This work concentrates on Ag, Au, Au@ Ag, and Ag@ Au nanoparticles in various configurations produced through pulsed laser ablation at a wavelength of 532 nm, examining various configurations generated at differe...
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This paper aims to predict and optimize the behavior of solid particle erosion in polymethyl methacrylate material through artificial neural networks assisted with the implementation of metaheuristic algorithms. For t...
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This paper aims to predict and optimize the behavior of solid particle erosion in polymethyl methacrylate material through artificial neural networks assisted with the implementation of metaheuristic algorithms. For the study, artificial neural networks (ANNs) and the corresponding metaheuristic algorithms, such as genetic algorithm (GA), particle swarm optimization (PSO), whale optimization algorithm (WOA), gray wolf optimizer (GWO), student psychology-based optimization algorithm (SPBO), ant lion optimizer (ALO), teaching learning-based optimization (TLBO), equilibrium optimizer (EO), flow direction algorithm (FDA), and covariance matrix adaptation evolution strategy (CMA-ES) have been implemented along with jellyfish search optimizer (JSO) to predict the erosion rate and erosion velocity of poly methyl methacrylate (PMMA) eroded by white aluminum oxide at different impact angles and particle sizes. It was indicated that ANN and metaheuristic prediction models were suited to the experimental results, affirming that the approach used is a successful one in predicting solid particle erosion of polymeric materials. JSO exhibited the most robust results with the lowest standard deviation of the erosion rate. In the present study, it is observed that the experimental data are in good agreement with what is obtained from the ANN model fed with input parameters optimized using various metaheuristic algorithms. In the experiment, characterization with polynomials was done regarding the aluminum oxide (Al2O3) abrasive particles' erosion behavior on PMMA at three different mesh sizes and three different blasting pressures. These polynomials were used as the fitness functions for the metaheuristic algorithms applied. The results show that the combined use of ANNs and metaheuristics yields even higher prediction accuracy than those provided by each alone. The JSO algorithm has demonstrated excellence in erosion rate and amount and in its ability to optimize over other approac
As autonomous vehicles continue to revolutionize transportation, addressing challenges posed by adverse weather conditions, particularly during winter, becomes paramount for ensuring safe and efficient operations. One...
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The robust stability study of the classic Smith predictor-based control system for uncertain fractional-order plants with interval time delays and interval coefficients is the emphasis of this *** uncertainties are a ...
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The robust stability study of the classic Smith predictor-based control system for uncertain fractional-order plants with interval time delays and interval coefficients is the emphasis of this *** uncertainties are a type of parametric uncertainties that cannot be avoided when modeling real-world ***,in the considered Smith predictor control structure it is supposed that the controller is a fractional-order proportional integral derivative(FOPID)*** the best of the authors'knowledge,no method has been developed until now to analyze the robust stability of a Smith predictor based fractional-order control system in the presence of the simultaneous uncertainties in gain,time-constants,and time *** three primary contributions of this study are as follows:ⅰ)a set of necessary and sufficient conditions is constructed using a graphical method to examine the robust stability of a Smith predictor-based fractionalorder control system—the proposed method explicitly determines whether or not the FOPID controller can robustly stabilize the Smith predictor-based fractional-order control system;ⅱ)an auxiliary function as a robust stability testing function is presented to reduce the computational complexity of the robust stability analysis;andⅲ)two auxiliary functions are proposed to achieve the control requirements on the disturbance rejection and the noise ***,four numerical examples and an experimental verification are presented in this study to demonstrate the efficacy and significance of the suggested technique.
The paper introduces a new path-planning robotic system methodology called Collision Avoidance and Routing based on Location Access (CARLA) for use in critical environments such as hospitals and crises where quick act...
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The attention is a scarce resource in decentralized autonomous organizations(DAOs),as their self-governance relies heavily on the attention-intensive decision-making process of“proposal and voting”.To prevent the ne...
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The attention is a scarce resource in decentralized autonomous organizations(DAOs),as their self-governance relies heavily on the attention-intensive decision-making process of“proposal and voting”.To prevent the negative effects of pro-posers’attention-capturing strategies that contribute to the“tragedy of the commons”and ensure an efficient distribution of attention among multiple proposals,it is necessary to establish a market-driven allocation scheme for DAOs’***,the Harberger tax-based attention markets are designed to facilitate its allocation via continuous and automated trading,where the individualized Harberger tax rate(HTR)determined by the pro-posers’reputation is ***,the Stackelberg game model is formulated in these markets,casting attention to owners in the role of leaders and other competitive proposers as *** equilibrium trading strategies are also discussed to unravel the intricate dynamics of attention ***,utilizing the single-round Stackelberg game as an illustrative example,the existence of Nash equilibrium trading strategies is ***,the impact of individualized HTR on trading strategies is investigated,and results suggest that it has a negative correlation with leaders’self-accessed prices and ownership duration,but its effect on their revenues varies under different *** study is expected to provide valuable insights into leveraging attention resources to improve DAOs’governance and decision-making process.
Changes in the Atmospheric Electric Field Signal(AEFS) are highly correlated with weather changes, especially with thunderstorm activities. However, little attention has been paid to the ambiguous weather information ...
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Changes in the Atmospheric Electric Field Signal(AEFS) are highly correlated with weather changes, especially with thunderstorm activities. However, little attention has been paid to the ambiguous weather information implicit in AEFS changes. In this paper, a Fuzzy C-Means(FCM) clustering method is used for the first time to develop an innovative approach to characterize the weather attributes carried by AEFS. First, a time series dataset is created in the time domain using AEFS attributes. The AEFS-based weather is evaluated according to the time-series Membership Degree(MD) changes obtained by inputting this dataset into the FCM. Second, thunderstorm intensities are reflected by the change in distance from a thunderstorm cloud point charge to an AEF apparatus. Thus, a matching relationship is established between the normalized distance and the thunderstorm dominant MD in the space domain. Finally, the rationality and reliability of the proposed method are verified by combining radar charts and expert experience. The results confirm that this method accurately characterizes the weather attributes and changes in the AEFS, and a negative distance-MD correlation is obtained for the first time. The detection of thunderstorm activity by AEF from the perspective of fuzzy set technology provides a meaningful guidance for interpretable thunderstorms.
Although the available traffic data from navigation systems have increased steadily in recent years,it only reflects average travel time and possibly Origin-Destination information as samples,***,the number of vehicle...
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Although the available traffic data from navigation systems have increased steadily in recent years,it only reflects average travel time and possibly Origin-Destination information as samples,***,the number of vehicles participating in the traffic-in other words,the traffic flows being the basic traffic engineering information for strategic planning or even for real-time management-is still missing or only available sporadically due to the limited number of traditional traffic sensors on the network *** tackle this gap,an efficient calibration process is introduced to exploit the Floating Car Data combined with the classical macroscopic traffic assignment *** optimally scaling the Origin-Destination matrices of the sample fleet,an appropriate model can be approximated to provide traffic flow data beside average *** iterative tuning method is developed using a genetic algorithm to realize a complete macroscopic traffic *** method has been tested through two different real-world traffic networks,justifying the viability of the proposed ***,the contribution of the study is a practical solution based on commonly available fleet traffic data,suggested for practitioners in traffic planning and management.
作者:
Rashid, SamadNemati, ArashHealthcare Systems Engineering
Department of Industrial Engineering Faculty of Materials and Industrial Engineering Babol Noshirvani University of Technology Mazandaran Province Babol CityPostal Code: 47148-71167 Iran
Continuous monitoring of individuals’ health, particularly those with chronic diseases, out of healthcare centers could result in lower patient traffic in healthcare centers, much more real-time health control, and f...
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Computational simulationmodels serve as powerful instruments for analysing complex systems, but individually they are often limited in representing systems of an interdisciplinary nature. This paper presents amulti-mo...
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