• International Journal of Air-Conditioning and Refrigeration
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• 제14권1호
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• pp.1-6
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• 2006

For the purpose of processing weather data for air conditioning equipment de sign in Busan area Korea, this study collected weather observations made by Busan weather Administration from 1970 to 2003, and then established external conditions for heating and air-conditioning design. For changes of temperature in external conditions for design, the highest temperature had little changed, whereas the lowest had been on the rise as the years went by through the 1970s, 1980s, 1990s, and 2000s, but insolation has a little lessened. Absolute humidity does not show a significant change but an incessant rise.

• 센서학회지
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• 제33권4호
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• pp.230-236
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• 2024

This study aimed to analyze the environmental factors affecting tomato growth by examining the correlation between weather and growth environment sensor data from P Smart Farm located in Gwangseok-myeon, Nonsan-si, Chungcheongnam-do. Key environmental variables such as the temperature, humidity, sunlight hours, solar radiation, and daily light integral (DLI) significantly affect tomato growth. The optimal temperature and DLI conditions play crucial roles in enhancing tomato growth and the photosynthetic efficiency. In this study, we developed a model to correct and predict the time-series variations in internal environmental sensor data using external weather sensor data. A linear regression analysis model was employed to estimate the external temperature variations and internal DLI values of P Smart Farm. Then, regression equations were derived based on these data. The analysis verified that the estimated variations in external temperature and internal DLI are explained effectively by the regression models. In this research, we analyzed and monitored smart-farm growth environment data based on weather sensor data. Thereby, we obtained an optimized model for the temperature and light conditions crucial for tomato growth. Additionally, the study emphasizes the importance of sensor-based data analysis in dynamically adjusting the tomato growth environment according to the variations in weather and growth conditions. The observations of this study indicate that analytical solutions using public weather data can provide data-driven operational experiences and productivity improvements for small- and medium-sized facility farms that cannot afford expensive sensors.

• 한국태양에너지학회 논문집
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• 제29권3호
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• pp.66-72
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• 2009

As 'Low Carbon Green Building' is highly required, programs to evaluate building performance are actively and commonly used. For most of these programs, dynamic responses of buildings against external weather changes are very important. In order to simulate the programs, weather data of each region must be properly entered to estimate accurate amount of building energy consumption. To this end, the existing weather data and weather data of KSES were compared and analyzed to find out how weather changes. Energy load of Korea's standard houses was also analyzed based on this data. As a result, data corresponding to June ${\sim}$ September when cooling is supplied shows 23% of average increase with 30% of peak increase(June). On the other hand, data corresponding to November ${\sim}$ February when heating is supplied shows 29% of average decrease with 34% of peak decrease(November). Increase in cooling load and decrease in heating load in the above data comparison/analysis show that KSES 2009 data reflects increase in average temperature caused by global warming unlike the existing data. Increase in dry-bulb temperature depending on weather change of standard houses increases cooling load by 17% and decreases heating load by 36%

• International Journal of Internet, Broadcasting and Communication
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• 제14권2호
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• pp.162-170
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• 2022

Today, automobiles have become an indispensable element in people's lives, and the distribution of vehicles with various autonomous driving functions is expanding. Sensors such as cameras are used to recognize various situations on the road as an essential element for autonomous driving functions, but camera sensors have disadvantages that are vulnerable to bad weather. In this paper, we present a derivation process that defines external weather environment factors that negatively affect the performance of a camera for an autonomous vehicle. Through the proposed process, it is expected that it will contribute to securing the reliability of the camera and further improving the safety of autonomous vehicles.

• 전기학회논문지
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• 제66권5호
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• pp.857-862
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• 2017

The management of the electric power facilities became important in accordance with the industrial development and electric power facilities were influenced by weather. Even if the same kind of electric power facilities is estimated for extracting the time-varying failure rate, the failure rate could be different depending on external effect such as climate. This research will show the data mining modeling of the weather-related outage and influence of weather on the electric power facility with recent data.

• Journal of Astronomy and Space Sciences
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• 제35권3호
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• pp.175-183
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• 2018

Many recent satellites have mission periods longer than 10 years; thus, satellite-based local space weather monitoring is becoming more important than ever. This article describes the instruments and data applications of the Korea Space wEather Monitor (KSEM), which is a space weather payload of the GeoKompsat-2A (GK-2A) geostationary satellite. The KSEM payload consists of energetic particle detectors, magnetometers, and a satellite charging monitor. KSEM will provide accurate measurements of the energetic particle flux and three-axis magnetic field, which are the most essential elements of space weather events, and use sensors and external data such as GOES and DSCOVR to provide five essential space weather products. The longitude of GK-2A is $128.2^{\circ}E$, while those of the GOES satellite series are $75^{\circ}W$ and $135^{\circ}W$. Multi-satellite measurements of a wide distribution of geostationary equatorial orbits by KSEM/GK-2A and other satellites will enable the development, improvement, and verification of new space weather forecasting models. KSEM employs a service-oriented magnetometer designed by ESA to reduce magnetic noise from the satellite in real time with a very short boom (1 m), which demonstrates that a satellite-based magnetometer can be made simpler and more convenient without losing any performance.

• 상하수도학회지
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• 제28권6호
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• pp.647-655
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• 2014

To perform long-term sewer monitoring, It is important to understand the nature of the wastewater flow that occurs at the point on early stage of the monitor and to prevent in advance a problem which may caused. We can infer the flow properties and external factors by analyzing the scatter graph obtained from the measured data flow rate monitoring data since an field external factor affecting the sewage flow is reflected in the flow rate monitoring data. In this study, Selecting the three points having various external factors, and we Inferred the sewer flow characteristics from depth-velocity scatter graph and determined the analysis equation for the dry-weather flow rate data. At the'point 1' expected non-pressure flow, we were able to see the drawdown effect caused by the free fall in the manhole section. At the'point 2', existed weir and sediments, there was backwater effect caused by them, and each of size calculated from the scatter graph analysis were 400 mm and 130 mm. At the'Point 3', there is specific flow pattern that is coming from flood wave propagation generated by the pump station at upstream. In common, adequate equations to explain the dry weather flow data are flume equation and modified manning equation(SS method), and the equations had compatibility for explaining the data because all of $R^2$ values are over 0.95.

• 한국지능시스템학회논문지
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• 제23권5호
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• pp.379-384
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• 2013

해상교통관제센터(Vessel Traffic Service, VTS)에서 항해중인 선박의 효과적인 관리를 위해 선박에 영향을 주는 외력에 대한 평가가 필요하다. 해상교통 빅데이터는 크게 선박 제원 및 통항정보 등 선박에 의하여 수집되는 정보가 있으며, 다른 하나는 해역에 관련된 바람, 파고, 조류흐름의 외력정보가 있다. 본 연구에서는 이러한 해상교통 빅데이터를 활용하여 선박에 영향을 주는 외력영향을 평가하는 방법에 대해 제안한다. 해상교통 빅데이터를 활용하기 위하여 바람, 파도, 조류 정보, 대수속력(Speed Over Water, SOW)에 대한 정보로 구성되는 해역외력코드(Waterway External Force Code)를 사용하였다. 해역외력코드를 데이터베이스로 하여 그 결과로서 선박에 작용하는 외력영향을 추정하였다.

• 대한조선학회논문집
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• 제50권6호
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• pp.450-457
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• 2013

For the design guide of a vessel operating in cold region, numerical analysis was carried out to evaluate the weather-tight door which installed the heating cables by using ANSYS 13.0 Transient Thermal. The numerical analysis was performed by considering Advection-Diffusion equation. This study based on the experimental results of 'A study on Anti-Icing Technique for Weather-Tight Door of Ice-Strengthened Vessels'(Jeong, et al., 2011a) in KIOST. For validation of the numerical analysis results, the cold chamber experimental data measured by the heat sensors in certain location of the weather-tight door was used. The external environmental temperature which varies from $5^{\circ}C$ to $-55^{\circ}C$ was considered in numerical analysis. Also three different heating cables which have the heat capacity of 33W/m, 45W/m and 66W/m were adapted for the design parameters to be the most efficient and guidelines for anti-icing design of the weather tight door.

• 센서학회지
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• 제31권3호
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• pp.180-186
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• 2022

Photosynthetically active radiation flux density (PPFD) and daily light integral (DLI) values related to plant photosynthesis were obtained using the sunlight time and insolation data points in the agricultural weather sensor data for Jinan-gun, Jeollabuk-do, Korea from 2016 to 2020. The objective was to optimize the photo-environmental conditions for cultivating ginseng. The range of average monthly sunshine duration was 395.5-664.1 min, with the longest duration observed in June. The range of average annual accumulated daily insolation was 11.98-17.65 MJ·m^-2. The range of average daily external DLI calculated from the insolation and solar time data was 22.3-36.1 mol·m^-2·d^-1, and the annual cumulative DLI was 8,156-13,175 mol·m^-2·d^-1. Both the insolation and DLI values were the highest in 2016 and lowest in 2020. Based on the PPFD required for ginseng growth (111-185 µmol·m^-2·s^-1), the monthly average daily DLI and monthly cumulative DLI were 3.51-5.87 and 82-228 mol·m^-2·d^-1, respectively. The range of five-year average value for the external monthly cumulative DLI was 298-1,459 mol·m^-2·d^-1, and the monthly cumulative DLI values when a black double shading film and blue-white shading film were applied were 101-496 and 36-175 mol·m^-2·d^-1, respectively. A comparative analysis of DLI values indicated that shading was required to ginseng growth throughout the year under natural light. When the black double shading film was used, shading was required from March to October. When the blue-white shading film was applied from April to August, (i.e., the period with active ginseng growth) the appropriate DLI for ginseng growth could be continuously maintained. Regional weather differences due to climate change are gradually increasing, and even in one region, monthly and cumulative DLI values are different every year. Therefore, in order to implement a precise agricultural environment for ginseng cultivation, precise analysis and continuous research using agricultural weather sensor big data is required.