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Survey on intrusion detection system based on analysis concept drift: Status and future directions
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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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Publication Date
Fri Jul 14 2023
Journal Name
International Journal Of Information Technology & Decision Making
A Decision Modeling Approach for Data Acquisition Systems of the Vehicle Industry Based on Interval-Valued Linear Diophantine Fuzzy Set
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Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
Damage Detection and Assessment of Stiffness and Mass Matrices in Curved Simply Supported Beam Using Genetic Algorithm
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In this study, a genetic algorithm (GA) is used to detect damage in curved beam model, stiffness as well as mass matrices of the curved beam elements is formulated using Hamilton's principle. Each node of the curved beam element possesses seven degrees of freedom including the warping degree of freedom. The curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory. The identification of damage is formulated as an optimization problem, binary and continuous genetic algorithms
(BGA, CGA) are used to detect and locate the damage using two objective functions (change in natural frequencies, Modal Assurance Criterion MAC). The results show the objective function based on change in natural frequency i

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Publication Date
Tue Feb 18 2025
Journal Name
Plasmonics
A Partial Least Squares (PLS2) Model Based on Kinetic-Spectrophotometric Measurement for the Simultaneous Determination of Tetracycline and Phenylephrine in Binary Mixtures
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Synthesis of Multifunctional Polymers Based on Tert-Butyl Acrylamide/Octyl Acrylate as Lubricant Additives and Adsorbents for Copper Ion from Aqueous Solution
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Two homopolymeric and three copolymeric additives for base oil were synthesized using octyl acrylate (OA) and tert-butyl acrylamide (TBA) monomers. The two additives named P1 and P2 are the homopolymers of TBA and OA, respectively, whereas copolymeric additives named Co1, Co2, and Co3 were synthesized by varying the ratios of TBA:OA as 1:3, 3:1 and 1:1, respectively. The prepared polymers were characterized by Fourier Transform Infrared (FTIR). Based on the solubility of synthesized polymers in base oil and reactivity ratios of TBA/OA copolymer (0.222, 0.434) calculated by Fineman-Ross method, P2, Co1, Co2 and Co3 were selected to evaluate their performance as pour point depressant (PPD), viscosity improver (VII), and anticorrosion addit

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Publication Date
Sat Feb 07 2026
Journal Name
Sensing And Imaging
Manufacturing and Improving Reduced Graphene Oxide (rGO) Membranes for Use as Highly Sensitive Humidity Sensors Based on the Mechanism of Proton Conductivity
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Publication Date
Fri Feb 17 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deploying Facial Segmentation Landmarks for Deepfake Detection
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Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

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Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Emerging Trends Technology In Computer Science
A survey of similarity measures in web image search
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Publication Date
Thu Jun 27 2019
Journal Name
Bulletin Of The Iraq Natural History Museum
SURVEY WITH CHECKLIST OF THE INVASIVE INSECTS TO IRAQ
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Publication Date
Fri Jun 20 2025
Journal Name
Bulletin Of The Iraq Natural History Museum
A SURVEY OF GASTROPODS IN THE GREENHOUSES OF IRAQ
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The humid and warm conditions in greenhouses provide an excellent environment for pests’ living conditions, and therefore, they provide ideal medium for alien introductions. Molluscs are among the most significant pests that infest plastic covered greenhouses. To identify and report their mollusc species, 23 greenhouses in Iraq were surveyed between March 2023 and April 2024. Of these, 11 were found to be infested with snails. A total of 158 specimens were collected and morphologically identified to seven species: Monacha obstructa (L. Pfeiffer, 1842), Eobania vermiculata (O.F. Müller, 1774), Xeropicta krynickii (Krynicki, 1833), Rumina decollata (Linnaeus, 1758), Polygyra cereolus (Megerle Von Mühlfeld, 1818), Cochlicella barba

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Publication Date
Wed Jul 01 2015
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
SURVEY OF BRACHYCERA; DIPTERA FROM SEVERAL REGIONS OF IRAQ
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    A total of 533 specimens were collected in survey of Brachyceran species from different regions of Iraq during February to November 2014 .This study was reported 16 species belonging to 13 genera and 7 families, the results showed that Dicranosepsis Duda, 1926 (Family; Sepsidae) is  recorded the genus  for the first time in Iraq.

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