In many applications, black-box prediction is not satisfactory, and understanding the data is of critical importance. Typically, approaches useful for understanding of data involve logical rules, evaluate similarity t...
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Summary form only given. The efficiency of a large-scale multicomputer is critically dependent on the performance of its underlying interconnection network. Dimension-ordered routing has been employed to transmit mess...
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Summary form only given. The efficiency of a large-scale multicomputer is critically dependent on the performance of its underlying interconnection network. Dimension-ordered routing has been employed to transmit messages in multicomputer networks, as it requires a simple deadlock-avoidance algorithm, resulting in an efficient router implementation. The performance of this routing algorithm has been widely analysed under the assumption of the traditional Poisson arrival process, which is inherently unable to model traffic self-similarity revealed by many real-world applications. In an effort towards providing cost-effective tools that help investigating network performance under more realistic traffic loads, we propose an analytical model for dimension-ordered routing in k-ary n-cube networks when subjected to self-similar traffic. As the service time, blocking probability and waiting time experienced by a message vary from a dimension to another with dimension-ordered routing, the design of this model poses greater challenges. The model validity is demonstrated by performance results obtained from simulation experiments.
Based on a number of reports and publications, primarily by Takahiko Ogino [14], [15], [16] (in these proceedings), and [17], on the emerging concept of CyberRail, we attempt to show what a formal domain model of Cybe...
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The MISSION system utilises query agents, in particular the matching and negotiation agents that are responsible for pre-integration where the matching agent decomposes the query into sub-queries, and then searches me...
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The MISSION system utilises query agents, in particular the matching and negotiation agents that are responsible for pre-integration where the matching agent decomposes the query into sub-queries, and then searches metadata to find datasets that match the query fragments. Such an approach provides a capability of automating the process of executing queries on heterogeneous statistical databases that are distributed over the Internet. The novelty lies in the provision of automated methods for statistical aggregation, where the heterogeneity essentially resides in the classification schemes of categorical data, including both heterogeneity of nomenclature and heterogeneity of granularity. In addition, our solution permits queries to be specified in a goal-driven query-by-example format. Rather than impose an a priori global standard, the user can query through a unified interface where integration is done at run-time.
One of the major issues that affect the performance of mobile ad hoc networks (MANET) is routing. Recently, position-based routing for MANET is found to be a very promising routing strategy for inter-vehicular communi...
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In a mobile ad hoc network (MANET), packet broadcast is common and frequently used to disseminate information. Broadcast consume large amount of bandwidth resource, which is scarce in MANET environment. The problem is...
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During the past few years, wireless local area networks (WLANs) have become extremely popular. The IEEE 802.11 protocol is the dominating standard for WLANs employing the distributed coordination function (DCF) as its...
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During the past few years, wireless local area networks (WLANs) have become extremely popular. The IEEE 802.11 protocol is the dominating standard for WLANs employing the distributed coordination function (DCF) as its essential medium access control (MAC) mechanism. This paper presents a simple and accurate analysis using Markov chain modelling to compute IEEE 802.11 DCF performance, in the absence of hidden stations and transmission errors. This mathematical analysis calculates in addition to the throughput efficiency, the average packet delay and the packet drop probability for both the basic access and RTS/CTS medium access schemes. The derived analysis, which takes into account packet retry limits, is validated by comparison with OPNET simulation results. The mathematical model is used to study the effectiveness of the RTS/CTS scheme at high data rates and the performance improvements of transmitting a burst of packets after winning the contention for medium access. Packet bursting considerably increases both throughput and packet delay performance but lowers the short-term fairness on medium access.
Microarray technology is a recent development in experimental molecular biology which can produce quantitative expression measurements for thousands of genes in a single, cellular mRNA sample. These many gene expressi...
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Microarray technology is a recent development in experimental molecular biology which can produce quantitative expression measurements for thousands of genes in a single, cellular mRNA sample. These many gene expression measurements form a composite profile of the sample, which can be used to differentiate samples from different classes such as tissue types or treatments. However, for the gene expression profile data obtained in a specific comparison, most likely only some of the genes will, be differentially expressed between the classes, while many other genes have similar expression levels. Selecting a list of informative differential genes from these data is important for microarray data analysis. In this paper, we describe a framework for selecting informative genes, called ranking and combination analysis (RAC), which combines various existing informative gene selection methods. We conducted experiments using three data sets and six existing feature selection methods. The results show that the RAC framework is a robust and efficient approach to identify informative gene for microarray data. The combination approach on two selecting methods almost always performed better than the less efficient individual, and in many cases, better than both. More significantly, when considering all three data sets together, the combination approach, on average, outperforms each individual feature selection method. All of these indicate that RCA might be a viable and feasible approach for the microarray gene expression analysis.
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