• Atmosphere
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• v.29 no.5
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• pp.671-687
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• 2019

This study evaluates the long-term seasonal predictability of summer (June, July and August) heatwaves over South Korea using 30-year (1989~2018) Hindcast data of the Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. Heatwave indices such as Number of Heatwave days (HWD), Heatwave Intensity (HWI) and Heatwave Warning (HWW) are used to explore the long-term seasonal predictability of heatwaves. The prediction skills for HWD, HWI, and HWW are evaluated in terms of the Temporal Correlation Coefficient (TCC), Root Mean Square Error (RMSE) and Skill Scores such as Heidke Skill Score (HSS) and Hit Rate (HR). The spatial distributions of daily maximum temperature simulated by WRF are similar overall to those simulated by NCEP-R2 and PNU CGCM. The WRF tends to underestimate the daily maximum temperature than observation because the lateral boundary condition of WRF is PNU CGCM. According to TCC, RMSE and Skill Score, the predictability of daily maximum temperature is higher in the predictions that start from the February and April initial condition. However, the PNU CGCM-WRF chain tends to overestimate HWD, HWI and HWW compared to observations. The TCCs for heatwave indices range from 0.02 to 0.31. The RMSE, HR and HSS values are in the range of 7.73 to 8.73, 0.01 to 0.09 and 0.34 to 0.39, respectively. In general, the prediction skill of the PNU CGCM-WRF chain for heatwave indices is highest in the predictions that start from the February and April initial condition and is lower in the predictions that start from January and March. According to TCC, RMSE and Skill Score, the predictability is more influenced by lead time than by the effects of topography and/or terrain feature because both HSS and HR varies in different leads over the whole region of South Korea.

• Korean journal of applied entomology
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• v.39 no.1
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• pp.31-41
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• 2000

Community analysis of oribatid mites was conducted in Namsan and Kwangreung coniferous forests which have been received by different degrees of environmental pressures through urbanization processes. Oribatid mites were sampled in the litter and soil layer of study sites from May 1993 to October 1994. Although two sites have been under similar weather condition, seasonal changes in oribatid mites density did not show a synchronized pattern. Density in spring and summer showed stable pattern with low fluctuations, but unstable pattern in autumn between 1993 and 1994. And these patterns were highly correlated with precipitation. The density and species number were higher in the litter layer than in the soil layer and showed no typical seasonal changes. The dominant species were Scheloribates latipes (1 l.78%), Pergalumna altera (8.92%), Eohypochthonius crassisetiger (7.58%), Scheloribates sp. (6.89%) and Suctobelbella yezoensis (5.04%) in Namsan, and Ceratozetes japonicus (25.72%), Punctoribates punctum (14.15%), Trichogalumna nipponica (10.96%) and Ramusella sengbuschi (5.08%) in Kwangreung. The number of species with high constany were 10 and 18 in Namsan and Kwangreung, respectively. Namsan showed the feature of urban forests. In analysis of species diversity, species richness was significantly higher in Kwangreung than in Namsan, while shannon (H') and evenness index (J') were higher in Namsan than in Kwangreung. The values of shannon index (H') in Namsan and Kwangreugn were 2.83 and 2.62, respectively and evenness index (J') were 0.78 and 0.67, respectively. The value of similarity index between two sites was 0.68.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1083-1093
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• 2021

It is an essential to predict water usage for establishing an optimal supply operation plan and reducing power consumption. However, the water usage by consumer has a non-linear characteristics due to various factors such as user type, usage pattern, and weather condition. Therefore, in order to predict the water consumption, we proposed the methodology linking various techniques that can consider non-linear characteristics of water use and we called it as KWD framework. Say, K-means (K) cluster analysis was performed to classify similar patterns according to usage of each individual consumer; then Wavelet (W) transform was applied to derive main periodic pattern of the usage by removing noise components; also, Deep (D) learning algorithm was used for trying to do learning of non-linear characteristics of water usage. The performance of a proposed framework or model was analyzed by comparing with the ARMA model, which is a linear time series model. As a result, the proposed model showed the correlation of 92% and ARMA model showed about 39%. Therefore, we had known that the performance of the proposed model was better than a linear time series model and KWD framework could be used for other nonlinear time series which has similar pattern with water usage. Therefore, if the KWD framework is used, it will be possible to accurately predict water usage and establish an optimal supply plan every the various event.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.851-858
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• 2021

Due to the increase in renewable energy and distributed resources, not only traditional data but also various energy-related data are being generated in the new energy industry. In other words, there are various renewable energy facilities and power generation data, system operation data, metering and rate-related data, as well as weather and energy efficiency data necessary for new services and analysis. Energy big data processing technology can systematically analyze and diagnose data generated in the first half of the power production and consumption infrastructure, including distributed resources, systems, and AMI. Through this, it will be a technology that supports the creation of new businesses in convergence between the ICT industry and the energy industry. To this end, research on the data analysis system, such as itemized characteristic analysis of the collected data, correlation sampling, categorization of each feature, and element definition, is needed. In addition, research on data purification technology for data loss and abnormal state processing should be conducted. In addition, it is necessary to develop and structure NIFI, Spark, and HDFS systems so that energy data can be stored and managed in real time. In this study, the overall energy data processing technology and system for various power transactions as described above were proposed.

• (The)Study of the Eastern Classic
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• no.57
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• pp.41-66
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• 2014

The Purpose of this paper is, through the character-figuration aspect of existing Yeoheon Jang Hyungwang(旅軒 張顯光, 1554~1637)-related folk tales, to determine the relation between the people's awareness on Yeoheon and the change in the folk tales. Only 4 pieces of Yeoheon-related folk tales are existed ; ; Forgiving a rude son of the provincial governor generously. ; Predicting 'the frost of May' and Preventing the cold-weather damage, when he served as Euiseong governor, and ; The folk tales of origins of the place name - Chimabawi Rockand Yeoheondae. shows the great scholar's liberal-hearted and generous personality. One day Jang Hyungwang looked shabby and a young person was quite rude to him. But Jang Hyungwang forgive him generously. Also Yeoheon teach him the thrift and modesty. described him as a governor filled with a love for the people. He tried to edify the people with the Confucian ethics and improve the life's work of the people. embodied him as a government official of high integrity. When his wife received the silk slip from the people, as farewell gift, he ordered his wife return that. and show the images of the Predicting the future and an extraordinary moralizer. Generally These folk tales are based on his personality, whereabouts and the real case. So we could find his images in the folk tales are close to his actual feature - thrift, modest, noble-minded, well-versed in Iching and practicing moral statesmanship.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.283-298
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• 2022

As Synthetic Aperture Radar (SAR) image can be acquired regardless of the weather and day or night, it is highly recommended to be used for Automatic Target Recognition (ATR) in the fields of surveillance, reconnaissance, and national security. However, there are some limitations in terms of cost and operation to build various and vast amounts of target images for the SAR-ATR system. Recently, interest in the development of an ATR system based on simulated SAR images using a target model is increasing. Attributed Scattering Center (ASC) matching and template matching mainly used in SAR-ATR are applied to target classification. The method based on ASC matching was developed by World View Vector (WVV) feature reconstruction and Weighted Bipartite Graph Matching (WBGM). The template matching was carried out by calculating the correlation coefficient between two simulated images reconstructed with adjacent points to each other. For the performance analysis of the two proposed methods, the Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset was used, which has been recently published by the U.S. Defense Advanced Research Projects Agency (DARPA). We conducted experiments under standard operating conditions, partial target occlusion, and random occlusion. The performance of the ASC matching is generally superior to that of the template matching. Under the standard operating condition, the average recognition rate of the ASC matching is 85.1%, and the rate of the template matching is 74.4%. Also, the ASC matching has less performance variation across 10 targets. The ASC matching performed about 10% higher than the template matching according to the amount of target partial occlusion, and even with 60% random occlusion, the recognition rate was 73.4%.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.97-107
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• 2024

Despite the rapid advancement in image recognition technology, achieving perfect digitization of tabular documents and handwritten documents still challenges. The purpose of this study is to improve the accuracy of digitizing the logbook by correcting errors by utilizing associated rules considered during logbook entries. Through this, it is expected to enhance the accuracy and reliability of data extracted from logbook through OCR programs. This model is to improve the accuracy of digitizing the logbook of the training ship "Saenuri" at the Mokpo Maritime University by correcting errors identified after Optical Character Recognition (OCR) program recognition. The model identified and corrected errors by utilizing associated rules considered during logbook entries. To evaluate the effect of model, the data before and after correction were divided by features, and comparisons were made between the same sailing number and the same feature. Using this model, approximately 10.6% of errors out of the total estimated error rate of about 11.8% were identified, and 56 out of 123 errors were corrected. A limitation of this study is that it only focuses on information from Dist.Run to Stand Course sections of the logbook, which contain navigational information. Future research will aim to correct more information from the logbook, including weather information, to overcome this limitation.

• Journal of the Korean Society of Food Culture
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• v.1 no.2
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• pp.116-126
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• 1986

This study was designed to be a link in the chain of the investigation on daily life and consciousness of longevous people in Korea, and to investigate the regional feature of longevity areas. The daily life and consciousness were investigated on 379 subjects(male 121, female 258) of the aged who were above 80 years of age, from June to November in 1985. This paper is to report the results investigated the longevity rate, distribution, classification and weather of longevity districts, and also the actual conditions such as the functions of daily life and educational degree of longevous people. 1. The number of longevous people in Korea was 171,449 (male 42,842, female 128,607), and the average longevity rate was 0.46% against total population in Korea(male 0.23%, female 0.69%). 2. Of the longevity rates of shi and/or do in Korea, Cheju(1.03%) was the highest among these districts, and decreased in the order of Chonnam(0.79%), Chonbuk(0.66%), Kyongbuk(0.65%) and Kyongnam(0.61%), whereas the large cities such as Inchon(0.22%), Seoul(0.23%), Pusan(0.23%) and Taegu(0.28%) were remarkably lower than districts in seasides and mountains. 3. The districts above 1.0% of longevity rate in Korea showed 17-guns, and the distribution of these districts was 10-guns of Chonnam, 2-guns of Kyongbuk and Kyongnam, and 1-gun of Kyonggi, Cho-nbuk and Cheju, respectively. 4. Of these districts, Pukcheju(1.65%) was the highest, and decreased in the order of Namhae(1.56%), Sungju(1.24%), Posong(1.22%) and Koksong(1.20%). The highest figure(male 0.71%, female 2.51%) was observed in Pukcheju as contrasted with 0.23%(male) and 0.69%(female) of the average longevity rate in Korea. 5. The sex ratio of longevous people in Korea showed the female/male ratio of 3.0. It is, therefore, believed that the longevity rate of female was 3 times higher than that of male. 6. The longevity districts were classified into seven districts in seasides, three districts in isolated islands, and seven rural districts in mountains. 7. The situation of weather in longevity districts was in the range of 11.2 to $14.8^{\circ}C$ at annual average temperature, and 878.5 to 1585.9mm at annual average rainfall. 8. Of the educational degree of longevous people, uneducated(71.5%) was the highest, and followed by the order of village school(15.8%) and above elementary school(4.8%). 9. In the functions of daily life, the aged moving actively(53.0%) was the highest among these longevous people, followed by the aged moving a little(23.5%). Therefore, it is believed that health degree of these longevous peoples by the functions of daily life was very gratifying.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.4
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• pp.104-117
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• 2017

This study compares the results of landscape image analysis using text mining techniques and factor analysis for Lotte World Tower, which is the first atypical skyscraper building in Korea, and identifies landscape images of the site to determine possibilities of use. Lotte World Tower's landscape image has been extracted from text mining analysis focusing on adjectives such as 'new', 'transformational', 'unusual', 'novelty', 'impressive', and 'unique', and phrases such as in the process of change, people's active elements(caliber, outing, project, night view), media(newspaper, blog), and climate(weather, season). As a result of the factor analysis, factors affecting the landscape image of Lotte World Tower were symbolic, aesthetic, and formative. Identification, which is a morphological feature, has characteristics of scale and visibility but it is not statistically significant in preference. Rather, the psychological factors such as the symbolism with characteristics such as poison and specialty, harmony with the characteristics of the surrounding environment, and beautiful aesthetic characteristics were an influence on the landscape image. The common results of the two research methods show that psychological characteristics such as factors that can represent and represent the city affect the landscape image more greatly than the morphological and physical characteristics such as location and location of the building. In addition, the text mining technique can identify nouns and adjectives corresponding to the images that people see and feel, and confirms the relationship between the derived keywords, so that it can focus the process of forming the landscape image and further the image of the city. It would appear to be a suitable method to complement the limitation of landscape research. This study is meaningful in that it confirms the possibility that big data can be utilized in landscape analysis, which is one research field of landscape architecture, and is significant for understanding the information of a big data base and contribute to enlarging the landscape research area.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.6
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• pp.422-429
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• 2013

It is generally known that the increase of the Earth surface temperature due to the global warming together with the land desertification by rapid urban development has caused severe climate and weather change. In desert or desertification land, it is observed that there are always severe flooding phenomena, even if desert sand has the high porosity, which could be believed as the favorable condition of rain water infiltration into ground water. The high runoff feature causes possibly another heavy rain by quick evaporation with the depletion of underground water due to the lack of infiltration. The basic physics of desert flooding is reasonably assumed due to the thermal buoyancy of the higher temperature of the soil temperature than that of the rain drop. Considering the importance of this topic associated with water resource management and climate disaster prevention, no systematic investigation has, however, been reported in literature. In this study, therefore, a laboratory scale experiment together with the effort of numerical calculation have been performed to evaluate quantitatively the basic hypothesis of run-off mechanism caused by the increase of soil temperature. To this end, first, of all, a series of experiment has been made repeatedly with the change of soil temperature with well-sorted coarse sand having porosity of 35% and particle diameter, 2.0 mm. In specific, in case 1, the ground surface temperature was kept at $15^{\circ}C$, while in case 2 that was high enough at $70^{\circ}C$. The temperature of $70^{\circ}C$ was tested as this try since the informal measured surface temperature of black sand in California's Coachella Valley up to at 191 deg. $^{\circ}F$ ($88^{\circ}C$). Based on the experimental study, it is observed that the amount of runoff at $70^{\circ}C$ was higher more than 5% compared to that at $15^{\circ}C$. Further, the relative amount of infiltration by the decrease of the surface temperature from 70 to $15^{\circ}C$ is about more than 30%. The result of numerical calculation performed was well agreed with the experimental data, that is, the increase of runoff in calculation as 4.6%. Doing this successfully, a basic but important research could be made in the near future for the more complex and advanced topic for this topic.