ABSTRACT. In April 2017, the Institute for Datability Science was established to promote advanced data utilization and the creation of intellectual value within and throughout all the fields of the university.

Datability is a new word that combines “data” and “ability.” Datability is all about the ability to use large volumes of data sustainably and responsibly. Using datability, our institution will support Osaka University’s research capability by interacting with this new society derived from huge volumes of data, and utilize that data for the integration and benefit for all areas of research. The process of data analysis also cultivates new interdisciplinary research fields.

The institute aims to promote interdisciplinary research and pioneer new academic fields through data analysis using AI technologies.

On September 19, 2018, Osaka University’s Initiative for Life Design Innovation Project was selected for the Ministry of Education, Culture, Sports, Science and Technology’s 2018- 19 Research Hub Support Project for the Realization of Society 5.0. Osaka University was the only university selected for this project.

At Osaka University, we will construct a research hub for verifying information and science technologies necessary for realizing Society 5.0 together with research institutes, local municipalities, and corporations.

From the inseparable link between everyday life and health, we will design a high quality of life (QOL) on the basis of physical health, mental health, social health, and environmental health to share various technological innovations with society and lead social reform. Specifically, we will concurrently promote research on: Lifestyle Research (research for maintaining and improving QOL), Wellness Research (research for improving physical and mental health), and Edutainment Research (research for realizing fun in learning).

In this presentation, I will briefly introduce the Institute for Datability Science and Initiative for Life Design Innovation.

ABSTRACT. The speaker will be highlighting process, matrix, and ethical context that are integral to (a) high-quality research, (b) impactful dissemination, and (c) ranking of world-class universities and institutions. Data and trends showing progression of global universities and institutions, in general, and those of Bangladesh, India, and Pakistan, in particular, will be presented and discussed.

ABSTRACT. Deep neural networks (DNNs) have revolutionized the use of artificial neural networks in complex applications such as computer vision, speech recognition, medical imaging, and bioinformatics. Deep learning essentially enables autonomous learning of multi-layered (deep) large scale neural networks using large scale data. The organization and workings of recurrent neural networks (RNNs) mimics the overall working principle of neural pathways observed in the biological vision system. This talk outlines the latest research in the Vision Lab at Old Dominion University on generalizing the DNNs by incorporating simultaneous recurrent connections for different types of recognition tasks.