Coloring of distance graphs with intervals as distance sets
Let D be a set of positive integers. The distance graph G(Z, D) with distance set D is the graph with vertex set Z in which two vertices x, y are adjacent if and only if |x - y| ∈ D. The fractional chromatic number, the chromatic number, and the circular chromatic number of G(Z, D) for various D have been extensively studied recently. In this paper, we investigate the fractional chromatic number, the chromatic number, and the circular chromatic number of the distance graphs with the distance sets of the form Dm, [k,k'] = {1, 2, ..., m} - {k, k + 1, ..., k'}, where m, k, and k' are natural numbers with m ≥ k' ≥ k. In particular, we completely determine the chromatic number of G(Z, Dm, [2,k']) for arbitrary m, and k'.

title: Several parameters of generalized Mycielskians
abstract: The generalized Mycielskians (also known as cones over graphs) are the natural generalization of the Mycielski graphs (which were first introduced by Mycielski in 1955). Given a graph G and any integer m ≥ 0, one can transform G into a new graph µm (G), the generalized Mycielskian of G. This paper investigates circular clique number, total domination number, open packing number, fractional open packing number, vertex cover number, determinant, spectrum, and biclique partition number of µm (G).

title: Some star extremal circulant graphs
abstract: The circular chromatic number @g"c(G) and the fractional chromatic number @g"f(G) are two generalizations of the ordinary chromatic number of a graph G. A graph is called star extremal if its circular chromatic number equals its fractional chromatic number. Gao and Zhu ( (1996) 147-156), Lih et al. ( (1999) 491-499) gave many classes of circulant graphs which are star extremal. In this paper, we study the star extremality of circulant graphs whose generating sets are of the form {1,2,...,m-1,k,k+1,...,k+m-2}, {k,k+1,...,k'}, and {k,k+1,...,k"1,k"2,k"2+1,...,@?p/[email protected]?}, where p is the vertex number of the graph. As a corollary, we give an improvement of a result of Gao and Zhu ( (1996) 147-156).

title: Circular chromatic numbers of some distance graphs
abstract: Given a set D of positive integers, the distance graph G(Z,D) has vertices all integers Z, and two vertices j and j^' in Z are adjacent if and only if |j-j^'|@?D. This paper determines the circular chromatic numbers of some distance graphs.

title: Circular Chromatic Numbers and Fractional Chromatic Numbers of Distance Graphs with Distance Sets Missing An Interval

title: The Promise and Perils of Near-Regular Texture
abstract: Motivated by the low structural fidelity for near-regular textures in current texture synthesis algorithms, we propose and implement an alternative texture synthesis method for near-regular texture. We view such textures as statistical departures from regular patterns and argue that a thorough understanding of their structures in terms of their translation symmetries can enhance existing methods of texture synthesis. We demonstrate the perils of texture synthesis for near-regular texture and the promise of faithfully preserving the regularity as well as the randomness in a near-regular texture sample.

title: Self-organizing fuzzy control of multi-variable systems using learning vector quantization network
abstract: Using learning vector quantization (LVQ) network to construct a self-organizing fuzzy controller (SOFC) for multi-variable nonlinear composite systems is developed in this paper. The LVQ network is used to provide information about the better locations of the IF-part membership functions through un-supervised learning. The generated fuzzy rule base is applied to the SOFC and updated by a self-learning procedure. Using Lyapunov stability methods, the proposed adaptive scheme is proven to provide the SOFC some degree of robust properties and guarantee uniform ultimate boundedness in the presence of disturbances, measurement noise and perturbed initialization error. The effectiveness of the proposed controller has been demonstrated numerically by applying to control a two-link manipulator.

title: Speaker Adaptation of Fuzzy-Perceptron-Based Speech Recognition
abstract: In this paper, we propose a speech recognition algorithm which utilizes hidden Markov models (HMM) and Viterbi algorithm for segmenting the input speech sequence, such that the variable-dimensional speech signal is converted into a fixed-dimensional speech signal, called TN vector. We then use the fuzzy perceptron to generate hyperplanes which separate patterns of each class from the others. The proposed speech recognition algorithm is easy for speaker adaptation when the idea of "supporting pattern" is used. The supporting patterns are those patterns closest to the hyperplane. When a recognition error occurs, we include all the TN vectors of the input speech sequence with respect to the segmentations of all HMM models as the supporting patterns. The supporting patterns are then used by the fuzzy perceptron to tune the hyperplane that can cause correct recognition, and also tune the hyperplane that resulted in wrong recognition. Since only two hyperplane need to be tuned for a recognition error, the proposed adaptation scheme is time-economic and suitable for on-line adaptation. Although the adaptation scheme cannot ensure to correct the wrong recognition right after adaptation, the hyperplanes are tuned in the direction for correct recognition iteratively and the speed of adaptation can be adjusted by a "belief" parameter set by the user. Several examples are used to show the performance of the proposed speech recognition algorithm and the speaker adaptation scheme.

title: Communication-Efficient Vector Manipulations on Binary N-Cubes
abstract: One way to find closest pairs in large datasets is to use hash functions , . In recent years locality-se nsitive hash functions for various metrics have been given: project ing an n-cube ontok bits is simple hash function that performs well. In this paper we investigate alternatives to projection. For various parameters hash functions given by complete decodi ng algorithms for codes work better, and asymptotically random codes perform better than projection.

title: Identifying Perspectives at the Document and Sentence Levels Using Statistical Models
abstract: In this paper we investigate the problem of identifying the perspective from which a document was written. By perspective we mean a point of view, for example, from the perspective of Democrats or Republicans. Can computers learn to identify the perspective of a document? Furthermore, can computers identify which sentences in a document strongly convey a particular perspective? We develop statistical models to capture how perspectives are expressed at the document and sentence levels, and evaluate the proposed models on a collection of articles on the Israeli-Palestinian conflict. The results show that the statistical models can successfully learn how perspectives are reflected in word usage and identify the perspective of a document with very high accuracy.