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Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when diagnosing a tissue sample. Small, unnoticeable changes in pixel density may indicate the beginning of cancer or tear tissue in the early stages. These details even expert pathologists might miss. Artificial intelligence (A.I.) and D.L. revolutionized radiology by enhancing efficiency and accuracy of both interpretative and non-interpretive jobs. When you look at AI applications, you should think about how they might work. Convolutional Neural Network (C.N.N.) is a part of D.L. that can be used to diagnose knee problems. There are existing algorithms that can detect and categorize cartilage lesions, meniscus tears on M.R.I., offer an automated quantitative evaluation of healing, and forecast who is most likely to have recurring meniscus tears based on radiographs.

Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Construction of Graduation Certificate Issuing System Based on Digital Signature Technique
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With the development of computer architecture and its technologies in recent years, applications like e-commerce, e-government, e-governance and e-finance are widely used, and they act as active research areas. In addition, in order to increase the quality and quantity of the ordinary everyday transactions, it is desired to migrate from the paper-based environment to a digital-based computerized environment. Such migration increases efficiency, saves time, eliminates paperwork, increases safety and reduces the cost in an organization. Digital signatures are playing an essential role in many electronic and automatic based systems and facilitate this migration. The digital signatures are used to provide many services and s

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Humanities And Social Sciences/ Rimak
AN EMPIRICAL ANALYSIS OF EDUCATIONAL RESEARCH BASED ON CRITICAL DISCOURSE ANALYSIS
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APDBN Rashid, International Journal of Humanities and Social Sciences/ RIMAK, 2023

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of College Of Education
Recognition the Arabic Characters Based on the Characteristics of Arabic Language
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Publication Date
Mon Feb 13 2023
Journal Name
Journal Of Educational And Psychological Researches
A Blended Learning Program Based on the Next Generation Standards (NYS) to Develop the Teaching Performance of Middle School Mathematics Teachers and Some Students’ Future Thinking Skills
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Abstract

The aim of the current research is to prepare an integrated learning program based on mathematics standards for the next generation of the NYS and to investigate its impact on the development of the teaching performance of middle school mathematics teachers and the future thinking skills of their students. To achieve the objectives of the research, the researcher prepared a list of mathematics standards for the next generation, which were derived from a list of standards. He also prepared a list of the teaching competencies required for middle school mathematics teachers in light of the list of standards, as well as clarified the foundations of the training program and its objectives and the mathematical

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
A Tri-Gene Ontology Migration Operator for Improving the Performance of Meta-heuristics in Complex Detection Problems
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      Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulate

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Publication Date
Tue Apr 19 2022
Journal Name
Chemistryselect
A Continuous Flow Injection/Indirect Photometric Method for the Detection of Fosetyl Aluminum in Commercial Pesticide Formulations
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Abstract<p>Because of their Physico‐chemical characteristics and its composition, the development of new specific analytical methodologies to determine some highly polar pesticides are required. The reported methods demand long analysis time, expensive instruments and prior extraction of pesticide for detection. The current work presents a new flow injection analysis method combined with indirect photometric detection for the determination of Fosetyl‐Aluminum (Fosetyl‐Al) in commercial formulations, with rapid and highly accurate determination involving only construction of manifold system combined with photometric detector without need some of the pre‐treatments to the sample before the analysis such a</p> ... Show More
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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Engineering
Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
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 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

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Publication Date
Mon Mar 21 2022
Journal Name
International Journal For Research In Applied Sciences And Biotechnology
Article Review: Toll-like Receptors and COVID-19
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By March 2020, a pandemic had been emerged Corona Virus Infection in 2019 (COVID-19), which was triggered through the sensitive pulmonary syndrome (SARS disease corona virus- 2 (SARS COV-2). Overall precise path physiology of SARS COV-2 still unknown, as does the involvement of every element of the acute or adaptable immunity systems. Additionally, evidence from additional corona virus groups, including SARS COV as well as the Middle East pulmonary disease, besides that, fresh discoveries might help researchers fully comprehend SARS CoV-2. Toll-like receptors (TLRs) serve a critical part in both detection of viral particles as well as the stimulation of the body's immune response. When TLR systems are activated, pro-inflammatory cy

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Publication Date
Tue Apr 01 2025
Journal Name
Iop Conference Series: Earth And Environmental Science
Review Article: Iron, Zinc and Boron in Sunflower
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There is a real problem when adding micro elements to the soil as a result of fixation, sedimentation, washing or toxicity, and thus economic loss. The plant needs micro elements in very small quantities that do not burn the leaves or cause poisoning to plants, including iron, zinc and boron, as they are essential elements for growth and completing the plant's life cycle, and increase the plant's resistance to diseases and insects, activate enzymes, and form the chlorophyll molecule, in addition to their role in oxidation and reduction processes and vital processes. The use of fertilizers with their modern technology has made the process of activating seeds or foliar nutrition a matter of interest to researchers as a complementary process t

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