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.
Charge transfer complex formation method has been applied for the spectrophotometric determination of cimetidine, in bulk sample and dosage form. The method was accurate, simple, rapid, inexpensive and sensitive depending on the formed charge- transfer complex between cited drug and, 2,3-Dichloro-5,6-dicyano-p- benzoquinone (DDQ) as a chromogenic reagent. The formed complex shows absorbance maxima at 587 nm against reagent blank. The calibration graph is linear in the ranges of (5.0 - 50.0) µg.mL-1 with detection limit of 0.268µg.mL-1. The results show the absence of interferences from the excipients on the determination of the drug. Therefore the proposed method has been successfully applied for the determination of cimetid
... Show More
(34)
(28)
This paper is summarized with one of the applications of adsorption behavior; A UV-Vis method has been applied to survey the isotherm of adsorption. Results for experimental showed the applicability of Langmuir equation. The effect of temperature on the adsorption of cobalt (II) Complex by bentonite surface was studied. The results shown that the amount of adsorption was formed to increase, such as the temperature increase (Endothermic process). Cobalt (II) Complex has adsorption studies by bentonite surface at different pH values (1.6-10); these studies displayed an increase in adsorption with increasing pH. ΔG, ΔH, and ΔS thermodynamic functions of the cobalt (II) Complex for their adsorption have been calculated.
(3)
(3)
Benthic invertebrates diversity on the Al-Dalmage the Lake in the middle of Iraq, in addition to the some chemical properties was the aim of the present study, for a period from January to the December 2013. Six stations of the lake were chosen for monthly samples collection. The result revealed that the water temperature ranged from (9-34) ◦C. According to the values of salinity (1.5-14.6) ‰ the lake was classified as Brackish, while the pH values were neutral tends to near alkaline and ranged from (7.2- 9). The study showed that the lake were well oxygenated due to the dissolved oxygen values which ranged from 7-12 mg/l. The lake considered as very hard according to the total hardness values which range from (825-6980) CaCo3 mg/l.
... Show More
(6)
(6)
Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable
... Show More
(2)
In this paper, we design a fuzzy neural network to solve fuzzy singularly perturbed Volterra integro-differential equation by using a High Performance Training Algorithm such as the Levenberge-Marqaurdt (TrianLM) and the sigmoid function of the hidden units which is the hyperbolic tangent activation function. A fuzzy trial solution to fuzzy singularly perturbed Volterra integro-differential equation is written as a sum of two components. The first component meets the fuzzy requirements, however, it does not have any fuzzy adjustable parameters. The second component is a feed-forward fuzzy neural network with fuzzy adjustable parameters. The proposed method is compared with the analytical solutions. We find that the proposed meth
... Show More
Analysis of image content is important in the classification of images, identification, retrieval, and recognition processes. The medical image datasets for content-based medical image retrieval ( are large datasets that are limited by high computational costs and poor performance. The aim of the proposed method is to enhance this image retrieval and classification by using a genetic algorithm (GA) to choose the reduced features and dimensionality. This process was created in three stages. In the first stage, two algorithms are applied to extract the important features; the first algorithm is the Contrast Enhancement method and the second is a Discrete Cosine Transform algorithm. In the next stage, we used datasets of the medi
... Show More
(3)
(1)
(58)
(40)
Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse dete
... Show More