The reasoning performance of Large Language Models (LLMs) on a wide range of problems critically relies on chain-of-thought prompting, which involves providing a few chain of thought demonstrations as exemplars in pro...
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AI and reinforcement learning (RL) have attracted great attention in the study of multiplayer systems over the past decade. Despite the advances, most of the studies are focused on synchronized decision-making to atta...
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In this article, a new coupled-inductors based three-level bipolar buck-boost ac-ac converter is proposed. The proposed converter can produce highly efficient and symmetric in-phase and antiphase buck and boost modes ...
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作者：
Alzaher, Hussain A.Alkhalifa, Ibrahim M.
Department of Electrical Engineering Dhahran31261 Saudi Arabia
Irc for Communication Systems and Sensing Dhahran31261 Saudi Arabia
Department of Electrical and Computer Engineering Thuwal23955 Saudi Arabia
This paper investigates the application of the operational current amplifier (OCA) in the design of quadrature sinusoidal oscillators. There are numerous quadrature sinusoidal oscillators based on the three fundamenta...
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Object detection has become an increasingly important application for mobile devices. However, state-of-the-art object detection relies heavily on deep neural network, which is often burdensome to compute on mobile de...
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The growing demand for reliable and sustainable energy has driven researchers and engineers to explore renewable energy sources to complement traditional power grids. Wind energy conversion systems (WECS), particularl...
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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
Amidst rising distributed generation and its potential role in grid management, this article presents a new realistic approach to determine the operational space and flexibility potential of an unbalanced active distr...
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To detect the improper sitting posture of a person sitting on a chair,a posture detection system using machine learning classification has been proposed in this *** addressed problem correlates to the third Sustainabl...
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To detect the improper sitting posture of a person sitting on a chair,a posture detection system using machine learning classification has been proposed in this *** addressed problem correlates to the third Sustainable Development Goal(SDG),ensuring healthy lives and promoting well-being for all ages,as specified by the World Health Organization(WHO).An improper sitting position can be fatal if one sits for a long time in the wrong position,and it can be dangerous for ulcers and lower spine *** novel study includes a practical implementation of a cushion consisting of a grid of 3×3 force-sensitive resistors(FSR)embedded to read the pressure of the person sitting on ***,the Body Mass Index(BMI)has been included to increase the resilience of the system across individual physical variances and to identify the incorrect postures(backward,front,left,and right-leaning)based on the five machine learning algorithms:ensemble boosted trees,ensemble bagged trees,ensemble subspace K-Nearest Neighbors(KNN),ensemble subspace discriminant,and ensemble RUSBoosted *** proposed arrangement is novel as existing works have only provided simulations without practical implementation,whereas we have implemented the proposed design in *** results validate the proposed sensor placements,and the machine learning(ML)model reaches a maximum accuracy of 99.99%,which considerably outperforms the existing *** proposed concept is valuable as it makes it easier for people in workplaces or even at individual household levels to work for long periods without suffering from severe harmful effects from poor posture.
This paper presents a high-security medical image encryption method that leverages a novel and robust sine-cosine *** map demonstrates remarkable chaotic dynamics over a wide range of *** employ nonlinear analytical t...
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This paper presents a high-security medical image encryption method that leverages a novel and robust sine-cosine *** map demonstrates remarkable chaotic dynamics over a wide range of *** employ nonlinear analytical tools to thoroughly investigate the dynamics of the chaotic map,which allows us to select optimal parameter configurations for the encryption *** findings indicate that the proposed sine-cosine map is capable of generating a rich variety of chaotic attractors,an essential characteristic for effective *** encryption technique is based on bit-plane decomposition,wherein a plain image is divided into distinct bit *** planes are organized into two matrices:one containing the most significant bit planes and the other housing the least significant *** subsequent phases of chaotic confusion and diffusion utilize these matrices to enhance *** auxiliary matrix is then generated,comprising the combined bit planes that yield the final encrypted *** results demonstrate that our proposed technique achieves a commendable level of security for safeguarding sensitive patient information in medical *** a result,image quality is evaluated using the Structural Similarity Index(SSIM),yielding values close to zero for encrypted images and approaching one for decrypted ***,the entropy values of the encrypted images are near 8,with a Number of Pixel Change Rate(NPCR)and Unified Average Change Intensity(UACI)exceeding 99.50%and 33%,***,quantitative assessments of occlusion attacks,along with comparisons to leading algorithms,validate the integrity and efficacy of our medical image encryption approach.
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