In the context of multiple-target tracking and surveillance applications,this paper investigates the challenge of determining the optimal positioning of a single autonomous aerial vehicle or agent equipped with multip...
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In the context of multiple-target tracking and surveillance applications,this paper investigates the challenge of determining the optimal positioning of a single autonomous aerial vehicle or agent equipped with multiple independently-steerable zooming cameras to effectively monitor a set of targets of *** camera is dedicated to tracking a specific target or cluster of *** key innovation of this study,in comparison to existing approaches,lies in incorporating the zooming factor for the onboard cameras into the optimization *** enhancement offers greater flexibility during mission execution by allowing the autonomous agent to adjust the focal lengths of the onboard cameras,in exchange for varying real-world distances to the corresponding targets,thereby providing additional degrees of freedom to the optimization *** proposed optimization framework aims to strike a balance among various factors,including distance to the targets,verticality of viewpoints,and the required focal length for each *** primary focus of this paper is to establish the theoretical groundwork for addressing the non-convex nature of the optimization problem arising from these *** this end,we develop an original convex approximation *** paper also includes simulations of diverse scenarios,featuring varying numbers of onboard tracking cameras and target motion profiles,to validate the effectiveness of the proposed approach.
The effects of changing learning rates, data augmentation percentage and numbers of epochs on the performance of Wasserstein Generative Adversarial Networks with Gradient Penalties (WGAN-GP) are evaluated in this stud...
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The hydrogen energy storage system(HESS)integrated with renewable energy power generation exhibits low reliability and flexibility under source-load *** address the above issues,a two-stage optimal scheduling model co...
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The hydrogen energy storage system(HESS)integrated with renewable energy power generation exhibits low reliability and flexibility under source-load *** address the above issues,a two-stage optimal scheduling model considering the operation sequences of HESSs is proposed for commercial community integrated energy systems(CIESs)with power to hydrogen and heat(P2HH)*** aims to optimize the energy flow of HESS and improve the flexibility of hydrogen production and the reliability of energy supply for ***,the refined operation model of HESS is established,and its operation model is linearized according to the operation domain of HESS,which simplifies the difficulty in solving the optimization problem under the premise of maintaining high approximate ***,considering the flexible start-stop of alkaline electrolyzer(AEL)and the avoidance of multiple energy conversions,the operation sequences of HESS are ***,a two-stage optimal scheduling model combining day-ahead economic optimization and intra-day rolling optimization is established,and the model is simulated and verified using the source-load prediction data of typical days in each *** simulation results show that the two-stage optimal scheduling reduces the total load offset by about 14%while maintaining similar operating cost to the day-ahead economic optimal ***,by formulating the operation sequences of HESS,the operating cost of CIES is reduced by up to about 4.4%.
Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms.K-clustering algorithms are sim...
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Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms.K-clustering algorithms are simplistic,with fast performance and relative ***,their implementation depends on the initial selection of clusters number(K),the initial clusters’centers,and the clustering *** paper investigated using Scott’s histogram formula to estimate the K number and the Link Expiration Time(LET)as a clustering *** traffic flows were considered for three maps,namely Highway,Traffic Light junction,and Roundabout junction,to study the effect of road layout on estimating the K number.A fast version of the PAM algorithm was used for clustering with a modification to reduce time *** Affinity propagation algorithm sets the baseline for the estimated K number,and the Medoid Silhouette method is used to quantify the ***++,Veins,and SUMO were used to simulate the traffic,while the related algorithms were implemented in *** Scott’s formula estimation of the K number only matched the baseline when the road layout was ***,the clustering algorithm required one iteration on average to converge when used with LET.
In this paper, we extend the state-space kriging(SSK) modeling technique presented in a previous work by the authors in order to consider non-autonomous systems. SSK is a data-driven method that computes predictions a...
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In this paper, we extend the state-space kriging(SSK) modeling technique presented in a previous work by the authors in order to consider non-autonomous systems. SSK is a data-driven method that computes predictions as linear combinations of past outputs. To model the nonlinear dynamics of the system, we propose the kernel-based state-space kriging(K-SSK), a new version of the SSK where kernel functions are used instead of resorting to considerations about the locality of the data. Also, a Kalman filter can be used to improve the predictions at each time step in the case of noisy measurements. A constrained tracking nonlinear model predictive control(NMPC) scheme using the black-box input-output model obtained by means of the K-SSK prediction method is proposed. Finally, a simulation example and a real experiment are provided in order to assess the performance of the proposed controller.
Ransomware attacks pose a significant threat to critical infrastructures,demanding robust detection *** study introduces a hybrid model that combines vision transformer(ViT)and one-dimensional convolutional neural net...
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Ransomware attacks pose a significant threat to critical infrastructures,demanding robust detection *** study introduces a hybrid model that combines vision transformer(ViT)and one-dimensional convolutional neural network(1DCNN)architectures to enhance ransomware detection *** common challenges in ransomware detection,particularly dataset class imbalance,the synthetic minority oversampling technique(SMOTE)is employed to generate synthetic samples for minority class,thereby improving detection *** integration of ViT and 1DCNN through feature fusion enables the model to capture both global contextual and local sequential features,resulting in comprehensive ransomware *** on the UNSW-NB15 dataset,the proposed ViT-1DCNN model achieved 98%detection accuracy with precision,recall,and F1-score metrics surpassing conventional *** approach not only reduces false positives and negatives but also offers scalability and robustness for real-world cybersecurity *** results demonstrate the model’s potential as an effective tool for proactive ransomware detection,especially in environments where evolving threats require adaptable and high-accuracy solutions.
When a long distance HVDC transmission system discharges current into the earth through its grounding electrode,ground potential differences appear in a large *** therefore part of the DC current may flow into nearby ...
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When a long distance HVDC transmission system discharges current into the earth through its grounding electrode,ground potential differences appear in a large *** therefore part of the DC current may flow into nearby pipelines which may be dangerous to the equipment and personnel,and may aggravate *** this paper,an equivalent circuit based on the method of moments is introduced to calculate the current and potential distributions along a pipeline with damaged anticorrosive *** current-dependent electrochemical polarization potential between soil and the metal pipe,due to the damage of the anticorrosive coating,is taken into account by using the Newton-Raphson *** circuit is verified through a reduced scale *** examining the circuit,the effect of the damaged anticorrosive coating on the leakage current and the pipe potential with respect to soil along the pipeline is analyzed.
Variable-flux permanent magnet synchronous machines (VF-PMSMs) were proposed to avoid the additional losses of conventional PMSMs during flux weakening (FW) operation at high speeds, as they allow dynamic manipulation...
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The IEEE 1588 Precision Time Protocol (PTP) has emerged as a critical standard for achieving highly accurate time synchronization across distributed systems, particularly where precision and low latency are essential....
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In this paper, a dynamic condition-based maintenance model is presented for a degrading system using a reinforcement learning approach. The system utilises a critical machine with multiple production states, which are...
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