Soon Woo Lee

Performance Evaluation of Mobile Agents for Knowledge-Based Web Information Services

Knowledge-based Web information system should be considered for performance with different types of mobile agents serviced by different mobile communication operators. The ubiquitous Web information server accessed by a user-group with various mobile agents should be a unified center for unified-and-ubiquitous (U2) knowledge-based Web information services. We studied the performance of Web information access, i.e. the registration and retrieval of information/knowledge, with mobile agents for U2knowledge-based Web information services. We show the empirical results based on the implementation and experience got both in Korea and in Japan.

Design of Analog Front End for Power-Line Communication of Korean Standard

In this paper, we present the design of the analog front end (AFE) module for power-line communication (PLC) which complies with the Korean industrial standard (KS) specifications. We measured the electromagnetic emission of the implemented AFE and verified that the measurement satisfies the regulation for PLC.

NLOS mitigation for low-cost IR-UWB RTLS

This paper proposes a method for mitigation of non-line-of-sight (NLOS) situations in a real time location system (RTLS) using an impulse radio ultra wide band (IR-UWB). Based on our experiment, we found that there is a slight chance to meet the line-of-sight (LOS) at all the readers of RTLS in a realistic scenario. In the NLOS environment, there are two problems of packet-miss error and multi-path error as well. To compensate for the packet-miss error, this paper presents a new algorithm (PPTi), which uses previous time information before the time difference of arrival (TDOA) positioning technique calculates the coordinate of the target. We also employed the Kalman Filter (KF) to mitigate multi-path error. Our proposed algorithm provides a 5.9% increased positioning success rate and a 25.6% decreased root mean square error (RMSE) in an NLOS environment.

Smart air condition load forecasting based on thermal dynamic model and finite memory estimation for peak-energy distribution

In this paper, we propose a new load forecasting method for smart air conditioning (A/C) based on the modified thermodynamics of indoor temperature and the unbiased finite memory estimator (UFME). Based on modified first-order thermodynamics, the dynamic behavior of indoor temperature can be described by the time-domain state-space model, and an accurate estimate of indoor temperature can be achieved by the proposed UFME. In addition, a reliable A/C load forecast can be obtained using the proposed method. Our study involves the experimental validation of the proposed A/C load forecasting method and communication construction between DR server and HEMS in a test bed. Through experimental data sets, the effectiveness of the proposed estimation method is validated.