• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.1-16
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• 1998

Microwave brightness temperature data measured from the Special Sensor Microwave/Imager (SSM/I) aboard Defense Meteorological Satellite Program (DMSP) satellite are used to investigate the characteristics of hydrological features of the East Asian summer monsoon during 1994 and 1995. The analyzed parameters include total columnar water vapor, cloud liquid water, and rain rate. These are estimated from SSM/I brightness temperature data for the two summer seasons (June, July, August) of 1994 and 1995 over the Asian monsoon region (0$^{\circ}$-60$^{\circ}$N, 45$^{\circ}$-180$^{\circ}$E). Results indicate that there are periodic westward movement of dry air over the 20$^{\circ}$-30$^{\circ}$N latitudinal belt with about 20-30 day period. Considering that the location of the North Pacific high is closely linked to the evolution of the monsoon activities over East Asia, the westward expansion of the North Pacific high may be the one important element modulating the monsoon intensity.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.27-27
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• 2018

최근 국지적인 집중 호우에 따른 홍수 피해와 도로에 홍수가 발생하고 있다. 또한, 기존의 도로위 강우관측 방식은 인근 강우관측소에서 관측된 강우량을 활용하며 지상 관측소 또는 AWS기상관측소의 관측 네트워크와 근접한 거리에서 강우량 편차가 크고 원하는 위치에서의 강우량과 다르며 인근관측소와의 거리가 멀어질수록 강우량의 정확도는 감소하게 된다. 국지적인 집중호우로 인한 도로위의 홍수에 따른 피해를 줄이기 위해서는 현재 운영 중인 관측망 외에 보다 상세화된 위치에서 강우량을 관측하고 이에 따라 실시간으로 강우정보를 수집하는 것이 필요하다. 따라서, 원하는 위치에서의 보다 정확한 강우량 값을 관측하기 위해서는 고해상도의 강우 관측망을 형성할 필요가 있다. 차량용 강우센서는 관측시 차량을 사용하기 때문에 고밀도 강우 관측 망을 형성하기 용이하다. 하지만 기존 강우량계와 달리 차량용 강우센서는 빛의 양을 이용하여 강우량을 변환시켜 측정되기 때문에 정확한 강우보정기술의 개발하는 것이 필수적이다. 본 연구에서는 차량용 강우센서를 활용하여 정확도 높은 강우량 관측을 위한 관계식을 개발했습니다. 관계식은 실내실제 관측되는 차량용 강우센서 정보 값에 적용하여 강우량을 생산하고 실제 강우관측 값과 비교 검실험을 통해 도출한 후 강우 관측장비 인근에서 실제 주행실험을 통해 강우관측소에서 관측된 강우량 값과 비교 및 검증을 수행하였습니다. 차량용 강우센서 정보 수집을 위해 데이터 스키마를 표준화하여 실시간으로 수집체계를 구축하였고 이는 보다 여러 위치에 있는 많은 차량에서 재해 관리를 위해 도로기상정보를 수집하고 활용할 수 있을 것입니다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.133-152
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• 2022

Rice is a fundamental staple food commodity all around the world. Globally, it is grown over 167 million hectares and occupies almost 1/5^th of total cultivated land under cereals. With a total production of 782 million metric tons in 2018. In Pakistan, it is the 2^nd largest crop being produced and 3^rd largest food commodity after sugarcane and rice. The stem borers a type of pest in rice and other crops, Scirpophaga incertulas or the yellow stem borer is very serious pest and a major cause of yield loss, more than 90% damage is recorded in Pakistan on rice crop. Yellow stem borer population of rice could be stimulated with various environmental factors which includes relative humidity, light, and environmental temperature. Focus of this study is to find the environmental factors changes i.e., temperature, relative humidity and rainfall that can lead to cause outbreaks of yellow stem borers. this study helps to find out the hot spots of insect pest in rice field with a control of farmer's palm. Proposed system uses temperature, relative humidity, and rain sensor along with artificial neural network to predict yellow stem borer attack and generate warning to take necessary precautions. result shows 85.6% accuracy and accuracy gradually increased after repeating several training rounds. This system can be good IoT based solution for pest attack prediction which is cost effective and accurate.

• Smart Media Journal
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• v.12 no.5
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• pp.81-87
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• 2023

In this paper, accidents in high-voltage overhead distribution lines, which provide stable power supply in the power system, cause inconvenience in life and disruption of production of companies. 22.9 [kV] high-voltage overhead power distribution lines aim to improve reliability and stability, such as damage caused by rain, snow, wind, etc., or electric shock prevention. Therefore, in order to prevent wire disconnection accidents due to deterioration of electrical conductivity or tensile strength due to corrosion of overhead distribution lines, it is necessary to prevent unexpected accidents in the future through regular inspection and repair. In order to diagnose deterioration due to corrosion of distribution lines, a diagnostic system (measuring instrument) is installed on the wires to monitor the condition of the wires. The manager on the ground receives the measured data through ZigBee wireless communication, controls the diagnosis system through the diagnosis system program, and grasps the condition of the overhead distribution line through the measured data and photographed photos, and predicts the life of the wire along with the visual inspection method. developed a program.

• Korean Journal of Hazardous Materials
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• v.2 no.1
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• pp.31-37
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• 2014

Since the unprecedented hydrogen fluoride leak accident in 2012, there has been growing demand for customized technical information for rapid response and chemical accident management agencies including the Ministry of Environment, the National Emergency Management Agency, and the National Police Agency need more information on chemicals and accident management. In this regard, this study aims to provide reliable technical data and guidelines to initial response agencies, similar to accident management technical reports of the US and Canada. In this study, we conducted a questionnaire survey and interviews on initial response agencies like fire stations, police stations, and local governments to identify new information items for appropriate initial response and improvements of current guidelines. We also collected and reviewed the Canada's TIPS, US EPA's hydrogen fluoride documents, domestic and foreign literature on applicability tests of control chemicals, and interview data, and then produced items to be listed in the technical guidelines. In addition, to establish database of on-site technical information, we carried out applicability tests for accident control data including ① emergency shut down devide, safety guard, shut down valve, ground connection, dyke, transfer pipe, scrubber, and sensor; ② literature and field survey on distribution type and transportation/storage characteristics (container identification, valve, ground connection, etc.); ③ classification and identification of storage/transportation facilities and emergency management methodslike leak prevention, chemicals control, and cutoff or bypass of rain drainage; ④ domestic/foreign analysis methods and environmental standards including portable detection methods, test standards, and exposure limits; and ⑤ comparison/evaluation of neutralization efficiency of control chemicals on toxic substances.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1023-1030
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• 2023

FMCW LiDAR system with robust target detection capabilities even under adverse operating conditions such as snow, rain, and fog is addressed in this paper. Our focus is primarily on enhancing the performance of FMCW LiDAR by improving the characteristics of the frequency-modulated laser, which directly influence range resolution, coherence length, and maximum measurement range etc. of LiDAR. We describe the utilization of an unbalanced Mach-Zehnder laser interferometer to measure real-time changes of the lasing frequency and to correct frequency modulation errors through an optical phase-locked loop technique. To extend the coherence length of laser, we employ an extended-cavity laser diode as the laser source and implement a laser interferometer with an photonic integrated circuit for miniaturization of optical system. The developed FMCW LiDAR system exhibits a bandwidth of 10.045GHz and a remarkable distance resolution of 0.84mm.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.5
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• pp.1035-1040
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• 2024

The main objective of inspecting structures is to ensure the safety of all entities that utilize these structures as cracks in structures if not attended to could lead to serious calamities. With that objective in mind, artificial intelligence (AI) based technologies to assist human inspectors are needed especially for retaining walls in structures. In this paper, we predict the crack displacement of retaining walls using an Polynomial Regressive (PR) analysis model, as well as Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) deep learning models, and compare their performance. For the performance comparison, we apply multi-variable feature inputs, by utilizing temperature and rainfall data that may affect the crack displacement of the retaining wall. The training and inference data were collected through measuring sensors such as inclinometers, thermometers, and rain gauges. The results show that the multi-variable feature model had a MAE of 0.00186, 0.00450 and 0.00842, which outperformed the single variable feature model at 0.00393, 0.00556 and 0.00929 for the polynomial regression model, LSTM model and the GRU model respectively from the evaluation performed.

• Journal of Satellite, Information and Communications
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• v.2 no.2
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• pp.41-47
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• 2007

The first geostationary satellite made by Korea, COMS, has the three different payload ; Meteorological sensor, Oceanographic sensor and Ka-band communication payload. There are Meteorological & Ocean Data Communication Subsystem(MODCS) and Telemetry, Command and Ranging Subsystem(TC&R) as other RF radiation sources. MODCS transmits and receives Meteo and Ocean measurement data from/to earth using L-band and TC&R using S-band. The Ka-band communication payload will provide high-speed multimedia services and communication services for natural disaster such as prediction, prevention, and recovery services in the government communications network.Ka-band beacon is for the earth antenna pointing and the experiment of rain fading. This paper gives the analysis results about the mutual radiation effect on Ka-band communication payload, Ka-band beacon, MODCS and TC&R. Up/Down link power and coupling factor including the geometrical position and distance of antenna, filter rejection and degradation factor due to the different polarization are considered. The results show MODCS and TC&R are compatible for Ka-band communication payload and Ka-band beacon does not interfere with MODCS and TC&R normal operation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.3
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• pp.34-46
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• 2021

In order to accelerate the commercialization of self-driving cars, it is necessary to accurately identify the causes of deteriorating the driving safety of the current self-driving cars and try to improve them. This study conducted a questionnaire survey of experts studying autonomous driving in Korea to identify the causes of problems in the driving safety of autonomous vehicles and the level of autonomous driving technology in Korea. As a result of the survey, the construction section, heavy rain/heavy snow conditions, fine dust conditions, and the presence of potholes were less satisfied with the current technology level than their importance, and thus priority research and development was required. Among them, the failure of road/road facilities and the performance of the sensor itself in the construction section and the porthole, and the performance of the sensor and the absence of an algorithm were the most responsible for the situation connected to the weather. In order to realize safe autonomous driving as soon as possible, it is necessary to continuously identify and resolve the causes that hinder the driving safety of autonomous vehicles.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1859-1867
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• 2021

This study investigated seasonal characteristics of the particulate matter (PM) in the atmosphere and rainwater quality in Busan, South Korea, and evaluated the seasonal effect of PM₁₀ concentration in the atmosphere on the rainwater quality using multivariate statistical analysis. The concentration of PM in the atmosphere and meteorological observations(daily precipitation amount and rainfall intensity) are obtained from automatic weather systems (AWS) by the Korea Meteorological Administration (KMA) from March 2020 to August 2020. Rainwater samples (n = 216, 13 rain events) were continuously collected from the beginning of the precipitation using the rainwater collecting device at Pukyong National University. The samples were analyzed for pH, EC (electrical conductivity), water-soluble cations(Na⁺, Mg²⁺, K⁺, Ca²⁺, and NH₄⁺), and anions(Cl^-, NO₃^-, and SO₄^2-). The concentration of PM₁₀ in the atmosphere was steadily measured before and after the precipitation with a custom-built PM sensor node. The measured data were analyzed using principal component analysis (PCA) and Pearson correlation analysis to identify relationships between the concentration of PM₁₀ in the atmosphere and rainwater quality. In spring, the daily average concentration of PM₁₀ (34.11 ㎍/m³) and PM_2.5 (19.23 ㎍/m³) in the atmosphere were relatively high, while the value of daily precipitation amount and rainfall intensity were relatively low. In addition, the concentration of PM₁₀ in the atmosphere showed a significant positive correlation with the concentration of water-soluble ions (r = 0.99) and EC (r = 0.95) and a negative correlation with the pH (r = -0.84) of rainwater samples. In summer, the daily average concentration of PM₁₀ (27.79 ㎍/m³) and PM_2.5 (17.41 ㎍/m³) in the atmosphere were relatively low, and the maximum rainfall intensity was 81.6 mm/h, recording a large amount of rain for a long time. The results indicated that there was no statistically significant correlation between the concentration of PM₁₀ in the atmosphere and rainwater quality in summer.