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.
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Background: Odontogenisis is a complex process controlled by dynamic and reciprocal interactions that regulated by various molecules. Thymosin β4 is a small bioactive peptide with wide spectrum biological effects on much cell types. The present study was designed to highlight the effect of synthetic exogenous Tβ4 on developing dental tissue of the upper central teeth of rats, by histological examination and immunohistochemical evaluation of TGFβ1. Materials and method: Thirty six Albino Wister pregnant rat 18control group received intraperitoneal injection of normal saline and the others are experimental group received 50µg/300µl of Tβ4 injection. The animals were sacrificed at periods 16th and 18th day I.U.L and one day p
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An experiment was conducted to study how SAE 50 engine oil contaminated with diesel fuel affects engine performance. The engine oil was contaminated with diesel fuel at concentrations of 0%, 1%, and 3%. The following performance characteristics were studied: brake-specific fuel consumption, brake thermal efficiency, friction power, and exhaust gas temperature. Each treatment was tested three times. The three treatments (0%, 1%, and 3%) were analyzed statistically with a one-way ANOVA model at the 5% probability level to determine if the three treatments produced significant differences in engine performance. The statistical results showed that there were significant differences in engine performance metrics among the three treatments. The 3
... Show MoreThe study aimed to identify the news framing on the Israeli Arabic-speaking i24 channel of the Israeli aggression on Gaza -2021 by analyzing the channel’s Program “this evening”. The study used the media survey method, and in its framework, it relied on the content analysis method for the program’s episodes from May 5, 2021 AD until June 4, 2021 AD, with 22 episodes. The study showed the program’s interest in launching the Palestinian resistance’s rockets significantly, followed by the Israeli military operations, and the program’s reliance on correspondents largely as a source of news material related to the aggression. It also proved that a news report and a reporter's report was the most important form of presenting news
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Administrative procedures in various organizations produce numerous crucial records and data. These
records and data are also used in other processes like customer relationship management and accounting
operations.It is incredibly challenging to use and extract valuable and meaningful information from these data
and records because they are frequently enormous and continuously growing in size and complexity.Data
mining is the act of sorting through large data sets to find patterns and relationships that might aid in the data
analysis process of resolving business issues. Using data mining techniques, enterprises can forecast future
trends and make better business decisions.The Apriori algorithm has bee
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This paper presents a numerical simulation of the flow around elliptic groynes by using CFD software. The flow was simulated in a flume with 4m long, 0.4m wide, and 0.175m high with a constant bed slope. Moreover, the first Groyne placed at 1m from the flow inlet with a constant the Groyne height of 10cm and a 1cm thickness, and the width of Groynes equals 7cm. A submergence ratio of the elliptic Groynes of 75% was assumed, corresponding to a discharge of 0.0057m3/sec. The CFD model showed a good ability to simulate the flow around Groynes with good accuracy. The results of CFD software showed that when using double elliptic Groy
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This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters (as done in the first edition 2019). Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. While the revised new chapters have been added (as the curr
... Show MoreThis Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters (as done in the first edition 2019). Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. While the revised new chapters have been added (as the curr
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