Some wafer fabrication processes are repeated processes, e.g. atomic layer deposition (ALD) process. For such processes, the wafers need to visit some processing modules for a number of times, which complicates the cy...
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Some wafer fabrication processes are repeated processes, e.g. atomic layer deposition (ALD) process. For such processes, the wafers need to visit some processing modules for a number of times, which complicates the cycle time analysis. This paper studies the cycle time analysis problem for such processes. With a Petri net model, it is found that such processes contain local cycles involving only the revisiting PMs and global cycles involving both revisiting and non-revisiting PMs. The process switches between these two types of cycles such that the process never reaches a steady state. Based on this finding, the mechanism underlying such processes is revealed and analytical expressions are given for the calculation of their cycle time. Illustrative examples are presented to show the application of the proposed approach.
In mathematics, various representations of real numbers have been investigated and all these representations are proved to be mathematically equivalent. Furthermore, it is known that all effective versions of these re...
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Rough set theory, proposed by Pawlak, has been proved to be a mathematical tool to deal with vagueness and uncertainty in intelligent information processing. In this paper, we propose the concept of knowledge granulat...
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Statistical background subtraction has proved to be a robust and effective approach for segmenting and extracting objects without any prior information of the foreground objects. This paper presents two contributions ...
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We study the general scaling laws of the capacity for random wireless networks under the generalized physical model. The generality of this work is embodied in three dimensions denoted by (λ ∈ [1, n], n d ∈ [1, n]...
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We study the general scaling laws of the capacity for random wireless networks under the generalized physical model. The generality of this work is embodied in three dimensions denoted by (λ ∈ [1, n], n d ∈ [1, n], n s ∈ (1, n]). It means that: (1) We study the random network of a general node density λ ∈ [1, n], rather than only study either random dense network (RDN, λ = n) or random extended network (REN, λ = 1) as in the literature. (2) We focus on the multicast capacity to unify unicast and broadcast capacities by setting the number of destinations for each session as a general value n d ∈ [1, n]. (3)We allow the number of sessions changing in the range n s ∈ (1, n], rather than assume that n s = Θ(n) as in the *** derive the general lower bounds on the capacity for the arbitrary case of (λ, n d , n s ). Particularly, we show that for the special cases (λ = 1, n d ∈ [1, n], n s = n) and (λ = n, n d ∈ [1, n], n s = n), our schemes achieve the highest multicast throughputs proposed in the existing works.
Interaction testing has addressed some issues on how to select a small subset of test cases. In many systems where interaction testing is needed, the entire test suite is not executed because of time or budget constra...
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For the purpose of reducing energy consumption and increasing spatial reuse, relay node deployment strategies have been studied widely in wireless network planning. In this paper, we propose a new deploy strategy when...
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In this paper, we proposed a novel network coding method called local-directed network coding to improve the throughput of the vehicular ad-hoc network. Different from other vehicular network coding methods, we consid...
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Web services composition (WSC) is the key techniques in its application. Dynamically selecting reliable Web services (WSs) becomes crucial to users. In fact, most works regard a Web service (WS) as the basic unit and ...
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To solve the problem of infeasible solutions in the constrained function optimization, a constraint-handling technique based on simulated annealing is proposed. The improved particle swarm optimization is also used to...
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To solve the problem of infeasible solutions in the constrained function optimization, a constraint-handling technique based on simulated annealing is proposed. The improved particle swarm optimization is also used to verify the effectiveness of this technique. The experimental results show that the proposed algorithm is suitable for solving such problems.
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