Neural network diagnosis of malignant melanoma from color images

Malignant melanoma is the deadliest form of all skin cancers. Approximately 32,000 new cases of malignant melanoma were diagnosed in 1991 in the United States, with approximately 80% of patients expected to survive 5 years. Fortunately, if detected early, even malignant melanoma may be treated successfully, Thus, in recent years, there has been rising interest in the automated detection and diagnosis of skin cancer, particularly malignant melanoma. Here, the authors present a novel neural network approach for the automated separation of melanoma from 3 benign categories of tumors which exhibit melanoma-like characteristics. The approach uses discriminant features, based on tumor shape and relative tumor color, that are supplied to an artificial neural network for classification of tumor images as malignant or benign. With this approach, for reasonably balanced training/testing sets, the authors are able to obtain above 80% correct classification of the malignant and benign tumors on real skin tumor images     

Copper removal from aqueous solutions by sugar beet pulp treated by NaOH and citric acid

Sugar beet pulp was converted into effective copper sorption material by treating subsequently with NaOH and citric acid. Compared with the untreated sugar beet pulp, the cation exchange capacity of the modified sugar beet pulp increased from 0.86 to 3.21 mequiv.g(-1). Swelling capacity and COD values of modified sugar beet pulp were found to be decreased in the ratio of 38% and 61%, respectively, compared to the corresponding values of native sugar beet pulp, meaning that modification causes stabilization. Sorption characteristics of the modified sugar beet pulp towards copper ions were studied with batch experiments. Pseudo-first, pseudo-second-order and intraparticle kinetic models were applied to the kinetic data and it was found that the sorption processes followed the pseudo-second-order rate kinetics with activation energy of 16.34 kJ mol(-1). The equilibration data fit best with the Langmuir isotherm the maximum copper sorption capacity of which is 119.43 mgg(-1). The mean free energy of copper sorption process calculated from Dubinin-Radushkevich model and the Polanyi potential concept was found to be in the range of 10.91-11.95 kJ mol(-1) showing that the main mechanism governing the sorption process is ion exchange. The negative values found for enthalpy change (-14.797 kJ mol(-1) over the range of 25-55 degrees C) and free energy change (-19.361 kJ mol(-1) for 25 degrees C) indicate that the sorption process is exothermic and spontaneous in nature.     

A Genetic Algorithm for Hybrid Flow-shop Scheduling with Multiprocessor Tasks

The hybrid flow-shop scheduling problem with multiprocessor tasks finds its applications in real-time machine-vision systems among others. Motivated by this application and the computational complexity of the problem, we propose a genetic algorithm in this paper. We first describe the implementation details, which include a new crossover operator. We then perform a preliminary test to set the best values of the control parameters, namely the population size, crossover rate and mutation rate. Next, given these values, we carry out an extensive computational experiment to evaluate the performance of four versions of the proposed genetic algorithm in terms of the percentage deviation of the solution from the lower bound value. The results of the experiments demonstrate that the genetic algorithm performs the best when the new crossover operator is used along with the insertion mutation. This genetic algorithm also outperforms the tabu search algorithm proposed in the literature for the same problem.