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 study, iron was coupled with copper to form a bimetallic compound through a biosynthetic method, which was then used as a catalyst in the Fenton-like processes for removing direct Blue 15 dye (DB15) from aqueous solution. Characterization techniques were applied on the resultant nanoparticles such as SEM, BET, EDAX, FT-IR, XRD, and zeta potential. Specifically, the rounded and shaped as spherical nanoparticles were found for green synthesized iron/copper nanoparticles (G-Fe/Cu NPs) with the size ranging from 32-59 nm, and the surface area was 4.452 m2/g. The effect of different experimental factors was studied in both batch and continuous experiments. These factors were H2O2 concentration, G-Fe/CuNPs amount, pH, initial DB15
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The security of message information has drawn more attention nowadays, so; cryptography has been used extensively. This research aims to generate secured cipher keys from retina information to increase the level of security. The proposed technique utilizes cryptography based on retina information. The main contribution is the original procedure used to generate three types of keys in one system from the retina vessel's end position and improve the technique of three systems, each with one key. The distances between the center of the diagonals of the retina image and the retina vessel's end (diagonal center-end (DCE)) represent the first key. The distances between the center of the radius of the retina and the retina vessel's end (ra
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Objective(s): To determine the effect of obesity and socioeconomic status upon adolescents' high school students' intelligence quotient in Baghdad City. Methodology: A descriptive design is carried throughout the study to determine the effect of obesity and socioeconomic status on adolescents' high schools students' intelligence quotient in Baghdad City for the period of January 7th 2017 to May 29th 2017. A non-probability, purposive sample, of (120) high school students, is selected. The sample is comprised of (12) students from 7th grade, (26) students from 8 th grade, (14) students from 9th grade, (3
The aim of the currnet study to examine the effect of subclinical hypothyroidism (SCH) in diabetic patients on coagulation parameters. This retrospective case–control study involves 130 patients diagnosed with type 2 diabetes mellitus (T2DM), divided into 65 T2DM with newly diagnosed SCH and 65 euthyroid (EUT) T2DM patients without SCH. Fibrinogen (FIB) was significantly higher in SCH (508.2 ± 63.0 mg/dL) than EUT (428.1 ± 44.8 mg/dL). In the SCH patients, FIB correlated with several parameters, such as age (β = 0.396), body mass index (β = 0.578), glycated hemoglobin (β = 0.281), and activated partial thromboplastin time (β = 0.276). In conclusion SCH in DM patients appears to increase the magnitude of coagulopathy.
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The laser micro-cutting process is the most widely commonly applied machining process which can be applied to practically all metallic and non-metallic materials. While this had challenges in cutting quality criteria such as geometrical precision, surface quality and numerous others. This article investigates the laser micro-cutting of PEEK composite material using nano-fiber laser, due to their significant importunity and efficiency of laser in various manufacturing processes. Design of experiential tool based on Response Surface Methodology (RSM)-Central Composite Design (CCD) used to generate the statistical model. This method was employed to analysis the influence of parameters including laser speed,
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Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of
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Features is the description of the image contents which could be corner, blob or edge. Corners are one of the most important feature to describe image, therefore there are many algorithms to detect corners such as Harris, FAST, SUSAN, etc. Harris is a method for corner detection and it is an efficient and accurate feature detection method. Harris corner detection is rotation invariant but it isn’t scale invariant. This paper presents an efficient harris corner detector invariant to scale, this improvement done by using gaussian function with different scales. The experimental results illustrate that it is very useful to use Gaussian linear equation to deal with harris weakness.
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This paper focuses on the most important element of scientific research: the research problem which is confined to the concept of concern or concern surrounding the researcher about any event or phenomenon or issue paper and need to be studied and addressed in order to find solutions for them, to influence the most scientific research steps from asking questions and formulating hypotheses, to employ suitable methods and tools to choose the research and sample community, to employ measurement and analysis tools. This problem calls for a great effort by the researcher intellectually or materially to develop solutions.
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