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Dynamic Virtual Network Embedding with Latency Constraint in Flex-Grid Optical Networks
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

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Publication Date
Sat Dec 14 2019
Journal Name
International Journal On Emerging Technologies
Utilizing an Artificial Neural Network Model to Predict Bearing Capacity of Stone Columns
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ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
SDN-RA: An Optimized Reschedule Algorithm of SDN Load Balancer for Data Center Networks Based on QoS
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Abstract<p>With the development of cloud computing during the latest years, data center networks have become a great topic in both industrial and academic societies. Nevertheless, traditional methods based on manual and hardware devices are burdensome, expensive, and cannot completely utilize the ability of physical network infrastructure. Thus, Software-Defined Networking (SDN) has been hyped as one of the best encouraging solutions for future Internet performance. SDN notable by two features; the separation of control plane from the data plane, and providing the network development by programmable capabilities instead of hardware solutions. Current paper introduces an SDN-based optimized Resch</p> ... Show More
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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm for Improving the Quantity and Quality of the Detected Complexes from Protein Interaction Networks
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One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

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Publication Date
Wed Oct 17 2018
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
ESTIMATION OF MUNICIPAL SOLID WASTE GENERATION AND LANDFILL VOLUME GENERATION AND LANDFILL VOLUME USING ARTIFICIAL NEURAL NETWORKS
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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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Publication Date
Sun Oct 01 2017
Journal Name
Al–bahith Al–a'alami
Social Media Networks and Freedom of Expression of Individual Rights and Social Diversity: Facebook is a Sample
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We are, today, facing a torrent of information, ideas, images and videos due to advances of communication technology and electronic publishing. In addition to the proliferation of social networking sites that allow individuals to use them and participate in their channels without any restrictions limiting their freedom in publishing. Due to these sites many terms have emerged like alternative media which use internet and its various techniques to serve its objectives notably the freedom of expression without restrictions. This research studies the phenomenon of interactive media i.e. alternative media through Facebook along with the freedom that makes it spreading in the society and the relation of individual freedom with social diversit

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
Transfer Learning and Hybrid Deep Convolutional Neural Networks Models for Autism Spectrum Disorder Classification From EEG Signals
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Publication Date
Tue Sep 17 2013
Journal Name
International Journal Of Engineering And Innovative Technology (ijeit)
Study of Optical Properties (Linear and Nonlinear) and Structures for CdS Thin Film Preparation in Spray Pyrolysis Technique
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Publication Date
Wed Feb 01 2023
Journal Name
Measurement: Sensors
Dynamic monitoring of saturated stiff clay soil foundation structure by falling weight deflectometer system under impact loads sensors effect
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Experiments research is done to determine how saturated stiff clayey soil responds to a single impulsive load. Models made of saturated, stiff clay were investigated. To supply the single pulse energy, various falling weights from various heights were tested using the falling weight deflectometer (FWD). Dynamic effects can range from the major failure of a sensitive sensor or system to the apparent destruction of structures. This study examines the response of saturated stiff clay soil to a single impulsive load (vertical displacement at the soil surface below and beside the bearing plates). Such reactions consist of displacements, velocities, and accelerations caused by the impact occurring at the surface depth induced by the impact loads

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