ppxscal/embedding_network huggingface dataset:
CGMN Revisited: Robust and Efficient Solution of Stiff Linear Systems Derived from Elliptic Partial Differential Equations
Authors: Dan Gordon, Rachel Gordon
Venue: ACM Transactions on Mathematical Software (TOMS) (2008)

Given a linear system Ax &thinsp;=&thinsp; b, one can construct a related &ldquo;normal equations&rdquo; system AATy&thinsp;=&thinsp;b, x&thinsp;=&thinsp;ATy. Bj&ouml;rck and Elfving have shown that the SSOR algorithm, applied to the normal equations, can be accelerated by the conjugate gradient algorithm (CG). The resulting algorithm, called CGMN, is error-reducing and in theory it always converges even when the equation system is inconsistent and/or nonsquare. SSOR on the normal equations is equivalent to the Kaczmarz algorithm (KACZ), with a fixed relaxation parameter, run in a double (forward and backward) sweep on the original equations. CGMN was tested on nine well-known large and sparse linear systems obtained by central-difference discretization of elliptic convection-diffusion partial differential equations (PDEs). Eight of the PDEs were strongly convection-dominated, and these are known to produce very stiff systems with large off-diagonal elements. CGMN was compared with some of the foremost state-of-the art Krylov subspace methods: restarted GMRES, Bi-CGSTAB, and CGS. These methods were tested both with and without various preconditioners. CGMN converged in all the cases, while none of the preceding algorithm/preconditioner combinations achieved this level of robustness. Furthermore, on varying grid sizes, there was only a gradual increase in the number of iterations as the grid was refined. On the eight convection-dominated cases, the initial convergence rate of CGMN was better than all the other combinations of algorithms and preconditioners, and the residual decreased monotonically. The CGNR algorithm was also tested, and it was as robust as CGMN, but slower.
A proactive management algorithm for self-healing mobile ad hoc networks
Authors: Adel F. Iskander, Akmal A. Younis
Venue: International Journal of Network Management (2008)

The ability to proactively manage mobile ad hoc networks (MANETs) is critical for supporting complex services such as quality of service, security and access control in these networks. This paper focuses on the problem of managing highly dynamic and resource-constrained MANET environments through the proposal of a novel proactive management algorithm (PMA) for self-healing MANETs. PMA is based on an effective integration of autonomous, predictive and adaptive distributed management strategies. Proactive management is achieved through the distributed analysis of the current performance of the mobile nodes utilizing an optimistic discrete event simulation method, which is used to predict the mobile nodes' future status, and execution a proactive fault-tolerant management scheme. PMA takes advantage of distributed parallel processing, flexibility and intelligence of active packets to minimize the management overhead, while adapting to the highly dynamic and resource-constrained nature of MANETs. The performance of the proposed architecture is validated through analytical performance analysis and comparative simulation with the Active Virtual Network Management Protocol. The simulation results demonstrate that PMA not only significantly reduces management control overhead, but also improves both the performance and the stability of MANETs.
Scalable Video Coding of H.264/AVC Video Streaming with QoS-Based Active Dropping in 802.16e Networks
Authors: Jen-Chun Chiang, Hsiang-Fu Lo, Wei-Tsong Lee
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

Multimedia applications over mobile wireless network are becoming popular in recent years. High video quality depends on the wide bandwidth but the wide bandwidth restricts the number of users in the network system. Effective bandwidth utilization is the major problem in wireless network because the bandwidth resource in wireless environment is limited and precious. For this reason, we propose an active dropping mechanism to deal with the effective bandwidth utilization problem. In the proposed mechanism, if the network loading exceeds the threshold, the dropping mechanism starts to drop the enhancement layer data for low level user and the dropping probability is varying with the different network loading. For the multimedia application, we use the characteristic of the Scalable Video Coding (SVC) extension of H.264/AVC standard to provide different video quality for different level user. By the dropping mechanism, base station increases the system capability and users can obtain better quality of service when the system is under heavy loading. In this paper, we study the network platform of the 802.16e standard and add the QoS-based Active Dropping mechanism to the MAC layer. In the simulation results, the system capability that releases bandwidth by dropping mechanism and service quality of users are observed.
Fuzzy approach to semi-parametric sample selection model
Authors: L. Muhamad Safiih, A. A. Basah Kamil, M. T. Abu Osman
Venue: Proceedings of the 12th WSEAS International Conference on Applied Mathematics (2007)

The sample selection model studied in the context of semi-parametric methods. With the deficiency of the parametric model, such as inconsistent estimators etc, the semi-parametric estimation methods provide the best alternative to handle this deficiency. Semi-parametric of a sample selection model is an econometric model has been found interesting application in empirical studies. The issue of uncertainty and ambiguity still become are major problem and complicated in the modeling of semi-parametric sample selection model as well as its parametric. In this study, we will focus in the context of fuzzy concept as a hybrid to the semi-parametric sample selection model. The best approach of accounting for uncertainty and ambiguity is to take advantage of the tools provided by the theory of fuzzy sets. It seems particularly appropriate for modeling vague concepts. Fuzzy sets theory and its properties through the concept of fuzzy number provide an ideal framework in order to solve the problem of uncertainty data. In this paper, we introduce a fuzzy membership function for solving uncertainty data of a semi-parametric sample selection model.
On the random generation of monotone data sets
Authors: K. De Loof, B. De Baets, H. De Meyer
Venue: Information Processing Letters (2008)

Many of the state-of-the-art classification algorithms for data with linearly ordered attribute domains and a linearly ordered label set insist on the monotonicity of the induced classification rule. Training and evaluation of such algorithms requires the availability of sufficiently general monotone data sets. In this short contribution we introduce an algorithm that allows for the (almost) uniform random generation of monotone data sets based on the Markov Chain Monte Carlo method.
DGS: Driving Guidance System Based on Wireless Sensor Network
Authors: Seong-eun Yoo, Poh Kit Chong, Taisoo Park, Youngsoo Kim, Daeyoung Kim, Changsub Shin, Kyungbok Sung, Hyunhak Kim
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

In this paper, we present DGS, a Driving Guidance System based on wireless sensor networks (WSN) which guides a driver to drive a car in safety. The system consists of two sub-systems: SMS (Speed Measurement Sub-system) and WPS (Weather information Providing Sub-system). SMS measures the speed of a car and captures the image of the speeding car using a speed camera. WPS provides weather information including the road conditions (icy, wet, etc.) via VMS or a telematics terminal. The paper describes the overall system architecture of DGS from the hardware platform to the application software in the view point of a WSN. We implemented the WSN based SMS of DGS from hardware to application software. The experimental results show that the accuracy of speed measurement is over 99% at 80kmph and the predicted battery life-time using measured current profiles is about 3 years. We also discuss the lessons acquired from the real-life experiments we performed. We believe that the lessons can be useful in other WSN applications as well as in typical telematics applications.
Processor-efficient parallel solution of linear systems. II. The positive characteristic and singular cases
Authors: E. Kaltofen
Venue: Proceedings of the 33rd Annual Symposium on Foundations of Computer Science (1992)

For pt.I see Proc. 3rd Ann. ACM Symp. Parallel Algms. Architecture, p. 180-91 (1991). The authors show that over any field, the solution set to a system of n linear equations in n unknowns can be computed in parallel with randomization simultaneously in poly-logarithmic time in n and with only as many processors as are utilized to multiply two n * n matrices. A time unit represents an arithmetic operation in the field. For singular systems the parallel timings are asymptotically as fast as those for non-singular systems, due to the avoidance of binary search in the matrix rank problem, except when the field has small positive characteristic; in that case, binary search is avoided at a somewhat higher processor count measure.
Unsupervised Learning in Spectral Genome Analysis
Authors: Lutz Hamel, Neha Nahar, Maria S. Poptsova, Olga Zhaxybayeva, J. Peter Gogarten
Venue: Proceedings of the 2007 Frontiers in the Convergence of Bioscience and Information Technologies (2007)

The tree representation as a model for organismal evolution has been in use since before Darwin. However, with the recent unprecedented access to biomolecular data it has been discovered that, especially in the microbial world, individual genes making up the genome of an organism give rise to different and sometimes conflicting evolutionary tree topologies. This discovery calls into question the notion of a single evolutionary tree for an organism and gives rise to the notion of an evolutionary consensus tree based on the evolutionary patterns of the majority of genes in a genome embedded in a network of gene histories. Here we discuss an approach to the analysis of genomic data of multiple genomes using bipartition spectral analysis and unsupervised learning. An interesting observation is that genes within genomes that have evolutionary tree topologies that are in significant conflict with the evolutionary consensus tree of an organism point to possible horizontal gene transfer events which often delineate significant evolutionary events.
Confusion of memory
Authors: Lawrence S. Moss
Venue: Information Processing Letters (2008)

It is a truism that for a machine to have a useful access to memory or workspace, it must ''know'' where its input ends and its working memory begins. Most machine models separate input from memory explicitly, in one way or another. We are interested here in computational models which do not separate input from working memory. We study the situation on deterministic single-queue machines working on a two symbol alphabet. We establish a negative result about such machines: they cannot compute the length of their input. This confirms the intuition that such machines are ''unable to tell'' where on the queue the input ends and the memory begins. On the positive side, we note that there are some interesting things that one can do with such queue machines: their halting problem is undecidable, there are self-replicating machines, and there are recognizable languages outside of the control hierarchy.
WODA 2008: the sixth international workshop on dynamic analysis
Authors: Ben Liblit, Atanas Rountev
Venue: Proceedings of the 2008 international symposium on Software testing and analysis (2008)

Dynamic analysis techniques reason over program executions and deal with data produced at program execution time. At WODA 2008, we bring together researchers and practitioners working in all areas of dynamic analysis to discuss new issues, share results and ongoing work, and foster collaborations.
Monitoring heated water pollution of the DaYaWan nuclear power plant using TM images
Authors: C. Wu, Q. Wang, Z. Yang, W. Wang
Venue: International Journal of Remote Sensing (2007)

Heated water pollution is one of the problems to which environmental protection efforts pay great attention. As traditional heated water pollution monitoring methods are inefficient, remote sensing plays an increasingly more and more important role, as it can monitor large areas in real time. This study focuses on how to use remote sensing technology effectively to monitor and evaluate heated water pollution. Therm-infrared bands of some TM images at different times are used to obtain the inverse water surface temperature around the DaYaWan nuclear power plant. With this technique, information about the intensity, range of diffusion and environmental effects of the plant's heated water discharge can be obtained.
Characterizing Intra-Die Spatial Correlation Using Spectral Density Method
Authors: Qiang Fu, Wai-Shing Luk, Jun Tao, Changhao Yan, Xuan Zeng
Venue: Proceedings of the 9th international symposium on Quality Electronic Design (2008)

A spectral domain method for intra-die spatial correlation function extraction is presented. Based on theoretical analysis of random field, the spectral density, as the spectral domain counterpart of correlation function, is employed to estimate the parameters of the correlation function effectively in the spectral domain. Compared with the existing extraction algorithm in the original spatial domain, the proposed method can obtain the same quality of results in the spectral domain. In actual measurement process, the unavoidable measurement error with arbitrary frequencycomponents would greatly confound the extraction results. A filtering technique is further proposed to diminish the high frequency components of the measurement error and recover the data from noise contamination for parameter estimation. Experimental results have shown that the proposed method is practical and stable.
Reducing the parallel complexity of certain linear programming problems
Authors: P. M. Vaidya
Venue: Proceedings of the 31st Annual Symposium on Foundations of Computer Science (1990)

The parallel complexity of solving linear programming problems is studied in the context of interior point methods. If n and m, respectively, denote the number of variables and the number of constraints in the given problem, an algorithm that solves linear programming problems in O((mn)/sup 1/4/ (log 1 n)/sup 3/L) time using O(M(n)m/n+1n/sup 3/) processors is given. (M(n) is the number of operations for multiplying two n*n matrices). This gives an improvement in the parallel running time for n=o(m). A typical case in which n=o(m) is the dual of the uncapacitated transportation problem. The algorithm solves the uncapacitated transportation problem in O((VE)/sup 1/4/(log V)/sup 3/ (log V gamma )) time using O(V/sup 3/) processors, where V (E) is the number of nodes (edges) and gamma is the largest magnitude of an edge cost or a demand at a node. As a by-product, a better parallel algorithm for the assignment problem for graphs of moderate density is obtained.
Approximating predicates and expressive queries on probabilistic databases
Authors: Christoph Koch
Venue: Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems (2008)

We study complexity and approximation of queries in an expressive query language for probabilistic databases. The language studied supports the compositional use of confidence computation. It allows for a wide range of new use cases, such as the computation of conditional probabilities and of selections based on predicates that involve marginal and conditional probabilities. These features have important applications in areas such as data cleaning and the processing of sensor data. We establish techniques for efficiently computing approximate query results and for estimating the error incurred by queries. The central difficulty is due to selection predicates based on approximated values, which may lead to the unreliable selection of tuples. A database may contain certain singularities at which approximation of predicates cannot be achieved; however, the paper presents an algorithm that provides efficient approximation otherwise.
A time-space tradeoff for Boolean matrix multiplication
Authors: K. Abrahamson
Venue: Proceedings of the 31st Annual Symposium on Foundations of Computer Science (1990)

A time-space tradeoff is established in the branching program model for the problem of computing the product of two n*n matrices over a certain semiring. It is assumed that each element of each n*n input matrix is chosen independently to be 1 with probability n/sup -1/2/ and to be 0 with probability 1-n/sup -1/2/. Letting S and T denote expected space and time of a deterministic algorithm, the tradeoff is ST= Omega (n/sup 3.5/) for T0. The lower bounds are matched to within a logarithmic factor by upper bounds in the branching program model. Thus, the tradeoff possesses a sharp break at T= Theta (n/sup 2.5/). These expected case lower bounds are also the best known lower bounds for the worst case.
High Content Cellular Analysis for Functional Screening of Novel Cell Cycle Related Genes
Authors: Desok Kim, Yong-su Chae, Soo Jung Kim
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

Functional screening of novel genes can be efficiently performed by detecting morphological changes of transfected cells. In this study, we developed automated cellular analysis software and found novel genes that induced mitotic phenotypes in transiently transfected HeLa cells. Systemic imaging errors common in high content microscopy were corrected by background subtraction and intensity normalization. Nuclear and chromatin objects were detected by tophat operations. Shape, intensity, and convex-hull features were extracted. Cell types were classified by several logistic regression formulas with 93.9% accuracy in average. The increased % mitotic cells were detected in 47 out of 571 transfected genes. Twenty genes showed more than two-fold increase in % mitotic cells confirmed by manual inspection. Among these, nine genes showed increased tissue expression levels in several tumors, thus, indicating their possible oncogenic roles. These genes will be further investigated biochemically to confirm their cell cycle related functions.
Would-be teachers' competence in applying ICT: exposition and preconditions for development
Authors: Palmira Pečiuliauskiene, Marija Barkauskaite
Venue: Informatics in education (2007)

Changes in educational technologies modify the role of the teacher and require new competencies. Scientific literature describes competence in using ICT as the wholeness of two structural components - basic and educational ICT competence. The conception has been considered conducting research on would-be teachers' competence in applying ICT. The article deals with the exposition of would-be teachers' competence in applying ICT in the process of teaching practice and focuses on the impact of studying informatics in forms 11 and 12 on the development of the latter competence. Research disclosed that would-be teachers had fully mastered ordinary abilities demonstrating basic and educational competencies in ICT. The development of would-be teachers' competence has been accepted as a permanent process starting yet before the studies at university within the process of learning informatics in forms 11 and 12.
Adaptive feature-preserving non-local denoising of static and time-varying range data
Authors: Oliver Schall, Alexander Belyaev, Hans-Peter Seidel
Venue: Computer-Aided Design (2008)

We present a new method for noise removal on static and time-varying range data. Our approach predicts the restored position of a perturbed vertex using similar vertices in its neighborhood. It defines the required similarity measure in a new non-local fashion which compares regions of the surface instead of point pairs. This allows our algorithm to obtain a more accurate denoising result than previous state-of-the-art approaches and, at the same time, to better preserve fine features of the surface. Another interesting component of our method is that the neighborhood size is not constant over the surface but adapted close to the boundaries which improves the denoising performance in those regions of the dataset. Furthermore, our approach is easy to implement, effective, and flexibly applicable to different types of scanned data. We demonstrate this on several static and interesting new time-varying datasets obtained using laser and structured light scanners.
Stochastic integral equation solver for efficient variation-aware interconnect extraction
Authors: Tarek Ei-Moselhy, Luca Daniel
Venue: Proceedings of the 45th annual Design Automation Conference (2008)

In this paper we present an efficient algorithm for extracting the complete statistical distribution of the input impedance of interconnect structures in the presence of a large number of random geometrical variations. The main contribution in this paper is the development of a new algorithm, which combines both Neumann expansion and Hermite expansion, to accurately and efficiently solve stochastic linear system of equations. The second contribution is a new theorem to efficiently obtain the coefficients of the Hermite expansion while computing only low order integrals. We establish the accuracy of the proposed algorithm by solving stochastic linear systems resulting from the discretization of the stochastic volume integral equation and comparing our results to those obtained from other techniques available in the literature, such as Monte Carlo and stochastic finite element analysis. We further prove the computational efficiency of our algorithm by solving large problems that are not solvable using the current state of the art.
Notions of Probabilistic Computability on Represented Spaces
Authors: Volker Bosserhoff
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2008)

We define and compare several probabilistically weakened notions of computability for mappings from represented spaces (that are equipped with a measure or outer measure) into effective metric spaces. We thereby generalize definitions by Ko [Ko, K.-I., ''Complexity Theory of Real Functions,'' Birkhauser, Boston, 1991] and Parker [Parker, M.W., Undecidability inR^n: Riddled basins, the KAM tori, and the stability of the solar system, Philosophy of Science 70 (2003), pp. 359-382; Parker, M.W., Three concepts of decidability for general subsets of uncountable spaces, Theoretical Computer Science 351 (2006), pp. 2-13], and furthermore introduce the new notion of computability in the mean. Some results employ a notion of computable measure that originates in definitions by Weihrauch [Weihrauch, K., Computability on the probability measures on the Borel sets of the unit interval., Theoretical Computer Science 219 (1999), pp. 421-437] and Schroder [Schroder, M., Admissible representations of probability measures, Electronic Notes in Theoretical Computer Science 167 (2007), pp. 61-78]. In the spirit of the well-known Representation Theorem, we establish dependencies between the weakened computability notions and classical properties of mappings. We finally present some positive results on the computability of vector-valued integration on metric spaces, and discuss certain measurability issues arising in connection with our definitions.