Hong Bong Hee 사진
Hong Bong Hee
POSITION
Prof.
EMAIL
bhhong@pusan.ac.kr
HOMEPAGE
http://dblab.pusan.ac.kr
Lab.
DataBase & Big Data LAB

1. Research Area

- Dynamic Rule Processing based on the RETE Algorithm for Continuous Spatiotemporal Complex Event Processing

- Development a test data set generator for validating stream data processing rules of naval target x-x-x-objects

- A Method for generating simulation data to predict the processing capability of container terminals

 

2. Research Overview

 When aerial, water and underwater target x-x-x-objects collected in real-time from naval vessels are collected as real-time stream data, continuous execution of space-time rules for risk analysis and weapon response is required. The existing RETE algorithm is a good technique for compiling a node-link of rules for processing scalar stream data such as temperature, gas, and fire. The RETE algorithm that processes scalar stream data processing rules is extended to support complex event processing rules that include spatiotemporal query conditions of target x-x-x-objects. We propose a spatiotemporal indexing method that extends the node-link structure of the RETE algorithm to support continuous queries, including sliding windows when processing complex events

 

 In naval vessels, the rule processing is most useful for filtering, analyzing, and making decisions about stream data collected by sensor types of equipment such as radar, sonar, and Infra-Red Search Tracker. Stream data processing rules collected from sensors attached to the side, front, and rear of a naval vessel may have different conditions for the rules depending on the vessel position and situation. This paper addresses the problem of generating a spatiotemporal data set of target x-x-x-objects to verify the rules for risk analysis and decision making of naval vessels. This paper discusses the issues of creating a spatiotemporal data set of target x-x-x-objects to check the rules for risk analysis and decision making of maritime vessels. The main contribution is the development of a technique for generating a test data set that can guarantee to verify a set of defined rules by making a target x-x-x-object's movement inertia and various movement patterns.

 

 Simulation is needed to predict processing capacity when an unexpected large container ship arrives at a container terminal currently in operation. The processing capacity of the container terminal depends on the number of loading and unloading equipment, operating time, scheduling policies for carrying in and out of the container, and operation policy. The hypothesis of this study is that the optimization method for each component of the container terminal is not an optimized solution for the entire terminal. The primary purpose of this paper is to find an optimized solution for the whole terminal using simulation data generated for various operating conditions of the container terminal.

 


 

3.  Research Achievements

 Prof. Hong Bong Hee recently published paper on the Big Data field as follows: Clustering learning model of CCTV  image pattern for producing road hazard meteorological information”(FGCS, 2018), Pattern graph tracking-based stock price prediction using big data”(FGCS, 2018), Monte Carlo Simulation-based Traffic Speed Forecasting Using Historical Big Data(FGCS, 2016). The "Clustering learning model of CCTV image pattern" paper published in the FGCS was awarded the BEST HIGH QUALITY FORUM AWARD CERTIFICATE at the 3rd IoTBDS conference(2017). He also received the BEST PAPER AWARD from the 13th IEEE Embedded and Real-Time Computing Systems and Applications(2007). In 2011, he won the best academy award from the oldest and most prominent KIISE(Korean Institute of Information Scientists and Engineers) in the computer field in Korea. He had been an associate editor of the Journal of RF Technologies as international academic activities. He is now the vice chair of the steering committee of the DASFAA conference as an international conference activity. DASFAA is included in the list of excellent international conferences officially recognized by the Korean and Chinese governments as equivalent to the SCI Journal. The steering committee of IEEE BigComp includes him as a very important member. He was the chairman of KIISE, one of the largest and best computer society of Korea in 2017