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In situ plasmonic & electrochemical fiber-optic sensor for multi-metal-ions detection

Science China(Information Sciences) 2024年第1期67卷 292-302页

作者： Xiaoling PENG Zhiyong YANG Bo PENG Zhi LI Zhicong REN Xicheng WANG Jiahai LI Zhencheng LI Liang CHEN Daotong YOU Kaiwei LI Jianqing LI Tuan GUO institute of Photonics Technology Jinan University School of computer Science and engineering Macau University of Science and Technology institute for Environmental and Climate Research Jinan University Key Laboratory of Bionic engineering of Ministry of Education Jilin University

High precision and high throughput detection of heavy metal ions is essential for water quality monitoring and ***,we propose a plasmonic & electrochemical dual-mode fiber sensing probe for label-free and real-time detection of multiple ions(Pb2+and Cu2+as examples).This sensor comprises a multimode fiber-single mode fiber reflection probe,the outer surface of which is coated with a gold nanofilm to excite the surface plasmon resonance(SPR) optically and simultaneously serves as an electrochemical working *** traditional electrochemical detection,the enrichment of ions cannot be detected in ***,by utilizing the plasmonic & electrochemical dual-mode detection method,various kinds of metal ions can be deposited onto the gold nanofilm and selectively oxidized during forward potential scanning,and the entire electrochemical process can be monitored by SPR *** experimentally demonstrate that the sensor can simultaneously detect Pb2+and Cu2+in a mixed solution in real-time,providing a linear response over the ion concentration range from 10-12to 10-7M and offering an excellent detection limit(1.69×10-14–5.49×10-13M).The proposed dual-mode fiber sensor has the benefits of remote sensing,compact footprint,and cost-effectiveness and shows excellent potential for water quality risk management in difficult-to-reach environments.

关键词： optical fiber sensor surface plasmon resonance electrochemical measurement ions detection water pollution

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A Novel 6G Scalable Blockchain Clustering-Based computer Vision Character Detection for Mobile Images

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computers, Materials & Continua 2024年第3期78卷 3041-3070页

作者： Yuejie Li Shijun Li department of Mathematics and computer engineering Ordos Institute of TechnologyOrdos017000China School of Mathematics and Physics North China Electric Power UniversityBeijing102206China School of Electrical Information Hunan University of EngineeringXiangtan411104China

6G is envisioned as the next generation of wireless communication technology,promising unprecedented data speeds,ultra-low Latency,and ubiquitous *** tandem with these advancements,blockchain technology is leveraged to enhance computer vision applications’security,trustworthiness,and *** the widespread use of mobile devices equipped with cameras,the ability to capture and recognize Chinese characters in natural scenes has become increasingly *** can facilitate privacy-preserving mechanisms in applications where privacy is paramount,such as facial recognition or personal healthcare *** can control their visual data and grant or revoke access as *** Chinese characters from images can provide convenience in various aspects of people’s ***,traditional Chinese character text recognition methods often need higher accuracy,leading to recognition failures or incorrect character *** contrast,computer vision technologies have significantly improved image recognition *** paper proposed a Secure end-to-end recognition system(SE2ERS)for Chinese characters in natural scenes based on convolutional neural networks(CNN)using 6G *** proposed SE2ERS model uses the Weighted Hyperbolic Curve Cryptograph(WHCC)of the secure data transmission in the 6G network with the blockchain *** data transmission within the computer vision system,with a 6G gradient directional histogram(GDH),is employed for character *** the deployment of WHCC and GDH in the constructed SE2ERS model,secure communication is achieved for the data transmission with the 6G *** proposed SE2ERS compares the performance of traditional Chinese text recognition methods and data transmission environment with 6G *** results demonstrate that SE2ERS achieves an average recognition accuracy of 88%for simple Chinese characters,compared to 81.2%with traditional ***

关键词： 6G technology blockchain end-to-end recognition Chinese characters natural scene computer vision algorithms convolutional neural network

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New Antenna Array Beamforming Techniques Based on Hybrid Convolution/Genetic Algorithm for 5G and Beyond communications

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computer Modeling in engineering & Sciences 2024年第3期138卷 2749-2767页

作者： Shimaa M.Amer Ashraf A.M.Khalaf Amr H.Hussein Salman A.Alqahtani Mostafa H.Dahshan Hossam M.Kassem electronics and communications engineering department Higher Institute of Engineering and TechnologyKafr ElsheikhEgypt electronics and Electrical communications engineering department Faculty of EngineeringMinia UniversityMiniaEgypt electronics and Electrical communications engineering department Faculty of EngineeringTanta UniversityTantaEgypt electronics and Electrical communications engineering department Faculty of EngineeringHorus University EgyptNew DamiettaEgypt department of computer engineering College of computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia School of Computing Mathematics and EngineeringCharles Sturt UniversityBathurstNSW2795Australia

Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to ***,it improves the array gain and directivity,increasing the detection range and angular resolution of radar *** study proposes two highly efficient SLL reduction *** techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,*** convolution process determines the element’s excitations while the GA optimizes the element *** M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,*** the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher *** the increased HPBWof the odd and even excitations,the element spacing is optimized using the ***,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the ***,for extreme SLL reduction,the DConv/GA is *** this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation *** provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.

关键词： Array synthesis convolution process genetic algorithm(GA) half power beamwidth(HPBW) linear antenna array(LAA) side lobe level(SLL) quality of service(QOS)

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A Traffic-Aware and Cluster-Based Energy Efficient Routing Protocol for IoT-Assisted WSNs

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computers, Materials & Continua 2024年第8期80卷 1831-1850页

作者： Hina Gul Sana Ullah Ki-Il Kim Farman Ali department of computer and Software Technology University of SwatMingora19130Pakistan department of computer Science and engineering Chungnam National UniversityDaejeon34134Republic of Korea department of Applied AI Sungkyunkwan UniversitySeoul03063Republic of Korea

The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industrial monitoring,transportation,and smart *** and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of *** paper presents a traffic-aware,cluster-based,and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such *** proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual *** protocol considers multi-criteria attributes,i.e.,energy,traffic load,and distance parameters to select the next hop for data delivery towards the base *** performance of the proposed protocol is evaluated through the network simulator *** different traffic rates,number of nodes,and different packet sizes,the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio,energy consumption,end-to-end delay,and network *** 100 nodes,the proposed protocol achieved a 13%improvement in packet delivery ratio,10 ms improvement in delay,and 10 mJ improvement in average energy consumption over LoRaWAN.

关键词： Internet of Things wireless sensor networks traffic load clustering routing energy efficiency

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电池衰减诊断及状态评估研究进展

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Science China Materials 2024年第4期67卷 1014-1041页

作者：袁君秦之理黄海坤甘兴栋王子为杨毅琛刘书江文安毕闯李白海孙成华 School of Materials and Energy University of Electronic Science and Technology of China Yangtze Delta Region institute(Huzhou) University of Electronic Science and Technology of China School of computer Science and engineering University of Electronic Science and Technology of China Power Research institute of State Grid Shaanxi Electric Power Company Limited department of Chemistry and Biotechnology Swinburne University of Technology

锂离子电池(LIB)广泛应用于储能及动力输出等领域.准确预测电池的健康状态对于优化性能、降低运营费用和防止电池故障等方面具有重要的意义.本文对预测LIB的荷电状态(SOC)、健康状态(SOH)和剩余使用寿命(RUL)方面的最新发展进行了全面回... 详细信息

锂离子电池(LIB)广泛应用于储能及动力输出等领域.准确预测电池的健康状态对于优化性能、降低运营费用和防止电池故障等方面具有重要的意义.本文对预测LIB的荷电状态(SOC)、健康状态(SOH)和剩余使用寿命(RUL)方面的最新发展进行了全面回顾,重点关注机器学习技术方面的研究进展,深入分析了LIB的退化机制及其基本理论,评估了各种传统方法及机器学习技术在预测SOC,SOH和RUL方面的优势和限制.此外,还探讨了电动汽车动力电池在实际应用中面临的挑战,特别是性能退化问题.最后提出了对LIB未来研究方向有价值的见解.尽管机器学习方法在提高预测SOC,SOH和RUL准确性方面具有巨大潜力,但在实际应用中仍然有许多技术和实际障碍需要克服.

关键词：锂离子电池剩余使用寿命状态评估机器学习技术健康状态动力输出运营费用退化机制

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Energy-efficient computation offloading assisted by RIS-based UAV

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The Journal of China Universities of Posts and Telecommunications 2024年第1期31卷 37-48页

作者： Li Linpei Zhao Chuan Su Yu Huo Jiahao Huang Yao Li Haojin School of Intelligence Science and Technology University of Science and Technology BeijingBeijing 100083China institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China Shunde Innovation School University of Science and Technology BeijingFoshan 528399China School of computer and communication engineering University of Science and Technology BeijingBeijing 100083China Research department of 5G and Drone China Mobile(Chengdu)Institute of Research and DevelopmentChengdu 610200China College of communication engineering Chengdu University of Information TechnologyChengdu 610225China Research and Development Center Sony(China)LimitedBeijing 100027China

The new applications surge with the rapid evolution of the mobile *** explosive growth of the data traffic aroused by the new applications has posed great computing pressure on the local *** is essential to innovate the computation offloading methods to alleviate the local computing burden and improve the offloading *** edge computing(MEC)assisted by reflecting intelligent surfaces(RIS)-based unmanned aerial vehicle(UAV)is a promising method to assist the users in executing the computation tasks in proximity at low *** this paper,we propose an energy-efficient MEC system assisted by RIS-based UAV,where the UAV with RIS mounted relays the computation tasks to the MEC *** energy efficiency maximization problem is formulated by jointly optimizing the UAV's trajectory,the transmission power of all users,and the phase shifts of the reflecting elements placed on the *** that the optimization problem is non-convex,we propose a deep deterministic policy gradient(DDPG)-based *** combining the DDPG algorithm with the energy efficiency maximization problem,the optimization problem can be ***,the numerical results are illustrated to show the performance of the system and the superiority compared with the benchmark schemes.

关键词： mobile edge computing unmanned aerial vehicle reflecting intelligent surface

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In-situ fabrication of on-chip 1T'-MoTe_(2)/Ge Schottky junction photodetector for self-powered broadband infrared imaging and position sensing

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Nano Research 2024年第6期17卷 5587-5594页

作者： Menglei Zhu Kunxuan Liu Di Wu Yunrui Jiang Xue Li Pei Lin Zhifeng Shi Xinjian Li Ran Ding Yalun Tang Xuechao Yu Longhui Zeng School of Physics and Microelectronics and Key Laboratory of Material PhysicsZhengzhou UniversityZhengzhou 450052China department of Electrical and computer engineering University of California San DiegoLa JollaCA 92093USA State Key Laboratory of Integrated Optoelectronics College of Electronic Science and EngineeringJilin UniversityChangchun 130012China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China

High-sensitivity room-temperature multi-dimensional infrared(IR)detection is crucial for military and civilian ***,the gapless electronic structures and unique optoelectrical properties have made the two-dimensional(2D)topological semimetals promising candidates for the realization of multifunctional optoelectronic ***,we demonstrated the in-situ construction of high-performance 1T’-MoTe_(2)/Ge Schottky junction device by inserting an ultrathin AlOx passivation *** good detection performance with an ultra-broadband detection wavelength range of up to 10.6 micron,an ultrafast response time of~160 ns,and a large specific detectivity of over 109 Jones in mid-infrared(MIR)range surpasses that of most 2D materials-based IR sensors,approaching the performance of commercial IR *** on-chip integrated device arrays with 64 functional detectors feature high-resolution imaging capability at room *** these outstanding detection features have enabled the demonstration of position-sensitive detection *** demonstrates an exceptional position sensitivity of 14.9 mV/mm,an outstanding nonlinearity of 6.44%,and commendable trajectory tracking and optoelectronic demodulation *** study not only offers a promising route towards room-temperature MIR optoelectronic applications,but also demonstrates a great potential for application in optical sensing systems.

关键词： MoTe_(2) broadband photodetection Schottky junction imaging position sensitive detector

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Low-modal-crosstalk doped-fiber amplifiers in few-mode-fiber-based systems

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Photonics Research 2024年第8期12卷 1768-1775页

作者： SHUAILUO HUANG LEI SHEN GANG QIAO YUANPENG DING YUYANG GAO JIAN CUI BAOLONG ZHU SIYUAN LIU MINGQING ZUO JINGLONG ZHU LEI ZHANG JIE LUO YONGQI HE ZHANGYUAN CHEN JUHAO LI State Key Laboratory of Advanced Optical communication Systems and Networks Peking UniversityBeijing 100871China State Key Laboratory of Optical Fiber and Cable Manufacture Technology Yangtze Optical Fibre and Cable Joint Stock Limited CompanyWuhan 430073China School of computer and communication engineering University of Science and Technology BeijingBeijing 100083China department of Networks China Mobile Communications Group Co.Ltd.Beijing 100033China department of Fundamental Network Technology China Mobile Research InstituteBeijing 100053China Pengcheng Laboratory Shenzhen 518055China

Independent light propagation through one or multiple modes is commonly considered as a basic demand for mode manipulation in few-mode fiber(FMF)-or multimode fiber(MMF)-based optical systems such as transmission links,optical fiber lasers,or distributed optical fiber ***,the insertion of doped-fiber amplifiers always kills the entire effort by inducing significant modal *** this paper,we propose the design of doped-fiber amplifiers in FMF-based systems adopting identical multiple-ring-core(MRC)index profiles for both passive and doped fibers to achieve low modal *** develop the direct-glass-transition(DGT)modified chemical vapor deposition(MCVD)processing for precise fabrication of few-mode erbium-doped fibers(FM-EDFs)with MRC profiles of both refractive index and erbium-ion doping ***,a few-mode erbium-doped-fiber amplifier(FM-EDFA)with a maximum gain of 26.08 dB and differential modal gain(DMG)of 2.3 dB is realized based on fabricated FM-EDF matched with a transmission FMF supporting four linearly polarized(LP)*** the insertion of the FM-EDFA,60+60 km simultaneous LP_(01)∕LP_(11)∕LP_(21)∕LP_(02)transmission without inter-modal multiple-input multiple-output digital signal processing(MIMO-DSP)is successfully *** proposed design of low-modal-crosstalk doped-fiber amplifiers provides,to our knowledge,new insights into mode manipulation methods in various applications.

关键词： fiber crosstalk amplifiers

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Phase-Dislocation-Mediated High-Dimensional Fractional Acoustic-Vortex communication

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Research 2024年第3期2023卷 575-584页

作者： Ruijie Cao Gepu Guo Wei Yue Yang Huang Xinpeng Li Chengzhi Kai Yuzhi Li Juan Tu Dong Zhang Peng Xi Qingyu Ma School of computer and electronic Information Nanjing Normal UniversityNanjing 210023China department of Biomedical engineering College of Future TechnologyPeking UniversityBeijing 100871China nstitute of Acoustics Nanjing UniversityNanjng 210093China National Biomedical Imaging Center Peking UniversityBeijing 100871China

With unlimited topological modes in mathematics,the fractional orbital angular momentum(FOAM)demonstrates the potential to infinitely increase the channel capacity in acoustic-vortex(AV)***,the accuracy and stability of FOAM recognition are still limited by the nonorthogonality and poor anti-interference of fractional AV *** popular machine learning,widely used in optics based on large datasets of images,does not work in acoustics because of the huge engineering of the 2-dimensional point-by-point ***,we report a strategy of phase-dislocation-mediated high-dimensional fractional AV communication based on pair-FOAM multiplexing,circular sparse sampling,and machine *** unique phase dislocation corresponding to the topological charge provides important physical guidance to recognize FOAMs and reduce sampling points from theory to practice.A straightforward convolutional neural network considering turbulence and misalignment is further constructed to achieve the stable and accurate communication without involving experimental *** experimentally present that the 32-point dual-ring sampling can realize the 10-bit information transmission in a limited topological charge scope from±0.6 to±2.4 with the FOAM resolution of 0.2,which greatly reduce the divergence in AV *** infinitely expanded channel capacity is further verified by the improved FOAM resolution of *** with other milestone works,our strategy reaches 3-fold OAM utilization,4-fold information level,and 5-fold OAM *** of the extra advantages of high dimension,high speed,and low divergence,this technology may shed light on the next-generation AV communication.

关键词： infinitely topological fractional

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Deep learning models for tuberculosis detection and infected region visualization in chest X-ray images

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Intelligent Medicine 2024年第2期4卷 104-113页

作者： Vinayak Sharma Nillmani Sachin Kumar Gupta Kaushal Kumar Shukla School of electronics and communication engineering Shri Mata Vaishno Devi University Jammu and KashmirIndia School of Biomedical engineering Indian Institute of TechnologyBanaras Hindu UniversityVaranasiIndia department of computer Science and engineering Indian Institute of TechnologyBanaras Hindu UniversityVaranasiIndia

Objective Tuberculosis(TB)is among the most frequent causes of infectious-disease-related *** being treatable by antibiotics,tuberculosis often goes misdiagnosed and untreated,especially in rural and low-resource *** X-rays are frequently used to aid diagnosis;however,this presents additional challenges because of the possibility of abnormal radiological appearance and a lack of radiologists in areas where the infection is most *** deep-learning-based imaging techniques for computer-aided diagnosis has the potential to enable accurate diagnoses and lessen the burden on medical *** the present work,we aimed to develop deep-learning-based segmentation and classification models for accurate and precise detection of tuberculosis in chest X-ray images,with visualization of infection using gradient-weighted class activation mapping(Grad-CAM)*** First,we trained the UNet segmentation model using 704 chest X-ray radiographs taken from the Montgomery County and Shenzhen Hospital ***,we implemented the trained UNet model on 1,400 tuberculosis and control chest X-ray scans to segment the lung *** images were taken from the National institute of Allergy and Infectious Diseases(NIAID)TB portal program ***,we applied the deep learning Xception model to classify the segmented lung region into tuberculosis and normal *** further investigated the visualization capabilities of the model using Grad-CAM to view tuberculosis abnormalities in chest X-rays and discuss them from radiological *** For segmentation by the UNet model,we achieved accuracy,Jaccard index,Dice coefficient,and area under the curve(AUC)values of 96.35%,90.38%,94.88%,and 0.99,*** classification by the Xception model,we achieved classification accuracy,precision,recall,F1-score,and AUC values of 99.29%,99.30%,99.29%,99.29%,and 0.999,*** Grad-CAM heatmap images from the tuberculos

关键词： Tuberculosis Artificial intelligence Deep learning Segmentation Classification Chest X-ray

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