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.
The Multiple Signal Classification (MUSIC) algorithm is the most popular algorithm to estimate the Angle of Arrival (AOA) of the received signals. The analysis of this algorithm (MUSIC) with typical array antenna element ( ) shows that there are two false direction indication in the plan
aligned with the axis of the array. In this paper a suggested modification on array system is proposed by using two perpendiculars crossed dipole array antenna in spite of one array antenna. The suggested modification does not affect the AOA estimation algorithm. The simulation and results shows that the proposed solution overcomes the MUSIC problem without any effect on the performance of the system.
Competitive swimming is a highly researched area and technological developments have aided advances in the understanding of the biomechanical principles that underpin these elements and govern propulsion. Moreover, those working in the sports field especially in swimming are interested in studying, analyzing, evaluating and developing motor skills by diagnosing the strengths and weaknesses of the skill, and accordingly, coaches and specialists correct these errors. The researchers chose this (Butterfly swimming) and the (arm length) is an important variable because the success of the stroke is greatly dependent on the propulsion generated from the arm pull, and swimmers with a longer arm span have a mechanical advantage with the resulting f
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The World witnessed over the past few decades a clear change in the urban existence map, where the number of cities' residents has increased and the cities geographic area expanded, also networks of roads and electric power stations were spread. This extraordinary events caused the drawing of a different identity to the world, race with itself in the field of energy and raw materials consumption. Therefore, the research issue individualizes in the lack of available knowledge concerning the subject of environment friendly ecological urban desiging and planning.So the research aims to define the environmentally friendly eco-city' structural elements and to clarify their most important planning and design foundations. To In
... Show MoreIn this paper, the general framework for calculating the stability of equilibria, Hopf bifurcation of a delayed prey-predator system with an SI type of disease in the prey population, is investigated. The impact of the incubation period delay on disease transmission utilizing a nonlinear incidence rate was taken into account. For the purpose of explaining the predation process, a modified Holling type II functional response was used. First, the existence, uniform boundedness, and positivity of the solutions of the considered model system, along with the behavior of equilibria and the existence of Hopf bifurcation, are studied. The critical values of the delay parameter for which stability switches and the nature of the Hopf bifurcat
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Energy use is second to staffing in building operating costs. Sustainable technology in the energy sector is based on utilizing renewable sources of energy such as solar, wind, glazing systems, insulation. Other areas of focus include heating, ventilation and air conditioning; novel materials and construction methods; improved sensors and monitoring systems; and advanced simulation tools that can help building designers make more energy efficient choices. The objective of this research is studying the effect of insulations on energy consumption of buildings in Iraq and identifying the amount of energy savings from application th
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The petroleum sector has a significant influence on the development of multiphase detection sensor techniques; to separate the crude oil from water, the crude oil tank is used. In this paper, a measuring system using a simple and low cost two parallel plate capacitance sensor is designed and implemented based on a Micro controlled embedded system plus PC to automatically identify the (gas/oil) and (oil/water) dynamic multi-interface in the crude oil tank. The Permittivity differences of two-phase liquids are used to determine the interface of them by measuring the relative changes of the sensor’s capacitance when passes through the liquid’s interface. The experiment results to determine the liquid’s interface is sa
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Target tracking is a significant application of wireless sensor networks (WSNs) in which deployment of self-organizing and energy efficient algorithms is required. The tracking accuracy increases as more sensor nodes are activated around the target but more energy is consumed. Thus, in this study, we focus on limiting the number of sensors by forming an ad-hoc network that operates autonomously. This will reduce the energy consumption and prolong the sensor network lifetime. In this paper, we propose a fully distributed algorithm, an Endocrine inspired Sensor Activation Mechanism for multi target-tracking (ESAM) which reflecting the properties of real life sensor activation system based on the information circulating principle in the endocr
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In developing countries, conventional physico-chemical methods are commonly used for removing contaminants. These methods are not efficient and very costly. However, new in site strategy with high treatment efficiency and low operation cost named constructed wetland (CW) has been set. In this study, Phragmites australis was used with free surface batch system to estimate its ability to remediate total
petroleum hydrocarbons (TPH) and chemical oxygen demand (COD) from Al-Daura refinery wastewater. The system operated in semi-batch, thus, new wastewater was weekly added to the plant for 42 days. The results showed high removal percentages (98%) of TPH and (62.3%) for COD. Additionally, Phragmites australis biomass increased significant
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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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