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- Y Takefuji, K C Lee
- Science
- 1989

A near-optimum parallel planarization algorithm is presented. The planarization algorithm, which is designed to embed a graph on a plane, uses a large number of simple processing elements called neurons. The proposed system, composed of an N x N neural network array (where N is the number of vertices), not only generates a near-maximal planar subgraph from… (More)

The authors propose the first parallel improvement algorithm using the maximum neural network model for the bipartite subgraph problem. The goal of this NP-complete problem is to remove the minimum number of edges in a given graph such that the remaining graph is a bipartite graph. A large number of instances have been simulated to verify the proposed… (More)

Multi-layer channel routing is one of cumbersome jobs in automatic layout design of VLSI chips and PCBs. As VLSI chips have been used in every field of electrical engineering , it becomes more important to reduce the layout design time. With the advancement of the VLSI technology, four-layer problems can be treated and the algorithms for more than… (More)

The application of the Hopfield neural network for the multispectral unsupervised classification of MR images is reported. Winner-take-all neurons were used to obtain a crisp classification map using proton density-weighted and T(2)-weighted images in the head. The preliminary studies indicate that the number of iterations needed to reach ;good' solutions… (More)

A parallel algorithm for finding a near-maximum independent set in a circle graph is presented. An independent set in a graph is a set of vertices, no two of which are adjacent. A maximum independent set is an independent set whose cardinality is the largest among all independent sets of a graph. The algorithm is modified for predicting the secondary… (More)

A variety of tools and architectures have been developed to detect security violations to Operating System kernels. However, they all have fundamental flaw in the design so that they fail to discover kernel-level attack. Few hardware solutions have been proposed to address the outstanding problem, but unfortunately they are not widely accepted. This paper… (More)

We present a novel approach for detecting, classifying, and linking entities from Twitter posts (tweets). The task is challenging because of the noisy, short, and informal nature of tweets. Consequently, the proposed approach introduces several methods that robustly facilitate successful realization of the task with enhanced performance in several measures .

Fuzzy inference engines based on the existing fuzzy theory are inadequate to perform reliable decision making. Besides requiring the fuzzy sets and data to be normalized, the inference engine is also sensitive to noise in observational data. Inaccurate conclusions are produced if noise is present and also when the fuzzy sets are not normalized. In this… (More)