• Proceedings of the KIEE Conference
• /
• 1998.11b
• /
• pp.663-665
• /
• 1998

The purpose of this paper is development of portable cardiovascular signal processing device. Beat-to-beat fluctuation in heart rate, respiration, and blood pressure have been known to be meditated by autonomic nervous system activities convergent on various effector organs. This system consists of data acquisition module, main data processing module and graphic LCD module. The data acquisition module is developed for data aquisition, data multiplexing and interfacing with main data processing system. And, main data processing module is developed for data storing, data processing and interfacing with graphic LCD module. The main processing system is based on 32-bit microprocessor.

• Proceedings of the KIPE Conference
• /
• 2005.07a
• /
• pp.624-627
• /
• 2005

This paper presents a new data classification method using the Robbins Monro stochastic approximation algorithm k-nearest neighbor and distribution analysis. To cluster the data set, we decide the centroid of the test data set using k-nearest neighbor algorithm and the local area of data set. To decide each class of the data, the Robbins Monro stochastic approximation algorithm is applied to the decided local area of the data set. To evaluate the performance, the proposed classification method is compared to the conventional fuzzy c-mean method and k-nn algorithm. The simulation results show that the proposed method is more accurate than fuzzy c-mean method, k-nn algorithm and discriminant analysis algorithm.

• Journal of the Korean Solar Energy Society
• /
• v.38 no.4
• /
• pp.11-31
• /
• 2018

Nowadays, domestic photovoltaic system market has been expanded and the governmental dissemination policy has been continued. There is only PV system output performance analysis which is called Performance Ratio(PR) analysis. However, there exists many parameters that can affect PV system output. This papers shows the PV system energy performance analysis using meteorological monitoring data. The meteorological monitoring system was installed in the H university and we analyzed the PV system which installed in the H university. We also investigated other three PV systems which located less than 3 kilometers from H university. We evaluated total 4 PV systems through the field survey data, design drawing data and power generation data. Finally, we compared the actual measuring data with the simulation data using PVSYST software.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.05a
• /
• pp.69-71
• /
• 2020

Principal Component Analysis (PCA) is an effective data analysis technique which is commonly used for fault detection on collected data of Wireless Sensor Networks (WSN), However, applying PCA on the whole data make the detection performance low. In this paper, we propose Joint PCA and Adaptive Threshold for Fault Detection (JPATAD). Experimental results on a real dataset show a remarkably higher performance of JPATAD comparing to conventional PCA model in detection of noise which is a popular fault in collected data of sensors.

• Journal of Computing Science and Engineering
• /
• v.3 no.4
• /
• pp.195-215
• /
• 2009

Worst-case execution time (WCET) analysis is critical for hard real-time systems to ensure that different tasks can meet their respective deadlines. While significant progress has been made for WCET analysis of instruction caches, the data cache timing analysis, especially for set-associative data caches, is rather limited. This paper proposes an approach to safely and tightly bounding data cache performance by computing the worst-case stack distance of data cache accesses. Our approach can not only be applied to direct-mapped caches, but also be used for set-associative or even fully-associative caches without increasing the complexity of analysis. Moreover, the proposed approach can statically categorize worst-case data cache misses into cold, conflict, and capacity misses, which can provide useful insights for designers to enhance the worst-case data cache performance. Our evaluation shows that the proposed data cache timing analysis technique can safely and accurately estimate the worst-case data cache performance, and the overestimation as compared to the observed worst-case data cache misses is within 1% on average.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.21 no.9
• /
• pp.87-94
• /
• 2007

This paper presents new criteria for DGA(Dissolved Gases Analysis) using CDF(Cumulative Distribution Function) obtained from the data from the diagnosis of transformers operated in KEPCO over a period of 16 years. Because of differences in operating environments, construction type, oil volume, and other factors, the interpretative criteria of DGA at KEPCO differs from other standards such as IEC-60599, or Rogers and Doernenburg. To suggest the most appropriate criteria, the DGA data from transformers under normal conditions as well as from developing fault transformers were collected. Using these data, this study suggests the limitative gas level of transformers under normal operating conditions and verifies the suitability of the criteria. Because the application of this new criterion to transformers at KEPCO increases the detectable ratio of incipient faults and reduces unnecessary follow-up sampling and analysis, the new criteria yields a more reliable prediction of transformer condition.

• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.4
• /
• pp.250-260
• /
• 2023

In this paper, we designed a IoT(Internet of Things) sensor block embedded lightweight house deck structures that can be implemented using Carbon Fiber Reinforced Polymer(CFRP). Deck-Sensor interconnection interface block via IoT connectivity Hub that can mount external environmental sensors such as fire sensors on the Deck body itself was also proposed. Additionally we described the configuration of devices for data acquisition and analysis based on IoT environmental detection sensors that can be commonly installed and used on these deck bodies. On the other hand, received sensing data based monitoring user interface(UI) also developed and used for sensing data analysis for remote monitoring center. Through the implementation of such IoT-based sensor data transmission and collection analysis devices and UI software, this paper confirmed the availability of CFRP based lightweight House deck structure and possibility of CFRP deck-based IoT sensor data networking and analysis functions.

• Proceedings of the KIEE Conference
• /
• 1999.07c
• /
• pp.1224-1226
• /
• 1999

When electrical engineers get started with the design of main electrical system of a complex petrochemical plant along with chemical and mechanical engineers, they are usually confronted with lack of power system data. This paper presents a procedure how to perform power system stability analysis for the purpose of design studies within the limited system data given and to verify the given data to get reliable convergence in dynamic simulation as well as to apply the stability analysis result on practical system design. The power system stability analysis on the Cadereyta petrochemical plant in Mexico is provided as a study case.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2192-2197
• /
• 2005

This paper describes how to diagnose SBR plant equipment using time-series data mining. It shows the equipment diagnostics based upon vibration signals that are acquired from each device for process control. Data transform techniques including two data preprocessing skills and data mining methods were employed in the data analysis. The proposed method is not only suitable for SBR equipment, but is also suitable for other industrial devices. The experimental results performed on a lab-scale SBR plant show a good equipment-management performance.

• Journal of Electrical Engineering and Technology
• /
• v.5 no.1
• /
• pp.16-20
• /
• 2010

Recently, the smart grid has become a hot issue and interest in related power sources have increased accordingly. The implementation of a smart grid can enable many generation resources to be linked to the power system, including small-scale reactors for the purpose of co-generation. Research on small-scale reactors is being carried out all over the world. Similarly, Korea is also conducting research on multi-purpose regional energy systems using nuclear energy. This paper proposes a real-time data acquisition and analysis system for small-scale reactors, and is known as the REX-10 (Regional Energy rX 10 MVA). This analysis requires real-time simulations for the power system since it needs data communication with a remote REX-10. A RTDS (Real Time Digital Simulator) has been used for the simulation, and a SCADA/HMI system interfaced with the RTDS is proposed for the purpose of monitoring and control of the regional energy system.