Operational loads have both static and dynamic characteristics. Dynamic loads occur during the operation of the considered mechanism, both during acceleration and deceleration periods, as well as during steady motion ...
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This work is concerned with interconnected networks with non-identical subsystems. We investigate the output consensus of the network where the dynamics are subject to external disturbance and/or reference input. For ...
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In the present paper, we investigate the impact of imperfections (non-idealities) of the energy storage system (e.g., batteries, capacitors, or supercapacitors) on the energy performance of green IoT nodes. In particu...
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ISBN:
(数字)9798331531300
ISBN:
(纸本)9798331531317
In the present paper, we investigate the impact of imperfections (non-idealities) of the energy storage system (e.g., batteries, capacitors, or supercapacitors) on the energy performance of green IoT nodes. In particular, we investigate the impact of energy leakage from the Energy Storage System (ESS) on important energy performance metrics, such as service outage probability, the density of the lifetime of the node, and the time-dependent mean number of energy packets (EPs) in the ESS. Also, we explore various strategies that can be employed to compensate for the impact of energy losses due to energy leakage on the energy performance metrics. Specifically, we examine two potential strategies for improving the energy performance of the IoT nodes: (i) through increasing the energy generation rate of the energy harvesters (e.g., by adding additional solar panels or replacing the existing solar panels with more efficient ones that can produce more energy), and (ii) through reducing the energy consumption rate of the IoT node (e.g., by configuring ESS energy thresholds below which the nodes are forced to operate in low energy consumption states).
We design a state-feedback controller, applied via piezoelectric actuators, that suppresses the effect of a distributed disturbance in the Euler-Bernoulli beam with viscous and Kelvin-Voigt damping. The controller is ...
We design a state-feedback controller, applied via piezoelectric actuators, that suppresses the effect of a distributed disturbance in the Euler-Bernoulli beam with viscous and Kelvin-Voigt damping. The controller is designed to improve performance on a finite number of modes. Its effect on the remaining (infinitely many) modes is analysed by constructing an appropriate Lyapunov functional, whose properties are guaranteed by the feasibility of linear matrix inequalities (LMIs). The LMIs allow us to design suitable controller gain and estimate the induced $L^2$ gain. A numerical example demonstrates how this modal decomposition approach leads to a controller that significantly reduces the $L^2$ gain.
The intelligent teaching assistant system, Line-ChatBot based on the ChatGPT API and LINE Bot is used to for homework recommendations and learning guidance. The system uses a generative language model as an accessible...
The intelligent teaching assistant system, Line-ChatBot based on the ChatGPT API and LINE Bot is used to for homework recommendations and learning guidance. The system uses a generative language model as an accessible and cost-effective learning support tool. It has been designed to effectively comprehend and decipher difficulties in doing homework and provides tailored suggestions and guidance. Overall, Line-ChatBot is a tool for aiding students in their learning by offering an efficient, flexible, and natural learning support system. We proposed the application of this system in educational contexts for the innovation and advancement of education.
We consider a recommender system that takes into account the interaction between recommendations and the evolution of user interests. Users opinions are influenced by both social interactions and recommended content. ...
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We consider finite Markov decision processes (MDPs) with convex constraints and known dynamics. In principle, this problem is amenable to off-the-shelf convex optimization solvers, but typically this approach suffers ...
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Pipelines are the most convenient ways to transport fluids (e.g., water, oil, and gas). However, leakage of fluids into the environment results in resource wastage (primarily water, which is becoming a scarce resource...
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ISBN:
(数字)9798350361261
ISBN:
(纸本)9798350361278
Pipelines are the most convenient ways to transport fluids (e.g., water, oil, and gas). However, leakage of fluids into the environment results in resource wastage (primarily water, which is becoming a scarce resource) and environmental pollution (in the case of leakage of toxic fluids like oil and gas). Emerging technologies like the Internet of Things (IoT), Wireless Sensor Networks (WSNs), Artificial Intelligence (AI), distributed computing, and cloud computing enable continuous monitoring of pipelines to detect leakages and corrosion on the pipeline. The main challenge with using battery-powered sensor nodes to monitor pipelines is the energy constraint, necessitating frequent battery replacement. Thus, there is a need to develop energy-saving mechanisms to prolong the lifetime of these sensor nodes. In this paper, we use the diffusion approximation modelling framework in which the data from the experimental testbed are used to model the dynamics of the battery’s energy content and to estimate the mean and variance of the device’s lifetime. The novelty in the proposed diffusion model of the battery of an IoT node is the introduction of multiple energy thresholds that split the energy state-space of the battery into multiple energy-saving regimes. As the battery discharges, the node gradually transitions into energy-saving regimes by reconfiguring some of its parameters to reduce energy consumption (sometimes at the cost of trading off some performance metrics). We investigate the impact of energy-saving regimes or the number of thresholds on the node’s lifetime.
Over the past decade, the continuous surge in cloud computing demand has intensified data center workloads, leading to significant carbon emissions and driving the need for improving their efficiency and sustainabilit...
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ISBN:
(数字)9783907144107
ISBN:
(纸本)9798331540920
Over the past decade, the continuous surge in cloud computing demand has intensified data center workloads, leading to significant carbon emissions and driving the need for improving their efficiency and sustainability. This paper focuses on the optimal allocation problem of batch compute loads with temporal and spatial flexibility across a global network of data centers. We propose a bilevel game-theoretic solution approach that captures the inherent hierarchical relationship between supervisory control objectives, such as carbon reduction and peak shaving, and operational objectives, such as priority-aware scheduling. Numerical simulations with real carbon intensity data demonstrate that the proposed approach success-fully reduces carbon emissions while simultaneously ensuring operational reliability and priority-aware scheduling.
In the realm of maritime transportation, autonomous vessel navigation in natural inland waterways faces persistent challenges due to unpredictable natural factors. Existing scheduling algorithms fall short in handling...
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