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.
In this review of literature, the light will be concentrated on the local drugs delivery systems for treating the periodontal diseases. Principles, types, advantages and indications of each type will be discussed in this paper.
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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Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them. This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, c
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The study aims to review the literature on the fundamental changes in Managerial Accounting (MA) in light of accelerating Digital Transformations (DT) and increasing Sustainability Requirements (SR) from 2020 to August 2025, with the purpose of informing researchers and professionals about recent developments. The study relied on a qualitative analysis of the content of a group of studies indexed in the Scopus database. The study included a literature review of topics such as artificial intelligence tools and techniques, cloud computing, linear programming, sustainability reporting, and strategic managerial accounting practices. The study results revealed that accelerated DT improves the efficiency of managerial accounting practices
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Translating news between Arabic and English is more complex than it may initially appear. The process is far more than the process of finding the same words, as it usually touches upon the structural differences, cultural allusions, and in most situations, the ideological pressure. This critical literature review is based on a narrative synthesis of 18 peer-reviewed studies published from 2023 to 2026 and explores the interaction of these factors in real journalistic practice. An even closer examination of the literature indicates that there are three common points of challenge. Firstly, structural and lexical differences between Arabic and English can be observed that have to be constantly adjusted to. Second, cultural and religious allusi
... Show MoreThis review discusses the gingival biotypes, their characteristics, analysis based on the measurement of the dentopapillary complex. Also discuss their response to inflammation, surgery, and ridge healing after tooth extraction, their influence in the behavior of the peri-implant tissue
The concept of the active contour model has been extensively utilized in the segmentation and analysis of images. This technology has been effectively employed in identifying the contours in object recognition, computer graphics and vision, biomedical processing of images that is normal images or medical images such as Magnetic Resonance Images (MRI), X-rays, plus Ultrasound imaging. Three colleagues, Kass, Witkin and Terzopoulos developed this energy, lessening “Active Contour Models” (equally identified as Snake) back in 1987. Being curved in nature, snakes are characterized in an image field and are capable of being set in motion by external and internal forces within image data and the curve itself in that order. The present s
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