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Jayanti's algorithm is one of the best known abortable mutual exclusion algorithms. A randomized approach has been used to overcome an already known limitation of the algorithm while preserving its all important properties and elegance. The limitation is that the token number used to assign process identification number to new incoming processes is unbounded. We have used some suitably adapted alternative...
Probabilistic data have recently become popular in applications such as scientific and geospatial databases. For images and other spatial datasets, probabilistic values can capture the uncertainty in extent and class of the objects in the images. Relating one such dataset to another by spatial joins is an important operation for data management systems. We consider probabilistic spatial join (PSJ)...
Graphs have become popular for modeling scientific data in recent years. As a result, techniques for mining graphs are extremely important for understanding inherent data and domain characteristics. One such exploratory mining paradigm is the k-MST (minimum spanning tree over k vertices) problem that can be used to discover significant local substructures. In this paper, we present an efficient approximation...
This paper propose a model for the complexity of Boolean functions with only XOR/XNOR min-terms using back propagation neural networks (BPNNs) applied to binary decision diagrams (BDDs). The developed BPNN model (BPNNM) is obtained through the training process of experimental data using Brain Maker software package. The outcome of this model is a unique matrix for the complexity estimation over a...
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