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A Comparative Study of Various Intelligent Algorithms based Path Planning for Mobile Robots
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In general, path-planning problem is one of most important task in the field of robotics. This paper describes the path-planning problem of mobile robot based on various metaheuristic algorithms. The suitable collision free path of a robot must satisfies certain optimization criteria such as feasibility, minimum path length, safety and smoothness and so on. In this research, various three approaches namely, PSO, Firefly and proposed hybrid FFCPSO are applied in static, known environment to solve the global path-planning problem in three cases. The first case used single mobile robot, the second case used three independent mobile robots and the third case applied three follow up mobile robot.  Simulation results, which carried out using MATLAB 2014 environment, show the validity of the kinematic model for Nonholonomic mobile robot and demonstration that the proposed algorithm perform better than original PSO and FF algorithms under the same environmental constraints by providing the smoothness velocity and shortest path for each mobile robot.                                                                              

 

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Publication Date
Tue Dec 22 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The effect of insider trading in accounting information on the investors decisions: An Applied Study In a sample of corporation listed in Iraq Securities Exchange
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This research aims to discuss an important issue because of its role in increasing the efficiency of financial markets and boost investor confidence by a insider trading, which arises as a result of leaking secret information to some investors and reliable in the process of trading shares in the Iraq Stock Exchange And thus obtain abnormal profits at the expense of other investors. Research was based on the assumption that " Where shortcomings in local regulations relating to disclosure and insider trading in accounting information leads to the activate the phenomenon of insider trading in accounting information in the Iraq Stock Exchange and including a negative impact on investors' decisions ". and Because of the difficulty the discove

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Publication Date
Mon Feb 13 2023
Journal Name
International Conference Of Computational Methods In Sciences And Engineering Iccmse 2021
Management of the flood disaster and assessment their damaged areas using remote sensing and GIS techniques: A case study of Tigris River – Maysan Governorate, Iraq
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Publication Date
Wed Jun 21 2006
Journal Name
College Of Languages
A Semantico-Syntactic Study of Verbs of Eating in English with Reference to Arabic دراسة دلالية نحوية لأفعال الاكل باللغة الانكليزية مع الاشارة الى العربية
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This study is an attempt to investigate the semantic and syntactic features of English and Arabic verbs of eating. After surveying the literature on the meaning of verbs in both languages, three chapters address the major issues in this subject. The problem to be investigated in this study can be summarized in the following points: 1. The overlapping of semantic and syntactic features within the category of verbs of eating in English and Arabic. 2. Which semantic classification is more accurate and through which method? 3. Which classification, the semantic or the syntactic, is more important? This study hypothesized the following: 1. The semantic features are more influential in analyzing the category of verbs of eating than the syntactic

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Publication Date
Tue Jan 31 2017
Journal Name
Journal Of Engineering
A Study on the Removal of Direct Blue 71 Dye From Textile Wastewater Produced From State Company of Cotton Industries by Electrocoagulation Using Aluminum Electrodes
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The removal of direct blue 71 dye from a prepared wastewater was studied employing batch electrocoagulation (EC) cell. The electrodes of aluminum were used. The influence of process variables which include initial pH (2.0-12.0), wastewater conductivity (0.8 -12.57) mS/cm , initial dye concentration (30 -210) mg/L, electrolysis time  (3-12) min, current density (10-50) mA/cm2   were studied in order to maximize the color removal from wastewater. Experimental results showed that the color removal yield increases with increasing pH until pH 6.0 after that it decreased with increasing pH. The color removal increased with increasing current density, wastewater conductivity, electrolysis time, and decreased with increasing the concen

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Publication Date
Tue Jan 21 2025
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A comparison between the hierarchical clustering methods for postgraduate students in Iraqi universities for the year 2019-2020 using the cophenetic and delta correlation coefficients
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The educational sector is one of the important sectors in the world, and it is considered one of the means of community development. In addition, it is one of the means of making the country’s renaissance and devel-opment because it represents the factory of thinking minds that make change. There is no doubt that this sector is the same as any other sector. The deficit in the studied scientific planning has been prolonged, which led to its deterioration, and the problems of education remain diverse and inherited from previous time periods, where the hierarchical cluster analysis was used on postgraduate students in universities in Iraq, except for Kurdistan region, and the number of universities that were included in the study was

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT
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Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Tue Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Influence of Coating with Some Natural Based Materials on the Erosion Wear Behavior of Glass Fiber Reinforced Epoxy Resin
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Abstract 

In the present study, composites were prepared by Hand lay-up molding. The composites constituents were epoxy resin as a matrix, 6% volume fractions of glass fibers (G.F) as reinforcement and 3%, 6% volume fractions of preparation natural material (Rice Husk Ash, Carrot Powder, and Sawdust) as filler. Studied the erosion wear behavior and coating by natural wastes (Rice Husk Ash) with epoxy resin after erosion. The results showed the non – reinforced epoxy have lower resistance erosion than natural based material composites and the specimen (Epoxy+6%glass fiber+6%RHA) has higher resistance erosion than composites reinforced with carrot powder and sawdust  at 30cm , angle 60

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Wed May 15 2024
Journal Name
Ieee Sensors Journal
Surface Crack Size Estimation Based on Quantification and Decoupling of Magnetic Flux Leakage (MFL) Signals of Circular Array Sensors
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