic networks
Authors: Tuyen N. Huynh, Raymond J. Mooney
Venue: Proceedings of the 25th international conference on Machine learning (2008)

Markov logic networks (MLNs) are an expressive representation for statistical relational learning that generalizes both first-order logic and graphical models. Existing methods for learning the logical structure of an MLN are not discriminative; however, many relational learning problems involve specific target predicates that must be inferred from given background information. We found that existing MLN methods perform very poorly on several such ILP benchmark problems, and we present improved discriminative methods for learning MLN clauses and weights that outperform existing MLN and traditional ILP methods.
Complexity analysis of problem-dimension using PSO
Authors: Buthainah S. Al-Kazemi, Sami J. Habib
Venue: Proceedings of the 7th WSEAS International Conference on Evolutionary Computing (2006)

This work analyzes the internal behavior of particle swarm optimization (PSO) algorithm when the complexity of the problem increased. The impact of number of dimensions for three well-known benchmark functions, DeJong, Rosenbrock and Rastrigin, were tested using PSO. A Problem-Specific Distance Function (PSDF) was defined to evaluate the fitness of individual solutions and test the diversity in neighboring individuals. The PSDF started with a large value, but converged to the optimum in few generations, irrespective of complexity of problem or objective benchmark function. The simulation illustrates that all parameters in any dimension behave in similar pattern and we can expect similar behavior for additional complexity in the problem.
Closed-Form Expression of the SAR Distribution in a Multilayered Planar Model for Shortwave Inductive Diathermy
Authors: Saverio Cristina, Mauro Parise
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02 (2008)

A new hybrid analytical-numerical method is derived that allows the fast and accurate computation of the specific absorption rate (SAR) induced inside a plane geometry fat-muscle tissue by exposure to shortwave diathermy induction coil. The electric field inside each layer of the medium is explicitly provided as combination of Hankel functions starting from the exact integral expressions for the electromagnetic (EM) field generated by a current-carrying loop located horizontally above a two-layered earth. The radial distribution of the SAR and the peak heating as a function of the frequency are computed by applying the proposed model and the zero-order model based on the quasi-static field assumption. Numerical results show that the zero-order model leads to over-estimate the SAR up to more than 20%.
Computing with Cells: Membrane Systems
Authors: Oscar H. Ibarra
Venue: Proceedings of the The International Symposium on Parallel Architectures, Algorithms, and Networks (2008)

Membrane computing, first introduced in 1998 by Gheorghe P\u aun, is a part of the general research effort of describing and investigating computing models, ideas, architectures, and paradigms from the processes taking place in nature. It is a branch of molecular computing that is motivated by cell biology. Membrane computing identifies an unconventional computing model, namely a P system, which abstracts from the way living cells process chemical compounds in their compartmental structure. Regions defined by a membrane structure contain multisets of objects that evolve according to specified rules. The objects can be represented as symbols or strings of symbols. By using the rules in a nondeterministic (deterministic) maximally parallel manner, transitions between the system configurationscan be obtained. A sequence of transitions is a computation of how the system is evolving. Various ways of controlling the transfer of objects from one region to another and applying the rules, as well as possibilities to dissolve, divide or create membranes have been studied. P systems have a great potential for implementing massively concurrent systems in an efficient way that would allow us to solve currently intractable problems once future bio-technology gives way to a practical bio-realization. Since its introduction, the literature in this area has grown rapidly (in 2003, the Institute for Scientific Information designated the intial paper as "fast breaking'' and the domain as an "emerging research front in computer science''). We give a brief overview of membrane computing and report on recent results that answer some interesting and fundamental open questions in the field. We also look at the recently introduced neural-like systems, called spiking neural P systems. These systems incorporate the ideas of spiking neurons into membrane computing. We present various classes and characterize their computing power and complexity. In particular, we analyze asynchronous and sequential systems and present some conditions under which they become (non-)universal. The non-universal variants are characterized by monotonic counter machines and partially blind countermachines. The latter devices are known to be equivalent to vector addition systems (or Petri nets) and, hence, have many decidable properties.
Random sampling in matroids, with applications to graph connectivity and minimum spanning trees
Authors: D. R. Karker
Venue: Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science (1993)

Random sampling is a powerful way to gather information about a group by considering only a small part of it. We give a paradigm for applying this technique to optimization problems, and demonstrate its effectiveness on matroids. Matroids abstractly model many optimization problems that can be solved by greedy methods, such as the minimum spanning tree (MST) problem. Our results have several applications. We give an algorithm that uses simple data structures to construct an MST in O(m+n log n) time. We give bounds on the connectivity (minimum cut) of a graph suffering random edge failures. We give fast algorithms for packing matroid bases, with particular attention to packing spanning trees in graphs.