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.
Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt
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The preparatory phase since it corresponds to adolescence are the most important stages of life , where the individual 's personality to take shape at this stage and start asking questions about the same , trying to discover the positive and negative traits hehas in order to form distinctive character and also is being he have Love Poll For everything that goes on around him.
And attention to cognitive motivation is important for students because the student who owns a motive cognitively looking for self - knowledge with conviction, and learning then be meaningful and lasts long. The motive of knowledge are common in which cognitive components does not mean exclusive knowledge on academic books and research in the narrow borders but a
The idea of carrying out research on incomplete data came from the circumstances of our dear country and the horrors of war, which resulted in the missing of many important data and in all aspects of economic, natural, health, scientific life, etc.,. The reasons for the missing are different, including what is outside the will of the concerned or be the will of the concerned, which is planned for that because of the cost or risk or because of the lack of possibilities for inspection. The missing data in this study were processed using Principal Component Analysis and self-organizing map methods using simulation. The variables of child health and variables affecting children's health were taken into account: breastfeed
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Docetaxel is an effective treatment approved for many types of cancers, but its effectiveness in clinical practice can be compromised by significant occurrence of adverse drug reactions. The aim of the current study was to measure the distribution of adverse drug reactions of docetaxel reported in Iraq and to assess the causality, severity, seriousness, preventability, expectedness and outcome of these adverse reactions. A retrospective study conducted on individual case safety reports from the Iraqi Pharmacovigilance Center / Ministry of Health. The study included 118 individual case safety report containing 236 adverse drug reactions.
Most of the adverse drug reactions were related to skin and subcutaneous tissue disorders(26.7%), f
This paper presents an enhancement technique for tracking and regulating the blood glucose level for diabetic patients using an intelligent auto-tuning Proportional-Integral-Derivative PID controller. The proposed controller aims to generate the best insulin control action responsible for regulating the blood glucose level precisely, accurately, and quickly. The tuning control algorithm used the Dolphin Echolocation Optimization (DEO) algorithm for obtaining the near-optimal PID controller parameters with a proposed time domain specification performance index. The MATLAB simulation results for three different patients showed that the effectiveness and the robustness of the proposed control algorithm in terms of fast gene
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The long-term monitoring of land movements represents the most successful application of the Global Navigation Satellite System (GNSS), particularly the Global Positioning System. However, the application of long term monitoring of land movements depends on the availability of homogenous and consistent daily position time series of stations over a period of time. Such time series can be produced very efficiently by using Precise Point Positioning and Double Difference techniques based on particular sophisticated GNSS processing softwares. Nonetheless, these rely on the availability of GNSS products which are precise satellite orbit and clock, and Earth orientation parameters. Unfortunately, several changes and modifications have been mad
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A security system can be defined as a method of providing a form of protection to any type of data. A sequential process must be performed in most of the security systems in order to achieve good protection. Authentication can be defined as a part of such sequential processes, which is utilized in order to verify the user permission to entree and utilize the system. There are several kinds of methods utilized, including knowledge, and biometric features. The electroencephalograph (EEG) signal is one of the most widely signal used in the bioinformatics field. EEG has five major wave patterns, which are Delta, Theta, Alpha, Beta and Gamma. Every wave has five features which are amplitude, wavelength, period, speed and frequency. The linear
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This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue
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