Optimal-Nearest-Neighbor Queries
Given two sets D<sub>A</sub> and D<sub>B</sub> of multidimensional objects, a spatial region R, and a critical distance dc, an optimal-nearest- neighbor (ONN) query retrieves outside R, the object in D<sub>B</sub> with maximum optimality. Let CAR (S<sub>p</sub>,p) be the cardinality of the subset Sp of objects in D<sub>A</sub> which locate within R and are enclosed by the vicinity circle centered at p with radius d<sub>c</sub>. Then, an object <i>o</i> is said to be better than another one o' if (i) CAR (S<sub>o</sub>,o) = CAR (S<sub>o</sub>,o'), or (ii) when CAR (S<sub>o</sub>,o) = CAR (S<sub>o</sub>',o') the sum of the weighted distance from each object in S<sub>o</sub> to <i>o</i> is smaller than the sum of the weighted distance between every object in So' and o'. This type of queries is quite useful in many decision making applications. In this paper, we formalize the ONN query, develop the optimality metric, and propose several algorithms for finding optimal nearest neighbors efficiently. Our techniques assume that both D<sub>A</sub> and D<sub>B</sub> are indexed by R-trees. Extensive experiments demonstrate the efficiency and scalability of our proposed algorithms using both real and synthetic datasets.

title: Dynamic Equivalents of Power System Based on Extended Two Particle Swarm Optimization
abstract: A novel methodology based on phaser measurement units (PMUs) for power system dynamic equivalents is presented. In this methodology the external system is reduced dynamically using the important quantities obtained by PMUs. An extended two particle swarm optimization (PSO) algorithm with the mutation operator is proposed to identify the parameters of the equivalent system. The proposed method is demonstrated and compared with the original system using the 10 machines 39 buses New England test system. The comparison shows that the proposed method can preserve the dynamic properties of the original system and has great value in engineering application.

title: Topic Distributions over Links on Web
abstract: It is well known that Web users create links with different intentions. However, a key question, which is not well studied, is how to categorize the links and how to quantify the strength of the influence of a web page on another if there is a link between the two linked web pages. In this paper, we focus on the problem of link semantics analysis, and propose a novel supervised learning approach to build a model, based on a training link-labeled and link-weighted graph where a link-label represents the category of a link and a link-weight represents the influence of one web page on the other in a link. Based on the model built, we categorize links and quantify the influence of web pages on the others in a large graph in the same application domain. We discuss our proposed approach, namely Pairwise Restricted Boltzmann Machines (PRBMs), and conduct extensive experimental studies to demonstrate the effectiveness of our approach using large real datasets.

title: Increase of potential intellectual bandwidth in a scientific community through implementation of an end-user information system
abstract: Qureshi, et al. (2002) presented a case study where they used a framework, the intellectual bandwidth model to measure an organization's ability to create value. The model consists of two dimensions, information assimilation and collaboration. The IB model is a useful tool for managers because it enables them to plan solutions to complex business problems and to easily communicate these plans to key individuals. The model can also serve as a guide when making investment decisions. While it is important to increase an organization's intellectual bandwidth, it is equally important to assure that the resulting increase is employed to improve the organization's ability to innovate since, as it has been shown, innovation is the number one creator of organizational wealth (Baum et al., 2000). In this paper we discuss how intellectual bandwidth as proposed by Nunamaker et al. (2001) can be extended beyond the highest level of information assimilation identified in the model, automated sense-making, to ensure implementation of product innovations. To do this we propose adding two new information assimilation features, automated utilization and automated implementation. A real business example from the bioscience industry is presented in order to demonstrate how the IB model with extensions can be used. The study discusses an end-user information system, its current use and its potential to enhance an organization's value-creating capability.

title: A Topic Modeling Approach and Its Integration into the Random Walk Framework for Academic Search
abstract: In this paper, we propose a unified topic modeling approach and its integration into the random walk framework for academic search. Specifically, we present a topic model for simultaneously modeling papers, authors, and publication venues. We combine the proposed topic model into the random walk framework. Experimental results show that our proposed approach for academic search significantly outperforms the baseline methods of using BM25 and language model, and those of using the existing topic models (including pLSI, LDA, and the AT model).

title: A Novel Method for Detecting Outlying Subspaces in High-dimensional Databases Using Genetic Algorithm
abstract: Detecting outlying subspaces is a relatively new research problem in outlier-ness analysis for high-dimensional data. An outlying subspace for a given data point p is the sub- space in which p is an outlier. Outlying subspace detection can facilitate a better characterization process for the detected outliers. It can also enable outlier mining for high- dimensional data to be performed more accurately and efficiently. In this paper, we proposed a new method using genetic algorithm paradigm for searching outlying subspaces efficiently. We developed a technique for efficiently computing the lower and upper bounds of the distance between a given point and its kth nearest neighbor in each possible subspace. These bounds are used to speed up the fitness evaluation of the designed genetic algorithm for outlying subspace detection. We also proposed a random sampling technique to further reduce the computation of the genetic algorithm. The optimal number of sampling data is specified to ensure the accuracy of the result. We show that the proposed method is efficient and effective in handling outlying subspace detection problem by a set of experiments conducted on both synthetic and real-life datasets.

title: A Novel Approach of Face Detection based on Skin Color Segmentation and PCA
abstract: Nowadays, face detection and recognition have gained importance in security and information access. In this paper, an efficient method of face detection based on skin color segmentation and principal components analysis(PCA) is proposed. Firstly, segmenting image using color model to filter candidate faces roughly; And then Eye-analogue segments at a given scale are discovered by finding regions which are darker than their neighborhoods to filter candidate faces farther; at the end, PCA method is used to extract the relevant information in human faces.