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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
Wed Jun 01 2022
Journal Name
Iraqi Journal Of Industrial Research (ijoir)
Biofuel Production and Its Impact on Global Food Security: A Review Article
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The aim of this study is to shed light on the importance of biofuels as an alternative to conventional energy, in addition to the importance of preserving agricultural crops, which are the main source of this fuel, to maintain food security, especially in developing countries. The increase in global oil prices, in addition to the fear of global warming, are among the main factors that draw the world’s attention to searching for alternative sources of traditional energy, which are sustainable on the one hand, and on the other hand reduce carbon emissions. Therefore, the volume of global investment in renewable energy in general, and in liquid biofuels and biomass in particular, has increased. Global fears emerged that the excessive convers

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Publication Date
Sun Jun 02 2019
Journal Name
Baghdad Science Journal
Fog Computing Resource Optimization: A Review on Current Scenarios and Resource Management
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            The unpredictable and huge data generation nowadays by smart computing devices like (Sensors, Actuators, Wi-Fi routers), to handle and maintain their computational processing power in real time environment by centralized cloud platform is difficult because of its limitations, issues and challenges, to overcome these, Cisco introduced the Fog computing paradigm as an alternative for cloud-based computing. This recent IT trend is taking the computing experience to the next level. It is an extended and advantageous extension of the centralized cloud computing technology. In this article, we tried to highlight the various issues that currently cloud computing is facing. Here

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Publication Date
Tue Jun 14 2022
Journal Name
Iraqi Journal Of Industrial Research
Biofuel Production and Its Impact on Global Food Security: A Review Article
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The aim of this study is to shed light on the importance of biofuels as an alternative to conventional energy, in addition to the importance of preserving agricultural crops, which are the main source of this fuel, to maintain food security, especially in developing countries. The increase in global oil prices, in addition to the fear of global warming, are among the main factors that draw the world’s attention to searching for alternative sources of traditional energy, which are sustainable on the one hand, and on the other hand reduce carbon emissions. Therefore, the volume of global investment in renewable energy in general, and in liquid biofuels and biomass in particular, has increased. Global fears emerged that the excessive

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
DAMAGE DETECTION AND LOCATION FOR IN AND OUT-OFPLANE CURVED BEAMS USING FUZZY LOGIC BASED ON FREQUENCY DIFFERENCE
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In this study, structures damage identification method based on changes in the dynamic characteristics
(frequencies) of the structure are examined, stiffness as well as mass matrices of the curved
(in and out-of-plane vibration) beam elements is formulated using Hamilton's principle. Each node
of both of them possesses seven degrees of freedom including the warping degree of freedom. The
curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory
in 1994. A computer program was developing to carry out free vibration analyses of the curved
beam as well as straight beam. Comparing with the frequencies for other researchers using the general
purpose program MATLAB. Fuzzy logic syste

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Data Analytics and Blockchain: A Review
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Blockchain technology relies on cryptographic techniques that provide various advantages, such as trustworthiness, collaboration, organization, identification, integrity, and transparency. Meanwhile, data analytics refers to the process of utilizing techniques to analyze big data and comprehend the relationships between data points to draw meaningful conclusions. The field of data analytics in Blockchain is relatively new, and few studies have been conducted to examine the challenges involved in Blockchain data analytics. This article presents a systematic analysis of how data analytics affects Blockchain performance, with the aim of investigating the current state of Blockchain-based data analytics techniques in research fields and

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Publication Date
Fri Nov 18 2022
Journal Name
International Journal Of Nanoscience
Plasma Production and Applications: A Review
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Large amounts of plasma, the universe’s fourth most common kind of stuff, may be found across our galaxy and other galaxies. There are four types of matter in the cosmos, and plasma is the most common. By heating the compressed air or inert gases to create negatively and positively charged particles known as ions, electrically neutral particles in their natural state are formed. Many scientists are currently focusing their efforts on the development of artificial plasma and the possible advantages it may have for humankind in the near future. In the literature, there is a scarcity of information regarding plasma applications. It’s the goal of this page to describe particular methods for creating and using plasma, which may be us

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Publication Date
Wed Mar 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Review on Models for Evaluating Rock Petrophysical Properties
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The evaluation of subsurface formations as applied to oil well drilling started around 50 years ago. Generally, the curent review articule includes all methods for coring, logging, testing, and sampling. Also the methods for deciphering logs and laboratory tests that are relevant to assessing formations beneath the surface, including a look at the fluids they contain are discussed. Casing is occasionally set in order to more precisely evaluate the formations; as a result, this procedure is also taken into account while evaluating the formations. The petrophysics of reservoir rocks is the branch of science interested in studying chemical and physical properties of permeable media and the components of reservoir rocks which are associated

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Publication Date
Sun Jun 30 2024
Journal Name
Journal Of Language Studies
Translation Challenges in Children's Literature: A Comparative Study of Story Narratives
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This paper presents the intricate issues and strategies related to the translation of children's books, and it particularly focuses on the comparative analysis of "The Tale of Peter Rabbit" by Beatrix Potter and "Le Petit Prince" (The Little Prince) by Antoine de Saint-Exupéry. The study finds that the typical problems in translation are, idiomatic expressions, cultural reference, and the voice preservation, along side-sheet-specific challenges which each of the text faces. The translator of Potter's work should have skills of transposing all culturally oriented peculiarities of the UK land to the international audience to keep it accessible. On the contrary, "Le Petit Prince" translation will be the process of capturing the abstra

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Construct an efficient distributed denial of service attack detection system based on data mining techniques
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<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynami

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Residual Network with Attention to Neural Cells Segmentation
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      Many neuroscience applications, including understanding the evolution of the brain, rely on neural cell instance segmentation, which seeks to integrate the identification and segmentation of neuronal cells in microscopic imagery. However, the task is complicated by cell adhesion, deformation, vague cell outlines, low-contrast cell protrusion structures, and background imperfections. On the other hand, existing segmentation approaches frequently produce inaccurate findings. As a result, an effective strategy for using the residual network with attention to segment cells is suggested in this paper. The segmentation mask of neural cells may be accurately predicted. This method is built on U-net, with EfficientNet serving as the e

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