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.
This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,
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An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to
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Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa
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In Production and Operations Management the specialists have tried to develop a strategy to counter the risks arising from the activities of the organization and of waste of various types and therefore the risk management in the contemporary framework represents a phenomenon of new quality, and can not be this phenomenon to take practical dimensions, but the development of culture of the organization towards the risks and deal with all aspects and paint ways to address them within an integrated program, and requires new skills and systems provide accurate information capable of coordination between the various parties within the organization.
The research aims to develop a blu
... Show MoreThe objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.
... Show MoreDespite the importance of this term in linguistics and rhetoric ancient and modern literary forms in general, is that it is possible to use in clarifying the foundations of the relationship hidden and manifest between shapes in models art adjacent or successive spatially, as the artwork plastic in general and sculpture in particular consists of formal structure somewhat similar to the structure in any language text and we can decode these blades structure and analyze the implications and come to their meanings and re-read and interpreted under the guidance of the concepts and techniques of neighboring developed primarily for linguistic analysis of texts or launched from their references. This split search to four chapters included the fi
... Show MoreThe Present study aims to shed some light on the concept of authority of university students and to find statistically significant differences as regards this concepts in accordance with three variables gender (males, females),field of study(scientific ,humanities)and grade(second ,fourth). To accomplish the study a ( 7) level scale was developed for the concept of authority and it subjected to validity and credibility the scale was used with 590 student sample (237) males and (353) females Results show that male students show obedience to authority forms below the Avery e component with the theoretical Avery of the scale besides ,reinforcement was on the top of authority chain ,followed by person traits ,friends, affect punishment and t
... Show MoreReceipt date:10/8/2019 acceptance date:18/12/2019 Publication date:31/12/2021
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This research is concerned with the concept of identity in general "Overall definition" and is not exposed to the classifications of identity or concepts that deal with their types and classifications, only the concept in terms of the initial picture as well as the views of thinkers on the proof of
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Abstract : The concept of moderation is one of the important concepts that have been discussed in political thought in general and in Islamic political thought in particular. It concerns the status of moderation and balance and the need of Islamic societies to apply them in contemporary times. The Islamic societies faced challenges facing Islamic advancement. And the right, which is the middle between the excessive and the excessive -and the exaggeration and cost-, and between negligence and default, moderation and integritybetween both two sides are: excessive and negligent". In addition, the concept of moderation and its intellectual roots have been sought in the Holy Quran and the noble prophetic, and the search for its charac
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This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat
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