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 area is the optimal self-organized service placement. In this paper a heuristic-based algorithm for service placement in future networks was presented. This algorithm achieves the ideal placement of services replicas by monitoring the load within the server and its neighborhood, choosing the node that contributes with the highest received load, and finally replicating or migrating the service to it based on specific criteria, so that the distance of requests coming from clients becomes as small as possible because of placing services within nearby locations. It was proved that our proposed algorithm achieves an improved performance by meeting the services within a shorter time, a smaller bandwidth, and thus a lower communication cost. It was compared with the traditional client-server approach and the random placement algorithm. Experimental results showed that the heuristic algorithm outperforms other approaches and meets the optimal performance with different network sizes and varying load scenarios.
Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi
... Show Moreأن للتطرف العنيف أسباب متنوعة تقف وراء ظهوره وتمدده في دول العالم المختلفة على نطاق واسع، إذ إن لكل بيئة ظروفها وخصوصياتها الكلية والفرعية التي تسهم في تعزيز القدرة التأثيرية للسلوكيات العنفية في إطار مجتمع ما، لاسيما إذا علمنا إن التطرف العنيف المؤدي الى الإرهاب كسلوكيات عنفية متطرفة مدمرة للبناء المجتمعي ما كان ليستمر لولا وجود بيئة حاضنة وظروف تساعد في انتشاره واستمرارية قدراته التأثيرية في البناء السي
... Show Moreأن للتطرف العنيف أسباب متنوعة تقف وراء ظهوره وتمدده في دول العالم المختلفة على نطاق واسع، إذ إن لكل بيئة ظروفها وخصوصياتها الكلية والفرعية التي تسهم في تعزيز القدرة التأثيرية للسلوكيات العنفية في إطار مجتمع ما، لاسيما إذا علمنا إن التطرف العنيف المؤدي الى الإرهاب كسلوكيات عنفية متطرفة مدمرة للبناء المجتمعي ما كان ليستمر لولا وجود بيئة حاضنة وظروف تساعد في انتشاره واستمرارية قدراته التأثيرية في البناء السي
... Show MorePrecision is one of the main elements that control the quality of a geodetic network, which defines as the measure of the network efficiency in propagation of random errors. This research aims to solve ZOD and FOD problems for a geodetic network using Rosenbrock Method to optimize the geodetic networks by using MATLAB programming language, to find the optimal design of geodetic network with high precision. ZOD problem was applied to a case study network consists of 19 points and 58 designed distances with a priori deviation equal to 5mm, to determine the best points in the network to consider as control points. The results showed that P55 and P73 having the minimum ellipse of error and considered as control points. FOD problem was applie
... Show MoreThis paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback
... Show MoreThe present paper aims at evaluating the vailability quality and future horizons of potable water in the city of Shatra as a model. This is done in accordance with certain subjective and objective factors alongside the classification map of Shatra as a residential area. This system follows geographical studies specialized in urban construction. The problem of the present paper as well as the data approaching that problem have been chosen from the records of 2018. The researcher offered (919) questionnaire forms to be answered by a sample of dwellers in that area. Besides, the researcher also followed lab analysis of water samples collected from districts in the city of Shatra. GIS technology was also used to arrive at the real water shar
... Show MoreThe current research aims to identify the self-regulation of university students, as well as to identify the significance of the difference in self-regulation according to the variable of sex (male-female), specialization (scientific-human), and grade (first-fourth). To achieve the research objectives, the two researchers developed a scale of (28) items about self-regulation According to the theory of (Pandora, 1991). The scale was administered to (500) students from the first and fourth stages of Al -Mustansiriyah University who were selected based on the random stratification method for the 2020/2021 academic year. The results showed that university students have a good level of self-regulation. There are no significant differences in
... Show MoreSurface water flow samples were collected with distances downstream over Saqlawiya main drain whose stretch of about 24.5 km. The drain travels through different land use pattern, before, flowing into Tigris River. Eight sampling points were carefully
selected downstream the channel during dry season. The examined water parameters were pH, NH3, NO3, PO= 4, BOD5, COD, TDS, S.S, Cl-, SO= 4, Na+ , Ca+2, Mg+2, and Oil and Grease. Descriptive and inferential methods through finding the best curve fit correlation were employed in the study to test the strength of the association between water chemical characteristics and distance downstream the channel. A comparison of the values of chemical parameters at the Al-Saqlawiya Drain-Tigris Riv
This study examines the impact of Digital Transformation (DT) on the Financial Reporting Quality (FRQ), taking into account the moderating role of the Trust Services Framework (TSF), in the context of rapid developments in the digital business environment and the resulting challenges and opportunities for accounting and financial systems. To achieve the study objectives, a descriptive–analytical approach was adopted, and a questionnaire was used as the primary data collection instrument. The study sample comprised 87 professionals working in accounting and financial functions. DT was measured through four dimensions: cloud computing, automation, data analytics, and systems integration. FRQ was assessed using the dimensions of accuracy and
... Show MoreAbstract—In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, t
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