• The Transactions of the Korean Institute of Electrical Engineers P
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• v.61 no.1
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• pp.41-46
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• 2012

Electrolytic power capacitors have been widely used in power conversion system such as inverter or UPS because of characteristics of large capacitance, high-voltage and low-cost. The electrolytic capacitor, which is most of the time affected by the aging effect, plays a very important role for the power-electronics system quality and reliability. Therefore it is important to diagnosis monitoring the condition of an electrolytic capacitor in real-time to predict the failure. In this paper, the on-line remote diagnosis monitoring system for UPS DC link electrolytic capacitors using low-cost single-chip zigbee communication modules is developed. To estimate the health status of the capacitor, the equivalent series resistor(ESR) of the component has to be determined. The capacitor ESR is estimated by using RMS computation using BPF modeling of DC link ripple voltage/current. Zigbee-based hardware experimental results show that the proposed remote capacitor diagnosis monitoring system can be applied to UPS successfully.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1683-1691
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• 2013

Concrete surface grinding is frequently used for flatness of concrete surface, concrete pavement rehabilitation, and adhesiveness in pavement construction. The procedure is, however, labor intensive and has a hazardous work condition. Also, the productivity and the quality of concrete surface grinding highly depend on the skills of worker. Thus, the development of remote controlled concrete surface grinding equipment is necessary to prevent the environmental pollution and to protect the workers from hazardous work condition. However, it is difficult to evaluate the grinded surface objectively in a remote controlled system. Also, The machine vision system developed in this study takes the images of grinded surface with the network camera for image processing. Then, by representing the quality test results to the integrated program of the remote control station, the quality control system is constructed. The machine vision algorithm means the image processing algorithm of grinded concrete surface and this paper presents the objective quality control standard of grinded concrete surface through the application of the suggested algorithm.

• Korean Journal of Artificial Intelligence
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• v.6 no.1
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• pp.1-10
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• 2018

Compressed Air is an important energy source used in most factories nowadays. The automation trend using air compressor has been gradually increasing with the interest of the 4th industry in recent years. With the air compressor system, it is possible to construct the device at low cost and easily achieve automation and energy saving. In addition, With trend of FA, miniaturation and light weight manufacturing trend expand their use in the electronics, medical, and food sectors. Research method is to design the technology for the remote control of the following information as USN base. Development of flexible sensing module from real time observation module for fusion of IT technology in compressed air systems, design and manufacture of flexible sensing module, and realiability assessment. Design of real-time integrated management system for observation data of compressed air system - Ability to process observation data measured in real time into pre-processing and analysis data. This study expects unconventionally decreasing effect of energy cost that takes up 60~70% of air compressor layout and operation and maintenance management cost through USN(Ubiquitous Sensor Network) technology by using optimum operational condition from real time observation module. In addition, by preventing maintenance cost from malfunction of air compressor beforehand, maintenance cost is anticipated to cut back.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.332-336
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• 1997

To order to remain competitive, a manufacturing company need to maintain the optimal condition of its manufacturing system. Machine tools as an important element of a manufacturing system comprises complex mechanical as well as electronic components. So, diagnosing the troubles of machine tools is tricky process which requires a lot of experience and knowledge. Since providing machine tool users with necessary serices at the right time is very difficult,a remote diagnosis system is to be regarded as a good alternative, with which users can diagnose and fix the machine troubles. This paper presents a method to implement a remote machine tool diagnosis system using the world wide web technology and backward reasoning expert system.

• Proceedings of the KIEE Conference
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• 1998.07e
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• pp.1734-1736
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• 1998

On-line partial discharge monitoring system for generator stator insulation is developed. This system consists of remote and host units. The remote unit detects partial discharge signals from SSC(Stator Slot Coupler) installed between wedge and stator windings. The host unit monitors the condition of winding insulation. This system will be used as a module of a generator on-line monitoring system utilizing global network.

• Journal of IKEEE
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• v.24 no.1
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• pp.293-301
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• 2020

Consultation with the patient and doctor is very important in the examination. However, if the consultation cannot be done directly, such as corona virus, it is difficult for the doctor to determine the patient's condition more accurately. Recently, an image counseling system has been developed based on the Internet, but in the case of heart disease, remote medical counseling cannot be performed because it is not possible to stethoscope the heart sounds remotely. In order to solve this problem, it is necessary to develop an interactive mobile robot capable of remote medical consultation, and a doctor and a patient should be able to set a planting sound during consultation and transmit it in real time. In this paper, we developed a robot that can remotely control a medical counseling robot to move to a hospital room where patients are hospitalized, and to consult a patient in the room remotely from a doctor's office. A remote medical imaging stethoscope system for real-time heart sound transmission is presented. The proposed system is a kind of P2P communication that transmits video information, audio information, and control signal independently through webRTC platform, so that there is no data loss. Consults and sees doctors in real time and finds it more effective than traditional methods for patient security. The system implemented in this paper will be able to perform remote medical care in the place where the spread of diseases between humans like the recent corona 19 as well as the remote medical care of heart disease patients in the future.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.1-16
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• 2008

Steam and advection fogs are frequently observed in the Yellow Sea from March to July except for May. This study uses remote sensing (RS) data for the monitoring of sea fog. Meteorological data obtained from the Ieodo Ocean Research Station provided a valuable information for the occurrence of steam and advection fogs as a ground truth. The RS data used in this study were GOES-9, MTSAT-1R images and QuikSCAT wind data. A dual channel difference (DCD) approach using IR and shortwave IR channel of GOES-9 and MTSAT-1R satellites was applied to detect sea fog. The results showed that DCD, texture-related measurement and the weak wind condition are required to separate the sea fog from the low cloud. The QuikSCAT wind data was used to provide the wind speed criteria for a fog event. The laplacian computation was designed for a measurement of the homogeneity. A new combined method, which includes DCD, QuikSCAT wind speed and laplacian computation, was applied to the twelve cases with GOES-9 and MTSAT-1R. The threshold values for DCD, QuikSCAT wind speed and laplacian are -2.0 K, $8m\;s^{-1}$ and 0.1, respectively. The validation results showed that the new combined method slightly improves the detection of sea fog compared to DCD method: improvements of the new combined method are $5{\sim}6%$ increases in the Heidke skill score, 10% decreases in the probability of false detection, and $30{\sim}40%$ increases in the odd ratio.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1303-1322
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• 2020

Indonesia is more prone to natural disasters due to its geological condition under the three main plates, making Indonesia experience frequent seismic activity, causing earthquakes, volcanic eruption, and tsunami. Those disasters could lead to other disasters such as landslides, floods, land subsidence, and coastal inundation. Monitoring those disasters could be essential to predict and prevent damage to the environment. We reviewed the application of remote sensing and Geographic Information System (GIS) for detecting natural disasters in the case of Indonesia, based on 43 articles. The remote sensing and GIS method will be focused on InSAR techniques, image classification, and susceptibility mapping. InSAR method has been used to monitor natural disasters affecting the deformation of the earth's surface in Indonesia, such as earthquakes, volcanic activity, and land subsidence. Monitoring landslides in Indonesia using InSAR techniques has not been found in many studies; hence it is crucial to monitor the unstable slope that leads to a landslide. Image classification techniques have been used to monitor pre-and post-natural disasters in Indonesia, such as earthquakes, tsunami, forest fires, and volcano eruptions. It has a lack of studies about the classification of flood damage in Indonesia. However, flood mapping was found in susceptibility maps, as many studies about the landslide susceptibility map in Indonesia have been conducted. However, a land subsidence susceptibility map was the one subject to be studied more to decrease land subsidence damage, considering many reported cases found about land subsidence frequently occur in several cities in Indonesia.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.347-349
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• 2009

Air quality of indoor space environment is affected by various pollutants like as particles and chemical stuffs. The indoor air pollution affects directly the human respiration organs to cause consequently unpleasant mental status. The $CO_2$ concentration level is one of the harmful components of air pollutants. Major factor to increase the $CO_2$ concentration level is the people's breath amount in indoor. The car exhaust gas diffused from the around road also has strong affect on $CO_2$ concentration. There are some other reasons to affect the $CO_2$ concentration change, such as, real-time change of the population movement, closeness to the indoor air flow inlet window and changes in road car traffic amount. A remote monitoring system to measure environmental indoor air pollution concerning on the $CO_2$ concentration was studied and installed realized set-up model. Zigbee network configuration was applied for this system and the $CO_2$ concentration data were collected through USN network. A software program was developed to assure systematic analysis and to display real-time data on web pages. For the experimental test various condition was set up, like as, window opening, stopping air condition operation and adjusting fan heater work, etc. The analysis result showed the relation of various environmental conditions to $CO_2$ concentration changes. The causes to increase $CO_2$ concentration were experimentally defined as windows closing, the stopping air condition system, fan heater operation. To keep the $CO_2$ concentration under the legally required ppm level in public access indoor space, the developed remote measurement system will be usefully applied.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.621-629
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• 2013

Desertification monitoring as a main portion for understand desertification, have been conducted by many scientists. However, the stage of research remains still in the level of comparison of the past and current situation. In other words, monitoring need to focus on finding methods of how to take precautions against desertification. In this study, Vegetation Temperature Condition Index (VTCI), derived from Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST), was utilized to observe the distribution change of vegetation. The index can be used to monitor drought occurrences at a regional level for a special period of a year, and it can also be used to study the spatial distribution of drought within the region. Techniques of remote sensing and Geographic Information System (GIS) were combined to detect the distribution change of vegetation with VTCI. As a result, assuming that the moisture condition is the only main factor that affects desertification, we found that the distribution of vegetation in Bulgan, Mongolia could be predicted in a certain degree, using VTCI. Although desertification is a complicated process and many factors could affect the result. This study is helpful to provide a strategic guidance for combating desertification and allocating the use of the labor force.