bluuebunny/crossref_metadata_2025_split huggingface dataset:
QUANTIFICATION OF SYNCHRONIZATION PROCESSES BY COHERENCE AND PHASE AND ITS APPLICATION IN ANALYSIS OF ELECTROPHYSIOLOGICAL SIGNALS
Authors: SCHACK BÄRBEL , RAPPELSBERGER PETER , ANDERS CHRISTOPH , WEISS SABINE , MÖLLER EVA 
Published: May 2003

Neuronal activity during information processing and muscle activity are generally characterized by oscillations. Mostly, widespread areas are involved and electrophysiological signals are measured on different sites of the cortex or of the muscle. In order to investigate functional relationships between different components of multidimensional electrophysiological signals, coherence and phase analyses turned out to be useful tools. These parameters allow the investigation of synchronization phenomena with regard to oscillations of defined frequencies or frequency bands. Coherence and phase are closely connected spectral parameters. Coherence may be understood as a measure of phase stability. Whereas coherence describes the amount of common information with regard to oscillations within certain frequency bands, the corresponding phase, from which time delays of these oscillations can be computed, hints at the direction of information transfer through oscillation. Coherence and phase analysis of surface EMG during continuous activity of deep and superficial muscles show distinct differences due to volume conduction properties of myoelectrical signals. Superficial activity therefore is characterized by significant coherence and stable phase relationships, which, additionally, can be used to determine motor unit action potential (MUAP) propagation velocity along the fibre direction without application of invasive methods. Deep muscle activity lacks significant coherence. Mental processes can be very brief and cooperation between different areas may be highly dynamic. For this reason in addition to usual Fourier estimation of coherence and phase, a two-dimensional approach of adaptive filtering was developed to estimate coherence and phase continuously in time. Statistical and dynamic properties of instantaneous phase are discussed. In order to demonstrate the value of this method for studying higher cognitive processes the method was applied to EEG recorded during word processing. During visual presentation of abstract nouns an information transfer through the propagation of oscillations from visual areas to frontal association areas in the α1-frequency band could be verified within the first 400 ms. In contrast, in case of auditory presentation positive phases from the temporal electrode locations T3 and T4 towards the occipital areas appear within the time interval of 300 ms–600 ms. The α1-band predominately seems to reflect sensory processing and attention processes.
SLOW MANIFOLDS OF SOME CHAOTIC SYSTEMS WITH APPLICATIONS TO LASER SYSTEMS
Authors: RAMDANI SOFIANE , ROSSETTO BRUNO , CHUA LEON O. , LOZI RENÉ 
Published: May 2003

In this work we deal with slow–fast autonomous dynamical systems. We initially define them as being modeled by systems of differential equations having a small parameter multiplying one of their velocity components. In order to analyze their solutions, some being chaotic, we have proposed a mathematical analytic method based on an iterative approach [Rossetto et al., 1998]. Under some conditions, this method allows us to give an analytic equation of the slow manifold. This equation is obtained by considering that the slow manifold is locally defined by a plane orthogonal to the tangent system's left fast eigenvector. In this paper, we give another method to compute the slow manifold equation by using the tangent system's slow eigenvectors. This method allows us to give a geometrical characterization of the attractor and a global qualitative description of its dynamics. The method used to compute the equation of the slow manifold has been extended to systems having a real and negative eigenvalue in a large domain of the phase space, as it is the case with the Lorenz system. Indeed, we give the Lorenz slow manifold equation and this allows us to make a qualitative study comparing this model and Chua's model. Finally, we apply our results to derive the slow manifold equations of a nonlinear optical slow–fast system, namely, the optical parametric oscillator model.
EXACT AND OPTIMAL CONVEX HULLS IN 2D
Authors: RATSCHEK HELMUT , ROKNE JON 
Published: May 2003

We present an algorithm for computing the convex hull of a finite set of points. The algorithm is based on a version of Graham scan with the following additional features: • If the points are already (single precision) machine numbers, the computation is rounding-error free, that is, the computed hull is the hull that would have been computed if real arithmetic was available. • If the points are arbitrary numbers, the algorithm renders the smallest possible machine representable convex hull that includes the exact convex hull. • The computation time is still O(n log 2n). • Only floating point arithmetic with double mantissa length is required. No mantissa splitting or other mantissa manipulations are needed; one only has to know the exponent parts of the numbers. Also, no fixed point accumulator is needed. • Single precision interval arithmetic is recommended for accelerating the computation, but is not necessary. • All of these aims are achieved with a new method for exact determination of the sign of a sum.
POINT AND LINE SEGMENT RECONSTRUCTION FROM VISIBILITY INFORMATION
Authors: WISMATH S. K. 
Published: May 2003

In general, visibility reconstruction problems involve determining a set of objects in the plane that exhibit a specified set of visibility constraints. In this paper, an algorithm is presented for reconstructing a set of parallel line segments from specified visibility information contained in an extended endpoint visibility graph. The algorithm runs in polynomial time and relies on simple vector arithmetic to generate a system of linear inequalities. A related problem, solvable with the same technique, is the point reconstruction problem, in which the cyclic ordering and the x-coordinates of a set of points is specified. A second contribution is the definition of an extension of the visibility graph called the Stab Graph, which contains extra visibility information.
HIGH QUALITY QUADRILATERAL SURFACE MESHING WITHOUT TEMPLATE RESTRICTIONS: A NEW APPROACH BASED ON NETWORK FLOW TECHNIQUES
Authors: MÜLLER–HANNEMANN MATTHIAS 
Published: May 2003

We investigate a purely combinatorial approach to the following mesh refinement problem: Given a coarse mesh of polygons in three-dimensional space, find a decomposition into well-shaped quadrilaterals such that the resulting mesh is conforming and satisfies prescribed local density constraints. We present a new approach based on network flow techniques. In particular, we show that this problem can efficiently be solved by a reduction to a minimum cost bidirected flow problem, if the mesh does not contain branching edges, that is, edges incident to more than two polygons. This approach handles optimization criteria such as density, angles and regularity. In our model we get rid of restrictions on the set of feasible solutions imposed by templates. On the other hand, we still use advantages of general templates with respect to mesh quality for the individual refinement of the mesh polygons. For meshes with branchings, the problem is feasible if and only if a certain system of linear equations over GF(2) has a solution. To enhance the mesh quality for meshes with branchings, we introduce a two-stage approach which first decomposes the whole mesh into components without branchings, and then uses minimum cost bidirected flows on the components in a second phase. We report on our computational results which indicate that this approach usually leads to a very high mesh quality.
HIGH FIDELITY INTERVAL ASSIGNMENT
Authors: MITCHELL SCOTT A. 
Published: May 2003

Quadrilateral meshing algorithms impose certain constraints on the number of intervals or mesh edges of the curves bounding a surface. When constructing a conformal mesh of a collection of adjoining surfaces, the constraints for all of the surfaces must be simultaneously satisfied. These constraints can be formulated as an integer linear program. Not all solutions to this problem are equally desirable, however. The user typically indicates a goal (soft-set) or required (hard-set) number of intervals for each curve. The hard-sets constrain the problem further, while the soft-sets influence the objective function. This paper describes an algorithm for solving this interval assignment problem. In a good solution, for each curve the positive or negative difference between its goal and assigned number of intervals is small relative to its number of goal intervals. The algorithm solves a series of linear programs, and comes close to minimizing the maximum lexicographic vector of these weighted differences. Then the algorithm solves a nearby mixed-integer linear program to satisfy certain "sum-even" constraints. The algorithm reliably produces numbers of intervals that are very close to the user's desires and is easily extendible to new constraints. Earlier versions of the algorithm1 were slower than alternative algorithms, but this is no longer a significant issue; in practice, the running time is a minor fraction of the time to mesh, even in models composed of thousands of curves.
VISIBILITY STABS AND DEPTH-FIRST SPIRALLING ON LINE SEGMENTS IN OUTPUT SENSITIVE TIME
Authors: KEIL MARK , MOUNT DAVID M. , WISMATH S. K. 
Published: May 2003

Given a set S of n non-intersecting line segments in the plane, we vpresent a new technique for efficiently traversing the endpoint visibility graph of S to solve a variety of visibility problems in output sensitive time. In particular, we develop two techniques to compute the 2n visibility polygons of the endpoints of S, in output sensitive time. Depth-first spiralling is a technique that relies on the ordered endpoint visibility graph information to traverse the endpoints of S in a spiral-like manner using a combination of Jarvis' March and depth-first search. It is a practical method and has been implemented in C++ using LEDA.
OBNOXIOUS FACILITY LOCATION: COMPLETE SERVICE WITH MINIMAL HARM
Authors: BEN-MOSHE BOAZ , KATZ MATTHEW J. , SEGAL MICHAEL 
Published: May 2003

We present efficient algorithms for several instances of the following facility location problem. Place k obnoxious facilities, with respect to n given demand sites and m given regions, where the goal is to maximize the minimal distance between a demand site and a facility, under the constraint that each of the regions must contain at least one facility. We also present an efficient solution to the following planar problem that arises as a subproblem. Given n transmitters, each of range r, construct a compact data structure that supports coverage queries, i.e., determine whether a query polygonal/rectangular region is fully covered by the transmitters.
LOWER BOUNDS FOR STREETS AND GENERALIZED STREETS
Authors: LÓPEZ-ORTIZ ALEJANDRO , SCHUIERER SVEN 
Published: May 2003

We present lower bounds for on-line searching problems in two special classes of simple polygons called streets and generalized streets. In streets we assume that the location of the target is known to the robot in advance and prove a lower bound of [Formula: see text] on the competitive ratio of any deterministic search strategy—which can be shown to be tight. For generalized streets we show that if the location of the target is not known, then there is a class of orthogonal generalized streets for which the competitive ratio of any search strategy is at least [Formula: see text] in the L2-metric—again matching the competitive ratio of the best known algorithm. We also show that if the location of the target is known, then the competitive ratio for searching in generalized streets in the L1-metric is at least 9 which is tight as well. The former result is based on a lower bound on the average competitive ratio of searching on the real line if an upper bound of D to the target is given. We show that in this case the average competitive ratio is at least 9-O(1/ log D).
TERRAIN DECOMPOSITION AND LAYERED MANUFACTURING
Authors: FEKETE SÁNDOR P. , MITCHELL JOSEPH S. B. 
Published: May 2003

We consider a problem that arises in generating three-dimensional models by methods of layered manufacturing: How does one decompose a given model P into a small number of sub-models each of which is a terrain polyhedron? Terrain polyhedra have a base facet such that, for each point of the polyhedron, the line segment joining the point to its orthogonal projection on the base facet lies within the polyhedron. Terrain polyhedra are exactly the class of polyhedral models for which it is possible to construct the model using layered manufacturing (with layers parallel to the base facet), without the need for constructing "supports" (which must later be removed). In order to maximize the integrity of a prototype, one wants to minimize the number of individual sub-models that are manufactured and then glued together. We show that it is NP-hard to decide if a three-dimensional model P of genus 0 can be decomposed into k terrain polyhedra. We also prove a two-dimensional version of this theorem, for the case in which P is a polygonal region with holes. Both results still hold if we are restricted to isothetic objects and/or axis-parallel layering directions.
AN EFFICIENT IMPLEMENTATION OF THE EXACT ENUMERATION METHOD FOR RANDOM WALKS ON SIERPINSKI CARPETS
Authors: FRANZ ASTRID , SCHULZKY CHRISTIAN , SEEGER STEFFEN , HOFFMANN KARL HEINZ 
Published: May 2003

In the following, we present a highly efficient algorithm to iterate the master equation for random walks on effectively infinite Sierpinski carpets, i.e. without surface effects. The resulting probability distribution can, for instance, be used to get an estimate for the random walk dimension, which is determined by the scaling exponent of the mean square displacement versus time. The advantage of this algorithm is a dynamic data structure for storing the fractal. It covers only a little bit more than the points of the fractal with positive probability and is enlarged when needed. Thus the size of the considered part of the Sierpinski carpet need not be fixed at the beginning of the algorithm. It is restricted only by the amount of available computer RAM. Furthermore, all the information which is needed in every step to update the probability distribution is stored in tables. The lookup of this information is much faster compared to a repeated calculation. Hence, every time step is speeded up and the total computation time for a given number of time steps is decreased.
ON THE MODIFICATION OF FRACTAL SELF-SPACE DURING CELL DIFFERENTIATION OR TUMOR PROGRESSION
Authors: WALISZEWSKI PRZEMYSLAW , KONARSKI JERZY , MOLSKI MARCIN 
Published: May 2003

A novel parameter called expansion coefficient has been defined to measure both connectivity and collectivity in a population of cells conquering the available space and self-organizing into tissue patterns of the higher order. Connectivity (i.e. interconnectedness) denotes that there are complex dynamic relationships, not just structural, static ones, in a population of cells enabling the emergence of global features in the system that would never appear in single cells existing out of the system. Collectivity denotes that all interconnected cells interact in a common mode.Evolution of this coefficient during differentiation or tumor progression was investigated by the box-counting method. The population of control or retinoid-treated primary cancer cells cultured in the monolayer (i.e. quasi-2D) system possessed fractal dimension and self-similarity. However, the expansion coefficient was close to zero, indicating that connectivity was low, and no collective state emerged. A significant change of the coefficient occurred when primary cells formed aggregates, quasi-3D systems with increased connectivity, and during treatment of the aggregates with retinoid resulting in a collective state (i.e. in differentiation of cells). Those statistical features were lost during tumor progression. All populations of the secondary cancer cells possessed integer dimension and the expansion coefficient was equal to zero.
PHASE-PERIODIC STRUCTURES OF SELF-SIMILAR STAIRCASE FRACTALS
Authors: PAVLOVITCH BULAEV BORIS 
Published: May 2003

The possibilities of investigating the self-similar staircase fractals in a discrete coordinate system are clearly very promising. Surprisingly, such fractals are found to have holographic properties. Some geometric shapes e.g. a circle or a quadrate, are produced by a well-defined boundary through generating the staircase fractals in 2D discrete space. The obtained "luminous boundaries" are remembered outer boundaries of any geometric form, regardless of the size. Actually, this process is similar to the photographing of an exterior form. Thus there is destruction of a natural phase-periodical structure of the fractal. The staircase fractals are subject to the same rules that apply in information theory. It is shown that the difference in sharpness of holographic shapes is a direct consequence of spectra informations of the forms. The Hausdorff-Besicovitch dimension for this fractal has been estimated to be 0.5. On this view, the structure of staircase fractals is that of a Cantor Set. As indicated in the picture, such fractal resembles a "goose-wing." Also, the self-similar staircase fractal has much in common with a set of straight lines in a discrete coordinate system.
A GENERALIZATION OF FRACTAL INTERPOLATION STOCHASTIC PROCESSES TO HIGHER DIMENSIONS
Authors: MAŁYSZ ROBERT 
Published: May 2003

We generalize the notion of fractal interpolation functions (FIFs) to stochastic processes. We prove that the Minkowski dimension of trajectories of such interpolations for self-similar processes with stationary increments converges to 2-α. We generalize the notion of vector-valued FIFs to stochastic processes. Trajectories of such interpolations based on an equally spaced sample of size n on the interval [0,1] converge to the trajectory of the original process. Moreover, for fractional Brownian motion and, more generally, for self-similar processes with stationary increments (α-sssi) processes, upper bounds of the Minkowski dimensions of the image and the graph converge to the Hausdorff dimension of the image and the graph of the original process, respectively.
ON THE PROPAGATION OF ACOUSTIC PULSES IN POROUS RIGID MEDIA: A TIME-DOMAIN APPROACH
Authors: FELLAH Z. E. A. , DEPOLLIER C. 
Published: May 2003

Wave propagation of acoustic waves in porous media is considered. The medium is assumed to have a rigid frame, so that the propagation takes place in the air which fills the material. The Euler equation and the constitutive relation are generalized to take into account the dispersive nature of these media. We show that the connection between the fractional calculus and the behavior of materials with memory allows to work out time domain wave equations, the coefficients of which are no longer frequency dependent. These equations are suited for direct and inverse scattering problems, and lead to the complete determination of the porous medium parameters.
HEDGE ALGEBRAS, LINGUISTIC-VALUE LOGIC AND THEIR APPLICATION TO FUZZY REASONING
Authors: NGUYEN CAT HO , TRAN DINH KHANG , VAN NAM HUYNH , NGUYEN HAI CHAU 
Published: May 2003

People use natural languages to think, to reason, to deduce conclusions, and to make decisions. Fuzzy set theory introduced by L. A. Zadeh has been intensively developed and founded a computational foundation for modeling human reasoning processs. The contribution of this theory both in the theoretical and the applied aspects is well recognized. However, the traditional fuzzy set theory cannot handle linguistic terms directly. In our approach, we have constructed algebraic structures to model linguistic domains, and developed a method of linguistic reasoning, which directly manipulates linguistic terms, In particular, our approach can be applied to fuzzy control problems. In many applications of expert systems or fuzzy control, there exist numerous fuzzy reasoning methods. Intuitively, the effectiveness of each method depends on how well this method satisfies the following criterion: the similarity degree between the conclusion (the output) of the method and the consequence of an if-then sentence (in the given fuzzy model) should be the "same" as that between the input of the method and the antecedent of this if-then sentence. To formalize this idea, we introduce a "measure function" to measure the similarity between linguistic terms in a domain of any linguistic variable and to build approximate reasoning methods. The resulting comparison between our method and some other methods shows that our method is simple and more effective.
A FUZZY DISTRIBUTED EXPERT SYSTEM DESIGN TOOL EXGEN AND ITS APPLICATION TO SENSORY FOODSTUFF EVALUATION
Authors: NGUYEN THANH THUY , NGUYEN TOAN THANG , THAC BINH CUONG , TRAN DINH KHANG 
Published: May 2003

Since the appearance of MYCIN, expert systems have been widely and successfully developed for various scientific and technological researches and applications. These applications require more and more fuzzy information resources because of the uncertainty, inexactness in labeling facts using linguistic terms and expressing human expertise. Sensory foodstuff evaluation is among this kind of fuzzy expert system applications. In the frame of the research project on fuzzy expert systems for science and technology at the Hanoi University of Technology, we have developed an expert system building tool called EXGEN which has the following features: – Knowledge editing in the form of production rules using Vietnamese in the natural language-like syntax. The tool is also capable to verify the consistency of an acquired knowledge base. – Inference engine consisting of two principal inference mechanisms (forward and backward inference) and control strategy module. We proposed also some heuristics for choosing a potential inference trace, allowing to get more information about conclusions. – Possibility of establishing a configuration for a distributed working session. It would be possible to carry out: + a deduction over a shared rule base (RB) in the server, based on information acquired from workstations (common RB and conclusion, distributed fact base (FB)) + a deduction over a shared RB in the server with different cognitive tasks (including hypotheses fact and conclusions) on workstations (common RB and distributed FB) + deductions on workstations with distributed knowledge bases (Distributed RB and FB) We have already implemented an application expert system SENEXSYS for sensory foodstuff evaluation using the building tool EXGEN. Experimental results have shown that qualification given by the expert system is comparable to evaluation results obtained by following up Vietnamese standard TCVN 3215.79
HIERARCHICAL DECISION MAKING IN STRATEGIC INVESTMENT BY A BOLTZMANN MACHINE
Authors: WATANABE TERUYUKI , WATADA JUNZO , ODA KENJI 
Published: May 2003

A conventional portfolio selection problem, which is based on a mean-variance model, is difficult to solve by using mathematical programming techniques. This difficulty is caused by the fact that the corresponding mathematical programming problems are large-dimensional one, since almost all variance-covariances of return rates are, typically, not zeros. In this paper, we propose an efficient method for solving a portfolio selection problem, a method which uses a Boltzmann machine. In a real-life problem, it is also important to find the optimal combination of a small number of invested securities out of many securities in a market, because of a limited amount of funds to invest into securities. So we also propose a portfolio selection method to obtain the invest ratio of limited number of securities out of huge number of securities using a multi-stage application of the Boltzmann machine.