• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.3
• /
• pp.376-382
• /
• 2014

E-Actuator is an essential part of an eVGT, it receives the command from the main ECU and controls the vane. An e-Actuator failure can cause an abrupt change in engine output and it may induce an accident. Therefore, it is required to detect anomalies in the e-Actuator in real time to prevent accidents. In this paper, an e-Actuator fault detection method using on-line parameter identification is proposed. To implement on-line fault detection algorithm, many constraints are considered. The test input and sampling rate are selected considering the constraints. And new recursive system identification algorithm is proposed which reduces the memory and MCU power dramatically. The relationship between the identified parameters and real elements such as gears, spring and motor are derived. The fault detection method using the relationship is proposed. The experiments with the real broken gears show the effectiveness of the proposed algorithm. It is expected that the real time fault detection is possible and it can improve the safety of eVGT system.

• The Journal of Industrial Distribution & Business
• /
• v.9 no.5
• /
• pp.25-35
• /
• 2018

Purpose - The purpose of this paper is to partition a last-mile delivery network into zones and to determine locations of last mile delivery centers (LMDCs) in Bangkok, Thailand. Research design, data, and methodology - As online shopping has become popular, parcel companies need to improve their delivery services as fast as possible. A network partition has been applied to evaluate suitable service areas by using METIS algorithm to solve this scenario and a facility location problem is used to address LMDC in a partitioned area. Research design, data, and methodology - Clustering and mixed integer programming algorithms are applied to partition the network and to locate facilities in the network. Results - Network partition improves last mile delivery service. METIS algorithm divided the area into 25 partitions by minimizing the inter-network links. To serve short-haul deliveries, this paper located 96 LMDCs in compact partitioning to satisfy customer demands. Conclusions -The computational results from the case study showed that the proposed two-phase algorithm with network partitioning and facility location can efficiently design a last-mile delivery network. It improves parcel delivery services when sending parcels to customers and reduces the overall delivery time. It is expected that the proposed two-phase approach can help parcel delivery companies minimize investment while providing faster delivery services.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.7
• /
• pp.3057-3075
• /
• 2020

End-to-end network delay plays an vital role in distributed services. This delay is used to measure QoS (Quality-of-Service). It would be beneficial to know all node-pair delay information, but unfortunately it is not feasible in practice because the use of active probing will cause a quadratic growth in overhead. Alternatively, using the measured network delay to estimate the unknown network delay is an economical method. In this paper, we adopt the state-of-the-art matrix completion technology to better estimate the network delay from limited measurements. Although the number of measurements required for an exact matrix completion is theoretically bounded, it is practically less helpful. Therefore, we propose an online adaptive sampling algorithm to measure network delay in which statistical leverage scores are used to select potential matrix elements. The basic principle behind is to sample the elements with larger leverage scores to keep the traits of important rows or columns in the matrix. The amount of samples is adaptively decided by a proposed stopping condition. Simulation results based on real delay matrix show that compared with the traditional sampling algorithm, our proposed sampling algorithm can provide better performance (smaller estimation error and less convergence pressure) at a lower cost (fewer samples and shorter processing time).

• Journal of Information Processing Systems
• /
• v.13 no.4
• /
• pp.987-999
• /
• 2017

Extraction of influential people from their respective domains has attained the attention of scholastic community during current epoch. This study introduces an innovative interaction strength metric for retrieval of the most influential users in the online social network. The interactive strength is measured by three factors, namely re-tweet strength, commencing intensity and mentioning density. In this article, we design a novel algorithm called IPRank that considers the communications from perspectives of followers and followees in order to mine and rank the most influential people based on proposed interaction strength metric. We conducted extensive experiments to evaluate the strength and rank of each user in the micro-blog network. The comparative analysis validates that IPRank discovered high ranked people in terms of interaction strength. While the prior algorithm placed some low influenced people at high rank. The proposed model uncovers influential people due to inclusion of a novel interaction strength metric that improves results significantly in contrast with prior algorithm.

• Smart Structures and Systems
• /
• v.33 no.3
• /
• pp.227-241
• /
• 2024

Safety and structural integrity of civil structures, like bridges and buildings, can be substantially enhanced by employing appropriate structural health monitoring (SHM) techniques for timely diagnosis of incipient damages. The information gathered from health monitoring of important infrastructure helps in making informed decisions on their maintenance. This ensures smooth, uninterrupted operation of the civil infrastructure and also cuts down the overall maintenance cost. With an early warning system, SHM can protect human life during major structural failures. A real-time online damage localization technique is proposed using only the vibration measurements in this paper. The concept of the 'Degree of Scatter' (DoS) of the vibration measurements is used to generate a spatial profile, and fractal dimension theory is used for damage detection and localization in the proposed two-phase algorithm. Further, it ensures robustness against environmental and operational variability (EoV). The proposed method works only with output-only responses and does not require correlated finite element models. Investigations are carried out to test the presented algorithm, using the synthetic data generated from a simply supported beam, a 25-storey shear building model, and also experimental data obtained from the lab-level experiments on a steel I-beam and a ten-storey framed structure. The investigations suggest that the proposed damage localization algorithm is capable of isolating the influence of the confounding factors associated with EoV while detecting and localizing damage even with noisy measurements.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.450-452
• /
• 2021

Recently, as interest in programming and artificial intelligence has increased, software education has been compulsory from elementary school. In order to achieve this goal of programming education, it is necessary to basically establish a lab environment suitable for students and teachers. However, there is a problem with performance problems caused by old computers in the lab environment of the school, and there is a problem that students must purchase and use the existing online platform while implementing an algorithm contest program in which students access and evaluate their problem-solving ability at the same time. Therefore, in this paper, to solve this problem, we propose a web-based online practice environment and algorithm contest scoring system using React and Spring boot. Through this, it is believed that even in a computer with low specifications, programming can be studied using only a web browser.

• Smart Structures and Systems
• /
• v.32 no.2
• /
• pp.101-109
• /
• 2023

In order to improve the measurement accuracy of the 6-dimensional accelerometer, the cross coupling compensation method of the accelerometer needs to be studied. In this paper, the non-linear error caused by cross coupling of piezoelectric six-dimensional accelerometer is compensated online. The cross coupling filter is obtained by analyzing the cross coupling principle of a piezoelectric six-dimensional accelerometer. Linear and non-linear fitting methods are designed. A two-level calibration hybrid compensation algorithm is proposed. An experimental prototype of a piezoelectric six-dimensional accelerometer is fabricated. Calibration and test experiments of accelerometer were carried out. The measured results show that the average non-linearity of the proposed algorithm is 2.2628% lower than that of the least square method, the solution time is 0.019382 seconds, and the proposed algorithm can realize the real-time measurement in six dimensions while improving the measurement accuracy. The proposed algorithm combines real-time and high precision. The research results provide theoretical and technical support for the calibration method and online compensation technology of the 6-dimensional accelerometer.

• The Journal of the Korea Contents Association
• /
• v.7 no.1
• /
• pp.32-39
• /
• 2007

An important application domain for online services is an interactive, multi-player game. In recent, many increase of users that use on-line services through networks have caused a heavy load to the server. In this paper, we propose a MMORPG(Massively Multi-player Online Role Playing Game) distributed game server using flayer-Cell. Our method provides efficient solution of a MMORPG distributed game server for large numbers of users. It is shown through the experiments that our method outperforms existing methods in terms of memory utilization rate and processing speed.

• Journal of Computing Science and Engineering
• /
• v.5 no.4
• /
• pp.346-353
• /
• 2011

With the advent of ubiquitous computing, a massive amount of trajectory data has been published and shared in many websites. This type of computing also provides motivation for online mining of trajectory data, to fit user-specific preferences or context (e.g., time of the day). While many trajectory clustering algorithms have been proposed, they have typically focused on offline mining and do not consider the restrictions of the underlying road network and selection conditions representing user contexts. In clear contrast, we study an efficient clustering algorithm for Boolean + Clustering queries using a pre-materialized and summarized data structure. Our experimental results demonstrate the efficiency and effectiveness of our proposed method using real-life trajectory data.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.4
• /
• pp.286-295
• /
• 2007

This paper presents an intelligent PID control for stochastic systems with nonstationary nature. We optimally determine parameters of a PID controller through learning algorithm and propose an online PID control to compensate system errors possibly occurred in realtime implementations. A dynamic Bayesian network (DBN) model for system errors is additionally explored for making decision about whether an online control is carried out or not in practice. We apply our control approach to traffic control of Transmission Control Protocol (TCP) networks and demonstrate its superior performance comparing to a fixed PID from computer simulations.