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A new associative classification algorithm based on weighted voting (ACWV) is presented. ACWV takes advantage of two methods: the optimal rule method preferring high-quality rules and the voting method considering the majority of the rules. Moreover, the method takes into account both the length and convictions of rules to calculate their weights. First, ACWV builds a class-count FP-tree (called CCFP-tree) from the given historical data. After that, the weighted voting result for a new...

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The Java virtual machine embodies a verifier that performs a set of checks on Java bytecode programs before their execution. The verifier carries out an efficient data-flow analysis applied to a type-level abstract interpretation of the code. The implementations of the bytecode verifier presented a significant problem with programs compiled with the Sun Java compiler (until version 1.4.1): there were legal Java programs which were correctly compiled into a bytecode that was rejected by the...

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Consistent with the divide-and-conquer approach to problem solving, a recursive result is presented in the domain of stochastic modelling that derives product-form solutions for the steady state probabilities of certain networks composed from interacting Markov chains. Practical applications include multi-tasking operating systems, communication channels and multi-tiered storage systems. The approach is also applied to the computation of response time quantiles, which are vital in...

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The hierarchical radiosity algorithm provides high-quality illumination and the view-independent results obtained can be re-employed for different camera positions. On the other hand, the utilization of multiresolution models is a common solution for the real-time rendering of complex scenes. In this case, the level of detail of each object depends on the specific camera position. Unfortunately, global illumination computations may present an important performance loss in this context. In...

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This work describes a parallel implementation of a distinctly different concept in self-organizing maps (SOMs)—processing of the input as a whole, in parallel, via neurons attracted to cover regions of the input space rather than single input instances. The algorithm is analyzed from the perspective of its parallelism and a simple multi-machine concept is utilized to demonstrate the parallel nature of the neural network architecture. The nature of the classic SOM (Ozdzynski, P., Lin, A.,...

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