This paper presents a minimum delay congestion control in differentiated Service communication networks. The premium and ordinary passage services based fluid flow theory is used to build the suggested structure in high efficient manage. The established system is capable to adeptly manage both the physical network resource limitations and indefinite time delay related to networking system structure.

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

Simulation  of  the  Linguistic  Fuzzy Trust  Model  (LFTM)  over  oscillating  Wireless  Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network

The road networks is considered to be one of the determinants that controls to specify the areas of human activities, which it depend on to specify the arrival cost , in addition it is useful to achieve the connectivity for interaction and human activities , and shorten the distance and time between the population and places of service. The density of the road network in any space directly affected by the density of population and the type of economic activities and administrative functions performed by the space. On this basis, the subject of this study is reflected in the quantitative analysis of the roads network in the Governorate of Karbala. The study consists the quantitative analysis for the roads network and the Urban Nodes in th

Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject

Fatigue failure is almost considered as the predominant problem affecting automotive parts under dynamic loading condition. Thus, more understanding of crack behavior during fatigue can strongly help in finding the proper mechanism to avoid the final fracture and extent the service life of components. The main goal of this paper is to study the fracture behavior of low carbon steel which is used mostly in automotive industry. For this purpose, the fractography of samples subjected to high and low stress levels in fatigue test then was evaluated and analyzed. Hardness and tensile tests were carried out to determine the properties of used steel. Also, the samples were characterized by microstructure test and XRD analysis to examine the con

The new ligand [N1,N4-bis((1H-benzo[d]Glyoxalin-2-yl)carbamothioyl)Butanedi amide] (NCB) derived from Butanedioyl diisothiocyanate with 2-aminobenz imidazole was used to prepare a chain of new metal complexes of Cr(III), Mn(II), Co(II), Ni(II), Cu(II), Pd(II), Ag(I), Cd(II) by general formula [M(NCB)]Xn ,Where M= Cr(III), n=3, X=Cl; Mn(II), Co(II), Ni(II), Cu(II), Pd(II), Cd(II) ,n=2 , X=Cl; Ag(I), n=1, X=NO3. Characterized compounds on the basis of 1H, 13CNMR (for (NCB), FT-IR and U.V spectrum, melting point, molar conduct, %C, %H, %N and %S, the percentage of the metal in complexes %M, Magnetic susceptibility, thermal studies (TGA),while its corrosion inhibition for mild steel in Ca(OH)2 solution is studied by weight loss. These measureme

The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional quality.

The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional