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.
A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.
This study aims to measure and analyze the direct and indirect effects of the financial variables, namely (public spending, public revenues, internal debt, and external debt), on the non-oil productive sectors with and without bank credit as an intermediate variable, using quarterly data for the period (2004Q1–2021Q4), converted using Eviews 12. To measure the objective of the study, the path analysis method was used using IBM SPSS-AMOS. The study concluded that the direct and indirect effects of financial variables have a weak role in directing bank credit towards the productive sectors in Iraq, which amounted to (0.18), as a result of market risks or unstable expectations in the economy. In addition to the weak credit ratings of borr
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KE Sharquie, A Noaimi, W Al-Janabi, American Journal of Dermatology and Venereology, 2014 - Cited by 4
Background: Nutrition and diet can affect the development and integrity of the oral cavity including the development and eruption of primary teeth. Aims of the study: The study was carried out to determine the effect of weight status of the child and gender on the number of deciduous teeth erupted in the oral cavity. Material and method: A children from the age 12 months -35 months attending Specialist Health Center and children of Nursery in Al-Khadraa, and nursery in Al- Aadamyia and Hay-Heteen. The number of teeth erupted, gender and body mass index were recorded. Results: The results showed that eruption of primary dentition was quicker in children who were overweight than those with normal weight and underweight and faster in girls
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Information security in data storage and transmission is increasingly important. On the other hand, images are used in many procedures. Therefore, preventing unauthorized access to image data is crucial by encrypting images to protect sensitive data or privacy. The methods and algorithms for masking or encoding images vary from simple spatial-domain methods to frequency-domain methods, which are the most complex and reliable. In this paper, a new cryptographic system based on the random key generator hybridization methodology by taking advantage of the properties of Discrete Cosine Transform (DCT) to generate an indefinite set of random keys and taking advantage of the low-frequency region coefficients after the DCT stage to pass them to
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This research is aimed at identifying the communicative habits and the impact of the content on the communicative process, especially the youth audience, which is one of the most important categories to which the advertisement is directed, as young people face life with passion and aspiration that make then responsive to all the influences used by the media in designing advertisements which use all the techniques and methocls to attract young people, such as relying on drama , artistic tricks, musical phrases and advertising slogans that respond to the desire of young people in entertainment.
The research aims to identify the reflection of television advertising and its impact on the development of the cognitive abilities of universi
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Purpose: The research aims to diagnose the current availability of knowledge workers characteristics and the role of these characteristics in knowledge acquision in the city of Sulaimaniya Directorate of Electricity, and to identify the differences between personal and occupational characteristics of a sample of research and its impact on the availability of such properties.Design/methodology/approach :to achieve the objectives of the research questionnaire was developed especially for it and then distributed to a sample of engineers and technicians working in the Directorate of Electricity city of Sulaimaniya, where the sample of the research (52) respondents.
Findings: the most important conclusions reached
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
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