Due to the existence of systematic bias in the measurements, inter-chip normalization is required before integrated data analysis of multiple microarray datasets. Current inter-chip normalization methods rely on some ...
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Due to the existence of systematic bias in the measurements, inter-chip normalization is required before integrated data analysis of multiple microarray datasets. Current inter-chip normalization methods rely on some assumptions, which can rarely be verified by experiments, such as the invariant expression level of housekeeping genes or the stability of statistical data distribution. In this paper, we present a highly verifiable inter-chip normalization method using genetic optimization algorithm, which depends only on a small number of housekeeping genes, and therefore facilitates experimental validation without any accuracy lost.
This chapter presents a formalization of functional and behavioural requirements, and a refinement of requirements to a design for CoCoME using the Relational Calculus of Object and Component Systems (rCOS). We give a...
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In most DHTs proposed so far, all nodes are assumed to be homogeneous, and all messages are routed using a common algorithm. In practice, however, nodes in large-scale systems might be heterogeneous with respect to th...
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In most DHTs proposed so far, all nodes are assumed to be homogeneous, and all messages are routed using a common algorithm. In practice, however, nodes in large-scale systems might be heterogeneous with respect to their capabilities, reputations, affiliations of administrative domains, and so on, which consequently makes it preferable to distinguish the heterogeneity of participant nodes. To achieve this, in this paper we present grouped tapestry (GTap), a novel tapestry-based DHT that supports organizing nodes into groups and allows flexible DHT routing. The effectiveness of our proposals is demonstrated through theoretical analysis and extensive simulations.
The weapon-target assignment (WTA) problem is a fundamental problem arising in defense-related applications of operations research. The WTA problem can be formulated as a nonlinear integer programming problem and is k...
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The weapon-target assignment (WTA) problem is a fundamental problem arising in defense-related applications of operations research. The WTA problem can be formulated as a nonlinear integer programming problem and is known to be NP-complete. We present firstly a technique founded on the use weapon cell, which enables one-to-many mapping about weapon-target to become one-to-one mapping. Next, we introduce a framework of solving the WTA problem. Based on this framework, an approximation algorithm that is grounded on the rules about weapon cells and targets is proposed. Finally, the simulative results show that the proposed algorithm indeed is very efficient.
Due to the characteristics of stream applications and the insufficiency of conventional processors when running stream programs, stream processors which support data-level parallelism become the research hotspot. This...
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Due to the characteristics of stream applications and the insufficiency of conventional processors when running stream programs, stream processors which support data-level parallelism become the research hotspot. This paper presents two means, stream partition (SP) and stream compression (SC), to optimize streams on Imagine. The results of simulation show that SP and SC can make stream applications take full advantage of the parallel clusters, pipelines and three-level memory hierarchy of the Imagine processor, and then reduce the execution time of stream programs.
Searching in large-scale unstructured peer-to-peer networks is challenging due to the lack of effective hint information to guide queries. In this paper, we propose POP, a Parallel, cOllaborative and Probabilistic sea...
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Searching in large-scale unstructured peer-to-peer networks is challenging due to the lack of effective hint information to guide queries. In this paper, we propose POP, a Parallel, collaborative and Probabilistic sea...
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Searching in large-scale unstructured peer-to-peer networks is challenging due to the lack of effective hint information to guide queries. In this paper, we propose POP, a Parallel, collaborative and Probabilistic search mechanism, in which query messages are viewed as search units to collaborate with each other and aggregate the distributed hints during the search process. A scheme called distributed Bloom filter (DBF) is presented to propagate the hints with a bandwidth-aware manner, in which a node divides the received Bloom filter vector into subvectors and disseminates the fragments to its neighbors according to their bandwidth capacity. The effectiveness of POP is demonstrated through theoretical analysis and extensive simulations.
As an innovative distributed computing technique for sharing the memory resources in high-speed network, RAM Grid exploits the distributed free nodes, and provides remote memory for the nodes which are short of memory...
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As an innovative distributed computing technique for sharing the memory resources in high-speed network, RAM Grid exploits the distributed free nodes, and provides remote memory for the nodes which are short of memory. One of the RAM Grid systems named DRACO, tries to provide cooperative caching to improve the performance of the user node which has mass disk I/O but lacks local memory. However, the performance of DRACO is constrained with the network communication cost. In order to hide the latency of remote memory access and improve the caching performance, we proposed using push- based prefetching to enable the caching providers to push the potential useful memory pages to the user nodes. Specifically, for each caching provider, it employs sequential pattern mining techniques, which adapts to the characteristics of memory page access sequences, on locating useful memory pages for prefetching. We have verified the effectiveness of the proposed method through system analysis and trace-driven simulations.
With the never-ending growth of the complexity of modern hardware and software systems, more and more sophisticated methods of verification are required. Model checking has been proved to be an effective approach to g...
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With the never-ending growth of the complexity of modern hardware and software systems, more and more sophisticated methods of verification are required. Model checking has been proved to be an effective approach to guaranteeing the correctness of design and implementation of software and hardware system. Model and temporal logics are used as specification languages in software and hardware verification. Modal μ-calculus is an extremely popular and important one among these logics. It is succinct in syntax and powerful in expressiveness. Since Kozen's paper on modal μ-calculus, it has received ever growing interest in both theoretical and application aspects. Based on the focus game theory, Lange and Stirling proposed the axiom systems for LTL and CTL. This paper extends that idea to that for modal μ-calculus. A game-theoretic approach is presented to test the satisfiability of modal μ-calculus formulas. In addition, this approach converts the satisfiability problem for μ-calculus into a solving problem for focus games. Consequently, based on these game rules, an axiom system for μ-calculus is developed, and the completeness of this deductive system can be proved via the game based satisfiability testing procedure. By comparison, this axiom system is much more intuitive and succinct than the existing μ-calculus axiom systems.
Data replication introduces well-known consistency issues. This paper puts forward the question about data dependence in data consistency, which embodies pseudo-conflict updates and update dependency. According to tha...
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