Machine learning is a technique that is widely employed in both the academic and industrial sectors all over the *** learning algorithms that are intuitive can analyse risks and respond swiftly to breaches and securit...
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Machine learning is a technique that is widely employed in both the academic and industrial sectors all over the *** learning algorithms that are intuitive can analyse risks and respond swiftly to breaches and security *** is crucial in offering a proactive security system in the field of *** real time,cybersecurity protects information,information systems,and networks from *** the recent decade,several assessments on security and privacy estimates have noted a rapid growth in both the incidence and quantity of cybersecurity *** an increasing rate,intruders are breaching information *** detection,software vulnerability diagnosis,phishing page identification,denial of service assaults,and malware identification are the foremost cyber-security concerns that require efficient *** have tried a variety of approaches to address the present cybersecurity obstacles and *** a similar vein,the goal of this research is to assess the idealness of machine learning-based intrusion detection systems under fuzzy conditions using a Multi-Criteria Decision Making(MCDM)-based Analytical Hierarchy Process(AHP)and a Technique for Order of Preference by Similarity to Ideal-Solutions(TOPSIS).Fuzzy sets are ideal for dealing with decision-making scenarios in which experts are unsure of the best course of *** projected work would support practitioners in identifying,prioritising,and selecting cybersecurityrelated attributes for intrusion detection systems,allowing them to design more optimal and effective intrusion detection systems.
Automated agriculture processing system are the need of today as food manufacturing industries are suffering great loss on part of defective vegetables and fruits. Many researches are working to develop an automated s...
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Quantum computing and secure communication have gained considerable interest in recent years, as quantum computing has a potent ability to accelerate certain complex problems, such as factoring problems and discrete l...
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A new type of error-control code is proposed in which a signal point within the modulator signal constellation diagram is selected as the target signal point. An incoming signal point is then encoded by using the numb...
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A multi-objective Scheduling approach for large-scale microservice Critical Notification system applications (SCN-DRL) based on Deep Reinforcement Learning is presented. This paper addresses optimization for three obj...
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Photoplethysmography (PPG) signals are vital for monitoring pulse rate, blood pressure, and more, but they are prone to motion artefacts and noise, leading to unreliable data. Assessing PPG signal quality is crucial f...
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The performance of central processing units(CPUs)can be enhanced by integrating multiple cores into a single *** performance can be improved by allocating the tasks using intelligent *** Small tasks wait for long time...
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The performance of central processing units(CPUs)can be enhanced by integrating multiple cores into a single *** performance can be improved by allocating the tasks using intelligent *** Small tasks wait for long time or executes for long time,then CPU consumes more ***,the amount of power consumed by CPUs can be reduced without increasing the *** are used to connect cores,which are organized together to form a network called network on chips(NOCs).NOCs are mainly used in the design of ***,its performance can still be enhanced by reducing power *** main problem lies with task scheduling,which fully utilizes the ***,we propose a novel randomfit algorithm for NOCs based on power-aware *** this algorithm,tasks that are under the same application are mapped to the neighborhoods of the same application,whereas tasks belonging to different applications are mapped to the processor cores on the basis of a series of *** scheduling process is performed during the run *** results show that the proposed randomfit algorithm reduces the amount of power consumed and increases system performance based on effective scheduling.
This research work presents a home automation system based on Li-Fi (Light Fidelity) technology as an alternative to the RF communication systems such as Wi-Fi or Bluetooth. Li-Fi uses visible light for transmitting s...
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Bilateral teleoperation system is referred to as a promising technology to extend human actions and intelligence to manipulating objects *** the tracking control of teleoperation systems,velocity measurements are nece...
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Bilateral teleoperation system is referred to as a promising technology to extend human actions and intelligence to manipulating objects *** the tracking control of teleoperation systems,velocity measurements are necessary to provide feedback ***,due to hardware technology and cost constraints,the velocity measurements are not always *** addition,the time-varying communication delay makes it challenging to achieve tracking *** paper provides a solution to the issue of real-time tracking for teleoperation systems,subjected to unavailable velocity signals and time-varying communication *** order to estimate the velocity information,immersion and invariance(I&I)technique is employed to develop an exponential stability velocity *** the proposed velocity observer,a linear relationship between position and observation state is constructed,through which the need of solving partial differential and certain integral equations can be ***,the mean value theorem is exploited to separate the observation error terms,and hence,all functions in our observer can be analytically *** the estimated velocity information,a slave-torque feedback control law is presented.A novel Lyapunov-Krasovskii functional is constructed to establish asymptotic tracking *** particular,the relationship between the controller design parameters and the allowable maximum delay values is ***,simulation and experimental results reveal that the proposed velocity observer and controller can guarantee that the observation errors and tracking error converge to zero.
In this article,the problem of state estimation is addressed for discrete-time nonlinear systems subject to additive unknown-but-bounded noises by using fuzzy set-membership ***,an improved T-S fuzzy model is introduc...
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In this article,the problem of state estimation is addressed for discrete-time nonlinear systems subject to additive unknown-but-bounded noises by using fuzzy set-membership ***,an improved T-S fuzzy model is introduced to achieve highly accurate approximation via an affine model under each fuzzy ***,compared to traditional prediction-based ones,two types of fuzzy set-membership filters are proposed to effectively improve filtering performance,where the structure of both filters consists of two parts:prediction and *** the locally Lipschitz continuous condition of membership functions,unknown membership values in the estimation error system can be treated as multiplicative noises with respect to the estimation ***-time recursive algorithms are given to find the minimal ellipsoid containing the true ***,the proposed optimization approaches are validated via numerical simulations of a one-dimensional and a three-dimensional discrete-time nonlinear systems.
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