Journal of Advances in Computer Engineering and Technology
Volume:3 Issue: 3, Summer 2017

Telecommunication companies have received a great deal of research attention, which have many advantages such as low cost, higher qualification, simple installation and maintenance, and high reliability. However, the using of technical maintenance approaches in Telecommunication companies could improve system reliability and users' satisfaction from Asymmetric digital subscriber line (ADSL) services. In ADSL systems, there are many variables giving some noise for classification and there are many fault patterns with overlapping data. Therefore, this paper proposes a multilayer perceptron (MLP) classifier integrated with Self Organization Map (SOM) models for fault detection and diagnosis (FDD) of occurred ADSL systems. The interest of this paper is to improve the performance of single MLP by dividing the fault pattern space into a few smaller sub-spaces using SOM clustering technique and triggering the right local classifier by designing a supervisor agent. The performances of this method are evaluated on the fault data of Iranian Telecommunication Company which develop ADSL services and then the proposed algorithm is also compared against single MLP. Finally, the results obtained by this algorithm are analyzed to increase user's satisfaction with reducing occurred faults for them with predicting before they face it.

The cloud computing is considered as a computational model which provides the uses requests with resources upon any demand and needs.The need for planning the scheduling of the user's jobs has emerged as an important challenge in the field of cloud computing. It is mainly due to several reasons, including ever-increasing advancements of information technology and an increase of applications and user needs for these applications with high quality, as well as, the popularity of cloud computing among user and rapidly growth of them during recent years. This research presents the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an evolutionary algorithm in the field of optimization for tasks scheduling in the cloud computing environment. The findings indicate that presented algorithm, led to a reduction in execution time of all tasks, compared to SPT, LPT, and RLPT algorithms.Keywords: Cloud Computing, Task Scheduling, Virtual Machines (VMs), Covariance Matrix Adaptation Evolution Strategy (CMA-ES)

his study aims to offer a model of propensity toward indebtedness using behavioral factors from 384 indebted customers of Maskan bank in Tehran. A questionnaire comprising 41 questions was administered. The questionnaire addressed demographic variables and seven behavioral factors: financial literacy, risk perception, risk behavior, emotion, materialism, indebtedness, and money-related values. The hypothesis test of Path Analysis used in this study shows that all of the offered hypothesis were accepted.Results show that financial literacy, risk behavior, money value and materialism have positive impact on propensity toward indebtedness. Risk perception has a negative impact on propensity toward indebtedness that means by increasing of risk perception propensity toward indebtedness decreases. The relationship between negative emotions caused by indebtedness have negative impact on risk perception but positive impact on risk behavioral. Money values has positive impact on materialism and finally, indebtedness shows negative impact on emotions. This means that increasing in debt levels will results in increasing negative emotions. The tests don’t reveal a significant difference in the level of debt according to demographic factors including gender, age, education, occupation and income.

The systems in which information and communication technologies and systems engineering concepts are utilized to develop and improve transportation systems of all kinds are called “The Intelligent Transportation Systems (ITS)”. ITS integrates information, communications, computers and other technologies and uses them in the field of transportation to build an integrated system of people, roads and vehicles by utilizing advanced data communication technologies. Vehicular Ad-hoc Networks which is a subset of Mobile Ad-hoc Networks, provide Vehicle to Vehicle (V2V), Vehicle to Roadside (V2R) and Vehicle to Infrastructure (V2I) communications and plays an important role in Intelligent Transportation System. Due to special characteristics of VANETs, QoS (Quality of Service) provisioning in these networks is a challenging task. QoS is the capability of a network for providing superior service to a selected network traffic over various heterogeneous technologies. In this paper we present an overview of Vehicular Networks, QoS Concepts, QoS challenges in VANETs and approaches which aim to enhance the Quality of Service in Vehicular Networks

The purpose of the present paper is that of researching the impact of corporate governance on financial performance, on a sample of 3 companies (Tamin Petroleum & Petrochemical Investment Co., Persian Gulf Petrochemical Industries Company and Parsian Oil and Gas Development Group), mainly from the chemical industry area, listed at Tehran Stock Exchange index, during the period 2011-2016. In this study the return on assets (ROA) is the proxy of financial performance. As variables for the corporate governance there have been considered: the characteristics of the board of directors (independence, salary, size, tenure, age and Risk Committees); firm size; the shareholder structure (the shares of institutional investors); the characteristics of CEO (duality) . The estimation techniques used in the empirical analysis have been multivariate regression models based on the method of econometric data based on the relationship between independent and dependent variables using software Eviews8. The results show that the percentage of institutional investors, the salary Board of Directors, the Risk Committee of the Board of Directors and the Board of Directors size have a positive and significant effect on the financial performance of companies listed on Tehran Stock Exchange chemicals industry.

The issue of management and allocation of resources in cloud computing environments, according to the breadth of scale and modern technology implementation, is a complicated issue. Issues such as: the heterogeneity of resources, resource dependencies to each other, the dynamics of the environment, virtualization, workload diversity as well as a wide range of management objectives of cloud service providers to provide services in this environment. In this paper, first, the description of cloud computing environment and related issues have been reported. According to the performed studies, challenges such as: the absence of a comprehensive management for resources in the cloud environment, the method of predicting the resource allocation process, optimum resource allocation methods to reduce energy consumption and reducing the time to access resources and also implementation of dynamic resources allocation methods in the mobile cloud environments, have been addressed. Finally, with regard to the challenges, some recommendations to improve the process of allocation of resources in a cloud computing environment is has been proposed.