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A batch microfabrication of a self-cleaning,ultradurable electrochemical sensor employing a BDD film for the online monitoring of free chlorine in tap water

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Microsystems & Nanoengineering 2022年第2期8卷 85-96页

作者： Jiawen Yin Wanlei Gao Weijian Yu Yihua Guan Zhenyu Wang Qinghui Jin Faculty of Electrical Engineering and Computer Science Ningbo University315211 NingboP.R.China State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of Sciences200050 ShanghaiP.R.China

Free chlorine is one of the key water quality parameters in tap ***,a free chlorine sensor with the characteristics of batch processing,durability,antibiofouling/antiorganic passivation and in situ monitoring of free chlorine in tap water continues to be a challenging *** this paper,a novel silicon-based electrochemical sensor for free chlorine that can self-clean and be mass produced via microfabrication technique/MEMS(Micro-Electro-Mechanical System)is proposed.A liquid-conjugated Ag/AgCI reference electrode is fabricated,and electrochemically stable BDD/Pt is employed as the working/counter electrode to verify the effectiveness of the as-fabricated sensor for free chlorine *** sensor demonstrates an acceptable limit of detection(0.056 mg/L)and desirable linearity(R^(2)=0.998).Particularly,at a potential of+2.5 V,hydroxyl radicals are generated on the BBD electrode by electrolyzing water,which then remove the organic matter attached to the surface of the sensor though an electrochemical digestion *** performance of the fouled sensor recovers from 50.2 to 94.1%compared with the initial state after self-cleaning for 30 *** addition,by employing the MEMS technique,favorable response consistency and high reproducibility(RSD<4.05%)are observed,offering the opportunity to mass produce the proposed sensor in the future.A desirable linear dependency between the pH,temperature,and flow rate and the detection of free chlorine is observed,ensuring the accuracy of the sensor with any hydrologic *** interesting sensing and selfcleaning behavior of the as-proposed sensor indicate that this study of the mass production of free chlorine sensors by MEMS is successful in developing a competitive device for the online monitoring of free chlorine in tap water.

关键词： chlorine batch electrode

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Secure beamforming designs for maximizing secrecy sum rate in MISO-NOMA networks

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Digital Communications and Networks 2025年第1期11卷 83-91页

作者： Yanbo Zhang Zheng Yang Jingjing Cui Xianfu Lei Yi Wu Jun Zhang Chao Fang Zhiguo Ding College of Photonic and Electronic Engineering Fujian Normal UniversityFuzhou 350007China School of Electronics and Computer Science University of SouthamptonSouthampton SO171BJUK Institute of Mobile Communications Southwest Jiaotong UniversityChengdu 610031China Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and TelecommunicationsNanjing 210003China Faculty of Information Technology Beijing University of TechnologyBeijingChina School of Electrical and Electronics Engineering The University of ManchesterManchester M139PLUK

In this paper,the application of Non-Orthogonal Multiple Access(NOMA)is investigated in a multiple-input single-output network consisting of multiple legitimate users and a potential *** support secure transmissions from legitimate users,two NOMA Secrecy Sum Rate Transmit Beam Forming(NOMA-SSR-TBF)schemes are proposed to maximise the SSR of a Base Station(BS)with sufficient and insufficient transmit *** BS with sufficient transmit power,an artificial jamming beamforming design scheme is proposed to disrupt the potential eavesdropping without impacting the legitimate *** addition,for BS with insufficient transmit power,a modified successive interference cancellation decoding sequence is used to reduce the impact of artificial jamming on legitimate *** specifically,iterative algorithm for the successive convex approximation are provided to jointly optimise the vectors of transmit beamforming and artificial *** results demonstrate that the proposed NOMA-SSR-TBF schemes outperforms the existing works,such as the maximized artificial jamming power scheme,the maximized artificial jamming power scheme with artificial jamming beamforming design and maximized secrecy sum rate scheme without artificial jamming beamforming design.

关键词： NOMA Secure transmission Artificial jamming Beamforming design

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An MPC-controlled Bidirectional Battery Charger with DC-DC and Three-level F-type Converters 4

An MPC-controlled Bidirectional Battery Charger with DC-DC a...

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4th International Conference on Smart Grid and Renewable Energy, SGRE 2024

作者： Guler, Naki Bagheri, Farzaneh Komurcugil, Hasan Bayhan, Sertac Gazi University Electrical and Electronic Engineering Technology Faculty Ankara Turkey Antalya Bilim University Department of Electrical and Electronic Engineering Antalya Turkey Eastern Mediterranean University Department of Computer Engineering FamagustaVia Mersin 10 Turkey Qatar Environment and Energy Research Institute Doha Qatar

ISBN: (纸本)9798350306262

This paper proposes a single-phase bidirectional battery charger which comprises a three-level F-type converter and a bidirectional dc-dc converter. The proposed charger is suitable for electric vehicles and battery energy storage systems. The bidirectional dc-dc converter is integrated into the system to prevent the charge current oscillations caused by double-line frequency voltage ripples of the F-type converter when operates as a single-phase rectifier. The F-type converter operates as rectifier and inverter during charging and discharging modes, respectively. The power flow of the battery is controlled with a bidirectional dc-dc converter. The current control of both F-type and bidirectional dc-dc converters is achieved by the model predictive control (MPC) method. The control strategy is designed by considering the power balance theory. For this purpose, the voltage of the common connection point of both converters (dc-link) is regulated. The grid current reference of the F-type converter is obtained by using a proportional-integral (PI) controller whose input is the dc-link voltage error. Thus, bidirectional power flow control is achieved. The effectiveness of the proposed power converter structure as well as the control strategy is investigated by simulation studies performed on MATLAB/Simulink environments. The results show that the proposed system is capable of controlling the grid and battery currents in both power directions. © 2024 IEEE.

关键词： Model predictive control

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Finite-time robust performance improvement for non-linear systems in the presence of input non-linearity and external disturbance

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IET Control Theory and Applications 2023年第6期17卷 672-682页

作者： Wang, Haoping Ghaffari, Valiollah Mobayen, Saleh Bartoszewicz, Andrzej Fekih, Afef Assawinchaichote, Wudhichai School of Automation Nanjing University of Science and Technology Nanjing China Department of Electrical Engineering Persian Gulf University Bushehr Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin Douliou Taiwan Institute of Automatic Control Lodz University of Technology Lodz Poland Department of Electrical and Computer Engineering University of Louisiana at Lafayette LafayetteLA United States Department of Electronic and Telecommunication Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand

The main focus of this research is on improving the performance of dynamic systems with actuator non-linearities and time-varying disturbances. To this end, using the concept of finite-time stability, a novel observer is presented to estimate the disturbances in systems with input non-linearities. Then, introducing an innovative sliding manifold, a robust observer-based technique is derived to guarantee the finite-time stability of the sliding surface. Hence, the closed-loop system would be stable in the presence of hard non-linearities and time-varying disturbances. The performance of the proposed approach was assessed in using a simulation study of two numerical examples. The obtained results and comparison with a conventional method confirmed the benefits of the suggested approach. © 2022 The Authors. IET Control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of engineering and technology.

关键词： Closed loop systems

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Feasibility Study and Energy Management of a Hybrid Microgrid for Ethiopian Rural Community

Feasibility Study and Energy Management of a Hybrid Microgri...

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2022 IEEE International Conference on electrical, computer, and Energy Technologies, ICECET 2022

作者： Ashetehe, Ahunim Abebe Shewarega, Fekadu Bantyirga, Belachew Bahir Dar Institute of Technology-Bahir Dar University Faculty of Electrical and Computer Engineering Bahir Dar Ethiopia University Duisburg-Essen Electrical and Computer Engineering Duisburg Germany

ISBN: (数字)9781665470872

ISBN: (纸本)9781665470872

This paper presents the feasibility study of a hybrid microgrid and its energy management for the Ethiopian rural community conducted on Dek island. Daily electric energy consumption of residential, public institutions, small industries (mills), commercial, and deferrable loads of the Island are considered and its average daily energy consumption is 3,596 kWh/day with 405 kW peak power demand. The proposed microgrid configuration is evaluated and collated based on the least net present cost and Levelized cost of energy. Using the Hybrid optimization Model for Electric Renewable software, the study presents the optimal microgrid configuration that meets the energy demand of the study site. The simulation result indicates that the Photovoltaic/Diesel generator/Battery hybrid microgrid configuration is feasible regarding technical, economical, and environmental issues with the net present cost of 4.13M at 0.149 cost of energy. For the optimal operation of the feasible hybrid microgrid, Multi-Agent System with a Fuzzy Logic Controller based energy management system is proposed. © 2022 IEEE.

关键词： Energy management

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Object Detection in UAV Aerial Images Based on Improved YOLOv7-tiny 4

Object Detection in UAV Aerial Images Based on Improved YOLO...

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4th International Conference on computer Vision, Image and Deep Learning, CVIDL 2023

作者： Wang, Ziyang Liu, Zhiwen Xu, Gen Cheng, Siyuan Ningbo University Faculty of Electrical Engineering and Computer Science Zhejiang Province Ningbo China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Zhejiang Province Ningbo China

ISBN: (纸本)9798350326444

With the wide application of unmanned aerial vehicle (UAV), the problem of object detection in UAV aerial image has attracted more and more attention. In order to detect objects in UAV aerial images more accurately, we made a series of improvements on the basis of YOLOv7-tiny to make it more suitable for detecting objects in UA V aerial images. Specifically, we added Global Attention Mechanism (GAM) to YOLOv7-tiny's neck network to better extract the features of the objects. We also introduced the Bidirectional Feature Pyramid Network (BiFPN) into the Neck network to enhance feature fusion capability. In order to detect small objects more accurately, we added a small object detection head in the YOLOv7-tiny Head section. Contextual Transformer module was introduced to make the network pay more attention to context information. To make the predicted box match the ground truth box more closely, we applied the SIoU loss function to YOLOv7-tiny. The experimental results showed that, mAP@0.5 is 38.1 % and mAP@0.5:0.95 is 21.3% by improved YOLOv7-tiny algorithm on VisDrone dataset. Compared with YOLOv7-tiny, mAP@0.5 is improved by 2.8% and mAP@0.5:0.95 is improved by 3%, which improved the accuracy of object detection in UAV aerial images. © 2023 IEEE.

关键词： Object detection

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An Improved Transfer Learning-Based Model with Data Augmentation for Brain Tumor Detection 6

An Improved Transfer Learning-Based Model with Data Augmenta...

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6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024

作者： Prayogo, Rizal Dwi Hamid, Nur Nambo, Hidetaka Graduate School of Natural Science and Technology Kanazawa University Division of Electrical Engineering and Computer Science Kanazawa Japan Institute of Philosophy in Interdisciplinary Sciences Kanazawa University Faculty of Transdisciplinary Sciences Kanazawa Japan

ISBN: (纸本)9798350344349

Current advances in deep learning have brought various breakthroughs in processing medical data. However, dealing with a limited number of medical datasets remains a challenge in deep learning and often leads to overfitting. To solve this research gap, here we show a new approach to improve the performance of a transfer learning-based model for brain tumor detection from 253 brain magnetic resonance imaging (MRI) sample images. The concept of transfer learning has been applied using a pretrained Inception V3combined with data augmentation. Modified layers using dropout and regularization have been additionally utilized to deal with overfitting. The proposed method shows an increase in accuracy of 6.430%, a precision of 5.531 %, a recall of 10.545%, and an F1-score of 8.040% compared to the baseline method. We show that our proposed method has been able to effectively enhance performance and reduce overfitting, even with a small number of datasets. Moreover, our proposed method outperforms state-of-The-Art brain tumor detection. © 2024 IEEE.

关键词： Tumors

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A Multi-Layered Gravitational Search Algorithm for Function Optimization and Real-World Problems

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IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 94-109页

作者： Yirui Wang Shangce Gao Mengchu Zhou Yang Yu the Faculty of Engineering University of ToyamaToyama 930-8555Japan the Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA

A gravitational search algorithm(GSA)uses gravitational force among individuals to evolve *** GSA is an effective population-based algorithm,it exhibits low search performance and premature *** ameliorate these issues,this work proposes a multi-layered GSA called *** by the two-layered structure of GSA,four layers consisting of population,iteration-best,personal-best and global-best layers are *** interactions among four layers are dynamically implemented in different search stages to greatly improve both exploration and exploitation abilities of *** comparison between MLGSA and nine existing GSA variants on twenty-nine CEC2017 test functions with low,medium and high dimensions demonstrates that MLGSA is the most competitive *** is also compared with four particle swarm optimization variants to verify its excellent ***,the analysis of hierarchical interactions is discussed to illustrate the influence of a complete hierarchy on its *** relationship between its population diversity and fitness diversity is analyzed to clarify its search *** computational complexity is given to show its ***,it is applied to twenty-two CEC2011 real-world optimization problems to show its practicality.

关键词： Artificial intelligence exploration and exploitation gravitational search algorithm hierarchical interaction hierarchy machine learning population structure

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Model Predictive Robust Control for A Capacitive-Coupling Grid-Connect Inverter (CGCI) in Power Quality Compensation 50

Model Predictive Robust Control for A Capacitive-Coupling Gr...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Chan, Pak-Ian Sou, Wai-Kit Lam, Chi-Seng State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau China Institute of Microelectronics University of Macau China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau China

ISBN: (纸本)9781665464543

In this paper, a model predictive robust control (MPRC) is proposed for a three-phase capacitive-coupling grid-connect inverter (CGCI) to improve the power quality compensation performance under deviating system parameters. A detail stability study and parameter design of the proposed MPRC is provided, while the robustness and power quality compensation performance of the proposed MPRC are verified by the simulation in comparison to the conventional model predictive control (MPC). © 2024 IEEE.

关键词： Predictive control systems

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Smart Data Augmentation for Multiclass Brain Tumor Detection with Imbalanced Data 8

Smart Data Augmentation for Multiclass Brain Tumor Detection...

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8th International Conference on Information technology, Information Systems and electrical engineering, ICITISEE 2024

作者： Prayogo, Rizal Dwi Nambo, Hidetaka Graduate School of Natural Science and Technology Kanazawa University Division of Electrical Engineering and Computer Science Kanazawa Japan Institute of Philosophy in Interdisciplinary Sciences Kanazawa University Faculty of Transdisciplinary Sciences Kanazawa Japan

ISBN: (纸本)9798350368970

Dealing with class imbalance is a significant issue in classification tasks that often leads to lower prediction performance. Many data augmentation methods have been suggested to tackle this problem, but their effectiveness can vary depending on the dataset. Utilizing augmentation methods can improve the learning and generalization abilities of the proposed convolutional neural network (CNN) model. However, it is challenging to find a single data augmentation method that can effectively address class imbalance problems across all scenarios. In this paper, we present a technique known as smart data augmentation (SDA) that is aimed at effectively improving classification performance by enhancing imbalanced data. SDA involves an equation that can be used to create an augmentation technique, combining different sampling methods for addressing multiclass imbalance and offering easy customization options. We perform the data balancing strategy including undersampling, oversampling, and SDA-based sampling. We evaluate our proposed framework using a CNN model to improve the detection of brain tumors in imbalanced data. Our experiments demonstrate that SDA-based sampling improves brain tumor detection performance by 3.546% in accuracy, 3.310% in precision, 3.432% in recall, and 3.371 % in Fl-score compared to the imbalanced data scenario. The findings suggest that utilizing SDA together with CNN can improve the classification performance of brain tumor detection with imbalanced data. © 2024 IEEE.

关键词： Brain tumor detection class imbalance problem convolutional neural network smart data augmentation

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