The stated project aims to investigate the development of theoretical foundations and the analysis of signals and images through the use of spline functions. This includes the digital processing and recovery of such data using splines, as well as the modeling of structures in multi-core processors and the implementation of parallel algorithms. This research may involve the development of new methods and tools for processing and analyzing data using splines, as well as the optimization of algorithms and processor structures to improve performance. The goal of the project may be to advance our understanding of the potential applications and capabilities of splines in signal and image processing, and to develop more efficient and effective techniques for working with such data.

Smart cities are urban environments that use digital technologies to improve the quality of life for their citizens, increase efficiency and sustainability, and support economic growth. Digital transformation in cities involves the adoption and integration of a wide range of digital technologies, including the internet of things (IoT), big data analytics, artificial intelligence (AI), and cloud computing, to improve and enhance various aspects of city life. These technologies can be used to improve transportation, energy management, public safety, healthcare, and other services, as well as to create new opportunities for innovation and economic development. Digital transformation in cities is driven by the desire to create more livable, sustainable, and connected communities, and to address the challenges and opportunities of urbanization in the 21st century.

Upon completion of this course program, technical professionals will understand:

• The most important aspects of the Digital Transformation of Smart city.

• The analysis and interpretation process of healthcare monitoring data study

This project focuses on the use of spline functions, which are piecewise polynomial functions formed by gluing together various pieces of polynomials, to facilitate digital signal and image processing. The smooth, homogeneous structure of spline functions makes them well-suited for use in a range of applications, including computer graphics, image processing and restoration, machine vision, multimedia, animation, and computer game programming. The project aims to explore the potential of spline functions in these areas and to identify solutions that can be widely applied.

This project aims to address a wide range of mental health conditions that affect mood, thinking, and behavior, with a particular focus on depression. Depression is a common condition that affects people of all ages and backgrounds, and has been on the rise due to the ongoing COVID-19 pandemic and its economic and social impacts. The project seeks to leverage artificial intelligence (AI) to develop solutions for addressing depression and other mental health conditions. This may involve the use of machine learning, natural language processing, and deep learning to analyze and understand human emotions, behaviors, and coping strategies, and to develop personalized interventions and support systems. The goal of the project is to use AI to help people better manage their mental health and well-being, and to promote resilience and happiness.

Workshops:

• Mental Health Crisis and Treatment (MHCT)

• AI-MHA: AI-Inspired Solutions for Mental Health Ailments: Prevention, Detection, and Treatment

This project aims to address the challenges and opportunities of the fourth industrial revolution, or Industry 4.0, which involves the integration of advanced digital technologies into industrial production and management. These technologies, including software, artificial intelligence, and microelectronics, enable the automation of prediction, monitoring, and planning, and can improve productivity, resource management, and overall performance. The project aims to explore the potential of Industry 4.0 to create positive impacts in a variety of areas, and to develop new approaches and solutions for optimizing production in this context.

Elastic-RAN: An adaptable multi-level elasticity model for Cloud Radio Access Networks, Computer Communications, Volumes 142–143, 15 June 2019, Pages 34-47

The automotive industry is working to develop intelligent and autonomous vehicles, but there is a need to understand the safety and security implications of this connected technology. The IEEE 5-course program on Automotive Cyber Security: Protecting the Vehicular Network aims to address these issues by providing a forum for discussing automotive cyber security solutions and requirements for both intelligent vehicles and the infrastructure of intelligent transportation systems. This program is designed to foster an understanding of the challenges and opportunities presented by the increasing connectivity of the automotive industry and to develop strategies for addressing these issues.

Upon completion of this course program, technical professionals will understand:

• The most important aspects of the automotive cyber security evolution.

• The implementation process of Vehicle-to-Vehicle (V2V) and Vehicle to Infrastructure (V2X) communication systems to work with autonomous vehicles and Intelligent Transportation Systems.

• The analysis and interpretation process of vehicular data on automotive technology.