The Second International Conference on Innovations in Computing Research (ICR’23) brings together a diverse group of researchers from all over the world with the intent of fostering collaboration and dissemination of the innovations in computing technologies. The conference is aptly segmented into six tracks: Data Science, Computer and Network Security, Health Informatics and Medical Imaging, Computer Science and Computer Engineering Education, Internet of Things, and Smart Cities/Smart Energy. These tracks aim to promote a birds-of-the-same-feather congregation and maximize participation.
The Data Science track covers a wide range of topics including complexity score for missing data, deep learning and fake news, cyberbullying and hate speech, surface area estimation, analysis of gambling data, car accidents predication model, augmenting character designers’ creativity, deep learning for road safety, effect of sleep disturbances on the quality of sleep, deep learning-basedpath-planning, vehicle data collection and analysis, predicting future stocks prices, and trading robot for foreign exchange.
Computer and Network Security track is dedicated to various areas of cybersecurity. Among these are decentralized solution for secure management of Io T access rights, multi-factor authentication as a service (MFAaa S) for federated cloud environments, user attitude toward personal data privacy and data privacy economy, host IP obfuscation and performance analysis, and vehicle OBD-II port countermeasures.
The Computer Science and Engineering Education track enfolds various educational areas, such as data management in industry–academia joint research: a perspective of conflicts and coordination in Japan, security culture and security education, training and awareness (SETA), influencing information security management, engaging undergraduate students in developing graphical user interfaces for NSF funded research project, and emotional intelligence of computer science teachers in higher education.
On the Internet of Things (Io T) track, the focus is on industrial air quality sensor visual analytics, social spider optimization meta-heuristic for node localization optimization in wireless sensor networks, and privacy aware Io T-based fall detection with infrared sensors and deep learning.
The Smart Cities and Smart Energy track spans various areas, which include, among others, research topics on heterogeneous transfer learning in structural health monitoring for high-rise structures and energy routing in energy Internet using the firefly algorithm.
