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Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both solar power automation subsystem and transformer simultaneously or consumption unit; otherwise it works with fully or lesser efficiency. Statistically independent failures and repairs are considered. Using the elementary probabilities phenomenon incorporated with differential equations is employed to examine the system reliability, for repairable and non-repairable system, and to analyze its cost function. The accuracy and consistency of the system can be improved by feed forward- back propagation neural network (FFBPNN) approach. Its gradient descent learning mechanism can update the neural weights and hence the results up to the desired accuracy in each iteration, and aside the problem of vanishing gradient in other neural networks, that increasing the efficiency of the system in real time. MATLAB code for FFBP algorithm is built to improve the values of reliability and cost function by minimizing the error up to 0.0001 precision. Numerical illustrations are considered with their data tables and graphs, to demonstrate and analyze the results in the form of reliability and cost function, which may be helpful for system analyzers.

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
A Software Defined Network of Video Surveillance System Based on Enhanced Routing Algorithms
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Software Defined Network (SDN) is a new technology that separate the ‎control plane from the data plane. SDN provides a choice in automation and ‎programmability faster than traditional network. It supports the ‎Quality of Service (QoS) for video surveillance application. One of most ‎significant issues in video surveillance is how to find the best path for routing the packets ‎between the source (IP cameras) and destination (monitoring center). The ‎video surveillance system requires fast transmission and reliable delivery ‎and high QoS. To improve the QoS and to achieve the optimal path, the ‎SDN architecture is used in this paper. In addition, different routing algorithms are ‎used with different steps. First, we eva

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Publication Date
Sat Dec 30 2023
Journal Name
مجلة نسق
Evaluating the Students’ Performance in the College of Education for Women in Using the Digital Transformation
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This study aims at evaluating the performance of MA students in the College of Education for Women in using the digital transformation and identifying the significant difference in performance evaluation according to the variable of academic qualification (Master or PHD). In order to achieve the aim of the research the researcher prepared a questionnaire of 20 items, and this happens after the researcher's getting acquaintance of the literature of previous studies related to the variable of the research. The apparent validity of the items was examined by exposing them to 10 juries specialized in education, psychology and evaluation and measurement. The stability of the items was examined via two methods, the test-repetition and half-divisio

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Automatic Spike Neural Technique for Slicing Bandwidth Estimated Virtual Buffer-Size in Network Environment
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The Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modifie

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Publication Date
Mon Sep 01 2014
Journal Name
Al-khwarizmi Engineering Journal
Using TermoDeck System for Pre-Cooling/ Heating to Control the Building Inside Conditions
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In this paper, experimental study has been done for temperature distribution in space conditioned with Ventilation Hollow Core Slab (TermoDeck) system. The experiments were carried out on a model room with dimensions of (1m 1.2m 1m) that was built according to a suitable scale factor of (1/4). The temperature distributions was measured by 59 thermocouples fixed in several locations in the test room. Two cases were considered in this work,  the first one during unoccupied period at night time (without external load) and the other at day period with external load of 800W/m2 according to solar heat gain calculations during summer season in Iraq. All results confirm the use of TermoDeck system for ventilation and cooling/heat

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Publication Date
Thu Jun 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Nahrain Mobile Learning System (NMLS)
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The work in this paper involves the planning, design and implementation of a mobile learning system called Nahrain Mobile Learning System (NMLS). This system provides complete teaching resources, which can be accessed by the students, instructors and administrators through the mobile phones. It presents a viable alternative to Electronic learning. It focuses on the mobility and flexibility of the learning practice, and emphasizes the interaction between the learner and learning content. System users are categorized into three categories: administrators, instructors and students. Different learning activities can be carried out throughout the system, offering necessary communication tools to allow the users to communicate with each other

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Choosing the best method for estimating the survival function of inverse Gompertz distribution by using Integral mean squares error (IMSE)
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In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes

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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness
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Abstract  

Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned according to Taguchi orthogonal array (OA) L27 (36) with three levels and six input parameters. Experimental estimation and optimization of input parameters for MAF process for stainless steel type 316 plate work piece, six input parameters including amplitude of tooth pole, and number of cycle between teeth, current, cutting speed, working gap, and finishing time, were performed by design of experiment

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Publication Date
Tue Feb 01 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Finger Vein Recognition Based on PCA and Fusion Convolutional Neural Network
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Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

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Publication Date
Fri Apr 28 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Design Optimal Neural Network for Solving Unsteady State Confined Aquifer Problem
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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Bioremediation of Petroleum Hydrocarbons Contaminated Soil using Bio piles System
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This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity.

Four bacterial strains were isolated from diesel contaminated soil samples. The isolates were identified by the Vitek 2 system, as Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae. The potential of biological surfactant production was tested using the Sigma 703D stand-alone tensiometer showed

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