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Gram stained direct smears test is clinically useful in early identification of infections. Unfortunately, this practice is considered time consuming and labour intensive. Most existing effort in this area is to perform highmagnification analysis of images taken from manually selected areas. In this paper, we address the problem of the automatic selection of candidate areas (or patches) for subsequent...
Understanding the spatio-temporal characteristics of human mobility in urban areas is invaluable especially for traffic management and urban planning. An opportunity to characterize and predict urban mobility is provided by mining Bike Sharing System (BSS) trip data spatially and temporally. This study focuses on identifying highly predictable BSS users, revealing their mobility characteristics and...
Device to device (D2D) communication is expected to become a promising technology of the next-generation wireless communication systems. Security issues have become technical barriers of D2D communication due to its “open-air” nature and lack of centralized control. Generating symmetric keys individually on different communication parties without key exchange or distribution is desirable but challenging...
Support vector machines (SVMs) have been dominant learning techniques for more than ten years, and mostly applied to supervised learning problems. These years two-class unsupervised and semi-supervised classification algorithms based on bounded C-SVMs, bounded j/-SVMs and Lagrangian SVMs (LSVMs) respectively, which are relaxed to semi-definite programming (SDP), get good classification results. These...
Support vector machines (SVMs) have been dominant learning techniques for more than ten years, and mostly applied to supervised learning problems. These years two-class unsupervised and semi-supervised classification algorithms based on bounded C-SVMs, bounded ??-SVMs and Lagrangian SVMs (LSVMs) respectively, which are relaxed to semi-definite programming (SDP), get good classification results. These...
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