Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermore, various uses in the real world, Data distributions in intrusion detection systems, for example, are non-stationary, which produce concept drift over time or non-stationary learning. The word "concept drift" is used to describe the process of changing one's mind about something in an online-supervised learning scenario, the connection between the input data and the target variable changes over time. We define adaptive learning, classify existing concept drift strategies, evaluate the most typical, distinct, and widely used approaches and algorithms, describe adaptive algorithm assessment methodology, and show a collection of examples, all of this is based on the assumption that you have a basic understanding of supervised learning. The survey examines the various aspects of concept drift in a comprehensive manner in order to think about the current fragmented "state-of-the-art". As a result, which intends to give scholars, industry analysts, and practitioners a comprehensive introduction to idea drift adaptability.
The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi
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Research aims to shed light on the concept of corporate failures , display and analysis the most distinctive models used to predicting corporate failure; with suggesting a model to reveal the probabilities of corporate failures which including internal and external financial and non-financial indicators, A tested is made for the research objectivity and its indicators weight and by a number of academics professionals experts, in addition to financial analysts and have concluded a set of conclusions , the most distinctive of them that failure is not considered a sudden phenomena for the company and its stakeholders , it is an Event passes through numerous stages; each have their symptoms that lead eve
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Background: Oxidative stress may contribute to the etiology of hypertension in humans. Oxidative stress is an imbalance between reactive oxygen species (ROS) and antioxidant defense mechanisms, causing damage to biological macromolecules and dysregulation of normal metabolism and physiology. Amlodipine as an antihypertensive agent is a long-acting calcium channel blocker that dilates blood vessels and improves blood flow. The aim of this study was to assess the oxidative stress in hypertensive patients on Amlodipine treatment through the assessment of salivary Malondialdehyde (MDA) and superoxide dismutase (SOD) as a marker of oxidative stress.
Mat
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Background/Aim There is an association between patient general health, socioeconomic status and fracture incidence. Aim of this study was to demonstrate the relation between the socioeconomic and health status and the occurrence of fractures in Al-Kindy Hospital residents. Methods A prospective cross-sectional study was performed by using data collected from fractured patients in Al-Kindy Teaching Hospital / Baghdad Orthopaedics Outpatient Clinic, between 12 December 2021 and 8 March 2022. A hundred patients aged 20 to 75 years were included in this study. The data were collected using a researcher-administered questionnaire, which included items to assess patient's socioeconomic status (accommodations, occupation, income status, level of e
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يهدف البحث الحالي الى استكشاف علاقات التفاعل والتاثير بين الاحتكام للمكانة والتوجه للفردية– الجماعية والدمج التنظيمي مستنداً على مزج اختلاف القيم الشخصية مع افكار نظرية الهوية الاجتماعية لبلورة نموذج البحث. وفي ضوء هذا تم صياغة عدد من الفرضيات التي توضح علاقات التفاعل ما بين ابعاد الاحتكام للمكانة والتوجه للفردية– الجماعية للتنبؤ بوجود الدمج التنظيمي. جمعت البيانات باستخدام استمارة الاستبيان ووزع
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Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou
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