• Korean Journal of Remote Sensing
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• v.10 no.1
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• pp.55-67
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• 1994

The International TOVS(TIROS Oprational Vertical Sounders) Process Package(ITPP-VI)is for a global usage, which needs a surface data to generate atmospheric soundings. If the initial input process in the ITPP-VI is not modified, it takes climatic surface data for producing sounding data in general. Korea Meteorological Administration(KMA) is trying to improve the quality of TOVS sounding data using real-time synoptic observations and make a use weather prediction and analysis in various ways. Serval cases in this study show that TOVS retrieved meteolorogical parameters such as atmopheric temperature, dew point depression and geopotential heights used by synoptic surface observations can delineate more detailed atmospheric feature rather than those used by climate surface data. In addition, the collocated comparisons of TOVS synoptic retrieved parameters with radiosonde observations are performed statistically. TOVS retrieved fields with the synoptic surface analyzed data show smaller bias reatively than those with the climatic data and also reduced root mean square differences below 700 hPa as expected.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.336-339
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• 2012

Accurate forecasting of pan evaporation (PE) is very important for monitoring, survey, and management of water resources. The purpose of this study is to develop and apply Kohonen self-organizing feature maps neural networks model (KSOFM-NNM) to forecast the daily PE for the dry climate region in south western Iran. KSOFM-NNM for Ahwaz station was used to forecast daily PE on the basis of temperature-based, radiation-based, and sunshine duration-based input combinations. The measurements at Ahwaz station in south western Iran, for the period of January 2002 - December 2008, were used for training, cross-validation and testing data of KSOFM-NNM. The results obtained by TEM 1 produced the best results among other combinations for Ahwaz station. Based on the comparisons, it was found that KSOFM-NNM can be employed successfully for forecasting the daily PE from the limited climatic data in south western Iran.

• Proceedings of the Korean Society of Crop Science Conference
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• 2006.04a
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• pp.478-479
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• 2006

• Journal of the Korean Institute of Rural Architecture
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• v.2 no.2
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• pp.1-10
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• 2000

The traditional farm houses in Yongdong area of Kangwon province have a different spatial structure from those of the other areas because of the characteristics of the climatic, geographic and sociocultural circumstances between the Taebaek mountains and the East Sea. So the purpose of this study is aimed at grasping how the spatial features of traditional farm houses in Yongdong area have been different in each regional circle. The plans of traditional farm houses of this region which are four types - ㅡ typed house without floor, ㅡ typed house with floor, ㄱ typed house without floor, ㄱ typed house with floor - show very similar but different space arrangements.

• Proceedings of the KIEE Conference
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• 2005.10c
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• pp.305-307
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• 2005

In the cold and temperate regions of Korea the icing and ice coats on 25[kV] electric car line during winter is a very serious problem. This generates shocks at the mechanical interface of the collecting strips of the pantograph and the contact wire and extra electrical resistance, which may affect quality of current collection at the contact wire / collecting strips of pantograph interface. De-icing operations should be performed just before train operation to avoid the formation of another ice layer. This paper presents temperature analysis of the de-icing system which could be applied to the electric car line of railways.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.131-138
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• 2022

Novel Coronavirus (COVID-19) is viewed as one of the main general wellbeing theaters on the worldwide level all over the planet. Because of the abrupt idea of the flare-up and the irresistible force of the infection, it causes individuals tension, melancholy, and other pressure responses. The avoidance and control of the novel Covid pneumonia have moved into an imperative stage. It is fundamental to early foresee and figure of infection episode during this troublesome opportunity to control of its grimness and mortality. The entire world is investing unimaginable amounts of energy to fight against the spread of this lethal infection. In this paper, we utilized machine learning and deep learning techniques for analyzing what is going on utilizing countries shared information and for detecting the climate factors that effect on spreading Covid-19, such as humidity, sunny hours, temperature and wind speed for understanding its regular dramatic way of behaving alongside the forecast of future reachability of the COVID-2019 around the world. We utilized data collected and produced by Kaggle and the Johns Hopkins Center for Systems Science. The dataset has 25 attributes and 9566 objects. Our Experiment consists of two phases. In phase one, we preprocessed dataset for DL model and features were decreased to four features humidity, sunny hours, temperature and wind speed by utilized the Pearson Correlation Coefficient technique (correlation attributes feature selection). In phase two, we utilized the traditional famous six machine learning techniques for numerical datasets, and Dense Net deep learning model to predict and detect the climatic factor that aide to disease outbreak. We validated the model by using confusion matrix (CM) and measured the performance by four different metrics: accuracy, f-measure, recall, and precision.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.57-65
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• 2023

Various studies to enhance the accuracy of rice production forecasting are focused on improving the accuracy of the models. In contrast, there is a relative lack of research regarding the data itself, which the prediction models are applied to. When applying the same dependent variable and prediction model to two different sets of rice production data composed of distinct features, discrepancies in results can occur. It is challenging to determine which dataset yields superior results under such circumstances. To address this issue, by identifying potential influential features within the data before applying the prediction model and centering the modeling around these, it is possible to achieve stable prediction results regardless of the composition of the data. In this study, we propose a method to adjust the composition of the data's features in order to select optimal base variables, aiding in achieving stable and consistent predictions for rice production. This method makes use of the Korea Meteorological Administration's ASOS data. The findings of this study are expected to make a substantial contribution towards enhancing the utility of performance evaluations in future research endeavors.

• Korean Journal of Medicinal Crop Science
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• v.15 no.4
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• pp.261-265
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• 2007

A climatic feature, growth condition and incidence phase of disease and pest in Korean ginseng (Panax ginseng C. A. Meyer) were surveyed, both the conventional cultivation and culture in the forest located in Jinan. The results were as follows. The forest field was lower $1^{\circ}C$ in the air temperature, lower $1.9^{\circ}C$ in the soil temperature and 11.8% lower in the soil temperature compared with the conventional field. The wind velocity of the forest field was three times slower, but the dew condensation time was 3.3 hours longer than the conventional field. Particularly, the amounts of solar radiation in the forest was remarkably lower, while the rainfall was little lower with no significance. The incidence of disease and pest in the forest field was severe compared with that of the conventional field. Among them, Colletotrichum gloeosporioides, Cylindrocarpon destructans, and Alternaria panax was severe in the forest field while, Botrytis cinerea was severe in the conventional field. The growth condition of forest field in Panax ginseng C. A. Meyer was 50% worse in general and the root weight was 87.2% less than the 3-year-old ginseng in the conventional field.

• KIEAE Journal
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• v.15 no.6
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• pp.93-100
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• 2015

Purpose: Ballparks of KBO which were built by local governments and operated for baseball game-centered have been required more sustainable development according to going into low growth phase in Korea recently. MLB ballparks with the teams having 100 year old tradition have been sustainable-developed economically, socially, environmentally and culturally. This research is to study the characteristics of cultural sustainability in architectural design of 30 MLB parks. Method: To begin with comparison analysis of usage rate of 10 ballparks of KBO with 30 ballparks of MLB, and architectural designs of facades, fields, accommodations, sculptures, greens, roof gardens, etc. are analyzed in the MLB ballpark. And finally, the characteristics of cultural sustainability in the architectural design are analyzed. Result: MLB ballparks have played role as core-space of urban community, accumulated space of citizens' memory being originated in natural climatic feature of region, historical image of city and tradition of home-ballpark. A basis of these characteristics could is nature of cultural sustainability, that is to say local community, historical restoration, social solidarity.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.21-28
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• 2017

The main goal of this paper is to assess application of UAV (Unmanned Aerial Vehicle) remote sensing and GIS based images in detection and measuring of rice field drought area in South Korea. Drought is recurring feature of the climatic events, which often hit South Korea, bringing significant water shortages, local economic losses and adverse social consequences. This paper describes the assesment of the near-realtime drought damage monitoring and reporting system for the agricultural drought region. The system is being developed using drought-related vegetation characteristics, which are derived from UAV remote sensing data. The study area is $3.07km^2$ of Wonbuk-myeon, Taean-gun, Chungnam in South Korea. UAV images were acquired three times from July 4 to October 29, 2015. Three images of the same test site have been analysed by object-based image classification technique. Drought damaged paddy rices reached $754,362m^2$, which is 47.1 %. The NongHyeop Agricultural Damage Insurance accepted agricultural land of 4.6 % ($34,932m^2$). For paddy rices by UAV investigation, the drought monitoring and crop productivity was effective in improving drought assessment method.