bluuebunny/crossref_metadata_2025_split huggingface dataset:
POWER LAWS ARE DISGUISED BOLTZMANN LAWS
Authors: RICHMOND PETER , SOLOMON SORIN 
Published: April 2003

Using a previously introduced model on generalized Lotka–Volterra dynamics together with some recent results for the solution of generalized Langevin equations, we derive analytically the equilibrium mean field solution for the probability distribution of wealth and show that it has two characteristic regimes. For large values of wealth, it takes the form of a Pareto style power law. For small values of wealth, w ≤ wm, the distribution function tends sharply to zero. The origin of this law lies in the random multiplicative process built into the model. Whilst such results have been known since the time of Gibrat, the present framework allows for a stable power law in an arbitrary and irregular global dynamics, so long as the market is "fair", i.e., there is no net advantage to any particular group or individual. We further show that the dynamics of relative wealth is independent of the specific nature of the agent interactions and exhibits a universal character even though the total wealth may follow an arbitrary and complicated dynamics. In developing the theory, we draw parallels with conventional thermodynamics and derive for the system some new relations for the "thermodynamics" associated with the Generalized Lotka–Volterra type of stochastic dynamics. The power law that arises in the distribution function is identified with new additional logarithmic terms in the familiar Boltzmann distribution function for the system. These are a direct consequence of the multiplicative stochastic dynamics and are absent for the usual additive stochastic processes.
Algorithmic Complexity with Page-Based Intelligent Memory
Authors: Oskin Mark , Lita Lucian-Vlad , Chong Frederic T. , Hensley Justin , Keen Diana 
Published: April 2003

High DRAM densities will make intelligent memory chips a commodity in the next five years [1] [2]. This paper focuses upon a promising model of computation in intelligent memory, Active Pages [3], where computation is associated with each page of memory. Computational hardware scales linearly and inexpensively with data size in this model, reducing the order of many algorithms. This scaling can, for example, reduce linear-time algorithms to [Formula: see text]. When page-based intelligent memory chips become available in commodity, they will change the way programmers select and utilize algorithms. In this paper, we analyze the asymptotic performance of several common algorithms as problem sizes scale. We also derive the optimal page size, as a function of problem size, for each algorithm running with intelligent memory. Finally, we validate these analyses with simulation results.
THEMIS: COMPONENT DEPENDENCE METADATA IN ADAPTIVE PARALLEL APPLICATIONS
Authors: KELLY PAUL H. J. , BECKMANN OLAV , FIELD TONY , BADEN SCOTT B. 
Published: April 2003

This paper describes THEMIS, a programming model and run-time library being designed to support cross-component performance optimization through explicit manipulation of the computation's iteration space at run-time. Each component is augmented with "component dependence metadata", which characterizes the constraints on its execution order, data distribution and memory access order. We show how this supports dynamic adaptation of each component to exploit the available resources, the context in which its operands are generated, and results are used, and the evolution of the problem instance. Using a computational fluid dynamics visualization example as motivation, we show how component dependence metadata provides a framework in which a number of interesting optimizations become possible. Examples include data placement optimization, loop fusion, tiling, memoization, checkpointing and incrementalization.
(SUPER)n-ENERGY FOR ARBITRARY FIELDS AND ITS INTERCHANGE: CONSERVED QUANTITIES
Authors: SENOVILLA JOSÉ M. M. 
Published: April 2003

Inspired by classical work of Bel and Robinson, a natural purely algebraic construction of super-energy (s-e) tensors for arbitrary fields is presented, having good mathematical and physical properties. Remarkably, there appear quantities with mathematical characteristics of energy densities satisfying the dominant property, which provides s-e estimates useful for global results and helpful in other matters. For physical fields, higher order (super)n-energy tensors involving the field and its derivatives arise. In special relativity, they provide infinitely many conserved quantities. The interchange of s-e between different fields is shown. The discontinuity propagation law in Einstein–Maxwell fields is related to s-e tensors, providing quantities conserved along null hypersurfaces. Finally, conserved s-e currents are found for any minimally coupled scalar field whenever there is a Killing vector.
DENSITY DEPENDENT STRONG COUPLING CONSTANT OF QCD DERIVED FROM COMPACT STAR DATA
Authors: RAY SUBHARTHI , DEY JISHNU , DEY MIRA 
Published: April 2003

Since 1996 there is major influx of X-ray and γ-ray data from binary stars, one or both of which are compact objects that are difficult to explain as neutron stars since they contain a mass M in too small a radius R. The suggestion has been put forward that these are strange quark stars (SS) explainable in a simple model with chiral symmetry restoration (CSR) for the quarks and the M, R and other properties like QPOs (quasi-periodic oscillations) in their X-ray power spectrum. It would be nice if this astrophysical data could shed some light on fundamental properties of quarks obeying QCD. One can relate the strong coupling constant of QCD, αs to the quark mass through the Dyson–Schwinger gap equation using the real time formalism of Dolan and Jackiw. This enables us to obtain the density dependence of αs from the simple CSR referred to above. This way fundamental physics, difficult to extract from other models like for example lattice QCD, can be constrained from present-day compact star data and may be put back to modeling the dense quark phase of early universe.
HIGH QUALITY FULLY IN-SITU MgB2 THIN FILMS OBTAINED BY DC MAGNETRON SPUTTERING
Authors: MAGLIONE M. G. , CHIARELLA F. , DI CAPUA R. , VAGLIO R. , SALVATO M. , MARITATO L. , PRISCHEPA S. L. 
Published: April 2003

MgB 2 thin films were grown in-situ at INFM- University of Naples by a magnetron sputtering technique in a UHV system (10-7 Pa) equipped with 3 focused 2′′ magnetron sources (a stoichiometric MgB 2 and metallic Mg and B targets by Superconducting Components Inc.). The substrates (sapphire or MgO) were placed "on axis" at 7 cm from the target surface on the surface of a molybdenum heater that could be operated up to 1000°C under vacuum. Best results were obtained codepositing MgB 2 and Mg at equal sputtering power (500W) for 10 min on cold substrates, resulting in a Mg rich Mg-B precursor film. The films were then annealed inhyphen;situ at 830°C for 10 min in a In sealed Nb box in presence of saturated Mg vapor. The process is highly reproducible and can be easily scaled to produce large area films. The resulting films were about 1μm thick, with 100nm surface roughness as measured by AFM Resistive transition showed a maximum T c of 35 K and a transition width lower than 0.5 K. The residual resistivity ratio was 1.6 for the best sample. Resistivity measurements in external magnetic field up to 8 T have been performed both in parallel and perpendicular configuration. The upper critical magnetic field vs. temperature behavior has been determined from the experimental data and the superconducting anisotropy has been calculated for samples with different T c .
EPR OF Mn2+ AND Fe3+ IONS DOPED IN BISMUTH–BORATE GLASSES
Authors: STEFAN R. , SIMON S. 
Published: April 2003

Experimental EPR results of 99.5%[x B2O3 (1-x) Bi2O3]0.5%MO glass samples (MO = MnO, Fe2O3 and 0.07 ≤ x ≤ 0.8) systems are presented. The resonance absorptions are centered at g ≈ 4.3 and g ≈ 2.0. For manganese-doped samples both lines show hyperfine structure for certain values of Bi/B ratio. In addition to these lines a well defined shoulder at g ≈ 9.8 is recorded from the samples doped with iron. The changes in matrix composition, corresponding to different values of x, induce changes in the surroundings of the resonance centers. Structural data obtained from the EPR measurements indicate various sites for Mn2+ and Fe3+ ions in environments characterized by different crystalline field intensities. The EPR data also provides evidence that the redox effect of bismuth–borate matrices on the doped paramagnetic ions is a function of Bi/B ratio.
PRACTICAL ISSUES IN MODELING LARGE DIAGNOSTIC SYSTEMS WITH MULTIPLY SECTIONED BAYESIAN NETWORKS
Authors: XIANG Y. , OLESEN K. G. , JENSEN F. V. 
Published: April 2003

As Bayesian networks become widely accepted as a normative formalism for diagnosis based on probabilistic knowledge, they are applied to increasingly larger problem domains. These large projects demand a systematic approach to handle the complexity in knowledge engineering. The needs include modularity in representation, distribution in computation, as well as coherence in inference. Multiply Sectioned Bayesian Networks (MSBNs) provide a distributed multiagent framework to address these needs. According to the framework, a large system is partitioned into subsystems and represented as a set of related Bayesian subnets. To ensure exact inference, the partition of a large system into subsystems and the representation of subsystems must follow a set of technical constraints. How to satisfy these goals for a given system may not be obvious to a practitioner. In this paper, we address three practical modeling issues.
A NOTE ON THREE-WAY TWO-DIMENSIONAL PROBABILISTIC TURING MACHINES
Authors: OKAZAKI TOKIO , INOUE KATSUSHI , ITO AKIRA , WANG YUE 
Published: April 2003

This paper introduces a three-way two-dimensional probabilistic Turing machine (tr2-ptm), and investigates several properties of the machine. The tr2-ptm is a two-dimensional probabilistic Turing machine (2-ptm) whose input head can only move left, right, or down, but not up. Let 2-ptms (resp. tr2-ptms) denote a 2-ptm (resp. tr2-ptm) whose input tape is restricted to square ones, and let 2-PTMs(S(n)) (resp. TR2-PTMs(S(n))) denote the class of sets recognized by S(n) space-bounded 2-ptms's (resp. tr2-ptms's) with error probability less than ½, where S(n): N→N is a function of one variable n (= the side-length of input tapes). Let TR2-PTM(L(m,n)) denote the class of sets recognized by L(m,n) space-bounded tr2-ptm's with error probability less than ½, where L(m,n): N2→N is a function of two variables m (= the number of rows of input tapes) and n (= the number of columns of input tapes). The main results of this paper are: (1) 2-NFAs - TR2-PTMs(S(n))≠ϕ for any S(n)=o(log n), where 2-NFAs denotes the class of sets of square tapes accepted by two-dimensional nondeterministic finite automata, (2) TR2-PTMsS(n)[Formula: see text]2-PTMs(S(n)) for any S(n)=o(log n), and (3) for any function g(n)=o(log n) (resp. g(n)=o(log n/log log n)) and any monotonic nondecreasing function f(m) which can be constructed by some one-dimensional deterministic Turing machine, TR2-PTM(f(m)+g(n)) (resp. TR2-PTM(f(m)×g(n))) is not closed under column catenation, column closure, and projection. Additionally, we show that two-dimensional nondeterministic finite automata are equivalent to two-dimensional probabilistic finite automata with one-sided error in accepting power.
SIMULTANEOUS DETECTION OF LINES AND EDGES USING COMPOUND GABOR FILTERS
Authors: VAN DEEMTER J. H. , DU BUF J. M. H. 
Published: April 2003

Lines and edges play an important role in pattern recognition because they mark object surfaces and boundaries. In spite of many attempts to construct optimal detectors, e.g. an edge detector, it appears that all known algorithms have problems at locations where lines and edges are very close and/or intersect. Furthermore, there are still very few schemes which can detect and classify lines and edges (events) simultaneously. In view of the fact that the human visual system does not seem to suffer from any problems, our aim is to develop an event detection scheme that makes use of biologically-motivated operators and, therefore, to overcome the problems known from the literature. In this scheme we apply 2D complex Gabor filters and exploit the local phase information. In order to cope with events having a different curvature, we develop an adaptive scheme that is based on compound Gabor filter kernels with different orientation bandwidths.
PATTERNS OF PREPOSITIONAL ATTACHMENTS — WHERE DICTIONARY SEMANTICS MEETS CORPUS STATISTICS
Authors: HARABAGIU SANDA M. 
Published: April 2003

This paper presents a novel methodology of disambiguating prepositional phrase attachments. We create patterns of attachments by classifying a collection of prepositional relations derived from Treebank parses. As a by-product, the arguments of every prepositional relation are semantically disambiguated. Attachment decisions are generated as the result of a learning process, that builds upon some of the most popular current statistical and machine learning techniques. We have tested this methodology on (1) Wall Street Journal articles, (2) textual definitions of concepts from a dictionary and (3) an ad hoc corpus of Web documents, used for conceptual indexing and information extraction.
EXTRACTION OF BIBLIOGRAPHY INFORMATION BASED ON IMAGE OF BOOK COVER
Authors: YANG HUA , KASHIMURA MASAAKI , ONDA NORIKADU , OZAWA SHINJI 
Published: April 2003

This paper describes a new system for extracting and classifying bibliography regions from the color image of a book cover. The system consists of three major components: preprocessing, color space segmentation and text region extraction and classification. Preprocessing extracts the edge lines of the book and geometrically corrects and segments the input image, into the parts of front cover, spine and back cover. The same as all color image processing researches, the segmentation of color space is an essential and important step here. Instead of RGB color space, HSI color space is used in this system. The color space is segmented into achromatic and chromatic regions first; and both the achromatic and chromatic regions are segmented further to complete the color space segmentation. Then text region extraction and classification follow. After detecting fundamental features (stroke width and local label width) text regions are determined. By comparing the text regions on front cover with those on spine, all extracted text regions are classified into suitable bibliography categories: author, title, publisher and other information, without applying OCR.
IMAGE RECOGNITION USING SIMPLIFIED FUZZY ARTMAP AUGMENTED WITH A MOMENT BASED FEATURE EXTRACTOR
Authors: RAJASEKARAN S. , PAI G. A. VIJAYALAKSHMI 
Published: April 2003

The capability of Kasuba's Simplified Fuzzy ARTMAP (SFAM) to behave as a Pattern Recognizer/Classifier of images both noisy and noise free has been investigated in this paper. This calls for augmenting the original Neuro–Fuzzy model with a modified moment-based RST invariant feature extractor. The potential of the SFAM based Pattern Recognizer to recognize patterns — monochrome and color, noisy and noise free — has been studied on two experimental problems. The first experiment which concerns monochrome images, pertains to recognition of satellite images, a problem discussed by Wang et al. The second experiment, which concerns color images, deals with the recognition of some sample test colored patterns. The results of the computer simulation have also been presented.
FORGERY DETECTION BY LOCAL CORRESPONDENCE
Authors: GUO JINHONG KATHERINE , DOERMANN DAVID , ROSENFELD AZRIEL 
Published: April 2003

Signatures may be stylish or unconventional and have many personal characteristics that are challenging to reproduce by anyone other than the original author. For this reason, signatures are used and accepted as proof of authorship or consent on personal checks, credit purchases and legal documents. Currently signatures are verified only informally in many environments, but the rapid development of computer technology has stimulated great interest in research on automated signature verification and forgery detection. In this paper, we focus on forgery detection of offline signatures. Although a great deal of work has been done on offline signature verification over the past two decades, the field is not as mature as online verification. Temporal information used in online verification is not available offline and the subtle details necessary for offline verification are embedded at the stroke level and are hard to recover robustly. We approach the offline problem by establishing a local correspondence between a model and a questioned signature. The questioned signature is segmented into consecutive stroke segments that are matched to the stroke segments of the model. The cost of the match is determined by comparing a set of geometric properties of the corresponding substrokes and computing a weighted sum of the property value differences. The least invariant features of the least invariant substrokes are given the biggest weights, thus emphasizing features that are highly writer-dependent. Random forgeries are detected when a good correspondence cannot be found, i.e. the process of making the correspondence yields a high cost. Many simple forgeries can also be identified in this way. The threshold for making these decisions is determined by a Gaussian statistical model. Using the local correspondence between the model and a questioned signature, we perform skilled forgery detection by examining the writer-dependent information embedded at the substroke level and try to capture unballistic motion and tremor information in each stroke segment, rather than as global statistics. Experiments on random, simple and skilled forgery detection are presented.
PEAKONS AND THEIR BIFURCATION IN A GENERALIZED CAMASSA–HOLM EQUATION
Authors: LIU ZHENGRONG , QIAN TIFEI 
Published: April 2003

Camassa and Holm [1993] recently derived a new dispersive shallow water equation known as the Camassa–Holm equation. They showed that it also has solitary wave solutions which have a discontinuous first derivative at the wave peak and thus are called "peakons". In this paper, from the mathematical point of view, we study the peakons and their bifurcation of the following generalized Camassa–Holm equation [Formula: see text] with a>0, k∈ℝ, m∈ℕ and the integral constants taken as zero. Using the bifurcation method of the phase plane, we first give the phase portrait bifurcation, then give the integral expressions of peakons through the bifurcation curves and the phase portraits, and finally obtain the peakon bifurcation parameter value and the number of peakons. For m=1, 2, 3, we give the explicit expressions for the peakons. It seems that the bifurcation method of phase planes is good for the study of peakons in nonlinear integrable equations.
CASE-BASED SOFTWARE QUALITY PREDICTION
Authors: GANESAN K. , KHOSHGOFTAAR TAGHI M. , ALLEN EDWARD B. 
Published: April 2003

Highly reliable software is becoming an essential ingredient in many systems. However, assuring reliability often entails time-consuming costly development processes. One cost-effective strategy is to target reliability-enhancement activities to those modules that are likely to have the most problems. Software quality prediction models can predict the number of faults expected in each module early enough for reliability enhancement to be effective. This paper introduces a case-based reasoning technique for the prediction of software quality factors. Case-based reasoning is a technique that seeks to answer new problems by identifying similar "cases" from the past. A case-based reasoning system can function as a software quality prediction model. To our knowledge, this study is the first to use case-based reasoning systems for predicting quantitative measures of software quality. A case study applied case-based reasoning to software quality modeling of a family of full-scale industrial software systems. The case-based reasoning system's accuracy was much better than a corresponding multiple linear regression model in predicting the number of design faults. When predicting faults in code, its accuracy was significantly better than a corresponding multiple linear regression model for two of three test data sets and statistically equivalent for the third.
KNOWLEDGE ACQUISITION AND PROCESS GUIDANCE FOR BUILDING SYSTEM DYNAMICS SIMULATION MODELS: AN EXPERIENCE REPORT FROM SOFTWARE INDUSTRY
Authors: PFAHL DIETMAR , LEBSANFT KARL 
Published: April 2003

System Dynamics (SD) is a method that allows for integrated modelling of technical as well as managerial aspects responsible for the dynamic complexity of systems. Therefore, simulation of SD models can also be a tool for problem analysis within software organisations. In this paper, experience with SD modelling of software processes and projects within Siemens is reported. Special focus is put on problems encountered during knowledge acquisition for SD model building, like inadequate guidance while conducting SD modelling projects, and insufficient methodical support for re-using available or generating missing knowledge. Both problems were addressed in a research project, jointly conducted by Fraunhofer IESE and Siemens Corporate Technology. One of the results of this project is a prescriptive process model for building SD models. This process model, which is briefly outlined in the paper, provides guidance for a systematic development of SD models in software organisations.
UML AS DOMAIN SPECIFIC LANGUAGE FOR THE CONSTRUCTION OF KNOWLEDGE-BASED CONFIGURATION SYSTEMS
Authors: FELFERNIG ALEXANDER , FRIEDRICH GERHARD E. , JANNACH DIETMAR 
Published: April 2003

In many domains, software development has to meet the challenges of developing highly adaptable software very rapidly. In order to accomplish this task, domain specific, formal description languages and knowledge-based systems are employed. From the viewpoint of the industrial software development process, it is important to integrate the construction and maintenance of these systems into standard software engineering processes. In addition, the descriptions should be comprehensible for the domain experts in order to facilitate the review process. For the realization of product configuration systems, we show how these requirements can be met by using a standard design language (UML-Unified Modeling Language) as notation in order to simplify the construction of a logic-based description of the domain knowledge. We show how classical description concepts for expressing configuration knowledge can be introduced into UML and be translated into logical sentences automatically. These sentences are exploited by a general inference engine solving the configuration task.
PRODUCTION AND MAINTENANCE OF GOAL-ORIENTED SOFTWARE MEASUREMENT MODELS
Authors: CANTONE GIOVANNI , DONZELLI PAOLO 
Published: April 2003

Production and maintenance of measurement models are crucial in the context of an advanced software development organization. The paper suggests a goal-oriented measurement model life cycle that, starting out from the high-level organizational goals, drives software organizations towards a structured process to deal with measurement models. The life cycle results into an integrated component of the management activities pointed to generate, refine, and fulfill the organizational goals, whereas the final measurement models become items of a purpose fitting measurement plan. For each phase of the life cycle, the main activities, with their inputs and outputs, are identified and, moreover, some driving templates are defined. The paper analyzes their interactions with the other software production and management-related tasks and proposes a possible allocation within an Experience Factory-based software organization.