Abstract

          Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s

         This study involves the design of 24 mixtures of fiber reinforced magnetic reactive powder concrete containing nano silica. Tap water was used for 12 of these mixtures, while magnetic water was used for the others. The nano silica (NS) with ratios (1, 1.5, 2, 2.5 and 3) % by weight of cement, were used for all the mixtures. The results have shown that the mixture containing 2.5% NS gives the highest compressive strength at age 7 days. Many different other tests were carried out, the results have shown that the carbon fiber reinforced magnetic reactive powder concrete containing 2.5% NS (CFRMRPCCNS) had higher compressive strength, modulus of rupture, splitting tension, str

Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

Previously many properties of graphene oxide in the field of medicine, biological environment and in the field of energy have been studied. This diversity in properties is due to the possibility of modification on the composition of this Nano compound, where the Graphene oxide is capable of more modification via addition other functional groups on its surface or at the edges of the sheet. The reason for this modification possibility is that the Sp3 hybridization (tetrahedral structure) of the carbon atoms in graphene oxide, and it contains many oxygenic functional groups that are able to reac with other groups. In this research the effect of addition of some amine compounds on electrical properties of graphene oxide has been studied by the

The research aims to identify the academic problems of family counseling diploma students at Saudi Universities. In addition, to identify the differences in these problems according to gender, marital status, place of study, academic specialization, and GPA. The sample consisted of (491) students. The researcher has used one questionnaire for academic problems prepared by the researcher.  The research revealed the following results: There were academic problems among family counseling diploma students at Saudi Universities, the most problems were related to the systems and administrations of the university, then the field training, the buildings, classrooms and campus facilities, then the academic courses, after that the exams, then

Due to economic reasons or need for environmental conservatism or also preserve the natural resources; there has been an increasing shift towards the use of reclaimed asphalt pavement (RAP) materials in the pavement construction industry. Therefore, use the Reclaimed Asphalt Pavement (RAP) has been enormously increased in pavement construction and has been become common practice in many countries. Nevertheless, this is a relatively new concept in Iraq, and has to be remarked that is not used RAP in the production of HMA and this valuable material is mostly degraded. For this purpose, the reclaimed materials were collected from deteriorated pavement segments. The components of asphalt mixtures consist of: two asphalt penetration grades (40-5

Enhancing fatigue resistance in asphalt binders and mixtures is crucial for prolonging pavement lifespan and improving road performance. Recent advancements in nanotechnology have introduced various nanomaterials such as alumina (NA), carbon nanotubes (CNTs), and silica (NS) as potential asphalt modifiers. These materials possess unique properties that address challenges related to asphalt fatigue. However, their effectiveness depends on proper dispersion and mixing techniques. This review examines the mixing methods used for each nanomaterial to ensure uniform distribution within the asphalt matrix and maximize performance benefits. Recent research findings are synthesized to elucidate how these nanomaterials and their mixing proce

This survey investigates the thermal evaporation of Ag2Se on glass substrates at various thermal annealing temperatures (300, 348, 398, and 448) °K. To ascertain the effect of annealing temperature on the structural, surface morphology, and optical properties of Ag2Se films, investigations and research were carried out. The crystal structure of the film was described by Xray diffraction and other methods.The physical structure and characteristics of the Ag2Se thin films were examined using X-ray and atomic force microscopy (AFM) based techniques. The Ag2Se films surface morphology was examined by AFM techniques; the investigation gave average diameter, surface roughness, and grain size mutation values with increasing annealing temperature

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne