The work presented in this paper has great significance in improving electromagnetic models based on the strong coupling between the magnetic and electric fields transient equations while considering a realistic rando...
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As internet use in communication networks has grown, fake news has become a big problem. The misleading heading of the news loses the trust of the reader. Many techniques have emerged, but they fail because fraudsters...
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With the recent advancements of deep learning-based methods in image classification,the requirement of a huge amount of training data is inevitable to avoid overfitting ***,supervised deep learning models require labe...
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With the recent advancements of deep learning-based methods in image classification,the requirement of a huge amount of training data is inevitable to avoid overfitting ***,supervised deep learning models require labelled datasets for *** such a huge amount of labelled data requires considerable human effort and *** this scenario,self-supervised models are becoming popular because of their ability to learn even from unlabelled ***,the efficient transfer of knowledge learned by self-supervised models into a target task,is an unsolved *** paper proposes a method for the efficient transfer of know-ledge learned by a self-supervised model,into a target *** such as the number of layers,the number of units in each layer,learning rate,and dropout are automatically tuned in these fully connected(FC)layers using a Bayesian optimization technique called the tree-structured parzen estimator(TPE)approach *** evaluate the performance of the proposed method,state-of-the-art self-supervised models such as SimClr and SWAV are used to extract the learned *** are carried out on the CIFAR-10,CIFAR-100,and Tiny ImageNet *** proposed method outperforms the baseline approach with margins of 2.97%,2.45%,and 0.91%for the CIFAR-100,Tiny ImageNet,and CIFAR-10 datasets,respectively.
This study introduces an adaptive integral sliding mode disturbance observer (AISMDOB)-based robust bidirectional platoon control method, aiming to ensure mesh stability in vehicular systems. Most existing platoon con...
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This study introduces an adaptive integral sliding mode disturbance observer (AISMDOB)-based robust bidirectional platoon control method, aiming to ensure mesh stability in vehicular systems. Most existing platoon control studies only focus on error propagation stability in either the longitudinal or lateral direction, neglecting the uncertainties in kinematics and dynamics of vehicular systems. The study proposes new coupled spacing error dynamics derived from vehicle kinematics and extended look-ahead-based coupled spacing errors to ensure both the longitudinal and lateral error propagation stability (that is, mesh stability) and are subsequently utilized to develop the novel AISMDOB, which improves the existing integral sliding mode disturbance observers (ISMDOBs) by incorporating adaptive estimation of unknown disturbance bounds while preserving their advantages. The AISMDOB-based platoon control method is then proposed using both robust kinematic and dynamic controllers to effectively compensate for the kinematic disturbances and dynamic model uncertainties, thereby reducing chattering phenomenon and ensuring the asymptotic convergence of spacing and velocity errors. Additionally, the proposed method can prevent cutting-corner behaviors during cornering maneuvers by utilizing the coupled spacing error dynamics. Simulation and experimental results verify the effectiveness of the proposed method through comparison with ISMDOB-based, sliding mode control (SMC)-based, and previous extended look-ahead-based methods. IEEE
Tear film,the outermost layer of the eye,is a complex and dynamic structure responsible for tear *** tear film lipid layer is a vital component of the tear film that provides a smooth optical surface for the cornea an...
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Tear film,the outermost layer of the eye,is a complex and dynamic structure responsible for tear *** tear film lipid layer is a vital component of the tear film that provides a smooth optical surface for the cornea and wetting the ocular *** eye syndrome(DES)is a symptomatic disease caused by reduced tear production,poor tear quality,or excessive *** diagnosis is a difficult task due to its multifactorial *** of several clinical tests available,the evaluation of the interference patterns of the tear film lipid layer forms a potential tool for DES *** instrument known as Tearscope Plus allows the rapid assessment of the lipid layer.A grading scale composed of five categories is used to classify lipid layer *** reported work proposes the design of an automatic system employing light weight convolutional neural networks(CNN)and nature inspired optimization techniques to assess the tear film lipid layer patterns by interpreting the images acquired with the Tearscope *** designed framework achieves promising results compared with the existing state-of-the-art techniques.
The microphysical structure of rain has a significant impact on the quality of radio signal transmission in the upcoming deployment of 5G millimetre-wave wireless communications in South Africa. To address this, mitig...
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Computational approaches can speed up the drug discovery process by predicting drug-target affinity, otherwise it is time-consuming. In this study, we developed a convolutional neural network (CNN)-based model named S...
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In vehicular ad-hoc networks (VANETs), ensuring passenger safety requires fast and reliable emergency message broadcasts. The current communication standard for messaging in VANETs is IEEE 802.11p. As IEEE 802.11p all...
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In vehicular ad-hoc networks (VANETs), ensuring passenger safety requires fast and reliable emergency message broadcasts. The current communication standard for messaging in VANETs is IEEE 802.11p. As IEEE 802.11p allows carrier-sense multiple access with collision avoidance (CSMA/CA) in the media access control (MAC) layer. A large contention window ($CW$) value will increase delay, whereas a small $CW$ value will increase the probability of collision. Therefore, adaptive regulation of the $CW$ value is needed to achieve high reliability and low delay in VANETs, in accordance with variations in the environment. However, the traditional MAC protocol cannot achieve the aforementioned requirements. Reinforcement learning (RL) emphasizes the selection of optimal action according to observations of the environment to achieve optimal system performance. In this study, a Q-learning (QL) RL algorithm based on IEEE 802.11p was used to achieve the requirements of adaptive broadcasting. Adaptive broadcasting was achieved based on a reward definition of high reliability and low delay for the QL algorithm. In this approach, the learning state is the $CW$ size, the system sets up a Q-table using RL, and the optimal action is based on the maximum Q-value. The $CW$ size can be provided with adaptive self-regulation by RL, providing high reliability and low delay for the broadcast of emergency messages. We also compared our proposed scheme to other QL-based MAC protocols in VANETs by performing simulations and demonstrated that it can achieve high reliability and low delay for the broadcast of emergency messages. IEEE
In the realm of medical datasets, particularly when considering diabetes, the occurrence of data incompleteness is a prevalent issue. Unveiling valuable patterns through medical data analysis is crucial for early and ...
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Photovoltaic(PV)modules age with time for various reasons such as corroded joints and terminals and glass coating defects,and their ageing degrades the PV array *** the help of the PV array numerical model,this paper ...
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Photovoltaic(PV)modules age with time for various reasons such as corroded joints and terminals and glass coating defects,and their ageing degrades the PV array *** the help of the PV array numerical model,this paper explores the effects of PV module ageing on the PV array power,and the power gains and costs of rearranging and recabling aged PV modules in a PV *** numerical PV array model is first revised to account for module ageing,rearrangement and recabling,with the relevant equations presented *** updated numerical model is then used to obtain the array powers for seven different PV *** power results are then analysed in view of the attributes of the seven PV array examples.A guiding method to recommend recabling after rearranging aged modules is then proposed,leading to further significant power gains,while eliminating intra-row *** certain conditions are met,it was shown that recabling PV modules after rearranging them may lead to further significant power gains,reaching 57%and 98%in two considered PV array *** gains are possible in other arrays.A cost-benefit analysis weighing annual power gains versus estimated recabling costs is also given for the seven considered PV array examples to guide recabling decisions based on technical and economic *** the considered examples,recabling costs can be recovered in<4 *** with the powers of the aged arrays,power gains due to our proposed rearranging and recabling the PV arrays ranged between 73%and 131%in the considered examples—well over the gains reported in the ***,the cost of our static module rearrangement and recabling method outshines the costs of dynamic reconfiguration methods recently published in the literature.
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