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jcoeduw-1361
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Convolutional Neural Network (CNN) has been chosen as a better option for the training process because it produces a high accuracy. The final accuracy has reached 91.18% in five different classes. The results are discussed in terms of the probability of accuracy for each class in the image classification in percentage. Cats class got 99.6 %, while houses class got 100 %.Other types of classes were with an average score of 90 % and above.

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Publication Date
Tue Mar 17 2026
Journal Name
Iraoi Journal Of Statistical Sciences
حول تقليص تقدير المركبات الرئيسة مع التطبيق
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This research deals with a shrinking method concerned with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained

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Publication Date
Tue Dec 31 2024
Journal Name
مجلة كلية التربية الاساسية
التعامل مع إدمان طلاب المدارس: التحديات والحلول
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Publication Date
Sun Jan 30 2022
Journal Name
مجلة كلية الاسراء الجامعة للعلوم الاجتماعية والانسانية
مدى تلازم التعويض مع الفسخ المبتسر للعقد
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يتناول البحث فكرة الفسخ المبتسر للعقد من حيث امكانية او عدم امكانية الحكم بهما مجتمعين ومدى تلازمهما

Publication Date
Mon Oct 30 2023
Journal Name
Aro-the Scientific Journal Of Koya University
Enhancing Upper Limb Prosthetic Control in Amputees Using Non-invasive EEG and EMG Signals with Machine Learning Techniques
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Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Development of Intelligent Control Strategy for an Anesthesia System Based on Radial Basis Function Neural Network Like PID Controller
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Publication Date
Wed Mar 23 2022
Journal Name
Journal Of Educational And Psychological Researches
The extent of the social worker’s use of group discussion technique in professional practice with school activity groups in Tubas Governorate schools
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This study aimed at identifying the extent to which the social worker used the techniques of group discussion in the professional practice with the groups of school activity in the schools of Tubas governorate in light of some variables (gender, years of experience, academic qualification). The analytical descriptive method was used due to its suitability for the objectives of the study.  A questionnaire was designed to collect data that included (30) items, distributed in three areas .The validity and reliability of the tool were verified and then distributed to the study sample.

 

The results of the study showed that the highest averages were in the discussion stage domain, where the pre-discussion stage was m

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
application of business managment in the field of football with studuy of the case of spanish club (Real Madrid) و (Barcelona
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Football has progressed from being a ritual and a celebration to become an amateur sport, a professional sport, and now, increasingly, a commercial sport. In the analysis of football business model, the systemic approach should be adopted. If sport is regarded as one of the business sectors, then the application of business system methodology can be fully justified. The interest to create strong football business system calls for the search of the ways of popularizing football business model and boosting the economic potential of its participants. In the research literature tend to ignore the business processes within the sports business. Besides, the systemic approach in football business is usually limited to p

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Effective Solution of University Course Timetabling using Particle Swarm Optimizer based Hyper Heuristic approach
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The university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a

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Publication Date
Thu Mar 12 2020
Journal Name
Al-khwarizmi Engineering Journal
Optimization the Effect of Electrode Material Change on EDM Process Performance Using Taguchi Method
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Electrical Discharge Machining (EDM) is a widespread Nontraditional Machining (NTM) processes for manufacturing of a complicated geometry or very hard metals parts that are difficult to machine by traditional machining operations. Electrical discharge machining is a material removal (MR) process characterized by using electrical discharge erosion. This paper discusses the optimal parameters of EDM on high-speed steel (HSS) AISI M2 as a workpiece using copper and brass as an electrode. The input parameters used for experimental work are current (10, 24 and 42 A), pulse on time (100, 150 and 200 µs), and pulse off time (4, 12 and 25 µs) that have effect on the material removal rate (MRR), electrode wear rate (EWR) and wear ratio (WR). A

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Qualitative and Quantitative Determination of Dapagliflozin Propanediol Monohydrate and Its Related Substances and Degradation Products Using LC-MS and Preparative Chromatography Methods
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Dapagliflozin is a novel sodium-glucose cotransporter type 2 inhibitor. This work aims to develop a new
validated sensitive RP-HPLC coupled with a mass detector method for the determination of dapagliflozin, its
alpha isomer, and starting material in the presence of dapagliflozin major degradation products and an internal
standard (empagliflozin). The separation was achieved on BDS Hypersil column (length of 250mm, internal
diameter of 4.6 mm and 5-μm particle size) at a temperature of 35℃. Water and acetonitrile were used as
mobile phase A and B by gradient mode at a flow rate of 1 mL/min. A wavelength of 224nm was selected to
perform detection using a photo diode array detector. The method met the

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