• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.1
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• pp.57-66
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• 2001

This study used four theoretical models, such as two-point linear model, linear regression model, quadratic regression model and cubic regression model which are presented from The Ministry of Science and Technology, for extraction of urban surface temperature from Landsat TM band 6 image. Through correlation and regression analysis between result of four models and AWS(automatic weather station) observation data, this study could verify spatial distribution characteristic of urban surface temperature using GIS spatial analysis method. The result of analysis for surface temperature by landcover showed that the urban and the barren land belonged to the highest surface temperature class. And there was also -0.85 correlation in the result of correlation analysis between surface temperature and NDVI. In this result, the meteorological environmental characteristics wuld be regarded as one of the important factor in urban planning.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.6
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• pp.780-786
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• 2005

This study presents a non-video, non-invasive, automatic, on-site monitoring system the system employs ultrasonic transducers to detect behavior in sows before, during and after parturition. An ultrasonic transmitting/receiving (T/R) circuit of 40 kHz was mounted above a conventional parturition bed. The T/R units use ultrasonic time-of-flight (TOF) ranging technology to measure the height of the confined sows at eight predetermined locations. From this data, three momentary postures of the sow are determined, characterized as standing-posture (SP), lateral-lying-posture (LLP) and sitting posture (STP). By examining the frequencies of position switch Stand-Up-Sequence (SUS) between standing-posture (SP), lateral-lying-posture (LLP) and sitting-posture (STP) rate can be determined for the duration of the sow' confinement. Three experimental pureblooded Landrace sows undergoing normal gestation were monitored for the duration of confinement. In agreement with common observation, the sows exhibited increased restlessness as parturition approached. Analysis of the data collected in our study showed a distinct peak in Stand-Up-Sequence (SUS, i.e. the transition from lying laterally to standing up ) and sitting-posture (STP) rate approximately 12 h prior to parturition, the observed peak being 5 to 10 times higher than observed on any other measurement day. It is concluded that the presented methodology is a robust, low-cost, lowlabor method for the continuous remote monitoring of sows and similar large animals for parturition and other behavior. It is suggested that the system could be applied to automatic prediction of sow parturition, with automatic notification of remote management personnel so human attendance at birth could reduce rates of sow and piglet mortality. The results of this study provide a good basis for enhancing automation and reducing costs in large-scale sow husbandry and have applications in the testing of various large mammals for the effects of medications, diets, genetic modifications and environmental factors.

• The Journal of the Korea Contents Association
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• v.15 no.6
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• pp.54-61
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• 2015

The ATVM(Automatic Ticket Vending Machine) of Seoul Metropolitan is a Kiosk which is called Ticket Vending and Reload Device at the subway station. It is implemented for integrating transportation card system which is separated from a paper subway ticket and replacing ticket selling employees. However, since the automatic ticket vending machine was accepted in 2009, there has been confusion of purchasing a ticket. Therefore, it requires improvement of usability. This study, conducts a literature search. Also, the interface of ATVM is analyzed. Finally user observation proceeded at Sinnonhyeon Station of Seoul Metro line 9. The results show that selecting a destination and section fares is confusing process for user. Based on this survey the improvements of UI are proposed to expect advanced directions of the ATVM.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.8
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• pp.1080-1088
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• 2018

General methods of controlling a drone are divided into manual control and automatic control, which means a drone moves along the route. In case of manual control, a man should be able to figure out the location and status of a drone and have a controller to control it remotely. When people control a drone, they collect information about the location and position of a drone with the eyes and have its internal information such as the battery voltage and atmospheric pressure delivered through telemetry. They make a decision about the movement of a drone based on the gathered information and control it with a radio device. The automatic control method of a drone finding its route itself is not much different from manual control by man. The information about the position of a drone is collected with the gyro and accelerator sensor, and the internal information is delivered to the CPU digitally. The location information of a drone is collected with GPS, atmospheric pressure sensors, camera sensors, and ultrasound sensors. This paper presents an investigation into drone control by a remote computer. Instead of using the automatic control function of a drone, this approach involves a computer observing a drone, determining its movement based on the observation results, and controlling it with a radio device. The computer with a Depth camera collects information, makes a decision, and controls a drone in a similar way to human beings, which makes it applicable to various fields. Its usability is enhanced further since it can control common commercial drones instead of specially manufactured drones for swarm flight. It can also be used to prevent drones clashing each other, control access to a drone, and control drones with no permit.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.93-99
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• 2019

In this paper, we propose a smart meter that uses GRU model, which is one of artificial neural networks, for the efficient energy management. We collected power consumption data that train GRU model through the proposed smart meter. The implemented smart meter has automatic power measurement and real-time observation function and load control function through power consumption prediction. We determined a reference value to control the load by using Root Mean Squared Error (RMS), which is one of performance evaluation indexes, with 20% margin. We confirmed that the smart meter with automatic load control increases the efficiency of energy management.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1215-1223
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• 2020

Recently, the number of natural disasters caused by inclement weather conditions such as localized heavy rainfall, Typhoon, etc. is increasing in Korea, which requires relevant prevention and water management measures. Rain gauges installed on the ground have strengths in continuously·directly measures ground precipitation but cannot provide accurate information on spatial precipitation distribution in the areas without the rain gauges. The present research has designed and developed an electromagnetic-based multi-purpose precipitation gauge(EWRG, Electromagnetic Wave Rain Gauge) that can measure rainfall at the real time, by overcoming spatial representativeness. In this paper, we propose an FPGA-based signal processing design method for EWRG. The signal processing of the EWRG was largely designed by calculating the ADC and DDC of the LFM waveform, pulse compression, correlation coefficient and estimating the precipitation parameter. In this study, the LFM waveform and pulse compressed signal were theoretically analyzed.

• Journal of Environmental Science International
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• v.19 no.8
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• pp.983-999
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• 2010

Wind power energy is one of the favorable and fast growing renewable energies. It is most important for exact analysis of wind to evaluate and forecast the wind power energy. The purpose of this study is to improve the performance of numerical atmospheric model by data assimilation over a complex coastal area. The benefit of the profiler is its high temporal resolution and dense observation data at the lower troposphere. Three wind profiler sites used in this study are inhomogeneously situated near south-western coastal area of Korean Peninsula. The method of the data assimilation for using the profiler to the model simulation is the three-dimensional variational data assimilation (3DVAR). The experiment of two cases, with/without assimilation, were conducted for how to effect on model results with wind profiler data. It was found that the assimilated case shows the more reasonable results than the other case compared with vertical observation and surface Automatic Weather Station(AWS) data. Although the effect of sonde data was better than profiler at a higher altitude, the profiler data improves the model performance at lower atmosphere. Comparison with the results of 4 June and 5 June suggests that the efficiency with hourly assimilated profiler data is strongly influenced by synoptic conditions. The reduction rate of Normalized Mean Error(NME), mean bias normalized by averaged wind speed of observation, on 4 June was 28% which was larger than 13% of 5 June. In order to examine the difference in wind power energy, the wind power density(WPD) was calculated and compared.

• Journal of Space Technology and Applications
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• v.4 no.2
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• pp.169-183
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• 2024

Korea Astronomy and Space Science Institute (KASI) developed the Geochang satellite laser ranging (SLR) system for the scientific research on the space geodesy as well as for the national space missions including precise orbit determination and space surveillance. The operation system was developed based on the server-client communication structure, which controls the SLR subsystems, provides manual and automatic observation modes based on the observation algorithm, generates the range data between satellites and SLR stations, and carry out the post-processing to remove noises. In this study, we analyzed the requirements of operation system, and presented the development environments, the software structure and the observation algorithm, for the server-client communications. We also obtained laser ranging data for the ground target and the space geodetic satellite, and then analyzed the ranging precision between the Geochang SLR station and the International Laser Ranging Service (ILRS) network stations, in order to verify the operation system.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.208-220
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• 2016

Automatic Mountain Meteorology Observation System (AMOS) is an important ingredient for several climatological and forest disaster prediction studies. In this study, we select the optimal sites for AMOS in the mountain areas of Honam and Jeju in order to prevent forest disasters such as forest fires and landslides. So, this study used spatial dataset such as national forest map, forest roads, hiking trails and 30m DEM(Digital Elevation Model) as well as forest risk map(forest fire and landslide), national AWS information to extract optimal site selection of AMOS. Technical methods for optimal site selection of the AMOS was the firstly used multifractal model, IDW interpolation, spatial redundancy for 2.5km AWS buffering analysis, and 200m buffering analysis by using ArcGIS. Secondly, optimal sites selected by spatial analysis were estimated site accessibility, observatory environment of solar power and wireless communication through field survey. The threshold score for the final selection of the sites have to be higher than 70 points in the field assessment. In the result, a total of 159 polygons in national forest map were extracted by the spatial analysis and a total of 64 secondary candidate sites were selected for the ridge and the top of the area using Google Earth. Finally, a total of 26 optimal sites were selected by quantitative assessment based on field survey. Our selection criteria will serve for the establishment of the AMOS network for the best observations of weather conditions in the national forests. The effective observation network may enhance the mountain weather observations, which leads to accurate prediction of forest disasters.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.436-445
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• 2023

Methane (CH₄) emissions from rice paddies are mainly observed using the closed chamber method or the eddy covariance method. In this study, a new observation technique combining a portable gas analyzer (Model LI-7810, LI-COR, Inc., USA) and an automatic opening/closing chamber (Model Smart Chamber, LI-COR, Inc., USA) was introduced based on the strengths and weaknesses of the existing measurement methods. A cylindrical collar was manufactured according to the maximum growth height of rice and used as an auxiliary measurement tool. All types of measured data can be monitored in real time, and CH₄ flux is also calculated simultaneously during the measurement. After the measurement is completed, all the related data can be checked using the software called 'SoilFluxPro'. The biggest advantage of the new observation technique is that time-series changes in greenhouse gas concentrations can be immediately confirmed in the field. It can also be applied to small areas with various treatment conditions, and it is simpler to use and requires less effort for installation and maintenance than the eddy covariance system. However, there are also disadvantages in that the observation system is still expensive, requires specialized knowledge to operate, and requires a lot of manpower to install multiple collars in various observation areas and travel around them to take measurements. It is expected that the new observation technique can make a significant contribution to understanding the CH₄ emission pathways from rice paddies and quantifying the emissions from those pathways.