Assoc. Prof. Fengming Du

Dalian Maritime University, China

Biography: 

Du Fengming, Ph.D. from Dalian University of Technology, Associate Professor and Doctoral Supervisor at the School of Marine Engineering, Dalian Maritime University, Postdoctoral Fellow in Ship and Ocean Engineering Flow Station. His main research areas include engine optimization design, advanced material preparation, artificial intelligence, machine vision. Received the titles of "Million Talents Project" talent in Liaoning Province, "Dalian Youth Science and Technology Star", and "Dalian High level Talent Youth Talent", as well as one Liaoning Province Natural Science Academic Achievement Award. Hosted 2 key projects of the Vehicle and Ship Power Special Project of the State Administration of Science and Technology for National Defense, 1 key project of the Liaoning Provincial Natural Science Foundation, 1 joint project of the Liaoning Provincial Shipping Joint Fund, 1 general project of the China Postdoctoral Fund, 1 project of the Dalian High level Talent Innovation Support Program, 2 special funds for undergraduate research and business expenses of central universities, and 7 horizontal projects. Participated in more than 10 projects, including the National Natural Science Foundation of China, the Ministry of Equipment Development's pre research project, and the Ministry of Industry and Information Technology's high-tech shipbuilding project. Published over 60 academic papers and 7 invention patents and 2 international invention patents. He is a senior member of the Chinese Society of Mechanical Engineering and industry and technology expert of dalian municipal bureau of industry and information technology, serving as a reviewer for journals such as Journal of Materials Processing Technology, The International Journal of Advanced Manufacturing Technology, Steel Research International, and International Journal of Engine Research. Served as a guest editor for journals such as Lubricants and Coatings.

Speech Title: The application of intelligent algorithms in the mechanical industry

Abstract: The wear of sliding bearings exhibits complex nonlinear characteristics. If accurately the laws of bearing wear changes can be grasped to guide wear tests, so the experimental research could be accelerated and the economic expenses and labor costs could be saved. The widely used BP neural network has lower prediction accuracy, so it can be optimized. In the case of optimizing the internal structure of the BP neural network, this work combines intelligent algorithms with the BP neural network organically, using genetic algorithms and sparrow search algorithms to optimize the initial threshold and initial weights of the BP neural network, solving the disadvantage of the BP neural network only being able to seek local optimization, improving the prediction accuracy of the BP neural network, and establishing a neural network prediction model with better prediction performance.

Assoc.Prof. Ata Jahangir Moshayedi 

IEEE Senior Member

Jiangxi University of Science and Technology, China

Biography: 

Dr. Ata Jahangir Moshayedi an Associate Professor at Jiangxi University of Science and Technology in China, holds a PhD in Electronic Science from Savitribai Phule Pune University in India. He is a distinguished member of IEEE(Senior Member) and ACM, as well as a Life Member of the Instrument Society of India and a Lifetime Member of the Speed Society of India. Additionally, he contributes to the academic community as a valued member of various editorial teams for international conferences and journals.Dr. Moshayedi's academic achievements are, marked by a portfolio of over 90 papers published ,2 patent and 12 copyright , across esteemed national and international journals and conferences along with 3 books on robotics (VR and mobile olfaction) and embedded systems.In addition to his scholarly publications, he has authored three books and is credited with two patents and nine copyrights, emblematic of his pioneering contributions to the field. His research interest includes Robotics and Automation/ Sensor modeling/Bio-inspired robot, Mobile Robot Olfaction/Plume Tracking, Embedded Systems / Machine vision-based Systems/Virtual reality, and Machine vision/Artificial Intelligence. Currently, Dr. Moshayedi is actively engaged in pioneering work at Jiangxi University, where he is developing a model for Automated Guided Vehicles (AGVs) and advancing the realm of Food Delivery Service Robots.

Speech Title: Ergonomically Designed Assistive Robots: Enhancing Elderly Care with Comfort, Safety, and Independence

Abstract: The aging population worldwide presents significant challenges to elderly care, particularly in maintaining their comfort, safety, and independence. Ergonomically designed assistive robots offer a promising solution to address these challenges by providing personalized support that aligns with the physical and cognitive needs of older adults. This talk will explore the role of assistive robots in elderly care, focusing on their ergonomic design, functionality, and impact on enhancing the well-being of elderly individuals. Key design principles such as user-centered ergonomics, adaptability to various physical conditions, ease of interaction, and safety features will be discussed. Additionally, the talk will highlight the integration of advanced technologies such as AI, machine learning, and sensor systems, which enable robots to assist with daily activities, mobility, medication management, and social interaction. Through case studies and recent advancements, we will examine the potential of these robots to improve elderly care by fostering independence, preventing injuries, and providing companionship. The session will conclude with an outlook on future research and the ongoing development of assistive robots to meet the evolving needs of the aging population.