• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1473-1483
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• 2014

A public restroom is different from a household toilet in terms of location and a large number of sharing users. In addition, public restroom is usually messy and filthy. Recently, public toilet tends to be clearly managed than before, but it still has hygienic and clear problems. In this paper, we propose a machine-to-machine (M2M)-based public restroom management system to solve these problems, in which the system with a wireless communication device sends the status information of the toilet, such as blockage or trouble detected by a sensor, to the manager of the restroom at a remote location. In particular, we have developed a prototype management system for public restroom taking into account several system requirements, and verified the basic operations and performance of the management system. With the application of the system to public facilities, it will furnish users with more pleasant environments by restroom administrators who can respond effectively to the troubled toilet.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.449-451
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• 2007

In the commercially managed timber lands, the information such as height, age, stand density, canopy closure and leaf area index need to be collected periodically. Stand volume is the most fundamental information in the valuation of timber, however, stand age information is the primary element of forest inventory and these two are highly correlated. Conventional method of collecting stand age information by field surveys such as ring count method is accurate; however, it is expensive, labor-intensive and time consuming. In the present study it was aimed to collect stand age information using modem techniques in a commercially managed timberland situated in Tennessee, USA. The Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM+) of three different periods, Shuttle Radar Topography Mission (SRTM), National elevation dataset (NED) and field inventory data were used. Normalized difference vegetation index (NDVI) and Tasselled Cap (TC) transformation techniques were applied on the TM and ETM+ data. The regression analysis was carried out to identify the correlation between stand age and NDVI, TC. In the present study about 2,469 datasets were analyzed. The $R^{2}$ value for stand age estimation was 0.713. The NDVI, TC2 and TC3 were found to produce accurate timber age information.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1629-1634
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• 2020

It is essential to convert the Digital Number (DN) measured from Earth observing satellites into the physical parameter of radiance when deriving the geophysical parameter such as surface temperature in the satellite data processing. The purpose of this study is to update the DN·Radiance equation established from lab measurements, using the KOMPSAT-3A mid-wave infrared data and the MODTRAN radiative transfer model. Results of this study show that the improved DN·Radiance equation allows us to produce the realistic values of radiance. We expect in the forthcoming study that the radiances calculated as such should be more quantitatively validated with the use of relevant in-situ measurements and a radiative transfer model.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.747-761
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• 2021

With the increasing application of UAVs in intelligent transportation systems, vehicle detection for aerial images has become an essential engineering technology and has academic research significance. In this paper, a vehicle detection method for aerial images based on the YOLOv4 deep learning algorithm is presented. At present, the most known datasets are VOC (The PASCAL Visual Object Classes Challenge), ImageNet, and COCO (Microsoft Common Objects in Context), which comply with the vehicle detection from UAV. An integrated dataset not only reflects its quantity and photo quality but also its diversity which affects the detection accuracy. The method integrates three public aerial image datasets VAID, UAVD, DOTA suitable for YOLOv4. The training model presents good test results especially for small objects, rotating objects, as well as compact and dense objects, and meets the real-time detection requirements. For future work, we will integrate one more aerial image dataset acquired by our lab to increase the number and diversity of training samples, at the same time, while meeting the real-time requirements.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.1-9
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• 2012

The diurnal variation in pollen vertical distributions in the atmosphere was observed by a surface-based lidar remote sensing technique. Aerosol extinction coefficient and depolarization ratio at 532 nm were obtained from lidar measurements in spring ($4^{th}$ May - $2^{nd}$ June) 2009 at Gwangju Institute of Science & Technology (GIST) located in Gwangju, Korea ($35.15^{\circ}E$, $126.53^{\circ}N$). Unusual variations of depolarization ratio were observed for six days from $4^{th}$ to $9^{th}$ May. Depolarization ratios varied from 0.08 to 0.14 were detected at the low altitude in the morning. The altitude with those high depolarization ratios was increased up to 1.5 - 2.0 km at the time interval between 12:00 and 14:00 LT and then decreased. The temporal variations in high values of depolarization ratios from lidar measurements show good agreement in patterns with the sampled pollen concentrations measured using the Burkard trap sampler. This study demonstrates that the pollen distribution data obtained by lidar measurements can be a useful tool for investigating spatial and temporal characteristic of pollen particles.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.200-202
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• 2018

Emergency care provides primary care and stability for the patient in the early stages. It saves a patient's life and minimizes the risk until that treated in a hospital. In the recent years, An attempts have been made to convergence medical technology and IT technology to overcome the limitations of temporal, spatial, and medical technology applications. In this study, we established an environment for emergency information services. The developed smart application for emergency rescue activities support can easily identify emergency situation and First Aid. Then, it can be transmitted to a remote medical guidance doctor so that emergency treatment and hospital response can be performed quickly.

• Proceedings of the KSRS Conference
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• v.1
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• pp.232-235
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• 2006

Using 30 days of hourly visible channel data and DIScrete Ordinate Radiative Transfer (DISORT) model (6S), Aerosol optical depth (AOD) at $0.55{\mu}m$ was retrieved over the East Asia. In contrast with the AOD retrieval using low-earth-orbit satellites such as MODIS (Moderate-Res olution Spectroradiometer) or MISR (Multiangle Imaging SpectroRadiometer), this algorithm with geostationary satellite can improve the monitoring of AOD without the limitation of temporal resolution. Due to the limited number of channels in the conventional meteorological imager onboard the geostationary satellite, an AOD retrieval algorithm utilizing a single visible channel has been introduced. This single channel algorithm has larger retrieval error of AOD than other multiple-channel algorithm due to errors in surface reflectance and atmospheric property. In this study, the effects of manifold atmospheric and surface properties on the retrieval of AOD from the geostationary satellite, are investigated and compared with the AODs from AERONET and MODIS. To improve the accuracy of retrieved AOD, efforts were put together to minimize uncertainties through extensive sensitivity tests. This algorithm can be utilized to retrieve aerosol information from previous geostationary satellite for long-term climate studies.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.300-306
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• 2000

This paper introduces a new concept of automation for bio-production with tele-operative system. The proposed system showed practical and feasible way of automation for the volatile bio-production process. Based on the proposition, recognition of the job environment with object identification was performed using computer vision system. A man-machine interactive hybrid decision-making, which utilized a concept of tele-operation was proposed to overcome limitations of the capability of computer in image processing and feature extraction from the complex environment image. Identifying watermelons from the outdoor scene of the cultivation field was selected to realize the proposed concept. Identifying watermelon from the camera image of the outdoor cultivation field is very difficult because of the ambiguity among stems, leaves, shades, and especially fruits covered partly by leaves or stems. The analog signal of the outdoor image was captured and transmitted wireless to the host computer by R.F module. The localized window was formed from the outdoor image by pointing to the touch screen. And then a sequence of algorithms to identify the location and size of the watermelon was performed with the local window image. The effect of the light reflectance of fruits, stems, ground, and leaves were also investigated.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.594-597
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• 2007

We present in this paper a novel mid and long term power load prediction method using temporal pattern mining from AMR (Automatic Meter Reading) data. Since the power load patterns have time-varying characteristic and very different patterns according to the hour, time, day and week and so on, it gives rise to the uninformative results if only traditional data mining is used. Also, research on data mining for analyzing electric load patterns focused on cluster analysis and classification methods. However despite the usefulness of rules that include temporal dimension and the fact that the AMR data has temporal attribute, the above methods were limited in static pattern extraction and did not consider temporal attributes. Therefore, we propose a new classification method for predicting power load patterns. The main tasks include clustering method and temporal classification method. Cluster analysis is used to create load pattern classes and the representative load profiles for each class. Next, the classification method uses representative load profiles to build a classifier able to assign different load patterns to the existing classes. The proposed classification method is the Calendar-based temporal mining and it discovers electric load patterns in multiple time granularities. Lastly, we show that the proposed method used AMR data and discovered more interest patterns.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.238-240
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• 2017

In the recent years, An attempts have been made to convergence medical technology and IT technology to overcome the limitations of temporal, spatial, and medical technology applications. In this study, we developed an application s/w to support emergency services for emergency medical services. The developed smart application for emergency rescue activities support can easily identify emergency situation and emergency diary. Then, it can be transmitted to a remote medical guidance doctor so that emergency treatment and hospital response can be performed quickly.