Mohamed Elhoseny

Bio: Mohamed Elhoseny is an academic researcher from Mansoura University. The author has contributed to research in topics: Computer science & Encryption. The author has an hindex of 49, co-authored 240 publications receiving 7044 citations. Previous affiliations of Mohamed Elhoseny include Maharaja Agrasen Institute of Technology & Cairo University.

Extending self-organizing network availability using genetic algorithm

Abstract: In this paper, we propose a novel method based on genetic algorithm for constructing the wireless sensor network to extend its functionality and availability. In our proposed method, the structure of the network is dynamically decided and the organization differs after each message transmission round. With the goal of optimizing the lifespan of the entire network, genetic algorithm is employed to search for the most suitable sensor nodes as the cluster heads to relay the messages to base station. Using the chosen cluster heads, sensor clusters are formed that minimize the total inner cluster node-to-cluster head distance. Compared with eight other methods, our experimental results demonstrated that our proposed method greatly extended the network life. The network life improvement rate with respect to the second best cases is in the range of 13% to 43.44%. In each transmission round, the remaining energy of sensor nodes are fairly even with some fluctuations. That is, as a consequence of our proposed method, the variance among remaining energy is quite low, which implies that the sensor nodes shared the burden of relaying messages and, hence, elongated the overall network life.

Social-spider optimization algorithm for improving ANFIS to predict biochar yield

Abstract: The production of renewable and sustainable energy has more attention because the traditional energy sources such as fossil fuel are decreasing dramatically. The prediction of biochar yield from manure pyrolysis is considered as one type of renewable energy that used to produce energy. However, the experimental methods that used to produce energy from biochar yield are time-consuming and expensive, therefore, computational methods are applied to solve this problem. There are many methods applied to predict the biochar like least square-support vector machine (LS-SVM) and neural network. However, these methods can get stuck in local point and time complexity. To avoid these drawbacks, this paper works to improve the Adaptive Neuro-Fuzzy Inference System (ANFIS) using Social-Spider Optimization algorithm to predict biochar yield. The results of the proposed method are compared to classic ANFIS, artificial bee colony, particle swarm optimization, and LS-SVM. The results of ANFIS-SSO approach outperformed the standard ANFIS and they are better than other approaches.

Loan portfolio optimization using Genetic Algorithm: A case of credit constraints

Abstract: With the increasing impact of capital regulation on banks financial decisions especially in competing environment with credit constraints, it comes the urge to set an optimal mechanism of bank lending decisions that will maximize the bank profit in a timely manner. In this context, we propose a self-organizing method for dynamically organizing bank lending decision using Genetic Algorithm (GA). Our proposed GA based model provides a framework to optimize bank objective when constructing the loan portfolio, which maximize the bank profit and minimize the probability of bank default in a search for an optimal, dynamic lending decision. Multiple factors related to loan characteristics, creditor ratings are integrated to GA chromosomes and validation is performed to ensure the optimal decision. GA uses random search to suggest the best appropriate design. We use this algorithm in order to obtain the most efficient lending decision. The reason for choosing GA is its convergence and its flexibility in solving multi-objective optimization problems such as credit assessment, portfolio optimization and bank lending decision.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Abstract: From the Publisher: The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Guidelines for the management of adults with hospital-acquired, ventilator-associated, and healthcare-associated pneumonia the official statement of the American Thoracic Society and the Infectious Disease Society of America (特集 救急診療ガイドライン) -- (海外のガイドライン)

Abstract: Executive Summary Introduction Methodology Used to Prepare the Guideline Epidemiology Incidence Etiology Major Epidemiologic Points Pathogenesis Major Points for Pathogenesis Modifiable Risk Factors Intubation and Mechanical Ventilation Aspiration, Body Position, and Enteral Feeding Modulation of Colonization: Oral Antiseptics and Antibiotics Stress Bleeding Prophylaxis, Transfusion, and Glucose Control Major Points and Recommendations for Modifiable Risk Factors Diagnostic Testing Major Points and Recommendations for Diagnosis Diagnostic Strategies and Approaches Clinical Strategy Bacteriologic Strategy Recommended Diagnostic Strategy Major Points and Recommendations for Comparing Diagnostic Strategies Antibiotic Treatment of Hospital-acquired Pneumonia General Approach Initial Empiric Antibiotic Therapy Appropriate Antibiotic Selection and Adequate Dosing Local Instillation and Aerosolized Antibiotics Combination versus Monotherapy Duration of Therapy Major Points and Recommendations for Optimal Antibiotic Therapy Specific Antibiotic Regimens Antibiotic Heterogeneity and Antibiotic Cycling Response to Therapy Modification of Empiric Antibiotic Regimens Defining the Normal Pattern of Resolution Reasons for Deterioration or Nonresolution Evaluation of the Nonresponding Patient Major Points and Recommendations for Assessing Response to Therapy Suggested Performance Indicators