Smart cities need energy and water to develop sustainably and meet economic, social, and environmental goals. These two systems depend actually on each other and are examined as a water-energy nexus. Cyber security is...
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Technologies that providemechanical assistance arerequired inthemdicalfeld,such asimplants that regenerate tssuethroughelongation and *** ofthe challenges is to develop actuators that combinethe benefits ofhigh axiale...
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Technologies that providemechanical assistance arerequired inthemdicalfeld,such asimplants that regenerate tssuethroughelongation and *** ofthe challenges is to develop actuators that combinethe benefits ofhigh axialextension at lowpressures,modularity,multifunction,and load bearing capabilities into one design while maintaining their shape and *** such a challenge wll provide implants with enhanced capacity for mechanical assistance to induce *** introduce two novel actuators(M2H)built of stacked Hyperelastic Balloning Membrane Actuators(HBMAs)that can be realized using helical and toroidal *** restraining the HBMA expansion deterministicallyusing a semisoft exoskeleton,the actuatorsors areendoweded withh axial extension and radial expansion *** actuatorsare thus built of modules that canconfiguured different therapeutical needs and multifunctionality,to provideanatomically congruent *** desigl,fabricationtestin;and numerical and experimental validation ofthe *** can aaxiallyind6 in their helicaland toroidal configurations at input pressuresas low as 26 and 24 kPa,*** the axial module is used separately,its extension capacity reaches>170%.The M2H-HBMAs can perform independent and simultaneousxpansion and extension motions with negligible intraluminaldeformation as well as stand at least 1kg of axial force without *** M2H-HBMAs overcome the limitations ofhyperexpanding machines that show low resistance to *** envisage M2H-HBMAs as promising tools to perform tisueregeneration procedures.
This article deals with the generic model for object monitoring and tracking in an industrial environment and manufacturing. We focus on the design of generic IoT Edge device model that enables the integration of vari...
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This article deals with the generic model for object monitoring and tracking in an industrial environment and manufacturing. We focus on the design of generic IoT Edge device model that enables the integration of various LoRa sensors independently on vendor solutions for common use cases. Our model is based on the MQTT protocol, which is proven for sensor applications and gives needed independency on proprietary protocols. The model was implemented in Node-RED software and subsequently validated with sensors of different vendors to confirm the generic approach and base for independent object tracking solutions. The proposed Edge device model supports independent object tracking, such as object status monitoring, localization and triggered events, giving independent approach for tailored solutions and wide application portfolio based on combined different sensors and devices.
In the current paper, a strategy for handling a stochastic optimization problem based on metaheuristic techniques is presented. This optimization problem is defined based on the impact of environmental factors such as...
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In order to carry out risk warning for high-voltage cable transmission system and realize differentiated operation and maintenance decision-making, it is necessary to carry out time series prediction for online monito...
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Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem ...
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This paper presents the possibility of using statistical modeling to automate the process of dynamic pricing management with revenue control and adaptation to current legislation in this area. In addition, it is propo...
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Multi-carrier microgrids with high renewable energy sources (RES) penetration have recently been modeled and enhanced to meet various needs, such as heat and electricity, while reducing greenhouse gas emissions. This ...
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Weighted vertex cover(WVC)is one of the most important combinatorial optimization *** this paper,we provide a new game optimization to achieve efficiency and time of solutions for the WVC problem of weighted *** first...
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Weighted vertex cover(WVC)is one of the most important combinatorial optimization *** this paper,we provide a new game optimization to achieve efficiency and time of solutions for the WVC problem of weighted *** first model the WVC problem as a general game on weighted *** the framework of a game,we newly define several cover states to describe the WVC ***,we reveal the relationship among these cover states of the weighted network and the strict Nash equilibriums(SNEs)of the ***,we propose a game-based asynchronous algorithm(GAA),which can theoretically guarantee that all cover states of vertices converging in an SNE with polynomial ***,we improve the GAA by adding 2-hop and 3-hop adjustment mechanisms,termed the improved game-based asynchronous algorithm(IGAA),in which we prove that it can obtain a better solution to the WVC problem than using a the ***,numerical simulations demonstrate that the proposed IGAA can obtain a better approximate solution in promising computation time compared with the existing representative algorithms.
Car-following is the most common driving scenario where a following vehicle follows a lead vehicle in the same lane. One crucial factor of car-following behavior is driving style which affects speed and gap selection,...
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Car-following is the most common driving scenario where a following vehicle follows a lead vehicle in the same lane. One crucial factor of car-following behavior is driving style which affects speed and gap selection, acceleration pattern, and fuel consumption. However, existing car-following research used limited categories of driving style through pre-defined patterns and failed to encode driving style into data-driven car-following models. To address these limitations, we propose the Aggressiveness Informed Car-Following (AICF) modeling approach, which embeds driving style as a dynamic input feature in data-driven car-following models. In detail, We design driving aggressiveness tokens using four physical quantities (jerk, acceleration, relative speed, and relative spacing) to capture the heterogeneity of driving aggressiveness. These tokens were then embedded into a physics-informed Long Short-Term Memory (LSTM) based car-following model for trajectory prediction. To evaluate the effectiveness of our approach, we conducted extensive experiments based on 12,540 car-following events extracted from the HighD dataset and 24,093 events from the Lyft dataset. Compared to models devoid of considerations for driving aggressiveness levels, AICF exhibits superior efficacy in mitigating the Mean Square Error (MSE) of spacing and collision rate. To the best of our knowledge, this is the first work to directly incorporate real-time driving aggressiveness tokens as input features into data-driven car-following models, enabling a more comprehensive understanding of aggressiveness in car-following behavior. IEEE
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