The current study is descriptive; it focuses on studying the contemporary geopolitical problem, and sectarian differences in Caucasus. Nagorno-Karabakh is considered an important disputed region nowadays. Many parties and states participated in this dispute, especially after the conflict had developed into an open war between Armenia and Azerbaijan. Thus, the study aims to examine the causes of the conflict in this region, analyze the international positions on this conflict, and find if Armenia was able to occupy this region. The methodology adopted by the researchers is the functional approach, and the theory of power analysis that Cohen created for analyzing all strengths that drove each of the parties t

In this research, a number of the western al-Anbar clays (red iron clays, Attapulgite) were modified by treating them thermally with a temperature of 650^oC. After that, these clays reflux with sodium hydroxide 5% for 1 hour by using microwave as a power supply. The research included fractionation alqayaira crude oil the fractionation included removing the asphaltene by precipitation from the crude using a simple paraffin solvent (normal hexane) as a non-soluble substance. After that it was filtered using the ash-free filter paper 42, the dissolved part, maltinate, was taken, drying a temperature of 75^oC and weight, and to find the percentage of the two parts. Malatine was divided into three main parts (paraf

The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To

Iraq suffers from lack of water resources supply because the headwaters of the rivers located outside its borders and the influence of upstream countries on the quantities of flowing water, in addition to the increase of pressure on available water as a result of population increase and not adopting the principle of rationalization where misuse and wastage and lack of strategic vision to treat and manage water use in accordance with the economic implications fall.  This is reflected fallout on water security and subsequently on national and food security, while the issue of using water resources is development top priority in different countries in the world because of the importance of water effect on the security of indivi

     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

The seasonal behavior of the light curve for selected star SS UMI and EXDRA during outburst cycle is studied. This behavior describes maximum temperature of outburst in dwarf nova. The raw data has been mathematically modeled by fitting Gaussian function based on the full width of the half maximum and the maximum value of the Gaussian. The results of this modeling describe the value of temperature of the dwarf novae star system leading to identify the type of elements that each dwarf nova consisted of.