A principal problem of any internet user is the increasing number of spam, which became a great problem today. Therefore, spam filtering has become a research fo-cus that attracts the attention of several security researchers and practitioners. Spam filtering can be viewed as a two-class classification problem. To this end, this paper proposes a spam filtering approach based on Possibilistic c-Means (PCM) algorithm and weighted distance coined as (WFCM) that can efficiently distinguish between spam and legitimate email messages. The objective of the formulated fuzzy problem is to construct two fuzzy clusters: spam and email clusters. The weight assignment is set by information gain algorithm. Experimental results on spam based benchmark

This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima

Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to enhance efficiency and maximize the output power of PV module, regardless the variation of temperature, irradiation, and the electrical characteristics of the load. A new MPPT system has been presented in this research, consisting of a synchronous DC-DC step-down Buck converter controlled by an Arduino microcontroller based unit. The MPPT process with Perturb and Observe method is performed with a DC-DC converter circuit to overcome the problem of voltage mismatch between the PV modules and the loads. The proposing system has high efficiency, lower cost and can be easily modified to handle more energy sources. The test results indicate that the u

Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

This paper presents a proposed neural network algorithm to solve the shortest path problem (SPP) for communication routing. The solution extends the traditional recurrent Hopfield architecture introducing the optimal routing for any request by choosing single and multi link path node-to-node traffic to minimize the loss. This suggested neural network algorithm implemented by using 20-nodes network example. The result shows that a clear convergence can be achieved by 95% valid convergence (about 361 optimal routes from 380-pairs). Additionally computation performance is also mentioned at the expense of slightly worse results.

لقد لاقت مواضيع استعمال التحليل الاحصاء المالي رواجاً كبيراً في الآونة الأخيرة سواء على مستوى الافراد والشركات العامة والخاصة مروراً بأسواق الاسهم والاوراق المالية (البورصات) وصولاً الى اقتصاديات الدول والبلدان. وذلك بعد وصول الباحثين والدارسين للظواهر الاقتصادية والمالية بكل أنماطها الى إدراك أهمية التحليل الكميّ عموماً والتحليل الاحصائي على وجه الخصوص، مما دفعنا لتأليف الطبعة الأولى من هذا الكتاب بالع

    This research includes the use of an artificial intelligence algorithm, which is one of the algorithms of biological systems which is the algorithm of genetic regulatory networks (GRNs), which is a dynamic system for a group of variables representing space within time. To construct this biological system, we use (ODEs) and to analyze the stationarity of the model we use Euler's method. And through the factors that affect the process of gene expression in terms of inhibition and activation of the transcription process on DNA, we will use TF transcription factors. The current research aims to use the latest methods of the artificial intelligence algorithm. To apply Gene Regulation Networks (GRNs), we used a progr

Background: Respiratory distress is one of interesting presentation of elective caesarean delivery, the presence of labor before elective caesarean delivery decrease the risk of Respiratory distress. adverse respiratory problem in neonate delivered before 39 weeks of gestation are increased.
Objective: To evaluate the association between gestational age at delivery and neonatal respiratory outcomes after elective caesarean delivery between 37 and 41completed weeks.
Patients and Methods: Descriptive study with prospectively collected data from Baghdad teaching hospital/Medical city at neonatal care unit. All infants of gestational age from 37 to 41 completed weeks, with uncomplicate

The present study aimed to demonstrate the extent to which the activity of a number of enzymes and genetic variation of β-globin genes were affected in the blood of 65 children with β - thalassemia major of both sexes. The patients, with an age range of 2 – 15 years, were registered in the Thalassemia Center at Ibn Al-Atheer Teaching Hospital for Children in the city of Mosul / Iraq. They were under continuous treatment after being diagnosed by specialist doctors. The study also involved 30 healthy children of both sexes with the same age range who were considered as a control group.

       The results showed significant increases (p≤0.05) in the activities of alanine transaminase (ALT), aspart

  Immuno-haematological genetic markers study was carried out to understand the genetic background variations among Kirkuk (Iraq) indigenous population. A cross-sectional study of 179 patients with thalassemia major was conducted in Kirkuk. A detailed review was undertaken to define the relationships between ethnic origins, phenotype and immuno-genetic markers uniformity in relation to genetic isolation and interethnic admixture. A total of 179 thalassemia major patients were subjected to analysis in the hereditary blood diseases centre, including (18(10.05 %)) of intermarriages between different ethnic groups origin, whereas the overall consanguinity marriage rate was estimated at (161 (89.9%)) including (63(35.1%)) for first cousi