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.
In this paper the queuing system (M/Er/1/N) has been considered in equilibrium. The method of stages introduced by Erlang has been used. The system of equations which governs the equilibrium probabilities of various stages has been given. For general N the probability of j stages of service are left in the system, has been introduced. And the probability for the empty system has been calculated in the explicit form.
For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers
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Background: Periodontal diseases (PD) are common chronic inflammatory diseases caused by pathogenic microorganisms colonizing the gingival area and inducing local and systemic elevations of pro-inflammatory cytokines resulting in tissue destruction by a destructive inflammatory process. Stress was considered as one of the important risk factors that cause many inflammatory diseases including PD. The purpose of this study wasto determines and compares clinical periodontal parameters (PLI, GI and BOP), stress level and salivary IL-1? level among dental students before, during and after mid-year exam, also to find the correlation among stress, IL-1? and clinical periodontal parameters. Materials and methods: The sample was consisted of 24 dent
... Show MoreBackground: COVID-19 is an ongoing disease that caused, and still causes, many challenges for humanity. In fact, COVID-19 death cases reached more than 4.5 million by the end of August 2021, although an improvement in the medical treatments and pharmaceutical protocols was obtained, and many vaccines were released. Objective: To, statistically, analyze the data of COVID-19 patients at Alshifaa Healthcare Center (Baghdad, Iraq). Methods: In this work, a statistical analysis was conducted on data included the total number, positive cases, and negative cases of people tested for COVID-19 at the Alshifaa Healthcare Center/Baghdad for the period 1 September – 31 December 2020. The number of people who got the test was 1080, where 424 w
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The purpose of this paper is to investigate Religious Human Rights Violations. Religious liberty is essential for everyone, everywhere. Because religion is significant to everyone, everywhere. Humans are religious by nature. Our nature drives us to seek answers to deep questions about ultimate things. We cannot live a fully human life unless we are free to seek those answers and live according to the truths we discover. In this study, the researcher used Marsh and White model for analysis A sample of an offensive image of an Islamic concept from the book "Mohammad believes it or else." this book is a comic book written by pseudonym Abdullah Aziz and published by Crescent Moon Publishing company. The book is marked with anti- Mohammad, preju
... Show MoreCarbonate reservoirs are an essential source of hydrocarbons worldwide, and their petrophysical properties play a crucial role in hydrocarbon production. Carbonate reservoirs' most critical petrophysical properties are porosity, permeability, and water saturation. A tight reservoir refers to a reservoir with low porosity and permeability, which means it is difficult for fluids to move from one side to another. This study's primary goal is to evaluate reservoir properties and lithological identification of the SADI Formation in the Halfaya oil field. It is considered one of Iraq's most significant oilfields, 35 km south of Amarah. The Sadi formation consists of four units: A, B1, B2, and B3. Sadi A was excluded as it was not filled with h
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The need for participants’ performance assessments in academia and industry has been a growing concern. It has attendance, among other metrics, is a key factor in engendering a holistic approach to decision-making. For institutions or organizations where managing people is an important yet challenging task, attendance tracking and management could be employed to improve this seemingly time-consuming process while keeping an accurate attendance record. The manual/quasi-analog approach of taking attendance in some institutions could be unreliable and inefficient, leading to inaccurate computation of attendance rates and data loss. This work, therefore, proposes a system that employs embedded technology and a biometric/ w
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<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver & kroeber, overlap, and pearson correlation
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