This book includes high-quality papers presented at 17th International Conference on Information Technology and Applications (ICITA 2023), held in Turin, Italy during 20 - -22 October 2023. The book presents original research work of academics and industry professionals to exchange their knowledge of the state-of-the-art research and development in information technology and applications. The topics covered in the book are cloud computing, business process engineering, machine learning, evolutionary computing, big data analytics, internet of things and cyber-physical systems, information and…mehr
This book includes high-quality papers presented at 17th International Conference on Information Technology and Applications (ICITA 2023), held in Turin, Italy during 20 - -22 October 2023. The book presents original research work of academics and industry professionals to exchange their knowledge of the state-of-the-art research and development in information technology and applications. The topics covered in the book are cloud computing, business process engineering, machine learning, evolutionary computing, big data analytics, internet of things and cyber-physical systems, information and knowledge management, computer vision and image processing, computer graphics and games programming, mobile computing, ontology engineering, software and systems modelling, human computer interaction, online learning /e-learning, computer networks, and web engineering.
Dr. Abrar Ullah is Associate Professor and Director of Postgraduate Studies at the School of Mathematical and Computer Science, Heriot Watt University, Dubai Campus. He received the M.Sc. (Computer Science, 2000) from University of Peshawar. He received the Ph.D. (Security and Usability) from University of Hertfordshire, UK. He has been working in industry and academia for over 20 years. He has vast experience in teaching and development of enterprise systems. He started his teaching career in 2002 as lecturer at the University of Peshawar and Provincial Health Services Academy Peshawar. In 2008, he joined the ABMU NHS UK as Lead Developer and contributed to a number of key systems in the NHS. He has published over 16 research articles in prestigious conferences and journals. Dr. Sajid Anwar is full Professor at the Center of Excellence in Information Technology Institute ofManagement Sciences (IMSciences), Peshawar, Pakistan. He received his M.S. (Computer Science, 2007) and Ph.D. degrees (Software Engineering, 2011) from NUCES-FAST, Islamabad. Previously, he was Head of Undergraduate Program in Software Engineering at IMSciences. He is Leading Expert in software architecture engineering and software maintenance prediction. His research interests are cross-disciplinary and industry focused and includes search-based software engineering; prudent-based expert systems; customer analytics, active learning and applying data mining and machine learning techniques to solve real-world problems. He has been Guest Editor of numerous journals, such as Neural Computing and Applications, Cluster Computing Journal Springer, Grid Computing Journal Springer, Expert Systems Journal Wiley, Transactions on Emerging Telecommunications Technologies Wiley, and Computational and Mathematical Organization Theory Journal Springer. He is also Member Board Committee Institute of Creative Advanced Technologies, Science and Engineering, Korea (iCatse.org). Dr. Davide Calandra is Assistant Professor at the University of Turin, Department of Management. He is Chartered Accountant, Auditor, and Author of multiple publications within the sustainability field, the impact of new technologies in businesses and smart cities. He is involved in numerous local, national, and international projects. Finally, over the years, he has been involved in multiple European projects, such as H2020 Avangard, to study proper business models for electric mobility and an Erasmus + on social entrepreneurship. Dr. Raffaele is Researcher in Educational Psychology at University of Foggia. He is Biomedical Engineer and has a Ph.D. in Human Mind and Gender Studies in University of Naples-Federico II. His research interests are focused on the advanced teaching/learning technologies and applications, tangible user interfaces (TUIs) with a multisensory approach in the education, and serious game applications. In 2017, he won the prize of the International ASLERD Contest for the best "People Centered Smart Learning Ecosystem" prototype. Now, he is Co-founder of the Serious Game Factory-SGF srl, a spin-off of the University of Foggia. He was Project Coordinator on behalf of ISTC-CNR of the LLP-Comenius project BLOCKMAGIC and led as Partner Project Manager 12 project in Erasmus+ in the field of TEL. Nowadays, he is Principal Investigator of the Erasmus+ project E-MEDIC on behalf of University of Foggia.
Inhaltsangabe
1. Exploring Practical Applications of Blockchain in Waste Management: Insights from Industry Experts.- 2. Uncovering Hidden Connections: Granular Relationship Analysis in Knowledge Graphs.- 3. Visually Detecting Drones in Drone Swarm Formations Topologies.- 4. Comparison of deep learning and machine learning algorithms to diagnose and predict breast cancer.- 5. Overcoming the Challenges of Data Harmonization: A platform approach from Li-Ion Battery Research.- 6. Exploring the effects of technology in fintech industry: a literature review to provide a research agenda.- 7. Effectiveness Of Internal Evaluation Matrices For Community Detection Based On Clustering.
1. Exploring Practical Applications of Blockchain in Waste Management: Insights from Industry Experts.- 2. Uncovering Hidden Connections: Granular Relationship Analysis in Knowledge Graphs.- 3. Visually Detecting Drones in Drone Swarm Formations Topologies.- 4. Comparison of deep learning and machine learning algorithms to diagnose and predict breast cancer.- 5. Overcoming the Challenges of Data Harmonization: A platform approach from Li-Ion Battery Research.- 6. Exploring the effects of technology in fintech industry: a literature review to provide a research agenda.- 7. Effectiveness Of Internal Evaluation Matrices For Community Detection Based On Clustering.
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