Assist. Prof. Dr. Lechen Li | Signal Processing | Best Researcher Award

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Assist. Prof. Dr. Lechen Li | Signal Processing | Best Researcher Award 

Assist. Prof. Dr. Lechen Li, Hohai University, China

Lechen Li is an Assistant Professor at the College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, China. He received his Ph.D. in Engineering Mechanics from Columbia University in 2023, where his research focused on smart grid development, data-driven system control, and computational structural dynamics. Prior to that, he earned an M.S. in Data Science from Columbia University, supported by the Robert A.W. and Christine S. Carleton Scholarship, and a B.S. in Engineering Mechanics from Sichuan University, where he won the First Prize in the Zhou Peiyuan National Mechanics Modeling Contest. His current research spans infrastructure intelligent monitoring, data-driven seepage analysis, computational dynamics, and renewable energy optimization. Dr. Li has presented award-winning work at major international conferences such as the 8th World Conference on Structural Control and Monitoring and has collaborated on interdisciplinary projects involving smart electricity networks and structural health monitoring.

Professional Profile:

SCOPUS

🏅 Summary of Suitability for Best Researcher Award

Dr. Lechen Li is a highly promising and accomplished early-career researcher whose interdisciplinary work spans Engineering Mechanics, Data Science, and Infrastructure Monitoring. His exceptional academic background, innovative research in intelligent structural control, and impactful contributions to renewable energy systems make him an excellent candidate for the Best Researcher Award.

🎓 Education

  • Ph.D. in Engineering Mechanics
    Columbia University, USA (09/2019 – 06/2023)
    🔍 Research: Smart Grid, Structural Dynamics, Signal Processing
    📊 GPA: 3.889/4.0

  • M.S. in Data Science
    Columbia University, USA (09/2018 – 08/2019)
    💡 Focus: Neural Networks, Dynamical Systems
    📚 Robert A.W. and Christine S. Carleton Scholarship
    📊 GPA: 3.917/4.0

  • B.S. in Engineering Mechanics
    Sichuan University, China (09/2014 – 06/2018)
    🧠 Strong foundation in Mechanics & Modelling
    📊 GPA: 3.6/4.0
    🥇 First Prize in Zhou Peiyuan National Mechanics Modeling Contest (2017)
    🏅 First Prize Scholarship (Twice between 2014–2016)

🧑‍🏫 Current Position

  • Assistant Professor
    College of Water Conservancy and Hydropower Engineering, Hohai University, China (06/2023 – Present)
    🌊 Research: Infrastructure Intelligent Monitoring, Seepage Control, Computational Dynamics, Renewable Energy.

🧪 Research & Projects

  • Structural Control & Health Monitoring
    Columbia University (2021 – 2023)
    🤖 Developed a Generalized Auto-Encoder (GAE) for damage detection
    🎙️ Presented at 8WCSCM, awarded Best Conference Paper (2022) 🏆

  • Smart Grid for Residential Buildings
    Columbia University (2019 – 2020)
    ⚡ Built ConvLSTM neural network for intelligent load control
    📈 Improved forecasting accuracy by 16%

💼 Industry Experience

  • Data Research Analyst
    CICT, Colombo, Sri Lanka (12/2017 – 03/2018)
    🚢 Applied ML for port logistics & road paving optimization
    🔁 Designed reinforcement learning system for transportation planning

  • CAE Analyst
    National Institute of Water, Energy & Transportation, China (06/2016 – 08/2016)
    🏗️ Simulated pile-soil stress using XFEM
    🔍 Assessed 70% lateral pressure effects on platform-supported pile groups

🏅 Achievements, Awards & Honors

  • 🥇 Best Conference Paper Award, 8WCSCM (2022)

  • 📚 Robert A.W. and Christine S. Carleton Scholarship (2018)

  • 🧠 First Prize, Zhou Peiyuan National Mechanics Modeling Contest (2017)

  • 🎖️ Sichuan University First Prize Scholarship (2014–2016, twice)

Publication Top Notes:

Experimental Study on Dynamic Characteristics of Coarse-Grained Materials and Its Application on Numerical Analysis for Permanent Deformation of Rockfll Dams

Dr. Liu Suiyang | Sensor Arrays | Best Researcher Award

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Dr. Liu Suiyang | Sensor Arrays | Best Researcher Award 

Dr. Liu Suiyang, Xi’an University of Technology, China

Liu Suiyang is from Xianyang, Shaanxi Province, China. She received her B.S. and M.S. degrees in Integrated Circuit Engineering from Xi’an University of Technology in 2019 and 2022, respectively. From 2022 to 2024, she was a Ph.D. student with the Ultra-Large Scale Integrated Circuits Laboratory at Xi’an University of Technology. Since 2021, she has authored 13 articles and contributed to nine inventions. Her research interests include large-format image sensors, high dynamic-range pixels, high-speed column buffers, organic photodetectors, and 3D integrated circuits. Ms. Liu was recognized as an Outstanding Graduate of Xi’an University of Technology in 2022 and received the Eighth Shaanxi Province Graduate Innovation Achievement Award in 2024.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award – Liu Suiyang

Liu Suiyang is a strong candidate for the Best Researcher Award due to her notable academic achievements and contributions to the field of integrated circuit engineering. Her research in large-format image sensors, high dynamic-range pixels, high-speed column buffers, organic photodetectors, and 3D integrated circuits demonstrates a high level of technical expertise and innovation.

🎓 Education

  • B.S. in Integrated Circuit Engineering – Xi’an University of Technology (2019)

  • M.S. in Integrated Circuit Engineering – Xi’an University of Technology (2022)

  • Ph.D. Student in Ultra-Large Scale Integrated Circuits Laboratory – Xi’an University of Technology (2022–2024)

💼 Work & Research Experience

  • Ph.D. Student at Ultra-Large Scale Integrated Circuits Laboratory, Xi’an University of Technology (2022–2024)

  • Author of 13 Research Articles (Since 2021) ✍️📄

  • Holder of 9 Invention Patents (Since 2021) 🏅🔬

  • Research Focus:

    • Large-format image sensors 📷

    • High dynamic-range pixels 🌟

    • High-speed column buffer ⚡

    • Organic photodetectors 🏭

    • 3D integrated circuits 🏗️

🏆 Awards & Honors

  • Outstanding Graduate of Xi’an University of Technology (2022) 🎖️

  • Eighth Shaanxi Province Graduate Innovation Achievement Award (2024) 🏅💡

Publication Top Notes:

Synchronous Driving Method for Stitching Pixel Arrays Based on an Adaptive Correction Technique

High Dynamic Pixel Circuit Based on Variable Integral Capacitance

Inverted ternary OPD based on PEIE

Inverted ternary OPD based on PEIE

Dr. Longbin Jin | Signal Processing Awards | Best Researcher Award

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Dr. Longbin Jin | Signal Processing Awards | Best Researcher Award 

Dr. Longbin Jin, Konkuk University, South Korea

Longbin Jin, is a Ph.D. candidate in Computer Science at Konkuk University, Korea, with an expected graduation in February 2025. His research focuses on adaptive visual prompting for video action recognition in vision-language models under the guidance of Professor Eun Yi Kim. He holds a Master’s degree in Smart ICT Convergence and a Bachelor’s degree in Mechanical Engineering & Automation from Shanghai University, China. Throughout his academic career, Longbin has received numerous accolades, including winning the ICASSP 2023 SPGC Challenge and multiple Excellence and Encouragement Prizes at the Korea Software Congress. Currently, he serves as an AI Researcher at Voinosis in Seoul, where he develops AI models for early detection of hearing loss and cognitive impairment in the elderly. He is also an instructor at Konkuk University, teaching courses on Artificial Intelligence, Computer Vision, and Machine Learning. His project experience includes collaborations on medical imaging and virtual reality, demonstrating his expertise in applying AI technologies across diverse fields. Longbin is proficient in English, Chinese, and Korean, reflecting his international background and commitment to advancing technology in healthcare and education.

Professional Profile:

GOOGLE SCHOLAR

Research for Community Impact Award: Longbin Jin’s Suitability

Longbin Jin is a highly qualified candidate for the Research for Community Impact Award due to his significant contributions in the fields of artificial intelligence and healthcare, particularly in projects that directly benefit the community.

📚 Education

  • Ph.D. in Computer Science
    Konkuk University, Korea
    Expected: February 2025
    Thesis: Adaptive Visual Prompting for Video Action Recognition in Vision-Language Models
    Advisor: Prof. Eun Yi Kim
  • M.S. in Smart ICT Convergence
    Konkuk University, Korea
    Graduated: August 2020
    Thesis: E-EmoticonNet: EEG-based Emotion Recognition with Context Information
    Advisor: Prof. Eun Yi Kim
  • B.S. in Mechanical Engineering & Automation
    Shanghai University, China
    Graduated: August 2018

💼 Work Experience

  • AI Researcher
    Voinosis, Seoul, Korea
    December 2022 – Present

    • Researcher on AI models for early detection of hearing loss and cognitive impairment based on voice analysis for the elderly (VoiceCheck & BrainGuardDoctor Apps).
  • Instructor
    Konkuk University, Seoul, Korea
    March 2022 – Present

    • Teaching courses on Computer Vision, Artificial Intelligence, and Machine Learning.
  • AI Engineer
    Lulla, Seoul, Korea
    October 2022 – November 2022

    • Main researcher for an AI model for a child face-matching system to assist kindergarten teachers (Lulla App).

🏆 Achievements, Awards, and Honors

  • Winner of ICASSP 2023 SPGC Challenge: Multilingual Alzheimer’s Dementia Recognition through Spontaneous Speech (First Author) 🥇
  • Excellence Prize, Korea Software Congress 2023 🥇
  • Encouragement Prize, ACM Student Research Competition, Computer Human Interaction 2020 (First Author) 🎖️
  • Excellence Prize, Korea Software Congress 2019 (First Author) 🏅
  • Encouragement Prize, Korea Software Congress 2019 (First Author) 🎖️
  • Excellent Presentation, International Conference on Culture Technology 2018 🌟

Publication Top Notes:

Interpretable Cross-Subject EEG-Based Emotion Recognition Using Channel-Wise Features†

CITED:29

Consen: Complementary and simultaneous ensemble for alzheimer’s disease detection and mmse score prediction

CITED:15

Eeg-based user identification using channel-wise features

CITED:7

E-EmotiConNet: EEG-based emotion recognition with context information

CITED:2

Emotion Recognition based BCI using Channel-wise Features

CITED:1

 

Mrs. Sabatina Criscuolo | Signal Processing Awards | Young Scientist Award

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Mrs. Sabatina Criscuolo | Signal Processing Awards | Young Scientist Award 

Mrs. Sabatina Criscuolo, University of Naples Federico II, Italy

Sabatina Criscuolo is an Italian biomedical engineer currently pursuing a Ph.D. in Information and Communication Technology for Health at the University of Naples Federico II, where she is affiliated with the National Research Council’s Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA). Her research focuses on the development of advanced artificial intelligence techniques to support precision medicine, with specific applications in neurodegenerative diseases, type 1 diabetes, and colorectal surgery. Sabatina has also collaborated internationally, including a visiting PhD position at the Applied Intelligence Research Centre in Dublin, where she worked on EEG artifact removal using variational autoencoders. With a strong academic background, she holds a Master’s degree in Biomedical Engineering, specializing in Bionic and Biorobotics, and has been involved in various research projects and initiatives aimed at enhancing health monitoring and rehabilitation technologies. In addition to her research activities, Sabatina contributes to the scientific community as a reviewer for multiple journals and has organized significant conferences in her field.

Professional Profile:

ORCID

Research for Young Scientist Award Evaluation for Sabatina Criscuolo

Sabatina Criscuolo is a promising candidate for the Research for Young Scientist Award, given her strong academic background, ongoing research initiatives, and contributions to the field of biomedical engineering and artificial intelligence. Here are several key points that highlight her suitability for this award.

Academic Experience

Sabatina is currently engaged in research at the National Research Council – STIIMA in Lecco, Italy, focusing on advanced artificial intelligence techniques to support precision medicine. Her work involves developing AI algorithms for applications in electroencephalographic (EEG) analysis related to neurodegenerative diseases, type 1 diabetes, and colorectal surgery.

PhD Studies: Since January 2022, she has been pursuing her PhD, with her thesis submission planned for December 2024 and expected graduation in March 2025. She has also been a visiting PhD student at the Applied Intelligence Research Centre in Dublin, Ireland, where she worked on EEG artifact removal using variational autoencoders and explainable AI.

Education

Sabatina holds a Master’s degree in Biomedical Engineering with a focus on Bionic & Biorobotics, where she developed a wearable Brain-Computer Interface system for robot-assisted rehabilitation in children with ADHD. She also completed a Bachelor’s degree in Biomedical Engineering, focusing on innovative enzyme immobilization methods.

Research Collaborations

Her collaborative research spans several institutions, including the University of Salento, Temple University, and the Interdepartmental Research Centre on Management and Innovation in Healthcare at her home university.

Scientific Impact

As of July 2024, Sabatina has an H-index of 5 on Scopus, reflecting her contributions to topics such as EEG signal analysis and diabetes management.

Publication Top Notes

Interpreting the latent space of a Convolutional Variational Autoencoder for semi-automated eye blink artefact detection in EEG signals

Improving Multiscale Fuzzy Entropy Robustness in EEG-Based Alzheimer’s Disease Detection via Amplitude Transformation

Exploring Nutritional Influence on Blood Glucose Forecasting for Type 1 Diabetes Using Explainable AI

A Novel Metric for Alzheimer’s Disease Detection Based on Brain Complexity Analysis via Multiscale Fuzzy Entropy

EEG complexity-based algorithm using Multiscale Fuzzy Entropy: Towards a detection of Alzheimer’s disease

Mr. Qiang Yu | Signal Theory Award | Best Researcher Award

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Mr. Qiang Yu | Signal Theory Award | Best Researcher Award

Mr. Qiang Yu, Shanxi Normal University, China

Dr. Qiang Yu is a distinguished professor in the Department of Mathematical Sciences at Shanxi Normal University, China. With a solid academic foundation, Dr. Yu obtained his B.S. in Mathematics Education from Shi He Zi University in 2003, followed by an M.S. in Applied Mathematics and a Ph.D. in Basic Mathematics from Shaanxi Normal University in 2009 and 2014, respectively. His doctoral research, under the guidance of Professor Baowei Wu, focused on nonlinear systems, stability, stabilization, and control. Dr. Yu’s professional career began as a mathematics teacher at Fukang No.1 Senior School in Xinjiang. He then advanced to academic positions at Heng Shui University and Shaanxi Normal University, where he steadily rose through the ranks from Lecturer to Associate Professor, and ultimately to Professor in December 2023. He also served as a visiting professor at the Shibaura Institute of Technology in Japan from 2019 to 2020, collaborating with Prof. Guisheng Zhai.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award

Dr. Qiang Yu demonstrates an exceptional academic and professional background that makes him highly suitable for the Best Researcher Award. His educational foundation in mathematics (B.S., M.S., and Ph.D. from Shi He Zi University and Shaanxi Normal University) underpins his rigorous work in complex areas like control theory, dynamical systems, and nonlinear systems. He has further specialized in switched systems, robust control, and time-delay systems—highly relevant research areas with widespread applications in engineering and mathematics.

📚 Academic Background

  • 🎓 B.S. in Mathematics Education (1999-2003) – Shi He Zi University
  • 🎓 M.S. in Applied Mathematics (2006-2009) – Shaanxi Normal University
  • 🎓 Ph.D. in Basic Mathematics (2011-2014) – Shaanxi Normal University
    • 📑 Advisor: Professor Baowei Wu
    • 🔍 Research Theme: Nonlinear Systems, Stability, Stabilization, and Control

🏫 Professional Experience

  • 🧑‍🏫 Math Teacher – Fukang No.1 Senior School, Xinjiang (2003-2006)
  • 📈 Lecturer – Heng Shui University, Hebei (2009-2011)
  • 🎓 Lecturer, Associate Professor, and Professor – Shaanxi Normal University, Shanxi (2014-present)
  • 🌏 Visiting Professor – Shibaura Institute of Technology, Saitama, Japan (2019-2020)

🔬 Research Interests

  • 🛠️ Switched Systems
  • 📏 Robust Control
  • ⏳ Time-Delay Systems
  • 📊 Control Theory and Engineering
  • 🧮 Applied Mathematics
  • 🔄 Dynamical Systems
  • 🤖 Neural Networks

🌐 Professional Memberships and Activities

  • 🔍 Reviewer for Mathematical Reviews
  • 🏅 Member, IEEE Control Systems Society
  • 🧩 Member, Chinese Mathematical Society
  • 🤖 Member, Chinese Association of Automation
  • 🇨🇳 Member, Society of Industry and Applied Mathematics of China
  • ✒️ Editorial Board Member, American Journal of Applied Mathematics (Since 2020)

🏆 Honors and Awards

  • 🥇 First Prize Gardener’s Scholarship, Shaanxi Normal University (2013)
  • 🥈 Second Prize in National College Student Academic Competitions (2013)
  • 🎖️ National Scholarship for Doctoral Students, Ministry of Education of China (2013)
  • 🏅 Excellent Postgraduate Student Award, Shaanxi Normal University (2014)
  • 🥉 Third Prize in Teachers’ Skills Competition, Shanxi Normal University (2015)
  • 🥈 Second Prize in National Mathematics Micro Course Design Competition (2016)
  • 🌟 Advanced Individual for Educational Excellence, Shanxi Normal University (2017)
  • 🥉 Third Prize for Excellent Academic Paper, Shanxi Science and Technology Department (2018)
  • 🥇 First Prize Science and Technology Award, Shaanxi Higher Education Institutions (2019)
  • 🏆 Second Prize of the Natural Science Award, Shaanxi Science and Technology (2022)

Publication top Notes:

Sampled-data synchronization of delayed multi-agent networks and its application to coupled circuit

CITED:62

Analysis of mixed convection flow in an inclined lid-driven enclosure with Buongiorno’s nanofluid model

CITED:56

Stability analysis for discrete-time switched systems with stable and unstable modes based on a weighted average dwell time approach

CITED:45

Coiflets solutions for Föppl-von Kármán equations governing large deflection of a thin flat plate by a novel wavelet-homotopy approach

CITED:39

Robust stability analysis of uncertain switched linear systems with unstable subsystems

CITED:38

Stability analysis of discrete-time switched linear systems with unstable subsystems

CITED:36

Dr. B. Omkar Lakshmi Jagan | Signal Estimation Award | Best Researcher Award

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Dr. B. Omkar Lakshmi Jagan | Signal Estimation Award | Best Researcher Award 

Dr. B. Omkar Lakshmi Jagan, Vignan’s Institute of Information Technology, India

Dr. Banana Omkar Lakshmi Jagan is an accomplished academic and researcher in the field of Statistical Signal Processing, with a Ph.D. from Koneru Lakshmaiah Education Foundation. Currently serving as an Assistant Professor in the Department of Computer Science Engineering at Vignan’s Institute of Information Technology, Dr. Jagan has a diverse teaching and research background. His previous roles include Assistant Professor in Artificial Intelligence and Machine Learning at Malla Reddy University and research positions with the NRB-DRDO projects focused on submarine target motion analysis and performance evaluation of algorithms. With over five years of research experience and nearly two years in teaching, Dr. Jagan has specialized in Deep Learning, Machine Learning, Linux Programming, and IoT. He has also earned additional certifications in Deep Learning and IoT from NPTEL. His commitment to both academic excellence and innovative research drives his career in exploring advanced technologies and methodologies in his field.

Professional Profile:

Suitability for the Best Researcher Award:

Dr. Banana Omkar Lakshmi Jagan has demonstrated significant achievements in research, teaching, and contributions to multiple domains, particularly in Statistical Signal Processing, Machine Learning, Deep Learning, and Target Tracking. Based on his extensive academic background, research projects, and publications, he is a strong candidate for the Best Researcher Award.

Education 

  • Ph.D. in Statistical Signal Processing
    2023
    Koneru Lakshmaiah Education Foundation (Deemed to be University), Andhra Pradesh
  • M.Tech. in Power Systems
    2016
    Koneru Lakshmaiah Education Foundation (Deemed to be University), Andhra Pradesh
  • B.Tech. in Electrical and Electronics Engineering
    2014
    Sri Sivani College of Engineering, JNTU Kakinada, Andhra Pradesh
  • Intermediate (M.P.C)
    2008
    Board of Intermediate Education, Andhra Pradesh
  • Xth Grade
    2006
    Council for the Indian School Examinations, Delhi

Work Experience

  1. Assistant Professor
    Department of Computer Science Engineering
    Vignan’s Institute of Information Technology (A), Duvvada, Visakhapatnam, Andhra Pradesh, India
    May 22, 2024 – Present
  2. Assistant Professor
    Department of Artificial Intelligence and Machine Learning, Department of Computer Science Engineering
    School of Engineering, Malla Reddy University, Hyderabad, Telangana, India
    December 28, 2022 – May 22, 2024
  3. Research Associate (RA)
    NSTL-DRDO Project, Department of Electronics and Communication Engineering
    Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
    July 17, 2022 – December 27, 2022
    Project Title: Performance Evaluation of all TMA Algorithms for Bot & Calculation of MLA & SOA for Identified Zigging Targets
  4. Senior Research Fellow (SRF)
    NRB-DRDO Project, Department of Electronics and Communication Engineering
    Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
    July 9, 2021 – January 8, 2022
    Project Title: State of Art Submarine Target Motion Analysis
  5. Junior Research Fellow (JRF)
    NRB-DRDO Project, Department of Electronics and Communication Engineering
    Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
    July 9, 2019 – July 8, 2021
    Project Title: State of Art Submarine Target Motion Analysis
  6. Junior Research Fellow (JRF)
    NRB-DRDO Project, Department of Electronics and Communication Engineering
    Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India
    July 12, 2016 – July 11, 2018
    Project Title: Advance Submarine Target Motion Analysis

Publication top Notes:

CITED:56
CITED:26
CITED:21
CITED:18
CITED:13
CITED:11

Assist Prof Dr. Hwa-Dong Liu | Signal Processing | Best Researcher Award

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Assist Prof Dr. Hwa-Dong Liu | Signal Processing | Best Researcher Award

Assist Prof Dr. Hwa-Dong Liu, Undergraduate Program of Vehicle and Energy Engineering, National Taiwan Normal University, Taiwan

Hwa-Dong Liu is an Assistant Professor at National Taiwan Normal University (NTNU) in Taipei, Taiwan, specializing in power electronics, microcontrollers, rail vehicle power systems, and solar power systems. He holds a Ph.D. in Electrical Engineering from National Taiwan University of Science and Technology (NTUST). His research interests include the development of advanced power converters, control strategies for renewable energy systems, and innovative solutions for electric vehicle charging. Dr. Liu has authored numerous papers in reputable journals, with a focus on improving the efficiency and performance of power electronic systems and renewable energy technologies. His recent work includes contributions to energy management systems, high-gain boost converters, and novel MPPT algorithms for solar power generation.

Professional Profile:

Summary of Suitability for Best Researcher Award 

Hwa-Dong Liu has expertise in several cutting-edge fields including power electronics, microcontrollers, rail vehicle power systems, and solar power systems. This diversity indicates a broad impact on multiple important areas of research.

Education

  • Ph.D. in Electrical Engineering from National Taiwan University of Science and Technology (NTUST).

Work Experience

  • Assistant Professor at National Taiwan Normal University (NTNU).

Expertise

  1. Power Electronics
  2. Microcontroller
  3. Rail Vehicle Power Systems
  4. Solar Power Systems

Publication top Notes:

An improved solar step-up power converter for next-generation electric vehicle charging

Hybrid Management Strategy for Outsourcing Electromechanical Maintenance and Selecting Contractors in Taipei MRT

An Improved High Gain Continuous Input Current Quadratic Boost Converter for Next-Generation Sustainable Energy Application

Novel MPPT algorithm based on honey bees foraging characteristics for solar power generation systems

High-Voltage Autonomous Current-Fed Push-Pull Converter with Wireless Communication Applied to X-Ray Generation