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Supervised Classification Accuracy Assessment Using Remote Sensing and Geographic Information System
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Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings, water bodies, and bare lands. During 2013-2022, vegetation cover increased from 63% in 2013 to 66% in 2022; buildings roughly increased by 1% to 3% yearly; water bodies showed a decrease of 2% to 1%; the amount of unoccupied land showed a decrease from 34% to 30%. Therefore, the classification accuracy was assessed using the approach of comparison with field data; the classification accuracy was about 85%.

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Publication Date
Mon Sep 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Certain Assessment of Using MWCNT Nps in Drilling Fluid to Mitigate Stick-Slip Problem during Drilling Operation System
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   Stick- slip is the continuous stopping& release of the Bit/BHA due to the irregular down-hole rotation prompted by the existing relationship between the friction torque and the torque applied from the surface to free the bit.

   Friction coefficient between BHA and wellbore is the main player of stick slip amount, which can be mitigated by support a good lubricators as additives in drilling mud.

   Mathematical (or empirical) solves should be done through adjusting all parameters which supposed to reduce stick- slip as low as possible using different models, one of the main parameters is drilling mud. As per Nanoparticles drilling fluid is a new technology that offers high performance

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
REVIEW THE ASSESSMENT OF EFFECTS OF LOST TIME INJURIES IN AN INDUSTRIAL SYSTEM BY USING AN EXPLANATORY PROGRAM
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Health and safety problem can be described by statistics it can only be understood by knowing and feeling the pain, suffering, and depression. Health and safety has a legal responsibility to protect it for everyone who can affect in the workplace. This includes manufacturers, suppliers, designers and controllers of work places and employees. Work injury is one of the major problems in manufacturing and production systems industries; it is reduced production efficiency and affects the cost. To gain flexibility from a traditional manufacturing system and production efficiency, this paper is about the application of estimating technology to preview and synthesis of Lost Time of Work Injuries in industry systems aims to provide a safe workin

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Publication Date
Wed Nov 25 2015
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Subject Independent Facial Emotion Classification Using Geometric Based Features
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Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Clouds Height Classification Using Texture Analysis of Meteosat Images
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In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

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Publication Date
Sat Feb 11 2023
Journal Name
Applied Sciences
A Preliminary Study and Implementing Algorithm Using Finite State Automaton for Remote Identification of Drones
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Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene

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Publication Date
Fri Jan 26 2024
Journal Name
Iraqi Journal Of Science
Classification of Cardiac Arrhythmia using ID3 Classifier Based on Wavelet Transform
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Accurate detection of Electro Cardio Graphic (ECG) features is an important demand for medical purposes, therefore an accurate algorithm is required to detect these features. This paper proposes an approach to classify the cardiac arrhythmia from a normal ECG signal based on wavelet decomposition and ID3 classification algorithm. First, ECG signals are denoised using the Discrete Wavelet Transform (DWT) and the second step is extract the ECG features from the processed signal. Interactive Dichotomizer 3 (ID3) algorithm is applied to classify the different arrhythmias including normal case. Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia Database is used to evaluate the ID3 algorithm. The experimental resul

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Publication Date
Tue Aug 03 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Using financial and non-financial information ) SASB standards) to enhance investor confidence
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Companies seek to enhance investor confidence by achieving the highest level of transparency in disclosure of financial and non-financial information (SASB standards) for Iraqi insurance companies listed on the financial market. The aim of the research is to identify the extent of the ability of financial and non-financial information to enhance transparency in reporting, which is reflected in Investor confidence. And the standards of sustainability development accounting issued by (SASB) through the electronic questionnaire that was distributed. Companies seek to achieve a set of goals, the most important of which is to enhance investor confidence by improving transparency in disclosure. Concerning the employment of financial an

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Publication Date
Mon Jan 01 2024
Journal Name
Studies In Systems, Decision And Control
The Effect of Using an Accounting Information System Based on Artificial Intelligence in Detecting Earnings Management to Enhance the Sustainability of Economic Units
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This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
information and communication technologies and their impact on changed the financial reporting system In a Sample in Iraqi banks
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paid recent developments in the information and communications technology and the accompanying developments in the global market to pay particular accounting information users to demand more sophistication in terms of corporate financial reporting systems, which led to the emergence of a new type of reporting (financial reporting in real time). where is the information and communications technology mainstay Nations for the development and progress, thanks to the development of technology that have made the transmission of information easily conducted and high speed to all who need it, communication is instantaneous and the flow of information via the internet dramatically exceeded the border temporal and spatial anywhere in the w

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Publication Date
Wed Jan 01 2020
Journal Name
Advances In Science, Technology And Engineering Systems Journal
Bayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

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