ABDULFATTAH AHMED QASEM ALWAH | Engineering and Technology | Best Researcher Award

ABDULFATTAH AHMED QASEM ALWAH | Engineering and Technology | Best Researcher Award

Assist Prof Dr ABDULFATTAH AHMED QASEM ALWAH, Ibb University, Yemen

Based on Mr. Tailong Lv’s educational background, research experience, and publication, here’s an assessment of whether he is a suitable candidate for the Best Researcher Award.

Publication profile

google scholar

Education

Mr. Tailong Lv holds a Bachelor’s degree in Automation from Henan University of Urban Construction and is currently pursuing a Master’s degree in Mechanical Engineering at Xi’an University of Posts & Telecommunications. His academic foundation is strong, particularly in technical fields relevant to his research focus.

Research Project

Mr. Lv’s main research project, “Deep Learning Based Human Activity Recognition,” showcases his proficiency in applying deep learning techniques to real-world problems. His work focuses on optimizing neural networks for better recognition of complex human activities. This is a cutting-edge area in artificial intelligence and has significant potential for applications in areas such as surveillance, healthcare, and human-computer interaction. His contribution to this field is commendable, given the complexity and real-world relevance of the project.

Awards & Recognition

Mr. Lv has received consecutive scholarships from Xi’an University of Posts and Telecommunications in 2022 and 2023, demonstrating academic excellence and a consistent track record of high achievement.

Research focus

The research focus of this person primarily revolves around urban planning, environmental sustainability, and public space management. Their work involves evaluating the disparity between supply and demand for green spaces 🌳, analyzing visual pollution in historical cities πŸ™οΈ, and predicting urban waterlogging risks 🌧️. Additionally, they contribute to developing tools to measure public space efficiency and studying the relationship between built environments and social sustainability 🏞️. Their research emphasizes creating better urban environments by addressing ecological concerns, enhancing public spaces, and promoting social well-being through thoughtful urban design.

Publication

His recent publication, “Multihead-Res-SE Residual Network with Attention for Human Activity Recognition” in the journal Electronics, reflects his engagement in research at an advanced level. Co-authoring this paper with established researchers like Hongbo Kang and Chunjie Yang, and contributing to a field as impactful as human activity recognition, highlights his research capabilities.

Conclusion

Mr. Tailong Lv’s solid educational background, innovative research in deep learning, continuous academic excellence, and publication record make him a strong candidate for the Best Researcher Award. His work contributes significantly to the field of AI and human activity recognition, aligning with the qualities expected of an award-winning researcher.

Publication top notes

Evaluating the disparity between supply and demand of park green space using a multi-dimensional spatial equity evaluation framework

Predicting urban waterlogging risks by regression models and internet open-data sources

Developing a quantitative tool to measure the extent to which public spaces meet user needs

Difficulty and complexity in dealing with visual pollution in historical cities: The historical city of Ibb, Yemen as a case study

Relationship between physical elements and density of use of public spaces in Sana’a City

Research of urban suitable ecological land based on the minimum cumulative resistance model: A Case Study from Hanoi, Vietnam

Analysis of visual pollution of the urban environment in the old city of Ibb

Characteristics of visiting urban open spaces in Sana’a city in Yemen

Relationship between the perceived characteristics of the built environment and social sustainability: Sana’a City, Yemen use case..

Predicting urban waterlogging risks by regression models and internet open-data sources. Water 12 (3): 879

 

 

 

Abdul Rehman | Engineering and Technology | Best Researcher Award

Abdul Rehman | Engineering and Technology | Best Researcher Award

Dr Abdul Rehman ,University of L’Aquila, Italy

Abdul Rehman is a dedicated researcher with a Ph.D. in Information and Communication Technologies from the University of L’Aquila, specializing in network architecture, industrial IoT, and simulation environments πŸŽ“πŸŒ. He has extensive experience in designing scalable communication systems and developing integrated simulators for complex networks, focusing on SDN and RIS technologies πŸ–§πŸ’». Abdul has published numerous papers in top-tier journals and conferences, contributing to advancements in wireless and high-frequency communications πŸ“šπŸ“‘. He has also taught at the Venture College of Engineering in Islamabad, Pakistan, and has a Master’s in Electronics and Communication Engineering from Shanghai πŸŒπŸ“˜.

Publication profile

google scholar

Education

Dr. Abdul Rehman is a dedicated researcher specializing in ICT with a Ph.D. from the University of L’Aquila, Italy (2021-2024). His thesis focuses on performance analysis of multiple access protocols for sidelink vehicular communications, encompassing 5/6G, URLLC, and wireless communication πŸ“‘πŸš—. He holds a Master’s in Electronics and Communication Engineering from Shanghai Jiao Tong University, China (2017-2019), where he researched GNSS integration for pedestrian smartphone navigation πŸ“±πŸ›°οΈ. His Bachelor’s in Electrical (Telecommunication) Engineering from Government College University Faisalabad, Pakistan (2013-2017) involved deforestation analysis using remote sensing πŸŒ²πŸ›°οΈ. His expertise includes sensor fusion, signal processing, and satellite communications.

Experience

From July 2021 to October 2024, He worked as a researcher at EX-EMERGE in L’Aquila, Italy, focusing on Energy Efficient Networks, URLLC in IoT, and Sidelink Vehicular Communications. He developed scalable and secure architectures for wireless systems, researched adaptive modulation and coding techniques, and designed integrable systems for efficient communication in varying conditions. He findings were published in top-tier journals and conferences. From July 2019 to December 2020, He lectured at Venture College of Engineering in Islamabad, Pakistan, teaching courses like Wireless Communication and supervising undergraduate research projects πŸ“‘πŸ“šπŸ”¬.

Honors and Awards

In 2019, the Certificate of Honor was awarded at the China Satellite Navigation Conference 🌟. Recognition for serving as Chairperson at IEEE-SAC was received in 2015 πŸ…. The same year saw the completion of the Continuing Professional Development Program (CPD-PEC) πŸ“œ. Significant contributions to the IEEE Young Professionals and Skill Development Program were acknowledged in 2014 πŸŽ“. Participation in the IEEE Tech-fair also occurred in 2014 πŸš€. Furthermore, a Certificate of Distinction was awarded for achieving 3rd position in BISE in 2014 πŸŽ–οΈ.

Research focus

A Rehman’s research focuses on advanced techniques in image processing, GNSS/PDR integration, and communication systems. Notable works include developing Mask RCNN-FPN for breast lesion detection 🩺, utilizing extended Kalman filters for precise pedestrian smartphone navigation πŸ“±, and analyzing deforestation in northern Pakistan using supervised classification 🌲. His contributions to GNSS and PDR fusion algorithms improve pedestrian navigation accuracy 🧭. Additionally, his research on multiple access interference in LTE-V2X and NR-V2X sidelink communications enhances vehicular communication networks πŸš—. These diverse studies highlight A Rehman’s expertise in biomedical imaging, navigation technology, and communication systems πŸ“‘.

Publication top notes

Multi-detection and segmentation of breast lesions based on mask rcnn-fpn

Accurate and direct GNSS/PDR integration using extended Kalman filter for pedestrian smartphone navigation

Deforestation analysis of northern areas (Pakistan) using image processing and maximum likelihood supervised classification

PDR/GNSS fusion algorithm based on joint heading estimation

On the Impact of Multiple Access Interference in LTE-V2X and NR-V2X Sidelink Communications

Analytical modeling of multiple access interference in C-V2X sidelink communications

Ming-Yen Wei | Engineering and Technology | Best Researcher Award

Ming-Yen Wei | Engineering and Technology | Best Researcher Award

Assist Prof Dr Ming-Yen, Wei National Formosa University, Department of Electrical Engineering, Taiwan

Assist. Prof. Dr. Ming-Yen was born in Taichung City, Taiwan πŸ‡ΉπŸ‡Ό on April 20, 1983. He earned his Bachelor’s and Master’s degrees in Electrical Engineering from National Formosa University in 2005 and 2007, and his Ph.D. from National Taiwan University of Science and Technology in 2012 πŸŽ“. After a decade in industrial technical roles, he joined National Formosa University as an Assistant Professor in early 2023 πŸ‘¨β€πŸ«. His research interests include motor drive control, embedded systems, control theory applications, mechatronics, and robotics πŸ€–βš™οΈ.

Publication profile

Scopus

Research focus

Dr. Ming-Yen Wei’s research primarily focuses on the design, control, and implementation of advanced motion control systems and platforms. His work encompasses the development of servo control systems, multi-axis motion chairs, and flight simulators, utilizing CAN bus and microcontroller technologies. Additionally, he has contributed to the creation of motion-cueing algorithms and inverse kinematics for six degrees of freedom (6DoF) platforms. His research has significant applications in robotics, aerospace, and virtual reality simulations, showcasing innovations in precision motion control and system integration.

Publication top notes

Design and Control of a Three-Axis Motion Servo Control System Based on a CAN Bus

Design and Implementation of a New Training Flight Simulator System

Design and Control of a Multi-Axis Servo Motion Chair System Based on a Microcontroller

Design of a DSP-Based Motion-Cueing Algorithm Using the Kinematic Solution for the 6-DoF Motion Platform

Design and implementation of inverse kinematics and motion monitoring system for 6dof platform

Optimal Control-based Motion Cueing Algorithm Design for 6DOF Motion Platform

Design and Implementation of the Inverse Kinematics and Monitoring Module for Six-axis Crank Arm Platform

Design, Analysis, and Implementation of a Four-DoF Chair Motion Mechanism