Developing and optimizing fuzzy relation equations are of great relevance in system modeling,which involves analysis of numerous fuzzy *** each rule varies with respect to its level of influence,it is advocated that t...
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Developing and optimizing fuzzy relation equations are of great relevance in system modeling,which involves analysis of numerous fuzzy *** each rule varies with respect to its level of influence,it is advocated that the performance of a fuzzy relation equation is strongly related to a subset of fuzzy rules obtained by removing those without significant *** this study,we establish a novel framework of developing granular fuzzy relation equations that concerns the determination of an optimal subset of fuzzy *** subset of rules is selected by maximizing their performance of the obtained *** originality of this study is conducted in the following *** with developing granular fuzzy relation equations,an interval-valued fuzzy relation is determined based on the selected subset of fuzzy rules(the subset of rules is transformed to interval-valued fuzzy sets and subsequently the interval-valued fuzzy sets are utilized to form interval-valued fuzzy relations),which can be used to represent the fuzzy relation of the entire rule base with high performance and ***,the particle swarm optimization(PSO)is implemented to solve a multi-objective optimization problem,in which not only an optimal subset of rules is selected but also a parameterεfor specifying a level of information granularity is determined.A series of experimental studies are performed to verify the feasibility of this framework and quantify its performance.A visible improvement of particle swarm optimization(about 78.56%of the encoding mechanism of particle swarm optimization,or 90.42%of particle swarm optimization with an exploration operator)is gained over the method conducted without using the particle swarm optimization algorithm.
An upper bound to the identification capacity of discrete memoryless wiretap channels is derived under the requirement of semantic effective secrecy, combining semantic secrecy and stealth constraints. A previously es...
An upper bound to the identification capacity of discrete memoryless wiretap channels is derived under the requirement of semantic effective secrecy, combining semantic secrecy and stealth constraints. A previously established lower bound is improved by applying it to a prefix channel, formed by concatenating an auxiliary channel and the actual channel. The bounds are tight if the legitimate channel is more capable than the eavesdropper’s channel. An illustrative example is provided for a wiretap channel that is composed of a point-to-point channel, and a parallel, reversely degraded wiretap channel. A comparison with results for message transmission and for identification with only secrecy constraint is provided.
This paper studies multi-microcontroller data acquisition systems in various industries, such as UAV attitude control, predictive maintenance, and healthcare solutions, specifically human-fall detection. We use state-...
This paper studies multi-microcontroller data acquisition systems in various industries, such as UAV attitude control, predictive maintenance, and healthcare solutions, specifically human-fall detection. We use state-of-the-art microcontrollers, L475 and L485I, from the STM32 family to capture sensor data. We propose a five-layered data acquisition architecture, which includes the development of a graphical user interface to make data collection more efficient. We then pre-process the collected data before feeding it to machine learning models and deep neural networks. We use a decision tree classifier for UAV stability control, a gradient boosting classifier for human fall detection, and a multi-layer perceptron classifier for predictive maintenance. The results show the robustness and reliability of the proposed architecture, and it offers promising implications for optimizing maintenance practices, providing safer options, and enhancing patient care.
The paper presents a mathematical model of a submerged evaporator laboratory plant for cooling beer. The model is derived as a system with distributed parameters of the counterclockwise type. Additionally, the results...
The paper presents a mathematical model of a submerged evaporator laboratory plant for cooling beer. The model is derived as a system with distributed parameters of the counterclockwise type. Additionally, the results of the experimental testing of the submerged evaporator laboratory plant are presented and based on such simplified a static model is identified, which is suitable for control system design.
Manipulating external stimuli is crucial for enhancing and controlling the optical response in chiral structures. This study introduces chiral structures composed of single, dimer, or trimer arrays of plasmonic and ma...
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Recent advances in artificial intelligence (AI), coupled with a surge in training data, have led to the widespread use of AI for digital content generation, with ChatGPT serving as an representative example. Despite t...
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The implementation of cyber-physical systems in real-world applications is challenged by safety requirements in the presence of sensor threats. Most cyber-physical systems, in particular the vulnerable multi-sensor sy...
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The objective of this paper is to provide a microfluidic platform that may be useful to manipulate and characterize different submicron particles such as latex spheres as well as viruses (E.g. SARS-COV-2) through the ...
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In this paper, a new framework for the resilient control of continuous-time linear systems under denial-of-service (DoS) attacks and system uncertainty is presented. Integrating techniques from reinforcement learning ...
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In this work, we present a powerful notch filter for power-line interference (PLI) cancelation from biomedical signals. This filter has a unit gain and a zero-phase response. Moreover, the filter can be implemented ad...
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