A network (or formally a graph) can be described by a set of nodes and a set of edges connecting these nodes. Networks model many real-world phenomena in various research domains, such as biology, engineering and sociology. Community mining is discovering the groups in a network where individuals group of membership are not explicitly given. Detecting natural divisions in such complex networks is proved to be extremely NP-hard problem that recently enjoyed a considerable interest. Among the proposed methods, the field of evolutionary algorithms (EAs) takes a remarkable interest. To this end, the aim of this paper is to present the general statement of community detection problem in social networks. Then, it visits the problem as an optimization problem where a modularity-based ( ) and normalized mutual information ( ) metrics are formulated to describe the problem. An evolutionary algorithm is then expressed in the light of its characteristic components to tackle the problem. The presentation will highlight the possible alternative that can be adopted in this study for individual representation, fitness evaluations, and crossover and mutation operators. The results point out that adopting as a fitness function carries out more correct solutions than adopting the modularity function . Moreover, the strength of mutation has a background role. When coupled with non elite selection, increasing mutation probability could results in better solutions. However, when elitism is used, increasing mutation probability could bewilder the behavior of EA.
A network (or formally a graph) can be described by a set of nodes and a set of edges connecting these nodes. Networks model many real-world phenomena in various research domains, such as biology, engineering and sociology. Community mining is discovering the groups in a network where individuals group of membership are not explicitly given. Detecting natural divisions in such complex networks is proved to be extremely NP-hard problem that recently enjoyed a considerable interest. Among the proposed methods, the field of evolutionary algorithms (EAs) takes a remarkable interest. To this end, the aim of this paper is to present the general statement of community detection problem in social networks. Then, it visits the problem as an optimization problem where a modularity-based ( ) and normalized mutual information ( ) metrics are formulated to describe the problem. An evolutionary algorithm is then expressed in the light of its characteristic components to tackle the problem. The presentation will highlight the possible alternative that can be adopted in this study for individual representation, fitness evaluations, and crossover and mutation operators. The results point out that adopting as a fitness function carries out more correct solutions than adopting the modularity function . Moreover, the strength of mutation has a background role. When coupled with non elite selection, increasing mutation probability could results in better solutions. However, when elitism is used, increasing mutation probability could bewilder the behavior of EA.
The research aims to develop alternatives to transportation at the entrance to the Educational City (University of Baghdad) during the morning and evening peaks, which result from of the traffic congestion at the entrances to the educational city (the University of Baghdad), and affects the emotional, functional, and social performance of the whole city, and leads to hotbeds of confluence and congestion at the entrances in the morning and evening peaks. This movement was measured on the ground for pedestrians and vehicles. Some criteria were adopted to determine the density of road length to the area and density of roads for the number of users and the rate of the area served by roads. The research reviews the experiences of some
... Show MoreSteganography is a useful technique that helps in securing data in communication using different data carriers like audio, video, image and text. The most popular type of steganography is image steganography. It mostly uses least significant bit (LSB) technique to hide the data but the probability of detecting the hidden data using this technique is high. RGB is a color model which uses LSB to hide the data in three color channels, where each pixel is represented by three bytes to indicate the intensity of red, green and blue in that pixel. In this paper, steganography based RGB image is proposed which depends on genetic algorithm (GA). GA is used to generate random key that represents the best ordering of secret (image/text) blocks to b
... Show MoreEmergency contraceptives (ECs) are indicated for preventing the chance of unintended pregnancy that follows unprotected sexual intercourse in cases of incorrectly used regular contraceptives and in sexual assault. It is considered a safe choice to prevent pregnancy than abortion which is considered life threating. The aim of this study was to assess knowledge, attitude, and practices (KAP) of community pharmacists towards emergency contraceptives and their association with sociodemographic variables. This study was a cross sectional study conducted between August and September 2021 on a convenient sample of community pharmacists from Iraq. The survey tool was an online, self-administered questionnaire, in English language and a paper-bas
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Purpose:To evaluate knowledge, practice and attitude of community pharmacists in Basra regarding modified release dosage forms which are widely used for many therapeutic purposes in pharmacy practice.
Methods:The current study was conducted among certified pharmacists in Basra governorate- south of Iraq. Data collection was carried out by a questionnaire.
Results:A total number of 175 community pharmacists responded to the questionnaire. The majority worked in OTC based dispensing pharmacies located in the center of the city. Most respondents missed K1 and were unable to state the difference between different types of modified products. There was a major positive agreemen
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With the increasing prevalence of breast cancer among female internationally, occupies about 25% of all cases of cancer, with a measured 1.57 million up to date cases in 2012. Breast cancer has turn a most warning to health of female in Iraq, where it is the major cause of death among women after cardiovascular diseases, with a mortality rate of 23% related cancer. Recently there is a crucial requirement to include community pharmacists in health elevation activities to support awareness and early diagnosis of cancer, specially breast cancer. The aim of this study is to assess knowledge, attitude and perceived barriers amongst Iraqi community pharmacists towards health promotion of breast cancer. This study is cross sectional research. A
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The objective of the conventional well testing technique is to evaluate well- reservoir interaction through determining the flow capacity and well potential on a short-term basis by relying on the transient pressure response methodology. The well testing analysis is a major input to the reservoir simulation model to validate the near wellbore characteristics and update the variables that are normally function of time such as skin, permeability and productivity multipliers.
Well test analysis models are normally built on analytical approaches with fundamental physical of homogenous media with line source solution. Many developments in the last decade were made to increase the resolution of transient response derivation to meet the
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Background: Tuberculosis (TB) is a major public health issue and a main cause of global morbidity and mortality. TB is the world's ninth leading cause of death despite the numerous treatment strategies for managing the disease.
Objective: To assess the traditional method (direct smear examination and culture) against real-time PCR as pulmonary and extrapulmonary tuberculosis laboratory diagnostic techniques.
Cases and methods: Samples were collected from (612) TB cases, (409) of whom were pulmonary tuberculosis (PTB) and (203) were extrapolmonary tuberculosis (EPTB). The cases were seeking care at the Specialized Chest and Respiratory Disease Center/ National Reference Laboratory for Tuberculosis (NRL) in Baghdad, during the period
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Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene
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