Abstract ABSTRACT: Machine learning aims of facilitating complex system data analysis, optimization, classification and prediction with the use of different mathematical and statistical algorithms. In this research, we are interested in establishing the process of estimating best optimal input parameters to train networks. Using WEKA, this paper implements a classifier with Back-Propagation Neural Networks and Genetic Algorithm towards efficient data classification... ABSTRACT: Machine learning aims of facilitating complex system data analysis, optimization, classification and prediction with the use of different mathematical and statistical algorithms. In this research, we are interested in establishing the process of estimating best optimal input parameters to train networks. Using WEKA, this paper implements a classifier with Back-Propagation Neural Networks and Genetic Algorithm towards efficient data classification and optimization. The implemented classifier is capable of reading and analyzing a number of population in giving datasets, and based on the identified population it estimates kinds of species in a population, hidden layers, momentum, accuracy, correct and incorrect instances. Read More Read Less

Abstract High Peak-to-Average Ratio of the transmitted signal is a major drawback of Orthogonal Frequency division multiple accesses (OFDMA). In this paper, we propose a Selected Mapping Technique, Partial Transmit Sequence and Discrete Fourier Transform Spreading Techniques to overcome the problem of high PAPR in Long term evaluation uplink transmitter. Performance enhancement of the OFDM signal uplink transmitter for Long-Term Evolution... High Peak-to-Average Ratio of the transmitted signal is a major drawback of Orthogonal Frequency division multiple accesses (OFDMA). In this paper, we propose a Selected Mapping Technique, Partial Transmit Sequence and Discrete Fourier Transform Spreading Techniques to overcome the problem of high PAPR in Long term evaluation uplink transmitter. Performance enhancement of the OFDM signal uplink transmitter for Long-Term Evolution has been observed and its Peak to average power ratio is investigated through MATLAB simulations. Read More Read Less

Abstract Enterprise Architecture (EA) Implementation Methodologies have become an important part of EA projects. Several implementation methodologies have been proposed, as a theoretical and practical approach, to facilitate and support the development of EA within an enterprise. A significant question when facing the starting of EA implementation is deciding which methodology to utilize. In order to answer this question, a framework... Enterprise Architecture (EA) Implementation Methodologies have become an important part of EA projects. Several implementation methodologies have been proposed, as a theoretical and practical approach, to facilitate and support the development of EA within an enterprise. A significant question when facing the starting of EA implementation is deciding which methodology to utilize. In order to answer this question, a framework with several criteria is applied in this paper for the comparative analysis of existing EA implementation methodologies. Five EA implementation methodologies including: EAP, TOGAF, DODAF, Gartner, and FEA are selected in order to compare with proposed framework. The results of the comparison indicate that those methodologies have not reached a sufficient maturity as whole due to lack of consideration on requirement management, maintenance, continuum, and complexities in their process. The framework has also ability for the evaluation of any kind of EA implementation methodologies. Read More Read Less