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Corona discharge-driven platform for precise manipulation of high-viscosity dielectric droplets on copper wires

Sensors and Actuators B: Chemical 2025年 442卷

作者： Qiang Tang Manfei Liu Dengqin Tan Yan Wang Ziyi Wang Xiaxia Cui Jia-Han Zhang Chengjun Wang Changguo Xue State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining Anhui University of Science & Technology Huainan 232001 China School of Artificial Intelligence Anhui University of Science and Technology Hefei 231131 China Electronic-Photonic Smart Sensing Device R&D Team Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal Processing School of Electronic Information Engineering Inner Mongolia University Hohhot 010021 China School of Artificial Intelligence Anhui Polytechnic University Wuhu 241000 China School of Materials Science and Engineering Anhui University of Science and Technology Huainan Anhui 232000 China

Dielectric fluids, including polymers, oils, and organic solvents, are integral to applications such as microreactors, optical devices, and thermal management systems due to their stability and resistance to evaporation. However, precise manipulation of dielectric droplets, especially those with high viscosity, remains challenging due to low surface tension and small contact angles. This study introduces a novel corona discharge-driven platform designed for the precise formation, transport, and control of dielectric droplets on one-dimensional copper wires. Utilizing dual needle-tip electrodes, the system generates localized electric fields that facilitate non-contact charge deposition, enabling reliable manipulation of droplets with viscosities up to 30,000 cSt. Comprehensive experiments demonstrate synchronized droplet movement with electrode motion, effective handling of complex geometries, and advanced operations such as droplet merging and splitting. Moreover, dielectric droplets are utilized as micro-containers for performing on-droplet chemical and biological assays. The platform also enables efficient aspiration and release of high-viscosity dielectric fluids, surpassing the capabilities of conventional pipette-based methods. These results highlight the platform’s robustness, versatility, and strong potential for integration into next-generation microfluidic and lab-on-a-chip systems.

关键词： Corona discharge Droplet manipulation Droplet-based microreactor High-viscosity fluids

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An Asynchronous Clustering and Mobile Data Gathering Schema Based on Timer Mechanism in Wireless Sensor Networks

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Computers, Materials & Continua 2019年第3期58卷 711-725页

作者： Jin Wang Yu Gao Wei Liu Wenbing Wu Se-Jung Lim Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer&Communication EngineeringChangsha University of Science&TechnologyChangsha410114China School of Information Science and Engineering Fujian University of TechnologyFuzhou350000China College of Information Engineering Yangzhou UniversityYangzhou225000China Department of Computer Engineering Chonnam National UniversityYeosu596597Korea.

Recently,Wireless sensor networks(WSNs)have become very popular research topics which are applied to many *** provide pervasive computing services and techniques in various potential applications for the Internet of Things(IoT).An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism(ACMDGTM)algorithm is proposed which would mitigate the problem of“hot spots”among sensors to enhance the lifetime of *** clustering process takes sensors’location and residual energy into consideration to elect suitable cluster ***,one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to *** experimental results display that the presented method can avoid long distance communicate between sensor ***,this algorithm reduces energy consumption effectively and improves package delivery rate.

关键词： Internet of things wireless sensor networks clustering mobile data collection timer.

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Beamforming Design and Association Scheme for Multi-RIS Multi-User mmWave Systems Through Graph Neural Networks

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IEEE Transactions on Wireless communications 2025年

作者： Liu, Mengbing Huang, Chongwen Alhammadi, Ahmed Renzo, Marco Di Debbah, Merouane Yuen, Chau Nanyang Technological University School of Electrical and Electronics Engineering 639798 Singapore Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China Zhejiang Provincial Key Laboratory of Multi-Modal Communication Networks and Intelligent Information Processing Hangzhou310027 China Technology Innovation Institute Masdar City Abu Dhabi United Arab Emirates Université Paris-Saclay CNRS Laboratoire des Signaux et Systèmes CentraleSupélec 3 Rue Joliot-Curie Gif-sur-Yvette91192 France King’s College London Centre for Telecommunications Research – Department of Engineering LondonWC2R 2LS United Kingdom Khalifa University KU6G. Research Center Department of Computer and Information Engineering Abu Dhabi127788 United Arab Emirates University Paris-Saclay CentraleSupelec Gif-sur-Yvette91192 France

Reconfigurable intelligent surface (RIS) is emerging as a promising technology for next-generation wireless communication networks, offering a variety of merits such as the ability to tailor the communication environment. Moreover, deploying multiple RISs helps mitigate severe signal blocking between the base station (BS) and users, providing a practical and efficient solution to enhance the service coverage. However, fully reaping the potential of a multi-RIS aided communication system requires solving a non-convex optimization problem. This challenge motivates the adoption of learning-based methods for determining the optimal policy. In this paper, we introduce a novel heterogeneous graph neural network (GNN) to effectively leverage the graph topology of a wireless communication environment. Specifically, we design an association scheme that selects a suitable RIS for each user. Then, we maximize the weighted sum rate (WSR) of all the users by iteratively optimizing the RIS association scheme, and beamforming designs until the considered heterogeneous GNN converges. Based on the proposed approach, each user is associated with the best RIS, which is shown to significantly improve the system capacity in multi-RIS multi-user millimeter wave (mmWave) communications. Specifically, simulation results demonstrate that the proposed heterogeneous GNN closely approaches the performance of the high-complexity alternating optimization (AO) algorithm in the considered multi-RIS aided communication system, and it outperforms other benchmark schemes. Moreover, the performance improvement achieved through the RIS association scheme is shown to be of the order of 30%. © 2002-2012 IEEE.

关键词： Beamforming

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Multi-Wavelength Narrow Linewidth Random Fiber Laser Based on Fiber Bragg Grating Fabry-Perot Filter

Multi-Wavelength Narrow Linewidth Random Fiber Laser Based o...

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International Conference on information Science and technology (ICIST)

作者： Sokliep Pheng Luo Xiaonan Zhongshuai Wang Yijie Zhu Zetao Jiang School of Information and Communication Guilin University of Electronic Technology Guilin China Guangxi Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin China School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China

ISBN: (数字)9781728155586

ISBN: (纸本)9781728155593

Recently, multi-wavelength narrow linewidth random fiber laser has very interested for every researcher in this field, because of their useful advantages application, such as high-resolution spectroscopy and fiber optic sensing. In this paper, the standard single-mode fiber is used to form a half-opened cavity structure for generating the narrow linewidth random fiber laser and used the FBG-FP as a filter to form the narrow linewidth RFL into multi-wavelength. Firstly, we used the Rayleigh scattering that processed as well as in a standard single-mode fiber to provide random distribution feedback at the same time while using erbium-doped fiber (EDF) to provide the gain or amplification for achieving a broadband random laser output. Then, FBG-FP is added to the half-open cavity random laser structure. The multi-wavelength and narrow linewidth RFL can be achieved when the broadband RFL goes through the FBG-FP. In this paper we have generated the multi-wavelength narrow linewidth random fiber laser which has more than 10 wavelengths and the 3dB bandwidth is less than 0.01 nm and the mode separation of each wavelength is 0.04nm.

关键词： Fiber gratings Erbium-doped fiber lasers Optical fiber couplers Optical fiber amplifiers

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Using NSGA-Ⅲ for optimising biomedical ontology alignment

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CAAI Transactions on Intelligence technology 2019年第3期4卷 135-141页

作者： Xingsi Xue Jiawei Lu Junfeng Chen College of Information Science and Engineering Fujian University of TechnologyFuzhouFujianPeople’s Republic of China Intelligent Information Processing Research Center Fujian University of TechnologyFuzhouFujianPeople’s Republic of China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of TechnologyFuzhouFujianPeople’s Republic of China Fujian Key Laboratory for Automotive Electronics and Electric Drive Fujian University of TechnologyFuzhouFujianPeople’s Republic of China College of IOT Engineering Hohai UniversityChangzhouJiangsuPeople’s Republic of China

To support semantic inter-operability between the biomedical information systems, it is necessary to determine the correspondences between the heterogeneous biomedical concepts, which is commonly known as biomedical ontology matching. Biomedical concepts are usually complex and ambiguous, which makes matching biomedical ontologies a challenge. Since none of the similarity measures can distinguish the heterogeneous biomedical concepts in any context independently, usually several similarity measures are applied together to determine the biomedical concepts mappings. However, the ignorance of the effects brought about by different biomedical concept mapping’s preference on the similarity measures significantly reduces the alignment’s quality. In this study, a non-dominated sorting genetic algorithm (NSGA)-III-based biomedical ontology matching technique is proposed to effectively match the biomedical ontologies, which first utilises an ontology partitioning technique to transform the large-scale biomedical ontology matching problem into several ontology segment-matching problems, and then uses NSGA-III to determine the optimal alignment without tuning the aggregating weights. The experiment is conducted on the anatomy track and large biomedic ontologies track which are provided by the Ontology Alignment Evaluation Initiative (OAEI), and the comparisons with OAEI’s participants show the effectiveness of the authors’ approach.

关键词： ontology ontologies transform together Ontology complex context effects

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Distributed Global Leader-Following Coordination of MASs with Heterogeneous Input Saturation: Scheduling Low-Gain Revisited

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Journal of the Franklin Institute 2025年第11期362卷

作者： Xiaoling Wang Shengnan Zhu Juan Qian Housheng Su College of Automation & AI Nanjing University of Posts and Telecommunications and Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot) Nanjing 210023 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai 200237 China Université Claude Bernard Lyon 1 CNRS LAGEPP UMR 5007 43 boulevard du 11 novembre 1918 F-69100 Villeurbanne France National Key Laboratory of Multispectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China

In this paper, we revisit the global coordinated tracking problem of the leader-following multi-agent systems with input saturation via the scheduling low-gain feedback technique, aiming to make breakthroughs from aspects such as the heterogeneity of saturation level and the distributed characteristic of scheduled tuning algorithms on the low-gain parameters, that is the newly proposed distributed scheduling low-gain approach. First, we provide a continuous-time tuning algorithm for the low-gain parameter of each follower to articulate the fundamental idea of the distributed scheduling low-gain technique on addressing heterogeneous saturation, so as to solve the global consensus tracking of multi-agent systems with heterogeneous input saturation and one leader. Then, this result is extended to the global containment tracking of multi-agent systems with multiple leaders. Furthermore, from the perspective of reducing communication burden, we further propose a distributed scheduling low-gain parameter algorithm by using the sampled relative information between each follower and its neighbors, and offer the upper and lower bounds on the sampling period to ensure the achievement of global coordination tracking. Finally, numerical simulations are performed to verify the theoretical results.

关键词：

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CROA: A content-based recommendation optimization algorithm for personalized knowledge services 21

CROA: A content-based recommendation optimization algorithm ...

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21st IEEE International Conference on High Performance Computing and communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Sun, Xiao Xu, Xiaolong Xia, Fei Jiangsu Key Laboratory Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Information and communication Branch State Grid Jiangsu Electric Power Company Nanjing China

ISBN: (纸本)9781728120584

information explosion is a typical feature of the Big data. Learners can easily find a wide variety of knowledge information online. However, the expansion of information also makes it difficult for learners to retrieve the information they want and fall into the problem of knowledge overload. In order to solve this problem effectively, we propose a content-based recommendation optimization algorithm for personalized knowledge services (CROA). First, the feature vector model is established, where each item information is represented by specific words and key information is highlighted by weighting. Second, a dynamic user vector model is then established to capture the latest preference information of the user. Finally, the feature vector model is combined with the multi-user comparison results thereby obtaining a list of recommendations. Experimental results indicate that CROA outstands in knowledge recommendation mechanism and can also alleviate knowledge overload. © 2019 IEEE.

关键词： Optimization

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An optimal profit route planning scheme based on ACO-OPP 21

An optimal profit route planning scheme based on ACO-OPP

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作者： Qiu, Yuhua Xu, Xiaolong Xia, Fei Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Information and communication Branch State Grid Jiangsu Electric Power Company Nanjing China

ISBN: (纸本)9781728120584

Taxi plays an important role of urban public transportation system. However, without appropriate route planning scheme, taxi drivers can only choose to wait or seek passengers in the absence of orders, leading to wasting a lot of time and fuel. In this paper, an optimal profit route planning scheme for taxi drivers with Ant Colony Optimization Algorithm based on Optimal Profit Points (ACO-OPP) is proposed. First, the taxi trajectory data are preprocessed and the pick-up and drop-off points are extracted to obtain high-quality data;second, the data spatiotemporal distribution is analyzed to plan a more appropriate and rational route;the clustering algorithm is used to obtain the optimal profit points to increase the occupancy rate of taxis;then, ACO-OPP is utilized to plan the profit routes for each taxi. A series of experiments are implemented based on the real taxi trajectory dataset to test and compare the performance of the simulated annealing algorithm, the genetic algorithm, the ant colony algorithm and ACO-OPP on the optimal route length and the profitability with the unit time profit function. The experimental results show that ACO-OPP has the shortest optimal route length and the best profit per unit time. © 2019 IEEE.

关键词： Profitability

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Relapse risk prediction for children with henoch-schonlein purpura based on GA-SVM

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International Journal Bioautomation 2020年第2期24卷 117-130页

作者： Liu, Yijun Wang, Beihong Li, Renpu He, Sheng Xi, Haixu Luo, Ye Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Jiangsu University of Technology 1801 Zhongwu Road Changzhou213001 China Department of Pediatrics Changzhou No. 2 People's Hospital 29 Xinglong Road Changzhou213003 China

The relapse risk prediction for children with Henoch-Schonlein purpura can help pediatricians make an accurate prognosis and offer personalized and appropriate follow-up nursing and relapse control to patients. In this study, we propose a Genetic algorithm-Support vector machine (GA-SVM) learning method combining the support vector machine with the genetic algorithm for parameter optimization to capture the nonlinear mapping from a panel of biomarkers to the relapse risk of HSP children. The GA-SVM prediction model is created by using the dataset of 40 samples in clinical treatment and observation of patients. The inputs of the model consist of 19 biomarkers including gender, age, immunoglobulin M, immunoglobulin G, immunoglobulin A, prothrombin time, etc. The outputs consist of 1 and-1, where 1 indicates high relapse risk and-1 indicates low relapse risk. For comparison, the GS-SVM prediction model based on parameter optimization of grid search is also created. The experimental results show that the GA-SVM prediction model has a high prediction accuracy of 90% and is strong in generalization ability. The GA-SVM model for predicting the relapse risk of HSP children is a promising decision support tool of clinical prognosis, which provides pediatricians with valuable assistance to offer rehabilitation treatment to patients. © 2020 by the authors.

关键词： Forecasting

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Flower Species Recognition System Combining Object Detection and Attention Mechanism 1

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15th International Conference on intelligent Computing, ICIC 2019

作者： Qin, Wei Cui, Xue Yuan, Chang-An Qin, Xiao Shang, Li Huang, Zhi-Kai Wan, Si-Zhe Tongji University Shanghai China Science Computing and Intelligent Information Processing of GuangXi Higher Education Key Laboratory Nanning Normal University NanningGuangxi China Department of Communication Technology College of Electronic Information Engineering Suzhou Vocational University Jiangsu China College of Mechanical and Electrical Engineering Nanchang Institute of Technology NanchangJiangxi China

ISBN: (数字)9783030267667

ISBN: (纸本)9783030267650

In this paper, a flower species recognition system combining object detection and Attention Mechanism is proposed. In order to strengthen the ability of the model to process images under complex backgrounds, we apply the method of object detection to locate flowers that we want to recognize. For less time of training, object detection and classification are Integrate into an end-to-end network stacked attention modules to generate attention-aware features. Experiments are conducted on Flower 102, our method can recognize flower species against a complex background. With model owning attention module and transfer learning, we increase mAP from 73.8% to 74.7% and training time is reduced by about 15%. © 2019, Springer Nature Switzerland AG.

关键词： Object recognition

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