Hybrid switch reluctance motors are the family of switch reluctance motors (SRMs) that attenuate the magnetic saturation and increase the air gap magnetic flux by exploiting permanent magnets. The permanent magnet aux...
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In late 2019, COVID-19 virus emerged as a dangerous disease that led to millions of fatalities and changed how human beings interact with each other and forced people to wear masks with mandatory lockdown. The ability...
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The escalating installation of distributed generation (DG) within active distribution networks (ADNs) diminishes the reliance on fossil fuels, yet it intensifies the disparity between demand and generation across vari...
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The escalating installation of distributed generation (DG) within active distribution networks (ADNs) diminishes the reliance on fossil fuels, yet it intensifies the disparity between demand and generation across various regions. Moreover, due to the intermittent and stochastic characteristics, DG also introduces uncertain forecasting errors, which further increase difficulties for power dispatch. To overcome these challenges, an emerging flexible interconnection device, soft open point (SOP), is introduced. A distributionally robust chance-constrained optimization (DRCCO) model is also proposed to effectively exploit the benefits of SOPs in ADNs under uncertainties. Compared with conventional robust, stochastic and chance-constrained models, the DRCCO model can better balance reliability and economic profits without the exact distribution of uncertainties. More-over, unlike most published works that employ two individual chance constraints to approximate the upper and lower bound constraints (e.g, bus voltage and branch current limitations), joint two-sided chance constraints are introduced and exactly reformulated into conic forms to avoid redundant conservativeness. Based on numerical experiments, we validate that SOPs' employment can significantly enhance the energy efficiency of ADNs by alleviating DG curtailment and load shedding problems. Simulation results also confirm that the proposed joint two-sided DRCCO method can achieve good balance between economic efficiency and reliability while reducing the conservativeness of conventional DRCCO methods.
Over the past two decades, the rise in video streaming has been driven by internet accessibility and the demand for high-quality video. To meet this demand across varying network speeds and devices, transcoding is ess...
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In the contemporary era of technological advancement,smartphones have become an indispensable part of individuals’daily lives,exerting a pervasive *** paper presents an innovative approach to passenger countingonbuse...
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In the contemporary era of technological advancement,smartphones have become an indispensable part of individuals’daily lives,exerting a pervasive *** paper presents an innovative approach to passenger countingonbuses throughthe analysis ofWi-Fi signals emanating frompassengers’mobile *** study seeks to scrutinize the reliability of digital Wi-Fi environments in predicting bus occupancy levels,thereby addressing a crucial aspect of public *** proposed system comprises three crucial elements:Signal capture,data filtration,and the calculation and estimation of passenger *** pivotal findings reveal that the system demonstrates commendable accuracy in estimating passenger counts undermoderate-crowding conditions,with an average deviation of 20%from the ground truth and an accuracy rate ranging from 90%to 100%.This underscores its efficacy in scenarios characterized by moderate levels of ***,in densely crowded conditions,the system exhibits a tendency to overestimate passenger numbers,occasionally doubling the actual *** acknowledging the need for further research to enhance accuracy in crowded conditions,this study presents a pioneering avenue to address a significant concern in public *** implications of the findings are poised to contribute substantially to the enhancement of bus operations and service quality.
Effective medium theory(EMT)has been widely applied in material science,electromagnetics and photonics to determine the effective material properties for inhomogeneous composites comprising subwavelength *** versatili...
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Effective medium theory(EMT)has been widely applied in material science,electromagnetics and photonics to determine the effective material properties for inhomogeneous composites comprising subwavelength *** versatility of this foundational approach has been established through its application in classical Maxwell-Garnet models,which encompass relatively simple structures。
Data-driven developments in lensless imaging, such as machine learning-based reconstruction algorithms, require large datasets. In this work, we introduce a data acquisition pipeline that can capture from multiple len...
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The degradation of optical remote sensing images due to atmospheric haze poses a significant obstacle,profoundly impeding their effective utilization across various *** methodologies have emerged as pivotal components...
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The degradation of optical remote sensing images due to atmospheric haze poses a significant obstacle,profoundly impeding their effective utilization across various *** methodologies have emerged as pivotal components of image preprocessing,fostering an improvement in the quality of remote sensing *** enhancement renders remote sensing data more indispensable,thereby enhancing the accuracy of target *** defogging techniques based on simplistic atmospheric degradation models have proven inadequate for mitigating non-uniform haze within remotely sensed *** response to this challenge,a novel UNet Residual Attention Network(URA-Net)is *** paradigmatic approach materializes as an end-to-end convolutional neural network distinguished by its utilization of multi-scale dense feature fusion clusters and gated jump *** essence of our methodology lies in local feature fusion within dense residual clusters,enabling the extraction of pertinent features from both preceding and current local data,depending on contextual *** intelligently orchestrated gated structures facilitate the propagation of these features to the decoder,resulting in superior outcomes in haze *** validation through a plethora of experiments substantiates the efficacy of URA-Net,demonstrating its superior performance compared to existing methods when applied to established datasets for remote sensing image *** the RICE-1 dataset,URA-Net achieves a Peak Signal-to-Noise Ratio(PSNR)of 29.07 dB,surpassing the Dark Channel Prior(DCP)by 11.17 dB,the All-in-One Network for Dehazing(AOD)by 7.82 dB,the Optimal Transmission Map and Adaptive Atmospheric Light For Dehazing(OTM-AAL)by 5.37 dB,the Unsupervised Single Image Dehazing(USID)by 8.0 dB,and the Superpixel-based Remote Sensing Image Dehazing(SRD)by 8.5 *** noteworthy,on the SateHaze1k dataset,URA-Net attains preeminence in overall performance,yieldi
With the exponential rise in global air traffic,ensuring swift passenger processing while countering potential security threats has become a paramount concern for aviation *** X-ray baggage monitoring is now standard,...
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With the exponential rise in global air traffic,ensuring swift passenger processing while countering potential security threats has become a paramount concern for aviation *** X-ray baggage monitoring is now standard,manual screening has several limitations,including the propensity for errors,and raises concerns about passenger *** address these drawbacks,researchers have leveraged recent advances in deep learning to design threatsegmentation ***,these models require extensive training data and labour-intensive dense pixelwise annotations and are finetuned separately for each dataset to account for inter-dataset ***,this study proposes a semi-supervised contour-driven broad learning system(BLS)for X-ray baggage security threat instance segmentation referred to as *** research methodology involved enhancing representation learning and achieving faster training capability to tackle severe occlusion and class imbalance using a single training routine with limited baggage *** proposed framework was trained with minimal supervision using resource-efficient image-level labels to localize illegal items in multi-vendor baggage *** specifically,the framework generated candidate region segments from the input X-ray scans based on local intensity transition cues,effectively identifying concealed prohibited items without entire baggage *** multi-convolutional BLS exploits the rich complementary features extracted from these region segments to predict object categories,including threat and benign *** contours corresponding to the region segments predicted as threats were then utilized to yield the segmentation *** proposed C-BLX system was thoroughly evaluated on three highly imbalanced public datasets and surpassed other competitive approaches in baggage-threat segmentation,yielding 90.04%,78.92%,and 59.44%in terms of mIoU on GDXray,SIXray,and Compass-XP,***,the lim
Space/air communications have been envisioned as an essential part of the next-generation mobile communication networks for providing highquality global connectivity. However, the inherent broadcasting nature of wirel...
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Space/air communications have been envisioned as an essential part of the next-generation mobile communication networks for providing highquality global connectivity. However, the inherent broadcasting nature of wireless propagation environment and the broad coverage pose severe threats to the protection of private data. Emerging covert communications provides a promising solution to achieve robust communication security. Aiming at facilitating the practical implementation of covert communications in space/air networks, we present a tutorial overview of its potentials, scenarios, and key technologies. Specifically, first, the commonly used covertness constraint model, covert performance metrics, and potential application scenarios are briefly introduced. Then, several efficient methods that introduce uncertainty into the covert system are thoroughly summarized, followed by several critical enabling technologies, including joint resource allocation and deployment/trajectory design, multi-antenna and beamforming techniques, reconfigurable intelligent surface(RIS), and artificial intelligence algorithms. Finally, we highlight some open issues for future investigation.
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