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.

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

Abstract                                                                                              

The methods of the Principal Components and Partial Least Squares can be regard very important methods  in the regression analysis, whe

Regression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well-  Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.

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A comparison study was made for the reaction of triruthenium carbonyl Ru3(CO)12 with azoarene ArN=NAr . This reaction was monitored in two kinds of solvents , toluene , and n- octane , which yielded new triruthenium carbonyl complex Ru3(μ3-NAr)2(CO)9 . The reactions of azoarenes ArN=NAr with Ru3(CO)12 formed the following trinuclear compound of Ru3((μ3- NAr)2(CO)9 (Ar-C6H4Br-4) in law yield . In addition , to new isomers species of mononuclear cyclometallated of Ru(BrC6H4N-NC6H4NBr-4)2(CO)2 in different percentages . The mechanism of the reaction domenstrates that the formation of trinuclear bis arylimido complexes , and ortho metallated was , the result of cleavage of nitrogen –nitrogen bond . Monitoring this gave evidence that the rea

Image quality plays a vital role in improving and assessing image compression performance. Image compression represents big image data to a new image with a smaller size suitable for storage and transmission. This paper aims to evaluate the implementation of the hybrid techniques-based tensor product mixed transform. Compression and quality metrics such as compression-ratio (CR), rate-distortion (RD), peak signal-to-noise ratio (PSNR), and Structural Content (SC) are utilized for evaluating the hybrid techniques. Then, a comparison between techniques is achieved according to these metrics to estimate the best technique. The main contribution is to improve the hybrid techniques. The proposed hybrid techniques are consisting of discrete wavel

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

The new media scene reveals that the unprecedented overlap of a number of technical, economic, and political factors has made the new media a very complicated issue; and the focus of specialized and public debates about its impact on traditional means of communication and forms of social media and social relations. Then, the same scene discloses the reality of the relationship between the new and the traditional. These are the axes that will be will be discussed in this study.