Esophageal adenocarcinoma (EA) is increasing faster than any other cancer in the U.S. In this report, we first show that EA can be distinguished from normal esophagus (NE) and esophageal squamous cell carcinoma by plotting expression values for EpCam, TFF1, and SBEM in three-dimensional Euclidean space. For monitoring progression of Barrett's esophagus (BE) to EA, we developed a highly sensitiv...

This paper presents the results of an experimental investigation on solving graph coloring problems with Evolutionary Algorithms (EAs). After testing different algorithm variants we conclude that the best option is an asexual EA using order-based representation and an adaptation mechanism that periodically changes the fitness function during the evolution. This adaptive EA is general, using no ...

Electromagnetism-like Mechanism (EM) heuristic is a population-based stochastic global optimization method inspired by the attraction-repulsion mechanism of the electromagnetism theory. EM was originally proposed for solving continuous global optimization problems with bound constraints and it has been shown that the algorithm performs quite well compared to some other global optimization metho...

This work explores different evolutionary approaches to Protein Structure Prediction (PSP), a highly constrained problem. These are the utilization of a repair procedure, and the use of evolutionary operators whose functioning is closed in feasible space. Both approaches rely on hybridizing the evolutionary algorithm (EA) with a backtracking algorithm. The so-obtained hybrid EAs are described, ...

This paper illustrates the application of evolutionary algorithms (EA) to data mining problems. The objectives are to demonstrate that EA can provide a competitive general purpose data mining scheme for classification tasks without constraining the knowledge representation, and that it can be achieved reducing the amount of time required using the inherent parallel processing nature of EA. Expe...

An Evolutionary Algorithm (EA) strategy for the optimization of generic Work-In-Process (WIP) scheduling fuzzy controllers is presented. The EA is used to tune a set of fuzzy control modules which are used for distributed and supervisory WIP scheduling. The distributed controllers objective is to control the rate in each production stage so that satisfies the demand for final products while red...

Recently, the use of artificial intelligence based data mining techniques for massive medical data classification and diagnosis has gained its popularity, whereas the effectiveness and efficiency by feature selection is worthy to further investigate. In this paper, we presents a novel method for feature selection with the use of opposite sign test (OST) as a local search for the electromagnetis...

Recently, medical data mining has become one of the most popular topics in the data mining community. This is due to the societal importance of the field and also the particular computational challenges posed in this domain of data mining. Early researches concentrated on sequential heuristics and later moved to meta-heuristic approaches due to the ability of these approaches to generate better...

Many problems in scientific research and engineering applications can be decomposed into the constrained optimization problems. Most of them are the nonlinear programming problems which are very hard to be solved by the traditional methods. In this paper, an electromagnetism-like mechanism (EM) algorithm, which is a meta-heuristic algorithm, has been improved for these problems. Firstly, some m...