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Aiming at the limitations of LEACH, PEGASIS and PEDAP, we present a multi-layer energy-efficient and delay-reducing chain-based data gathering protocol (MEDC) for wireless sensor network, under consideration of the characteristics of wireless sensing traffic monitoring network (WSTMN) such as band monitoring area, high-speed target, long-distance base(More)
Curve let transform has been recently proved to be a powerful tool for multi-resolution analysis on images. In this paper we propose a new approach for facial expression recognition based on features extracted via curve let transform. First curve let transform is presented and its advantages in image analysis are described. Then the coefficients of curve(More)
The use of Wireless Sensor Network (WSN) has proved to be a very beneficial in the design of adaptive and dynamic traffic light intersection system that will minimize the waiting time of vehicles and also manage the traffic load at the intersection adaptively. In this paper, we propose an adaptive traffic intersection system based on Wireless Sensor Network(More)
As a powerful tool, ontology has been widely applied in social science, medicine science and computer science. In computer networks, especially, ontology is used for search extension, thus boost the quality of information retrieval. Ontology concept similarity calculation is an essential problem in these applications. A new method to get similarity between(More)
The SIFT (Scale Invariant Feature Transform) is a computer vision algorithm that is used to detect and describe the local image features. The SIFT features are robust to changes in illumination, noise, and minor changes in viewpoint. The SIFT features have been used object recognition, image retrieval and matching, and so on.. The research of SIFT(More)
All graphs considered in this paper are finite, loopless, and without multiple edges. The notation and terminology used but undefined in this paper can be found in [2]. Let G be a graph with the vertex set V (G) and the edge set E(G). For a vertex x ∈ V (G), we use dG(x) and NG(x) to denote the degree and the neighborhood of x in G, respectively. Let δ(G)(More)
The goal of ranking is to learn a real-valued ranking function that induces a ranking or ordering over an instance space. A learning algorithm is stable if the algorithm satisfies the hypothesis that the output of the algorithm varies in a limited way in response to small changes made to the training set. This paper studies the ‘almost(More)