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Optical Mark Recognition using Modify Bi-directional Associative Memory
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Optical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using MBAM make it timeless because it will deal with a complete answer sheet, it no need to extract the answer boxes from the answers sheet. The proposed OMR exhibits accuracy is 99.998% in the recognition of marked and non-marked.    

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Publication Date
Mon Feb 26 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
10.28936 USING NATTOKINASE IN CHEDDAR RIPENING: USING NATTOKINASE IN CHEDDAR RIPENING
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The crude enzyme Nattokinase produced by Bacillus subtilis was used in ripening cheddar cheese by adding three concentration of enzyme 80, 160 and 320mg/Kg beside the control treatment without enzyme, the product was checked for three months to determine humidity, protein, fat, non-protein nitrogen, soluble nitrogen and pH, sensory evaluation was conducted, it was noticed that the variety in protein percentages and the soluble nitrogen percentage during second month of ripening for T2, T3 and T4 treatments were (11.2, 15.54 and 18.48) respectively, in comparison with control which was 7.6%, while in the third month it was (17.37, 20.67 and 22.26) respectively, in comparison with control which was only 10%, on the other hand, non-protein

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Publication Date
Sun Jan 02 2022
Journal Name
Journal Of The College Of Languages (jcl)
The Role Of Historical Memory In Promoting The Concept Of Belonging To The Homeland In A Novel "Mazurka For Two Dead Men" Of The Spanish Novelist Camilo Jose Cela: El Papel De La Memoria Histórica En El Apoyo Del Concepto De Pertenencia A La Patria , En La Novela “Mazurca Para Dos Muertos”, De Camilo José Cela
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       The present study discusses the significant role of the historical memory in all the Spanish society aspects of life. When a novelist takes the role and puts on the mask of one of the novel’s protagonists or hidden characters, his memory of the events becomes the keywords of accessing the close-knit fabric of society and sheds lights on deteriorating social conceptions in  a backwards social reality that rejects all new progressive ideas and  modernity. Through concentrating on the society flawing aspects and employing everything of his stored memory, the author uses sarcasm to criticize and change such old deteriorating reality conceptions.   

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Publication Date
Sun Dec 01 2024
Journal Name
Energy Storage
Comprehensive Study of <scp>PAN</scp>‐<scp>NaBF<sub>4</sub></scp> Solid Polymer Electrolytes: Insights Into Optical, Structural, Thermal, Electrical, and Electrochemical Properties for Sodium‐Ion Batteries
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ABSTRACT<p>This research explores the use of solid polymer electrolytes (SPEs) as a conductive medium for sodium ions in sodium‐ion batteries, presenting a possible alternative to traditional lithium‐ion battery technology. The researchers prepare SPEs with varying molecular weight ratios of polyacrylonitrile (PAN) and sodium tetrafluoroborate (NaBF<sub>4</sub>) using a solution casting method with dimethyl formamide as the solvent. Through optical absorbance measurements, we identified the PAN:NaBF<sub>4</sub> (80:20) SPE composition as having the lowest energy band gap value (4.48 eV). This composition also exhibits high thermal stability based on thermogravimetric analysis results. </p> ... Show More
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Publication Date
Mon May 21 2007
Journal Name
Journal Of Planner And Development
Using the Input - Output Model in building the economic plan using the computer
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The origin of this technique lies in the analysis of François Kenai (1694-1774), the leader of the School of Naturalists, presented in Tableau Economique. This method was developed by Karl Marx in his analysis of the Departmental Relationships and the nature of these relations in the models of " "He said. The current picture of this type of economic analysis is credited to the Russian economist Vasily Leontif. This analytical model is commonly used in developing economic plans in developing countries (p. 1, p. 86). There are several types of input and output models, such as static model, mobile model, regional models, and so on. However, this research will be confined to the open-ended model, which found areas in practical application.

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Publication Date
Sun Nov 24 2024
Journal Name
Polymer-plastics Technology And Materials
Li <sub>2</sub> CO <sub>3</sub> as a Modifier for PVA/PVP/PEG Blend Polymer Electrolytes: Effects on Structural Integrity, Electrical Performance, Thermal Behavior and Optical Properties
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Publication Date
Sun Mar 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
The Influence of x ratio and Annealing Temperatures on Structural and Optical Properties for (CuO)<sub>x</sub>(ZnO)<sub>1-x</sub> Composite Thin Films Prepared by PLD
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Abstract<p>Thin films of (CuO)<sub>x</sub>(ZnO)<sub>1-x</sub> composite were prepared by pulsed laser deposition technique and x ratio of 0≤ x ≤ 0.8 on clean corning glass substrate at room temperatures (RT) and annealed at 373 and 473K. The X-ray diffraction (XRD) analysis indicated that all prepared films have polycrystalline nature and the phase change from ZnO hexagonal wurtzite to CuO monoclinic structure with increasing x ratio. The deposited films were optically characterized by UV-VIS spectroscopy. The optical measurements showed that (CuO)<sub>x</sub>(ZnO)<sub>1-x</sub> films have direct energy gap. The energy band gaps of prepared thin films </p> ... Show More
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Publication Date
Fri May 30 2025
Journal Name
Journal Of Internet Services And Information Security
Enhancing Lung Cancer Classification using CT Images using Processing Techniques Employing U-Net Architecture
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Publication Date
Sun Jan 01 2023
Journal Name
Ssrn Electronic Journal
Sustainable ENERGY by using AI
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As we live in the era of the fourth technological revolution, it has become necessary to use artificial intelligence to generate electric power through sustainable solar energy, especially in Iraq and what it has gone through in terms of crises and what it suffers from a severe shortage of electric power because of the wars and calamities it went through. During that period of time, its impact is still evident in all aspects of daily life experienced by Iraqis because of the remnants of wars, siege, terrorism, wrong policies ruling before and later, regional interventions and their consequences, such as the destruction of electric power stations and the population increase, which must be followed by an increase in electric power stations,

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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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