A Heuristic Greedy Optimum Algorithm for Target Coverage in Wireless Sensor Networks

title: An Ontology-Based Approach to Knowledge Management
abstract: Combining with the respective advantages of ontology and Web Service, this paper puts forward a knowledge management approach to overcome the problem of semantic heterogeneity in distributed environments. The emphasis is placed on establishing an XML-oriented semantic data model and the mapping between XML data based on a global semantic view, which enhances knowledge process efficiency, accuracy and the semantic interoperability as well.

title: MAC Performance and Improvement in Mobile Wireless Sensor Networks
abstract: Former Media Access Control (MAC) protocols for Wireless Sensor Networks (WSNs) are mainly for static networks. In the networks where mobile nodes exist, the performance will degrade greatly. In this paper the performance of MAC in mobile WSNs (mWSNs) is analyzed and improved algorithms are presented. Simulations validate the effects. A new MAC protocol also is presented for the scenario with more mobile nodes.

title: Support Vector Machines for Text Categorization in Chinese Question Classification
abstract: Question classification plays a crucial important role in the question answering system because categorizing a given question is beneficial to identify an answer in the documents. The goal of question classification is to accurately assign labels to question based on expected answer type. Recently, many machine learning algorithms are used for question classification. However many research results show that SVM perform best in this task, because it is well known to work well for nonlinear, sparse, high dimensional problems. In this experiment, we perform the One-against-One SVM algorithm and a feature extraction method of Chinese questions to get high classification accuracy

title: Design and Analysis of Test Signals for System Identification
abstract: The toolbox supports virtually all polynomial (transfer function) and state-space model representations and model identification by nonparametric correlation and spectral analysis. Toolbox functions can identify continuousor discrete-time models with an arbitrary number of input and output channels. You can import and preprocess measured data, generate parametric and nonparametric models, and validate estimated models against measured data.

title: Learning from Positive and Unlabeled Examples with Different Data Distributions
abstract: We study the problem of learning from positive and unlabeled examples. Although several techniques exist for dealing with this problem, they all assume that positive examples in the positive set P and the positive examples in the unlabeled set U are generated from the same distribution. This assumption may be violated in practice. For example, one wants to collect all printer pages from the Web. One can use the printer pages from one site as the set P of positive pages and use product pages from another site as U. One wants to classify the pages in U into printer pages and non-printer pages. Although printer pages from the two sites have many similarities, they can also be quite different because different sites often present similar products in different styles and have different focuses. In such cases, existing methods perform poorly. This paper proposes a novel technique A-EM to deal with the problem. Experiment results with product page classification demonstrate the effectiveness of the proposed technique.

title: Robot Obstacle Avoidance based on an Improved Ant Colony Algorithm
abstract: Obstacle Avoidance for mobile robot is a nondeterministic polynomial hard (NP-hard) problem. Ant algorithm is the bionic algorithm which simulated ants foraging behavior, which can effectively solve the problems of this kind. In this paper, we propose an improved ant colony algorithm for robot obstacle avoidance, in which heuristic information is adjusted at run-time during the searching process. The proposed algorithm can effectively alleviate the local optimum problem, global optimal path can be robustly found in our experiments.

title: Finding the Shortest Route Using Cases, Knowledge, and Djikstra's Algorithm
abstract: This prototype system integrates Dijkstra's algorithm with knowledge-based and case-based components, reducing the time required to find the shortest path between points in a road network.