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Student visitor from Japan to Big Data Group at Vestlandsforsking


To achieve the optimal users’ quality of experience, there are two fundamental challenges needed to be tackled: firstly, how to predict users’ future viewport accurately based on users’ past motion traces; and secondly, how to adaptively select bitrates in both space (viewport areas has higher bitrate than non-viewport areas) and time (bitrate between adjacent time step should not change a lot) dimensions under various network conditions.

Xiaolan Jiang, a PhD student at National Institute of Informatics (NII Tokyo) Japan, is currently visiting the Big Data Research Group at Vestlandsforsking, Norway under the student mobility programme of the BDEM project. His institute is a formal partner in the BDEM project.

At NII, Xiaolan is working on Virtual Reality (VR) (360-degree) video streaming, under the supervision of Professor Yusheng Ji.


He designed a Long Short-Term Memory (LSTM) -based model to predict users' future viewport and applied deep reinforcement learning to train a neural network to adaptively select bitrates for 360 video chunks under dynamic network conditions.

At Vestlandsforsking, Xiaolan is collaborating with Professor Akerkar and researchers, Dr. Minsung Hong and Dr. Hoang Long Nguyen on video stream processing challenges for capturing and processing video data from geographically distributed cameras.

Research Summer Intern Exploring Big Disaster Data

BDEM summer intern Andreas Iden (Master student at the University of Bergen) & researchers at Big Data Research Group, Vestlandsforsking are investigating the potential for Big Data — harnessed through integrated & networked data resources, along with suitable analytics — to benefit Emergency Preparedness, Resilience & Response.

Minsung Hong and Andreas Iden

Hong Kong researchers visit to Vestlandsforsking

Professor Song Guo of Hong Kong Polytechnic University visited the Big Data Research Group at Vestlandsforsking, Sogndal in June 2019. His research interests are mainly in the areas of big data, cloud computing and networking, and distributed systems with over 400 papers published in major conferences and journals. He is a project partner in the INTPART BDEM and is contributing to the project with his expertise in the areas of resource management for cloud computing and big data in emergency situations and response.

His PhD student Joey Lau has also visited under student mobility programme of BDEM project. He has spent three months in the Big Data Research Group at Vestlandsforsking to earn a research experience on real-time data processing in emergency management. He joined the Group in April 2019 and working on an Automatic Disaster Keyword Expansion (ADKE) framework based on real-time social media data with Dr. Minsung Hong and Professor Rajendra Akerkar. Our two research groups are expanding collaboration on design and development of a road safety framework that adapts to the evolving mobility environment, new types of vehicles and users based on integrated solution that utilises the sensing and communication capabilities of road users.

Just out a new research article by the BDEM researcher team

A new research paper entitled “A Framework to Integrate Social Media and Authoritative Data for Disaster Relief Detection and Distribution Optimization“ has been published in the International Journal of Disaster Risk Reduction. In this paper, the BDEM researchers propose an interdisciplinary approach to (natural) disaster relief management. Our framework combines dynamic and static databases, which consist of social media and authoritative data of an afflicted region, respectively, to model rescue demand during a disaster situation. Using Global Particle Swarm Optimization and Mixed-Integer Linear Programming, we then determine the optimal amount and locations of temporal rescue centers. Furthermore, our disaster relief system identifies an efficient distribution of supplies between hospitals and rescue centers and rescue demand points. By leveraging the temporal dimension of the social media data, our framework manages to iteratively optimize the disaster relief distribution.

It is a joint work of Timothy Schempp (CICS, San Diego State University), Haoran Zhang (The University of Tokyo), Alexander Schmidt (Uni Hohenheim), Minsung Hong and Rajendra Akerkar (Vestlandsforsking).

Full article can be found at the journal website.

WNRI researcher's visit to the University of Tokyo

In order to discuss ongoing research cooperation and further research direction, Dr. Minsung Hong (researcher at the Western Norway Research Institute) had meeting with the BDEM partner research group in Tokyo on December 3rd, 2018. The research group at Intelligent Perception and Urban Computing Laboratory of the University of Tokyo is headed by Dr. Xuan Song.

Dr. Minsung Hong (WNRI) presenting research at Intelligent Perception and Urban Computing Laboratory, Japan.

Dr. Minsung Hong (WNRI) presenting research at Intelligent Perception and Urban Computing Laboratory, Japan.

In this meeting research students and postdocs at the University of Tokyo presented and shared their work. Moreover, Minsung presented the basic idea of a victim detection technology platform as well as preliminary results from joint research on a framework that efficiently integrates victim detection technologies considering sensing, communication and computing issues. The research aims to achieve a significant time reduction related to Victim Search and Rescue phase by providing wide-area situational awareness solutions for improved detection and localization of trapped victim.

They also discussed student-staff exchange visits to Norway.