Several parameters of generalized Mycielskians
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: 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: Neighborhood Union Condition with Distance for Vertex-pancyclicity

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

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: 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.

title: Assessing Effectiveness in Video Retrieval
abstract: This paper examines results from the last two years of the TRECVID video retrieval evaluations. While there is encouraging evidence about progress in video retrieval, there are several major disappointments confirming that the field of video retrieval is still in its infancy. Many publications blithely attribute improvements in retrieval tasks to the different techniques without paying much attention to the statistical reliability of the comparisons. We conduct an analysis of the official TRECVID evaluation results, using both retrieval experiment error rates and ANOVA measures, and demonstrate that the difference between many systems is not statistically significant. We conclude the paper with the lessons learned from both results with and without statistically significant difference.

title: Extreme video retrieval: joint maximization of human and computer performance
abstract: We present an efficient system for video search that maximizes the use of human bandwidth, while at the same time exploiting the machine's ability to learn in real-time from user selected relevant video clips. The system exploits the human capability for rapidly scanning imagery augmenting it with an active learning loop, which attempts to always present the most relevant material based on the current information. Two versions of the human interface were evaluated, one with variable page sizes and manual paging, the other with a fixed page size and automatic paging. Both require absolute attention and focus of the user for optimal performance. In either case, as users search and find relevant results, the system can invisibly re-rank its previous best guesses using a number of knowledge sources, such as image similarity, text similarity, and temporal proximity. Experimental evidence shows a significant improvement using the combined extremes of human and machine power over either approach alone.

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: News video classification using SVM-based multimodal classifiers and combination strategies
abstract: Video classification is the first step toward multimedia content understanding. When video is classified into conceptual categories, it is usually desirable to combine evidence from multiple modalities. However, combination strategies in previous studies were usually ad hoc. We investigate a meta-classification combination strategy using Support Vector Machine, and compare it with probability-based strategies. Text features from closed-captions and visual features from images are combined to classify broadcast news video. The experimental results show that combining multimodal classifiers can significantly improve recall and precision, and our meta-classification strategy gives better precision than the approach of taking the product of the posterior probabilities.