• 한국작물학회:학술대회논문집
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• 한국작물학회 2017년도 9th Asian Crop Science Association conference
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• pp.352-352
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• 2017

Recently, the South Korean government encourages the cultivation of upland crops in the paddy field to maintain an adequate level of rice production and then to balance the demand and supply of rice. This is mainly because the rice consumption per capita per year has continued to decline from 135 kg in 1979 to 61.9 kg in 2016, although the rice production was relatively stable. As a result, the rice overproduction became a big social problem. As a part of that, various upland crops such as soybean, maize, minor cereals and forage crops are planted in the paddy field 10 years ago. The cultivation of these crops may settle the problem of short supply and mass import of the crops to some extent. However, a systematic remote observation of upland crops in the paddy field is very scarce. This study investigated the cultivation status of upland crops and any changes of crop harvesting in the paddy field by using an unmanned aerial vehicle (UAV). Also, we analyzed the kind of upland crops and cultivation area in the paddy field by utilizing time series observation images. A fixed wing UAV is used for the investigation. This is because it is easy to use the flight operation and to control flight management software, and it can automatically cope with various emergency states such as a strong wind and battery discharge. The material of UAV is expanded polypropylene, which has an advantage of less equipment damage and risk during takeoff and landing. We acquired observed images in Buljeong-myeon, Goesan-gun, Chungcheongbuk-do, South Korea by using fixed wing UAV in 2015 and 2016. The total investigated area reaches 6,045 ha, and among them the agricultural area was 1,377 ha. For the next step, we created an orthoimage from all images taken using Pix 4D mapper program. According to the results of image analyses in 2015, the paddy field covered total 577 ha (75.9%) with crop plant. The cultivation area of beans, ginseng, maize, tobacco and peach was 256 ha (36.6%), 63 ha (9.2%), 37 ha (5.4%), 31 ha (4.5%) and 27 ha (3.8), respectively. And in 2016, the total covered area was 586 ha (77.1%), and it was comprised of 253 ha (35.5%), 88 ha (12.3%), 29 ha (4.1%), 22 ha (3.1%) and 32 ha (4.5%) in the same order. In this study, we focused on identifying the paddy field which was converted to the cultivation of upland crops by using UAV. And, it has been indicated that the cultivation area of rice decreased from 141 ha in 2015 to 127 ha in 2016, although that of ginseng increased by 25 ha. As a result, it is expected that a lot of paddy field could be replaced by high-income crops such as ginseng and fruit tree (peach) instead of relative low-income rice. More specific and widespread research on the remote sensing in the paddy field needs to be done.

• 대한원격탐사학회지
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• 제28권6호
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• pp.653-660
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• 2012

This study classified paddy fields according to rice varieties and monitored temporal changes in rice growth using SAR backscatter coefficients (${\sigma}^{\circ}$). A growing period time-series of backscatter coefficients was set up for nine fine-beam mode RADARSAT-1 SAR images from April to October 2005. The images were compared with field-measured rice growth parameters such as leaf area index (LAI), plant height, fresh and dry biomass, and water content in grain and plants for 45 parcels in Dangjin-gun, Chungnam Province, South Korea. The average backscatter coefficients for early-maturing rice varieties (13 parcels) ranged from -18.17 dB to -6.06 dB and were lower than those for medium-late maturing rice varieties during most of the growing season. Both crops showed the highest backscatter coefficient values at the heading stage (late July) for early-maturing rice, and the difference was greatest before harvest for early-maturing rice. The temporal difference in backscatter coefficients between rice varieties may play a key role in identifying early-maturing rice fields. On the other hand, comparisons with field-measured parameters of rice growth showed that backscatter coefficients decreased or remained on a plateau after the heading stage, even though the growth of the rice canopy had advanced.

• Journal of Biosystems Engineering
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• 제41권2호
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• pp.138-144
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• 2016

Purpose: Phosphorus is an essential element for water quality control. Excessive amounts of phosphorus causes algal bloom in water, which leads to eutrophication and a decline in water quality. It is necessary to maintain the optimum amount of phosphorus present. During the last decades, various studies have been conducted to determine phosphorus content in water. In this study, we present a comprehensive overview of colorimetric, electrochemical, fluorescence, microfluidic, and remote sensing technologies for the measurement of phosphorus in water, along with their working principles and limitations. Results: The colorimetric techniques determine the concentration of phosphorus through the use of color-generating reagents. This is specific to a single chemical species and inexpensive to use. The electrochemical techniques operate by using a reaction of the analyte of interest to generate an electrical signal that is proportional to the sample analyte concentration. They show a good linear output, good repeatability, and a high detection capacity. The fluorescence technique is a kind of spectroscopic analysis method. The particles in the sample are excited by irradiation at a specific wavelength, emitting radiation of a different wavelength. It is possible to use this for quantitative and qualitative analysis of the target analyte. The microfluidic techniques incorporate several features to control chemical reactions in a micro device of low sample volume and reagent consumption. They are cheap and rapid methods for the detection of phosphorus in water. The remote sensing technique analyzes the sample for the target analyte using an optical technique, but without direct contact. It can cover a wider area than the other techniques mentioned in this review. Conclusion: It is concluded that the sensing technologies reviewed in this study are promising for rapid detection of phosphorus in water. The measurement range and sensitivity of the sensors have been greatly improved recently.

• 대한간호학회지
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• 제16권2호
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• pp.44-52
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• 1986

Maternal and child health(MCH) status is considered as an important indicator of the level of health and civilization of a community and a country. MCH services for the rural population in the remote ar deserves priority by the government, since more than half(52.9%) of the delivery was occured at home and almost half (45.5%) of the delivery was assited by family members or neighbors. The purpose of the study was to analyse the health fare behavior related to pregnancy and delivery, which can be contributed maternal health care policy mating for the rural people. Specifically, it was intended to analyze the variables which affect the health care behavior in selecting birth places and birth attendants. This study utilized the data which had been already collected for an experimental study on primary health program model in Korean rural communities, funded by the USAID. 184 sample households with women who had delivered a baby during March 1982 to February 1983 were selected. Discriminant Analysis was employed for statistical analysis by utilizing SPSS computer package program. Birth places and birth attendants were considered as dependent variables. Among 12 independent variables in 5 groups considered, 7 independent variables were found statistically significant to affect the selection of birth place. Significant variables by the order of importance are mother's age, order of baby, number of prenatal care, accessibility of emergency medical care, coverage of medical insurance, mother's membership in community organization and husband's educational level. The degree of correct classification of the grouped cases by employing a discriminant . analysis was significantly improved to 78.2％ in comparison to Cmax（56%) and Cpro(51%). Policy implications for each significant variable were discussed to improve the maternal and child health. in Korean ruralarea.

• 한국농공학회논문집
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• 제61권4호
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• pp.1-10
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• 2019

Unmanned aerial vehicle(UAV) can acquire images with lower cost than conventional manned aircraft and commercial satellites. It has the advantage of acquiring high-resolution aerial images covering in the field area more than 50 ha. The purposes of this study is to develop the rice grain yield distribution using UAV. In order to develop a technology for estimating the rice yield using UAV images, time series UAV aerial images were taken at the paddy fields and the data were compared with the rice yield of the harvesting area for two rice varieties(Singdongjin, Dongjinchal). Correlations between the vegetation indices and rice yield were ranged from 0.8 to 0.95 in booting period. Accordingly, rice yield was estimated using UAV-derived vegetation indices($R^2=0.70$ in Sindongjin, $R^2=0.92$ in Donjinchal). It means that the rice yield estimation using UAV imagery can provide less cost and higher accuracy than other methods using combine with yield monitoring system and satellite imagery. In the future, it will be necessary to study a variety of information convergence and integration systems such as image, weather, and soil for efficient use of these information, along with research on preparing management practice work standards such as pest control and nutrient use based on UAV image information.

• 한국농공학회논문집
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• 제64권1호
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• pp.15-26
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• 2022

3D open-field farm model developed from UAV (Unmanned Aerial Vehicle) data could make crop monitoring easier, also could be an important dataset for various fields like remote sensing or precision agriculture. It is essential to separate crops from the non-crop area because labeling in a manual way is extremely laborious and not appropriate for continuous monitoring. We, therefore, made a 3D open-field farm model based on UAV images and developed a crop segmentation model using a supervised machine learning algorithm. We compared performances from various models using different data features like color or geographic coordinates, and two supervised learning algorithms which are SVM (Support Vector Machine) and KNN (K-Nearest Neighbors). The best approach was trained with 2-dimensional data, ExGR (Excess of Green minus Excess of Red) and z coordinate value, using KNN algorithm, whose accuracy, precision, recall, F1 score was 97.85, 96.51, 88.54, 92.35% respectively. Also, we compared our model performance with similar previous work. Our approach showed slightly better accuracy, and it detected the actual crop better than the previous approach, while it also classified actual non-crop points (e.g. weeds) as crops.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.229-233
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• 2007

This study is to test the applicability of QuickBird image for non-point source pollution assessment. SWAT (Soil and Water Assessment Tool) model was adopted and the model was calibrated for a stream watershed of 255.4 $km^2$ Landsat land use data. For model application with QuickBird image, a precise agricultural land use map of 1.16 $km^2$ area located in the upstream watershed was produced by field investigation. The model was run with the combination of land use and soil map scales (1:5,000, 1:25,000 and 1:50,000). The results were compared and analyzed for the contribution of non-point source pollution by the land use scale and contents.

• 농촌의학ㆍ지역보건
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• 제33권3호
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• pp.346-355
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• 2008

- Abstract - Objectives: The purpose of this study is to describe and analyze the characteristics of which laypersons want the cardiopulmonary resuscitation(CPR) education. Methods: Based on a health survey(ｎ=913) of 5 remote places in Korea, tests of the differences between the group that wants the CPR education(ｎ=416) and the group that doesn't(ｎ=497), and a logistic regression analysis of two groups was performed on socio-economic status and health-medical conditions. Results: Even the participation rate of the CPR education in Korea is only 5.8%, which is extremely lower than other developed countries, there are statistically significant differences between the group that wants the CPR and the group that doesn't on gender(ｐ=0.001), age(ｐ=0.000), education level(ｐ=0.000), economic status(ｐ=0.007), and CPR education taken(ｐ=0.000), and health status(ｐ=0.042). Furthermore, age(OR=1.599, ｐ=0.002), age(OR=0.964, ｐ=0.000), economic status(OR=0.804, ｐ=0.028), and CPR education taken(OR=2.072, ｐ=0.026) are statistically significant factors on the willingness to receive the CPR education. Conclusions: This study indicates that there is considerable variation in socio-economic status and health-medical conditions associated with the willingness to receive the CPR education. In remote places. certain subgroups of laypersons such as high-risk patients and family members need targeted outreach programs in CPR education.

• 대한원격탐사학회지
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• 제40권3호
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• pp.257-268
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• 2024

Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.73-76
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• 2005

The advanced information and communication technology gives vehicles another role of the third digital space, merging a physical space with a virtual space in a ubiquitous society. In the ubiquitous environment, the vehicle becomes a sensor node, which has a computing and communication capability in the digital space of wired and wireless network. An intelligent vehicle information system with a remote control and diagnosis is one of the future vehicle systems that we can expect in the ubiquitous environment. However, for the intelligent vehicle system, many issues such as vehicle mobility, in-vehicle communication, service platform and network convergence should be resolved. In this paper, an in-vehicle gateway is presented for an intelligent vehicle information system to make an access to heterogeneous networks. It gives an access to the server systems on the internet via CDMA-based hierarchical module architecture. Some experiments was made to find out how long it takes to communicate between a vehicle's intelligent information system and an external server in the various environment. The results show that the average response time amounts to 776ms at fixec place, 707ms at rural area and 910ms at urban area.