Mohamed Zaki

The objective of this paper is to present the strength of fuzzy artmap which is kind of neural networks in the medical field by improving its performance by genetic algorithm. Fuzzy ARTMAP is both much faster and incrementally stable than the other ordinary neural networks models like Multilayer Perceptron. Fuzzy artmap’s parameters have legal range of values that should be determined in the simulation. These parameters should be adjusted and tuned many times to get the best results and optimum solution in order to generate accurate classification system. As there are large ranges of parameter’s values so that lead to huge number of possible solutions. The problem is to try to find the best solution among whole possibilities in the problem search space and each point in the search space represents one feasible solution. The proposed solution to this problem is using genetic algorithms to optimize fuzzy artmap parameters and this yield to improving fuzzy artmap performance. Genetic algorithms are a part of evolutionary computing which can be used to quickly scan a vast solution set. This enhanced approached evolved fuzzy artmap will be used to generate breast cancer diagnosis system.

The university course timetabling problem (UCTP) is a combinatorial NP-complete problem that has been subject to research since the early 1960’s. Numerous solution techniques have been applied to the timetabling problem ever since. This paper aims at formulating an immune-inspired algorithm, namely the Clonal Selection Algorithm1 (CSA1) and testing its ability in solving the UCTP against the Genetic algorithm (GA). An Immune-Genetic algorithm (IGA) was also created, which combines the crossover operator borrowed from the genetic algorithm with immune-inspired concepts. Also, experimenting with the effects of changing the selection and re-selection schemes of the algorithms motivated the creation of a second
version of CSA1, that is CSA2 and three more versions of IGA: IGA1, IGA2 and IGA3. All the devised algorithms were contrasted in their performances against the GA. Enhancements were applied to the mutation operator of the formulated algorithms by introducing a ‘move factor’. As a means of improving the results attained by the algorithms, local search consisting of three variable neighborhoods was incorporated into each of them. The algorithms were tested over two problem instances, with varying complexities and the results demonstrate the effectiveness of the algorithms in solving the UCTP.

Mobile services are becoming increasingly commonplace in everyday life; however, Mobile payment (M-payment) is not among frequently used mobile services. The slowness of the diffusion of this service is the point of departure of the current research. The authors discuss why consumers are slow in adopting M-payment service and develop a proposed model that measures the customer’s attitude and intention to use this technology in Egypt. Different theories from diverse fields are reviewed to formulate the study’s conceptual framework. Empirical data were collected via an online survey for a sample of 490 students in “open education”, a type of e-distance learning. The results suggest that although the most important determinants influencing the customer’s attitude toward the service are perceived behavioral control and perceived usefulness, those influencing the intention to use it are perceived innovativeness, perceived expressiveness, facilitating condition, perceived usefulness, and social pressure. The results of the research differ from those of previous studies because of the effect of the Egyptian culture. Service providers can benefit from the results when formulating the marketing strategies to increase the usage of this service, improving mobile commerce.

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Previous studies showed that non-cycling cells have a higher multidrug resistance (MDR) expression, which may be down-regulated by proliferation induction.Triggering these cells into proliferation down-regulates high MDR expression. The aim of this study was to determine the expression of P-glycoprotein (PGP) and cell cycle parameters (cyclin D1 and Ki-67) in acute lymphoblastic leukemia (ALL) at diagnosis, and to evaluate the correlation between the expressions of each marker, and the clinical significance of such expression with response to induction chemotherapy and overall survival. A total of 78 newly diagnosed ALL patients were enrolled in our study. PGP, cyclin D1 and Ki-67 were determined by flow cytometry. PGP expression was encountered in 10/78 (12.8%) of ALL cases. Cyclin D1 and Ki-67 were expressed in 16/77 (20.6%) and 27/76 (34.6%) of ALL cases, respectively. None of the parameters were associated with response to induction chemotherapy and overall survival. Based on the current analysis, we conclude that a joint immunophenotypic evaluation of PGP and cell cycle parameters like that adopted in this study is unlikely to reveal mechanisms of multidrug resistance associated with the clinical outcome.