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ijs-4036
A Multi-Objective Task Offloading Optimization for Vehicular Fog Computing
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      Internet of Vehicle (IoV) is one of the most basic branches of the Internet of Things (IoT), which provides many advantages for drivers and passengers to ensure safety and traffic efficiency. Most IoV applications are delay-sensitive and require resources for data storage and computation that cannot be afforded by vehicles. Thus, such tasks are always offloaded to more powerful nodes, like cloud or fog. Vehicular Fog Computing (VFC), which extends cloud computing and brings resources closer to the edge of the network, has the potential to reduce both traffic congestion and load on the cloud. Resources management and allocation process is very critical for satisfying both user and provider needs. However, the strategy of task offloading to fog node in constraints of energy and latency is still an open issue. Several research works have tackled the resource scheduling problem in the field of VFC; however, the recent studies have not carefully addressed the transmission path to the destination node, nor has it considered the energy consumption of vehicles. This paper aims to optimize the task offloading process in the VFC system in terms of latency and energy objectives while taking the deadline constraint into considerations by adopting a Multi-Objective Evolutionary Algorithm (MOEA). Four different execution/transmission models are proposed where vehicle resources are utilized for tasks execution and transmission, and the well-known Dijkstra's algorithm is adopted to find the minimum path between each two nodes. The simulation results show that the models which involve the vehicles in the transmission process have reduced the latency and the total energy for the VFC system significantly in comparison with other models and the current state of the art methods.

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

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Publication Date
Wed Feb 29 2012
Journal Name
Al-khwarizmi Engineering Journal
Design a Fault Tolerance for Real Time Distributed System
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This paper designed a fault tolerance for soft real time distributed system (FTRTDS). This system is designed to be independently on specific mechanisms and facilities of the underlying real time distributed system. It is designed to be distributed on all the computers in the distributed system and controlled by a central unit.

Besides gathering information about a target program spontaneously, it provides information about the target operating system and the target hardware in order to diagnose the fault before occurring, so it can handle the situation before it comes on. And it provides a distributed system with the reactive capability of reconfiguring and reinitializing after the occurrence of a failure.

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Publication Date
Tue Jun 08 2021
Journal Name
Biomolecules
A Pan-Inhibitor for Protein Arginine Methyltransferase Family Enzymes
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Protein arginine methyltransferases (PRMTs) play important roles in transcription, splicing, DNA damage repair, RNA biology, and cellular metabolism. Thus, PRMTs have been attractive targets for various diseases. In this study, we reported the design and synthesis of a potent pan-inhibitor for PRMTs that tethers a thioadenosine and various substituted guanidino groups through a propyl linker. Compound II757 exhibits a half-maximal inhibition concentration (IC50) value of 5 to 555 nM for eight tested PRMTs, with the highest inhibition for PRMT4 (IC50 = 5 nM). The kinetic study demonstrated that II757 competitively binds at the SAM binding site of PRMT1. Notably, II757 is selective for PRMTs over a panel of other methyltransferases, w

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Publication Date
Sat Jul 01 2017
Journal Name
Journal Of King Saud University - Science
A semi-analytical iterative technique for solving chemistry problems
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Publication Date
Tue May 16 2023
Journal Name
Mathematics
A Mathematical Study for the Transmission of Coronavirus Disease
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Globally, the COVID-19 pandemic’s development has presented significant societal and economic challenges. The carriers of COVID-19 transmission have also been identified as asymptomatic infected people. Yet, most epidemic models do not consider their impact when accounting for the disease’s indirect transmission. This study suggested and investigated a mathematical model replicating the spread of coronavirus disease among asymptomatic infected people. A study was conducted on every aspect of the system’s solution. The equilibrium points and the basic reproduction number were computed. The endemic equilibrium point and the disease-free equilibrium point had both undergone local stability analyses. A geometric technique was used

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
A Review for Arabic Sentiment Analysis Using Deep Learning
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     Sentiment Analysis is a research field that studies human opinion, sentiment, evaluation, and emotions towards entities such as products, services, organizations, events, topics, and their attributes. It is also a task of natural language processing. However, sentiment analysis research has mainly been carried out for the English language. Although the Arabic language is one of the most used languages on the Internet, only a few studies have focused on Arabic language sentiment analysis.

     In this paper, a review of the most important research works in the field of Arabic text sentiment analysis using deep learning algorithms is presented. This review illustrates the main steps used in these studies, which include

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Publication Date
Tue Aug 31 2021
Journal Name
Iraqi Journal Of Science
A lightweight AES Algorithm Implementation for Secure IoT Environment
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In recent years, the rapid development in the field of wireless technologies led to the appearance of a new topic, known as the Internet of things (IoT). The IoT applications can be found in various fields of our life, such as smart home, health care, smart building, and etc. In all these applications, the data collected from the real world are transmitted through the Internet; therefore, these data have become a target of many attacks and hackers. Hence, a secure communication must be provided to protect the transmitted data from unauthorized access. This paper focuses on designing a secure IoT system to protect the sensing data. In this system, the security is provided by the use of Lightweight AES encryption algorithm to encrypt the d

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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Analytical Methods for Determination of Ketoprofen Drug: A review
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Ketoprofen has recently been proven to offer therapeutic potential in preventing cancers such as colorectal and lung tumors, as well as in treating neurological illnesses. The goal of this review is to show the methods that have been used for determining ketoprofen in pharmaceutical formulations. Precision product quality control is crucial to confirm the composition of the drugs in pharmaceutical use. Several analytical techniques, including chromatographic and spectroscopic methods, have been used for determining ketoprofen in different sample forms such as a tablet, capsule, ampoule, gel, and human plasma. The limit of detection of ketoprofen was 0.1 ng/ ml using liquid chromatography with tandem mass spectrometry, while it was 0.01-

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
A Novel Water Quality Index for Iraqi Surface Water
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The study aims to build a water quality index that fits the Iraqi aquatic systems and reflects the environmental reality of Iraqi water. The developed Iraqi Water Quality Index (IQWQI) includes physical and chemical components. To build the IQWQI, Delphi method was used to communicate with local and global experts in water quality indices for their opinion regarding the best and most important parameter we can use in building the index and the established weight of each parameter. From the data obtained in this study, 70% were used for building the model and 30% for evaluating the model. Multiple scenarios were applied to the model inputs to study the effects of increasing parameters. The model was built 4 by 4 until it reached 17 parame

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Publication Date
Thu May 18 2023
Journal Name
College Of Islamic Sciences
Borrowing in a diwan Moon Tree for Nazik Angels
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The moon tree, the lover of the night, cholera, the sea changes its colors are poetic products left by the pioneer of free poetry, as many have called her. She used to write poetry and publish it in magazines and newspapers until she published it with collections that came into existence from an early age. Several factors helped her in that that contributed to the formation of her personality and the maturity of her talent, including factors Family, including environmental, and psychological, until she later became the focus of attention of many, so she became taught in the universities of London, and students stood by her method of writing free poetry, this poetic color that Badr Shaker Al-Sayyab participated in pioneering. Whoever exam

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