Alzheimer’s disease (AD) is a persistent neurological disorder with almost no current cure, although available medications can mitigate its progression. The timely identification and staging of AD is pivotal in imped...
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In edge control systems(ECSs),edge computing demands more local data processing power,while traditional industrial programmable logic controllers(PLCs)cannot meet this ***,edge intelligent controllers(EICs)have been d...
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In edge control systems(ECSs),edge computing demands more local data processing power,while traditional industrial programmable logic controllers(PLCs)cannot meet this ***,edge intelligent controllers(EICs)have been developed,making their secure and reliable operation ***,as EICs communicate sensitive information with resource-limited terminal devices(TDs),a low-cost,efficient authentication solution is urgently needed since it is challenging to implement traditional asymmetric cryptography on *** this paper,we design a lightweight authentication scheme for ECSs using low-computational-cost hash functions and exclusive OR(XOR)operations;this scheme can achieve bidirectional anonymous authentication and key agreement between the EIC and TDs to protect the privacy of the *** security analysis,we demonstrate that the authentication scheme can provide the necessary security features and resist major known *** analysis and comparisons indicate that the proposed authentication scheme is effective and feasible for deployment in ECSs.
Abstract: The hole transport layer (HTL) and electron transport layer (ETL) materials are critical in the CZTS photovoltaic (PV) cell, which provides excellent hole and electron capturing rates and a low minority carr...
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In academic institutions, the gathering of students within buildings significantly influences the ecological parameters of these spaces. Understanding and enhancing the environmental impact of academic buildings requi...
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Processing underwater digital images is critical in ocean engineering,biology,and environmental studies,focusing on challenges such as poor lighting,image de-scattering,and color *** to environmental conditions on the...
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Processing underwater digital images is critical in ocean engineering,biology,and environmental studies,focusing on challenges such as poor lighting,image de-scattering,and color *** to environmental conditions on the sea floor,improving image contrast and clarity is essential for underwater navigation and obstacle *** in turbid,low-visibility waters,we require robust computer vision techniques and *** the past decade,various models for underwater image enrichment have been proposed to address quality and visibility issues under dynamic and natural lighting *** research article aims to evaluate various image improvement methods and propose a robust model that improves image quality,addresses turbidity,and enhances color,ultimately improving obstacle avoidance in autonomous *** proposed model demonstrates high accuracy compared to traditional *** result analysis indicates the proposed model produces images with greatly improved visibility and exceptional color ***,research can unlock new possibilities for underwater exploration,monitoring,and intervention by advancing the state-of-the-art models in this domain.
In the present study, the multiple rectangular and a plus shaped slots microstrip patch antenna (MPA) is designed and its performance has been analysed on the basis of various dielectric constants material such as sil...
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The conventional reconfigurable intelligent surface(RIS) is limited to reflecting incident signals,thereby imposing constraints on the placement of the transmitter and receiver, which hinders achieving comprehensive s...
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The conventional reconfigurable intelligent surface(RIS) is limited to reflecting incident signals,thereby imposing constraints on the placement of the transmitter and receiver, which hinders achieving comprehensive signal coverage across an entire area. This paper investigates a simultaneously transmitting and reflecting(STAR)-RIS-aided simultaneous wireless information and power transfer(SWIPT) system with a nonlinear energy harvesting model under three different RIS transmission protocols: energy splitting(ES),time switching(TS), and mode switching(MS). The objective of this paper is to maximize the weighted sum power(WSP) of all energy harvesting receivers(EHRs) while ensuring fairness in the collected power among them. This is achieved by jointly optimizing the transmit beamforming at the base station(BS)and the transmission and reflection coefficients at the STAR-RIS, subject to rate constraints for information decoding receivers(IDRs), transmit power constraint at the BS, and coefficient constraints of each element at the STAR-RIS corresponding to the three protocols. Solving this optimization problem poses challenges because of the complicated objective function and numerous coupled optimization variables of the ES STAR-RIS. To address this complexity, an efficient alternating optimization(AO) approach is proposed as an iterative solution method that achieves suboptimal results. The AO algorithm is then extended to MS STAR-RIS and TS STAR-RIS. Specifically, for MS STRA-RIS, binary constraints in the STAR-RIS coefficient optimization subproblem are handled using the first-order approximation technique along with the penalty function method. For TS STAR-RIS, apart from optimizing BS transmit beamforming and STAR-RIS coefficients subproblems, the transmission and reflection time allocation of STAR-RIS also needs *** findings demonstrate that compared to conventional RIS-aided systems, utilizing three different protocols in a STAR-RIS-aided sy
VANET clustering solves scalability issues while fortifying the network and extending its lifespan. The following phases are included in the developed work on Energy-Efficient Cluster-based Routing (EECR) and Fuzzy-To...
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Heartbeat detection stays central to cardiovascular an electrocardiogram(ECG)is used to help with disease diagnosis and *** Convolutional Neural Network(CNN)-based methods suffer from the less generalization problem t...
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Heartbeat detection stays central to cardiovascular an electrocardiogram(ECG)is used to help with disease diagnosis and *** Convolutional Neural Network(CNN)-based methods suffer from the less generalization problem thus;the effectiveness and robustness of the traditional heartbeat detector methods cannot be *** contrast,this work proposes a heartbeat detector Krill based Deep Neural Network Stacked Auto Encoders(KDNN-SAE)that computes the disease before the exact heart rate by combining features from multiple ECG *** are classified independently and multiple signals are fused to estimate life threatening conditions earlier without any error in classification of heart *** work contained Training and testing stages,in the preparation part at first the Adaptive Filter Enthalpy-based Empirical Mode Decomposition(EMD)is utilized to eliminate the motion artifact in the *** that point,the robotic process automation(RPA)learning part extracts the effective features are extracted,and normalized the value of the feature then estimated utilizing the RPA loss *** last KDNN-SAE prepared training for the data stored in the *** the subsequent stage,input signal compute motion artifact and RPA Learning the evaluation part determines the detection of *** early diagnosis of heart failures is an essential *** results of the experiments show that our proposed method has a high score outcome of *** to the CIF,which reaches *** CNN and Artificial Neural Network(ANN)had less score 0.95115 and 0.90147.
Gesture recognition has diverse application prospects in the field of human-computer ***,gesture recognition devices based on strain sensors have achieved remarkable results,among which liquid metal materials have con...
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Gesture recognition has diverse application prospects in the field of human-computer ***,gesture recognition devices based on strain sensors have achieved remarkable results,among which liquid metal materials have considerable advantages due to their high tensile strength and *** improve the detection sensitivity of liquid metal strain sensors,a sawtooth-enhanced bending sensor is proposed in this *** with the results from previous studies,the bending sensor shows enhanced resistance *** addition,combined with machine learning algorithms,a gesture recognition glove based on the sawtooth-enhanced bending sensor is also fabricated in this study,and various gestures are accurately *** the fields of human-computer interaction,wearable sensing,and medical health,the sawtooth-enhanced bending sensor shows great potential and can have wide application prospects.
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