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Experimental Evaluation and Finite Element Simulation to Produce Square Cup by Deep Drawing Process
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Deep drawing process to produce square cup is very complex process due to a lot of process parameters which control on this process, therefore associated with it many of defects such as earing, wrinkling and fracture. Study of the effect of some process parameters to determine the values of these parameters which give the best result, the distributions for the thickness and depths of the cup were used to estimate the effect of the parameters on the cup numerically, in addition to experimental verification just to the conditions which give the best numerical predictions in order to reduce the time, efforts and costs for producing square cup with less defects experimentally is the aim of this study. The numerical analysis is used to study the effect of some parameters such as die profile radius, radial clearance between die and punch, blank diameter on the length and thickness  distributions on the cup, dynamic-explicit (ANSYS11) code based on finite element method is utilized to simulate the square deep drawing operation. Experiments were done for comparison and verification the numerical predictions. effective square cup with less defects and acceptable thickness distributions were produced in this study. It is concluded  the most thinning appear in the corner cup due to excessive stretching occur in this region and also it is found the cup thickness and height prediction by numerical analysis and in general in harmony with experimental analysis.

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Publication Date
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
Deep Reinforcement Learning: Bridging Learning and Control in Intelligent Systems
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Publication Date
Thu Mar 13 2025
Journal Name
Academia Open
Deep Learning and Fusion Techniques for High-Precision Image Matting:
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning
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Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An Adaptive Harmony Search Part-of-Speech tagger for Square Hmong Corpus
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Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.

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Publication Date
Sat Dec 11 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Difference in Contributing Factors and Costs Associated with Outpatient Refusal to Accept Cardiovascular Medications or Analgesics During Dispensing Process.
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Background: Study looking into cardiovascular disorders (CVD) medicines or analgesics cost-saving activities during dispensing process is lacking.

Aim: To determine differences in factors and costs associated with refused CVD medicines or analgesics during dispensing process

Method: This study was approved by Medical Research and Ethics Committee (MREC) (Registration number: NMRR-20-177-53153(IIR)). Participants receiving CVD medicines or analgesics during dispensing process were recruited via convenience sampling technique between February and March 2020 at the Specialist Pharmacy Department of Jerantut Hospital, Malaysia. Refusal to medications and its reasons were asked based on the questionnaire developed by the resea

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Business Risk Assessment Using Client Strategy Analysis Approach in order to Increase the Efficiency and Effectiveness of the Audit Process
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Abstract

This study aimed to identify the business risks using the approach of the client strategy analysis in order to improve the efficiency and effectiveness of the audit process. A study of business risks and their impact on the efficiency and effectiveness of the audit process has been performed to establish a cognitive framework of the main objective of this study, in which the descriptive analytical method has been adopted. A survey questionnaire has been developed and distributed to the targeted group of audit firms which have profession license from the Auditors Association in the Gaza Strip (63 offices). A hundred questionnaires have been distributed to the study sample of which, a total of 84 where answered and

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Publication Date
Sun Sep 01 2013
Journal Name
Baghdad Science Journal
Synthesis and Evaluation of Antimicrobial activity of several new Maleimides to Benzothiazole moiety
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In this work, a series of new maleimides linked to substituted benzothiazole moiety were synthesized. Synthesis of these new cyclic imides were performed via three steps, the first one involved preparation of a series of 2-aminobenzothiazole substituted with different substituents via reaction of different primary aromatic amines with ammonium thiocyanate and bromine in glacial acetic acid. The prepared 2- amino benzothiozoles were introduced in the second step in reaction with maleic anhydride producing a series of N-(substituted benzothiazole-2-yl) maleamic acids.The resulted maleamic acids were dehydrated in the third step via treatment with acetic anhydride and anhydrous sodium acetate to afford a series of the desirable N-(substitu

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Publication Date
Wed Jun 21 2023
Journal Name
Journal Of Electrochemical Science And Engineering
Phenol removal by electro-Fenton process using a 3D electrode with iron foam as particles and carbon fibre modified with graphene
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The 3D electro-Fenton technique is, due to its high efficiency, one of the technologies suggested to eliminate organic pollutants in wastewater. The type of particle electrode used in the 3D electro-Fenton process is one of the most crucial variables because of its effect on the formation of reactive species and the source of iron ions. The electrolytic cell in the current study consisted of graphite as an anode, carbon fiber (CF) modified with graphene as a cathode, and iron foam particles as a third electrode. A response surface methodology (RSM) approach was used to optimize the 3D electro-Fenton process. The RSM results revealed that the quadratic model has a high R2 of 99.05 %. At 4 g L-1 iron foam particles, time of 5 h, and

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Publication Date
Sat Dec 11 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Ameliorative Role of Nutraceutical Quercetin and its Derivatives Against Cognitive Impairment Process Induced by Lead Exposure in Drosophila melanogaster(Fruit Fly)
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Cumulative lifetime lead (Pb) exposure has been associated with accelerated declines in cognition through the free radical generation and epigenetic effects. Several pieces of literature have identified a correlation between exposure to lead and neurodegenerative disorders. Harwich strain Drosophila melanogaster was exposed to lead acetate for two weeks, and changes in pulse transmission by acetylcholinesterase and systemic redox were evaluated. Besides, molecular docking studies of acetylcholinesterase against Quercetin and its most common derivatives contained in food have been performed. Pharmacokinetic studies on Quercetin and its derivatives have also been performed in silico toxicity. The data obtained showed alterations in antioxi

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