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Hospital beds are a scarce resource and always in need. The beds are often organized by clinical specialties for better patient care. When the Accident & Emergency Department (A&E) admits a patient, there may not be an available bed that matches the requested specialty. The patient may be thus asked to wait at the A&E till a matching bed is available, or assigned a bed from a different...
Popular photo-sharing sites have attracted millions of people and helped construct massive social networks in cyberspace. Different from traditional social relationship, users actively interact within groups where common interests are shared on certain types of events or topics captured by photos and videos. Contributing images to a group would greatly promote the interactions between users and expand...
The concepts of symbolic dynamics and partitioning of time series data have been used for feature extraction and anomaly detection. Although much attention has been paid to modeling of finite state machines from symbol sequences, similar efforts have not been expended for partitioning of time series data to optimally generate symbol sequences. This paper addresses this issue and proposes a partitioning...
This paper presents a new page replacement algorithm called Adaptive Page Replacement Algorithm (APRA), aiming at reducing the number of read, write, and erase operations and thereby improving the performance of NAND flash memory based storage systems. APRA uses a learning rule to adaptively and continually revise its parameter in response to diverse workloads with different access patterns. Experiments...
H.264/AVC introduces the variable block size macroblock mode for motion estimation, which brings huge computational cost. In this paper, a novel fast inter macroblock mode decision algorithm for H.264/AVC has been proposed. The proposed algorithm evaluates the modes based on residual information. The residual is obtained after the motion search of P16 ?? 16 mode or P8 ?? 8 mode. Then the characteristic...
Theoretical analysis of the precision ensuring mechanism of reconfigurable machine interface using over-positioning technology was thoroughly presented. Based on the obtained rule of over-positioning precision, positioning pin number and interfere probability, the concept of two-state positioning aiming at the positioning difficulty of rigid over-positioning machine interface was proposed. In addition,...
It is a challenging issue to analyze video content for video mining tasks due to lacking of effective representation of video. In this paper, we propose a novel key frame representation algorithm based on rough sets (RS) in discrete cosine transform (DCT) compressed-domain. Firstly, we extract DCT coefficients in compressed-domain, select and preprocess the DC coefficients that derived from DCT coefficients...
Clustering is an unsupervised knowledge discovery process that groups a set of data such that the intra-cluster similarity is maximized and the inter-cluster similarity is minimized. Existing clustering algorithms, such as k-means and PAM, are designed to find clusters that fit static models. In this paper, we describe a clustering algorithm called fuzzy artificial immune system clustering (FAISC),...
Network security has become a critical issue with the rapid increase in connectivity of computer systems over the Internet which has resulted in a great deal of opportunities for intrusions. One commonly used defense measure against such malicious attacks in the Internet is Intrusion Detection System (IDS). In this paper we describe a new data mining based method for intrusion detection based on network...
Recently developed SAGE technology enables us to simultaneously quantify the expression levels of thousands of genes in a population of cells. SAGE data is helpful in classification of different types of cancers. However, one main challenge in this task is the availability of a smaller number of samples compared to huge number of genes, many of which are irrelevant for classification. Another main...
In this paper, the theory of natural immune system is first briefly introduced. Several representative artificial immune networks are next discussed. Their principles and learning algorithms are given here in details. Moreover, we demonstrate the applications of these artificial immune networks in the fields of data mining, pattern recognition, and optimization
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