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The impact of training on the development of the composite efficiency Alibd your faith and endurance of the effectiveness of the 100-meter run
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Is the efficiency of physical and your endurance is of great importance for some activities and field, as it whenever the situation has improved student career was able to perform physical exertion more with energy saving efforts, so the identification of physical aptitude and endurance private students, was based on that there are positively correlated the carrying of training and pregnancy fact on the shoulders of the student. In other words, physical aptitude and endurance in your control level that can be shown by the student during the performance of training and competitions. Therefore, lies the importance of research to test physical aptitude and endurance your help to reveal the career of the body in the light of their relationship to the level of performance for judging the effectiveness of the training process as possible through the identification of physical aptitude to obtain much data on students and use these results in scientific studies when comparing the dynamic impact training during the training season to the students. The problem with research in the curriculum material Aalsahp and in the field of Latvia and the purpose of the terms of the number of units during the week are not sufficient for the development of physical aptitude and endurance private students, which leads to the failure of students in achieving the desired objectives and thus to an injury, which may result in a break with the student once and for all playing lesson. Therefore, the researcher wanted to try to examine the efficiency of physical and your endurance through the development of training curriculum for training by using compound (weights + Blayomturk) to obtain the scientific data and realistic contribution to the enhancement of the effectiveness of the 100-meter run. The study aimed to identify the impact of the training compound on the development of physical aptitude and endurance of your students. The researcher used the experimental method on a sample of students in the first phase of the Faculty of Physical Education course during 2009-2010 m The number of sample subjects (24 students), were divided into two groups equal in number, the number of each (12) Student was homogeneity of the sample of the research in the background variables. The researcher concluded the training compound a positive role in the development of physical aptitude and endurance on the effectiveness of the 100-meter run for the students. Therefore, the researcher recommends using the training compound because of its role in the development of a positive physical aptitude and endurance on the effectiveness of the 100-meter run for the students

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Qin Seal Script Character Recognition with Fuzzy and Incomplete Information
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The dependable and efficient identification of Qin seal script characters is pivotal in the discovery, preservation, and inheritance of the distinctive cultural values embodied by these artifacts. This paper uses image histograms of oriented gradients (HOG) features and an SVM model to discuss a character recognition model for identifying partial and blurred Qin seal script characters. The model achieves accurate recognition on a small, imbalanced dataset. Firstly, a dataset of Qin seal script image samples is established, and Gaussian filtering is employed to remove image noise. Subsequently, the gamma transformation algorithm adjusts the image brightness and enhances the contrast between font structures and image backgrounds. After a s

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Publication Date
Mon Jul 01 2019
Journal Name
2019 International Joint Conference On Neural Networks (ijcnn)
A Fast Feature Extraction Algorithm for Image and Video Processing
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Publication Date
Mon Aug 01 2022
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Dorsal hand veins features extraction and recognition by correlation coefficient
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Publication Date
Fri Sep 01 2023
Journal Name
Civil Engineering Journal
Fundamental Challenges and Management Opportunities in Post Disaster Reconstruction Project
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The study examines the root causes of delays that the project manager is unable to resolve or how the decision-maker can identify the best opportunities to get over these obstacles by considering the project constraints defined as the project triangle (cost, time, and quality) in post-disaster reconstruction projects to review the real challenges to overcome these obstacles. The methodology relied on the exploratory description and qualitative data examined. 43 valid questionnaires were distributed to qualified experienced engineers. A list of 49 factors causes was collected from previous international and local studies. A Relative Important Index (RII) is adapted to determine the level of importance of each sub-criterion in the fou

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Publication Date
Wed Jan 01 2025
Journal Name
Fusion: Practice And Applications
Enhanced EEG Signal Classification Using Machine Learning and Optimization Algorithm
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This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

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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
Sun Sep 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Torque and Drag Forces Problems in Highly Deviated Oil Well
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Excessive torque and drag can be critical limitation during drilling highly deviated oil wells. Using the modeling is regarded as an invaluable process to assist in well planning and to predict and prevent drilling problems. Identify which problems lead to excessive torque and drag to prevent cost losses and equipment damage. Proper modeling data is highly important for knowing and prediction hole problems may occur due to torque and drag and select the best method to avoid these problems related to well bore and drill string. In this study, Torque and drag well plan program from landmark worldwide programming group (Halliburton Company) used to identify hole problems.one deviated well in Zubair oil fields named, ZB-250 selected for

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Publication Date
Wed Sep 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Performance Comparison between Recycled Single Stage and Double Stage Hydrocyclones
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   This research presents a comparison of performance between recycled single stage and double stage hydrocyclones in separating water from water/kerosene emulsion. The comparison included several factors such as: inlet flow rate (3,5,7,9, and 11 L/min), water feed concentration (5% and 15% by volume), and split ratio (0.1 and 0.9). The comparison extended to include the recycle operation; once and twice recycles. The results showed that increasing flow rate as well as the split ratio enhancing the separation efficiency for the two modes of operation. On the contrary, reducing the feed concentration gave high efficiencies for the modes. The operation with two cycles was more efficient than one cycle. The maximum obtained effici

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Publication Date
Sun Aug 01 2021
Journal Name
Safety Science
Evaluating OSHA’s fatality and catastrophe investigation summaries: Arc flash focus
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Publication Date
Tue Dec 17 2019
Journal Name
Lecture Notes In Electrical Engineering
Aspect Categorization Using Domain-Trained Word Embedding and Topic Modelling
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Aspect-based sentiment analysis is the most important research topic conducted to extract and categorize aspect-terms from online reviews. Recent efforts have shown that topic modelling is vigorously used for this task. In this paper, we integrated word embedding into collapsed Gibbs sampling in Latent Dirichlet Allocation (LDA). Specifically, the conditional distribution in the topic model is improved using the word embedding model that was trained against (customer review) training dataset. Semantic similarity (cosine measure) was leveraged to distribute the aspect-terms to their related aspect-category cognitively. The experiment was conducted to extract and categorize the aspect terms from SemEval 2014 dataset.

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