ppxscal/embedding_network huggingface dataset:
URSA: the universal robotic service architecture
Authors: Michael Nooner, Han-Chieh Wei
Venue: Journal of Computing Sciences in Colleges (2005)

In a distributed heterogeneous robotic system, robots have different drivers, API's, sensor data format, and capabilities. Some of the information may not be available prior to the application development. This presents difficulties in the interaction between users/programs and robots. It also limits the scalability of the robotic system. In this paper, we propose the Universal Robotic Service Architecture (URSA) with the goals of simplicity, adaptability, and scalability. The architecture allows the system to interact with any type and/or different manufacture's robot systems. It also simplifies the application program by only focusing on the applications and not about the communication and data mapping implementations.
N-queens pattern generation: an insight into space complexity of a backtracking algorithm
Authors: Adrijan Bozinovski, Stevo Bozinovski
Venue: Proceedings of the 2004 international symposium on Information and communication technologies (2004)

It is proposed a method for tracking partial solutions while executing a backtracking algorithm. That enables observation of space requirements of a backtracking algorithm. To illustrate the method, the well known benchmark N-queens problem is considered. Results of the experiments are shown and discussed.
Partial diagnostic data to plasma etch modeling using neural network
Authors: Byungwhan Kim, Sebum Kim
Venue: Microelectronic Engineering (2004)

Partial diagnostic data are used to construct a neural network model for plasma control. The diagnostic data were collected using an optical emission spectroscopy (OES) during the etching of oxide films in CHF"3/CF"4 discharges. The etch process was systematically characterized by means of a statistical experimental design. The etch outputs to model include an etch rate, profile angle, and etch rate nonuniformity. The experimental data were modeled using a backpropagation neural network, while optimizing its prediction performance as a function of hidden neuron variable. Four types of models were constructed, including two partial OES models (type I and II), conventional model (type III), and principal component analysis (PCA)-OES model (type IV). The latter two models were prepared for performance comparison. The type I model was built using the partial OES data composed of important radicals. The type II model was trained with the partial OES data plus one dc bias variable. The type I model yielded better performance than the type II for the profile angle and etch rate nonuniformity. Meanwhile, the type II model considerably improved the type I model particularly in modeling the etch rate. Compared to the type III model, the type I model demonstrated improved predictions in all cases. A drastic improvement of partial OES models was obtained with respect to conventional PCA-OES models.
A rough-fuzzy document grading system for customized text information retrieval
Authors: Shailendra Singh, Lipika Dey
Venue: Information Processing and Management: an International Journal (2005)

Due to the large repository of documents available on the web, users are usually inundated by a large volume of information, most of which is found to be irrelevant. Since user perspectives vary, a client-side text filtering system that learns the user's perspective can reduce the problem of irrelevant retrieval. In this paper, we have provided the design of a customized text information filtering system which learns user preferences and modifies the initial query to fetch better documents. It uses a rough-fuzzy reasoning scheme. The rough-set based reasoning takes care of natural language nuances, like synonym handling, very elegantly. The fuzzy decider provides qualitative grading to the documents for the user's perusal. We have provided the detailed design of the various modules and some results related to the performance analysis of the system.
OBJ CUT
Authors: M. Pawan Kumar, Philip H. S. Torr, A. Zisserman
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01 (2005)

In this paper we present a principled Bayesian method for detecting and segmenting instances of a particular object category within an image, providing a coherent methodology for combining top down and bottom up cues. The work draws together two powerful formulations: pictorial structures (PS) and Markov random fields (MRFs) both of which haveefficient algorithms for their solution. The resulting combination, which we call the Object Category Specific MRF, suggests a solution to the problem that has long dogged MRFs namely that they provide a poor prior for specific shapes. In contrast, our model provides a prior that is global across the image plane using the PS. We develop an efficient method, OBJ CUT, to obtain segmentations using this model. Novel aspects of this method include an efficient algorithm for sampling the PS model, and the observation that the expected log likelihood of the model can be increased by a single graph cut. Results are presented on two object categories, cows and horses. We compare our methods to the state of the art in object category specific image segmentation and demonstrate significant improvements.
A generalization of the 0-1 principle for sorting
Authors: Sanguthevar Rajasekaran, Sandeep Sen
Venue: Information Processing Letters (2005)

The traditional zero-one principle for sorting networks states that "if a network with n input lines sorts all 2n binary sequences into nondecreasing order, then it will sort any arbitrary sequence of n numbers into nondecreasing order". We generalize this to the situation when a network sorts almost all binary sequences and relate it to the behavior of the sorting network on arbitrary inputs. We also present an application to mesh sorting.
Simulation of resource synchronization in a dynamic real-time distributed computing environment: Research Articles
Authors: Chen Zhang, David Cordes
Venue: Concurrency and Computation: Practice Experience (2004)

Today, more and more distributed computer applications are being modeled and constructed using real-time principles and concepts. In 1989, the Object Management Group (OMG) formed a Real-Time Special Interest Group (RT SIG) with the goal of extending the Common Object Request Broker Architecture (CORBA) standard to include real-time specifications. This group's most recent efforts have focused on the requirements of dynamic distributed real-time systems.One open problem in this area is resource access synchronization for tasks employing dynamic priority scheduling. This paper presents two resource synchronization protocols that the authors have developed which meet the requirements of dynamic distributed real-time systems as specified by Dynamic Scheduling Real-Time CORBA (DSRT CORBA). The proposed protocols can be applied to both Earliest Deadline First (EDF) and Least Laxity First (LLF) dynamic scheduling algorithms, allow distributed nested critical sections, and avoid unnecessary runtime overhead. In order to evaluate the performance of the proposed protocols, we analyzed each protocol's schedulability. Since the schedulability of the system is affected by numerous system configuration parameters, we have designed simulation experiments to isolate and illustrate the impact of each individual system parameter. Simulation experiments show the proposed protocols have better performance than one would realize by applying a schema that utilizes dynamic priority ceiling update. Copyright &copy; 2004 John Wiley & Sons, Ltd.
Constructions of sparse asymmetric connectors with number theoretic methods
Authors: Andreas Baltz, Gerold Jäger, Anand Srivastav
Venue: Networks (2005)

We consider the problem of connecting a set 1 of n inputs to a set O of N outputs (n &le; N) by as few edges as possible such that for every injective mapping f : I &rarr; O there are n vertex disjoint paths from i to f(i) of length k for a given k &isin; IN. For k = &Omega;(logN + log2n) Oru&ccedil; (J Parallet Distributed Comput 1994, 359366(10) gave the presently best (n,N)-connector with O(N + n &middot; logn) edges. For k = 2 and N the square of a prime, Richards and Hwang (1985) described a construction using $N\lceil\sqrt{n + 5/4} - 1/2\rceil + n\lceil\sqrt{n + 5/4} - 1/2 \rceil \sqrt{N}$ edges. We show by a probabilistic argument that an optimal (n,N)-connector has &Theta;(N) edges, if n &le; N&frac12;-&epsilon; for some &isin; &ge; 0. Moreover, we give explicit constructions based on a new number theoretic approach that need at most $N\lceil \sqrt{3n/4}\rceil + 2n\lceil \sqrt {3n/4}\rceil\lceil\sqrt{N}\rceil$ edges for arbitrary choices of n and N. The improvement we achieve is based on applying a generalization of the Erd&ouml;s-Heilbronn conjecture on the size of restricted sums. &copy; 2005 Wiley Periodicals, Inc. NETWORKS, Vol. 45(3), 119124 2005A preliminary version of this paper appeared in the proceedings of the 23rd conference on foundations of software technology and theoretical computer science (FSTTCS), Mumbai, India, December 2003, LNCS 2914, 1322.
Attack-Potential-Based Survivability Modeling for High-Consequence Systems
Authors: J. McDermott
Venue: Proceedings of the Third IEEE International Workshop on Information Assurance (2005)

Previous quantitative models of security or survivability have been defined on a range of probable intruder behavior. This measures survivability as a statistic such as mean time to breach. This kind of purely stochastic quantification is not suitable for high-consequence systems. For high-consequence systems the quantified survivability should be based on the most competent intruders the system is likely to face. We show how to accomplish this with a contingency analysis based on variations in intruder attack-potential. The quantitative results are then organized and presented according to intruder attack potential. Examples of the technique are presented using stochastic process algebra. An interesting result for diverse replication is included in the examples.
Book reivew: Advanced Database Techniques by Daniel Martin (MIT Press 1986)
Venue: Issue 102 (October 1987) (1987)

This book was originally published in French in 1985. The author attempts to treat in details some topics which are often ignored in most standard database texts [1, 2]. In his book, Daniel Martin attempts to point out the weakness of the relational data model such as the uselessness of functional dependency and normal forms in practical DBMSs, and the lack of power in modeling the semantics of application problems [pp. 44, 52]. Much attention was paid on practical aspects such as physical design, the construction and use data dictionary, and functional specification and requirement analysis. The author presents a new data model, called Dynamic Model, in which a fourth schema, the dynamic schema, is introduced to model the processing requirements of the transactions. The book is divided into seven chapters as follows:
Neural Network Based Channel Estimation and Performance Evaluation of a Time Varying Multipath Satellite Channel
Authors: Quazi M. Rahman, M. Ibnkahla, M. Bayoumi
Venue: Proceedings of the 3rd Annual Communication Networks and Services Research Conference (2005)

Neural network (NN) based channel estimation method has been proposed for identifying the parameters of a nonlinear time varying satellite channel. A multipath time-varying Ricean-fading channel has been considered in the analysis for a down link scenario. To study the flexibility and performance of the proposed method, the channel has been varied over a reasonable range of Doppler frequencies, and the estimation for each case has been made by employing 16-quadrature amplitude modulation(16-QAM) technique. Back propagation (BP) and natural gradient (NG) algorithms have been studied for the channel identification technique. Based on different learning rates and normalized Doppler frequencies, a comparative analysis between the algorithms has been provided. Finally, a NN maximum likelihood sequence estimator (NN-MLSE) based receiver has been studied for the addressed system. Simulation results show that the NN-MLSE receiver performs close to that of the ideal MLSE receiver in terms of symbol error rate (SER).
The educational value chain as a modelling tool in re-engineering efforts
Authors: Alta van der Merwe, Johannes Cronje
Venue: Proceedings of the 2004 international symposium on Information and communication technologies (2004)

Educational models are used within an institution to describe different educational components and the existing relationships between them. The important components within an educational domain are in a sense similar to business environments, including institutional structures, processes and resources. In the educational domain, the developer may use educational models to gain a better understanding of the key mechanisms of the specific problem domain or as a basis for improving the current structures and operations of the different processes within the problem domain. In this paper, we introduce the educational value chain as a graphical tool that developers may use in re-engineering efforts to identify possible bottlenecks that are likely to occur, as well as providing a route to follow when determining the value that can be added by technology.
A Built-in-Self-Test Scheme for Segmented and Binary Weighted DACs
Authors: Sunil Rafeeque K.P., Vinita Vasudevan
Venue: Journal of Electronic Testing: Theory and Applications (2004)

This paper describes a new Built-In-Self-Test(BIST) scheme for estimation of static non-linearity errors in segmented and binary weighted digital to analog converters (DACs). The BIST scheme comprises of a hierarchy of tests including tests for non-monotonicity, checks to detect if the DNL/INL errors exceed ±0.5 LSB and actual estimation of the DNL/INL. The BIST scheme has been experimentally verified on 10-bit segmented current steering DAC. The DAC, along with the additional circuits required for testing, was designed and fabricated using a 0.35 ¿m process. Both simulation and experimental results are included in this paper. Errors estimated using the BIST scheme match well with measurements done on the fabricated device.
Visibility Constrained Surface Evolution
Authors: Jan Erik Solem, Fredrik Kahl, Anders Heyden
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02 (2005)

The problem of feature-based surface reconstruction is considered in this paper. Our main contribution is the ability to handle visibility constraints, obtained from the projections of points, curves and silhouettes, in the surface fitting process. While traditional methods often ignore such information, we show that visibility constraints not only give better initial surface estimates and faster convergence, but also provide an important cue for determining surface topology. The problem is cast as a variational problem with constraints within the level set framework. It is shown how to evolve the surface without violating the visibility constraints using methods from variational calculus. Applications of the theory are detailed for a number of important cases of geometric primitives: points, curves and visual hulls. Several experiments on real image sequences are given to demonstrate the performance of the approach.
Adaptive Recompression of **-Matrices for BEM
Authors: L. Grasedyck
Venue: Computing (2005)

The efficient treatment of dense matrices arising, e.g., from the finite element discretisation of integral operators requires special compression techniques. In this article, we use a hierarchical low-rank approximation, the so-called **-matrix, that approximates the dense stiffness matrix in admissible blocks (corresponding to subdomains where the underlying kernel function is smooth) by low rank matrices. The low rank matrices are assembled by the ACA+ algorithm, an improved variant of the well-known ACA method. We present an algorithm that can determine a coarser block structure that minimises the storage requirements (enhanced compression) and speeds up the arithmetic (e.g., inversion) in the **-matrix format. This coarse approximation is done adaptively and on-the-fly to a given accuracy such that the matrix is assembled with minimal storage requirements while keeping the desired approximation quality. The benefits of this new recompression technique are demonstrated by numerical examples.
Random combinatorial structures: the convergent case
Authors: A. D. Barbour, Boris L. Granovsky
Venue: Journal of Combinatorial Theory Series A (2005)

This paper studies the distribution of the component spectrum of combinatorial structures such as uniform random forests, in which the classical generating function for the numbers of (irreducible) elements of the different sizes converges at the radius of convergence; here, this property is expressed in terms of the expectations of independent random variables Zj, j ≥ 1, whose joint distribution, conditional on the event that Σnj=1 jZj = n, gives the distribution of the component spectrum for a random structure of size n. For a large class of such structures, we show that the component spectrum is asymptotically composed of Zj components of small sizes j, j ≥ 1, with the remaining part, of size close to n, being made up of a single, giant component.
The one-round Voronoi game replayed
Authors: Sándor P. Fekete, Henk Meijer
Venue: Computational Geometry: Theory and Applications (2005)

We consider the one-round Voronoi game, where the first player ("White", called "Wilma") places a set of n points in a rectangular area of aspect ratio ρ ≤ 1, followed by the second player ("Black", called "Barney"), who places the same number of points. Each player wins the fraction of the board closest to one of his points, and the goal is to win more than half of the total area. This problem has been studied by Cheong et al. who showed that for large enough n and ρ = 1, Barney has a strategy that guarantees a fraction of 1/2 + α for some small fixed α.We resolve a number of open problems raised by that paper. In particular, we give a precise characterization of the outcome of the game for optimal play: we show that Barney has a winning strategy for n ≥ 3 and ρ > √2/n, and for n = 2 and ρ > √3/2. Wilma wins in all remaining cases, i.e., for n ≥ 3 and ρ ≤ √2/n, for n = 2 and ρ ≤ √3/2, and for n = 1. We also discuss complexity aspects of the game on more general boards, by proving that for a polygon with holes, it is NP-hard to maximize the area Barney can win against a given set of points by Wilma.
Microsoft Excel VBA Programming for the Absolute Beginner, Second Edition
Authors: Duane Birnbaum
Venue:  (2005)

Coverage includes- Duane Birnbaum began programming in graduate school, where he wrote custom software for interfacing the electronic equipment required for his experiments and analyzing the data obtained from them. Since completing his Ph.D. in physical chemistry in 1991, he has worked as a post-doctoral and research scientist in academia and industry while continuing to teach on a part-time basis. He has been teaching courses in introductory programming, database design, and data analysis in the Computer Science department at Indiana University/Purdue University at Indianapolis for the past 8 years. Geared towards beginning programmers, whether students or professionals, who have a basic understanding of the Excel application. Readers will learn how to program using VBA as it applies to Microsoft Excel as they are guided through several programming concepts common to any programming language. Each chapter contains small code snippets and programs to illustrate the chapter topic and concludes with the development of a larger program based on a simple game, making beginning programming fun and accessible. Teaches the reader how to write useful applications for data analysis in Excel for use with workbooks, worksheets, ranges, and formulas, charts, menus and toolbars, and Microsoft Access databases.
An efficient implementation of PRNGs based on the digital sawtooth map: Research Articles
Authors: Massimo Alioto, Simone Bernardi, Ada Fort, Santina Rocchi, Valerio Vignoli
Venue: International Journal of Circuit Theory and Applications (2004)

In this paper, the sawtooth map digitally implemented is analysed to evaluate its suitability for pseudo-random binary numbers generation. Period and statistical properties of the sequences generated by the digital map are evaluated versus arithmetic precision, approximation strategy and characteristic parameter of the map.In general, the digital implementation of the sawtooth map requires the use of a multiplier, which is quite expensive in terms of gate count. However, results show that values of design parameters that lead to adequate statistical features and to a relatively high period also allow for significantly reducing the complexity required in the implementation.To better evaluate performance of the digital sawtooth map as a pseudo-random number generator, it is compared to a linear feedback shift register with the same number of flip-flops, which is well known for its output sequences with a long period, appealing statistical quality, and for a reduced gate count. Performance comparison and implementation on a programmable logic device show that the digital sawtooth map is suitable for pseudo-random number generation, also requiring a relatively small amount of hardware. Copyright &copy; 2004 John Wiley & Sons, Ltd.
High-throughput distributed spacecraft network: architecture and multiple access technologies
Authors: Marcos A. Bergamo
Venue: Computer Networks and ISDN Systems (2005)

BBN Technologies (BBN), under a task for the Space Communications Project, designed the High-Throughput Distributed Spacecraft Network, or Hi-DSN. It provides a self-forming vertically integrated network infrastructure for establishing and maintaining high-throughput multi-hop communications among spacecraft operating in diverse orbits. The Hi-DSN integrates the predictability of orbital movement to establish and maintain cross-links and multihop routes, ad hoc networking capabilities to autonomously discover "new" neighbors, null-steered spatial multiplexing to maximize re-use of the allocated spectrum, and variable-rate cross-links to maximize network connectivity under large inter-spacecraft distances and distance differentials. The Hi-DSN architecture is hierarchical and can be extended to provide dynamic "terminal affiliation and handoff" for transferring data from spacecraft to aircraft and spacecraft to ground terminals and sensors. The descriptions included in this paper focus on the aspects of the architecture that are relevant for the planet vicinity networks, part of NASA's future space-based internetwork communications infrastructure, and specifically on the enabling physical-layer, medium-access control (MAC) layer and sub-network level (i.e., below IP) technologies required to create a scalable communications infrastructure that can be used to extend the (terrestrial) Internet to space. In a follow-on development for NASA, BBN is designing the architectural extensions and developing the protocols to extend Internet VPNs to space, or SpaceVPNs.
Early Evaluation of the Cray X1
Authors: T. H. Dunigan,  Jr., M. R. Fahey, J. B. White III, P. H. Worley
Venue: Proceedings of the 2003 ACM/IEEE conference on Supercomputing (2003)

Oak Ridge National Laboratory installed a 32 processor Cray X1 in March, 2003, and will have a 256 processor system installed by October, 2003. In this paper we describe our initial evaluation of the X1 architecture, focusing on microbenchmarks, kernels, and application codes that highlight the performance characteristics of the X1 architecture and indicate how to use the system most efficiently.