• Title/Summary/Keyword: Result indices

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Fish Reproduction Potential Indices in the Coastal and Offshore Ecosystems in Korea (한국 연근해 생태계의 잠재 재생산 지수)

  • Lee, Sun-Kil;Lee, Jae-Bong;Zhang, Chang-Ik;Lee, Dong-Woo
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.40 no.1
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    • pp.24-30
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    • 2007
  • We developed an ecosystem indicator (EI) for the coastal and offshore areas of Korean waters. One of the major scientific challenges of this undertaking was to translate broad policy statements for ecosystem-based fisheries management (EBFM) into practical terms. Fish reproduction potential (FRP) was defined as an EI to describe the reproductive probability of adult fisheries resources in Korean waters. The FRP was estimated as the ratio of adult fish composition to total catch, catches (in metric tons) by species and by ecosystem, and fishery effort (in horse power per metric ton). The FRP indices of the East/japan Sea Ecosystem (EJSE), Yellow Sea Ecosystem (YSE), and East China Sea Ecosystem (ECSE) began to decrease after the mid-1980s, and the current indices have decreased further, at 0.63 (EJSE), 1.22 (YSE), and 0.68 (ECSE) index points compared to the indices of 1975, when similar catch amounts were recorded. Lower FRPs in the Korean marine ecosystems were the result of higher proportion of immature fisheries resources in the total catch. Because this kind of ecosystem-level indicator is thought to reflect scientific approaches to EBFM and to provide an important tool for assessing the current status of marine ecosystems with respect to both quantity and quality, more EIs should be developed for Korean waters.

Effects of on-base and slugging ability on run productivity in Korean professional baseball (한국 프로야구에서 출루 능력과 장타력이 득점 생산성에 미치는 영향)

  • Kim, Hyuk Joo
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1065-1074
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    • 2012
  • The purpose of this paper is to statistically analyze the effects of on-base and slugging ability on the run productivity in Korean professional baseball. In Section 2, we have investigated the OPS (On-base percentage Plus Slugging average) and introduced new indices of batting ability by modifying the OPS. In Section 3, we have examined the correlation which the batting average, on-base percentage, slugging average, IsoP (Isolated Power), OPS and the indices introduced in Section 2 have with the average runs per game, using the data from all the games of the regular seasons in 2007~2011. In addition, by generalizing the OPS and the indices introduced in Section 2, we have analyzed the correlation of the indices with various weights between the average runs per game. As a result, the weighted OPS consisting of on-base percentage (with weight 57%) and slugging average (with weight 43%) has been found to give the best explanation of the run productivity.

Comparison of SAR Backscatter Coefficient and Water Indices for Flooding Detection

  • Kim, Yunjee;Lee, Moung-Jin
    • Korean Journal of Remote Sensing
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    • v.36 no.4
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    • pp.627-635
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    • 2020
  • With the increasing severity of climate change, intense torrential rains are occurring more frequently globally. Flooding due to torrential rain not only causes substantial damage directly, but also via secondary events such as landslides. Therefore, accurate and prompt flood detection is required. Because it is difficult to directly access flooded areas, previous studies have largely used satellite images. Traditionally, water indices such asthe normalized difference water index (NDWI) and modified normalized difference water index (MNDWI) which are based on different optical bands acquired by satellites, are used to detect floods. In addition, as flooding likelihood is greatly influenced by the weather, synthetic aperture radar (SAR) images have also been used, because these are less influenced by weather conditions. In this study, we compared flood areas calculated from SAR images and water indices derived from Landsat-8 images, where the images were acquired at similar times. The flooded area was calculated from Landsat-8 and Sentinel-1 images taken between the end of May and August 2019 at Lijiazhou Island, China, which is located in the Changjiang (Yangtze) River basin and experiences annual floods. As a result, the flooded area calculated using the MNDWI was approximately 21% larger on average than that calculated using the NDWI. In a comparison of flood areas calculated using water indices and SAR intensity images, the flood areas calculated using SAR images tended to be smaller, regardless of the order in which the images were acquired. Because the images were acquired by the two satellites on different dates, we could not directly compare the accuracy of the water-index and SAR data. Nevertheless, this study demonstrates that floods can be detected using both optical and SAR satellite data.

Sensitivity Assessment of Meteorological Drought Index using Bayesian Network (베이지안 네트워크를 이용한 기상학적 가뭄지수의 민감도 평가)

  • Yoo, Ji-Young;Kim, Jin-Young;Kwon, Hyun-Han;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.6
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    • pp.1787-1796
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    • 2014
  • The main purpose of this study is to assess the sensitivity of meteorological drought indices in probabilistic perspective using Bayesian Network model. In other words, this study analyzed interrelationships between various drought indices and investigated the order of the incident. In this study, a Bayesian Network model was developed to evaluate meteorological drought characteristics by employing the percent of normal precipitation (PN) and Standardized Precipitation Index (SPI) with various time scales such as 30, 60, and 90 days. The sensitivity analysis was also performed for posterior probability of drought indices with various time scales. As a result, this study found out interdependent relationships among various drought indices and proposed the effective application method of SPI to drought monitoring.

Landscape Ecological Analysis of Coastal Sand Dune Ecosystem in Korea (해안사구생태계의 경관생태분석)

  • Kim, Jae-Eun;Hong, Sun-Kee
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.12 no.3
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    • pp.21-32
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    • 2009
  • Coastal sand dune area is the important ecosystem as an ecotone which located between coastal area and terrestrial area. Moreover, it is very complicate landscape that have geomorphological interaction between erosion and accumulation of sand. Therefore, it is necessary to understand the sand dune ecosystem in view point of landscape scale including background landscape affecting origin of sand dune. Landscape ecological approach in the complicate ecosystem already started in developed countries, and it is applied to land management and biodiversity conservation strategies even in national scale. In this paper, landscape ecological analysis using landscape pattern analysis was carried out on 7 study areas (Yellow Sea : Hakampo and Doksan, South Sea : Namyeol and Balpo, East Sea : Hosan, Hupo and Goraebul) in Korean coastal sand dune ecosystem. Landscape elements were composed by 9 elements in these study areas. Major background landscape elements was the forest land and agricultural field. Namyeol (S06) has larger patch landscape compare to other areas. In patch shape indices, Hupo (E10) shows more complicate patch shapes. The high landscape heterogeneity showed in the Doksan sand dune area and that of Hosan. It shows that these areas were composed by various patch types. However, using landscape indices have to use very carefully because several variables have influence to the result such as scale and spatial pattern of study areas. Although landscape analysis through landscape indices shows sometimes difficult to explain the ecosystem, landscape scale approach on ecosystem assessment still useful to interpret in ecological process in large range of habitat.

An Application of Various Drought Indices for Major Drought Analysis in Korea (우리나라의 주요가뭄해석을 위한 각종 가뭄지수의 적용)

  • Lee, Jae-Joon;Lee, Chang-Hoon
    • Journal of the Korean Society of Hazard Mitigation
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    • v.5 no.4 s.19
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    • pp.59-69
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    • 2005
  • Drought is difficult to detect and monitor, but it is easy to interpret through the drought index. The Palmer Drought Severity Index(PDSI), which is most commonly used as one of drought indices, have been widely used, however, the index have limitation as operational tools and triggers for policy responses. Recently, a new index, the Standardized Precipitation Index(SPI), was developed to improve drought detection and monitoring capabilities. The SPI has an improvement over previous indices md has several characteristics including its simplicity and temporal flexibility that allow its application for water resources on all timescales. Keetch-Byram Dought Index(KBDI) was defined as a number representing the net effect of evapotranspiration and precipitation in producing cumulative moisture deficiency in deep duff or upper soil layer. The purpose of this study is to analyze drought in Korea by using PDSI, SPI and KBDI. The result of this study suggests standard drought index by comparing of estimated drought indices. The data are obtained from Korea Meteorological Administration 56 stations over 30 years in each of the 8 sub-basins covering the whole nation. It is found that the PDSI had the advantage to detect the stage of drought resulting from cumulative shortage of rainfall, while SPI and KBDI had the advantage to detect the stage of drought resulting from short-term shortage of rainfall.

Deep Learning-Based Stock Fluctuation Prediction According to Overseas Indices and Trading Trend by Investors (해외지수와 투자자별 매매 동향에 따른 딥러닝 기반 주가 등락 예측)

  • Kim, Tae Seung;Lee, Soowon
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.9
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    • pp.367-374
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    • 2021
  • Stock price prediction is a subject of research in various fields such as economy, statistics, computer engineering, etc. In recent years, researches on predicting the movement of stock prices by learning artificial intelligence models from various indicators such as basic indicators and technical indicators have become active. This study proposes a deep learning model that predicts the ups and downs of KOSPI from overseas indices such as S&P500, past KOSPI indices, and trading trends by KOSPI investors. The proposed model extracts a latent variable using a stacked auto-encoder to predict stock price fluctuations, and predicts the fluctuation of the closing price compared to the market price of the day by learning an LSTM suitable for learning time series data from the extracted latent variable to decide to buy or sell based on the value. As a result of comparing the returns and prediction accuracy of the proposed model and the comparative models, the proposed model showed better performance than the comparative models.

Monthly Changes in Temperature Extremes over South Korea Based on Observations and RCP8.5 Scenario (관측 자료와 RCP8.5 시나리오를 이용한 우리나라 극한기온의 월별 변화)

  • Kim, Jin-Uk;Kwon, Won-Tae;Byun, Young-Hwa
    • Journal of Climate Change Research
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    • v.6 no.2
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    • pp.61-72
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    • 2015
  • In this study, we have investigated monthly changes in temperature extremes in South Korea for the past (1921~2010) and the future (2011~2100). We used seven stations' (Gangneung, Seoul, Incheon, Daegu, Jeonju, Busan, Mokpo) data from KMA (Korea Meteorological Administration) for the past. For the future we used the closest grid point values to observations from the RCP8.5 scenario of 1 km resolution. The Expert Team on Climate Change Detection and Indices (ETCCDI)'s climate extreme indices were employed to quantify the characteristics of temperature extremes change. Temperature extreme indices in summer have increased while those in winter have decreased in the past. The extreme indices are expected to change more rapidly in the future than in the past. The number of frost days (FD) is projected to decrease in the future, and the occurrence period will be shortened by two months at the end of the $21^{st}$ century (2071~2100) compared to the present (1981~2010). The number of hot days (HD) is projected to increase in the future, and the occurrence period is projected to lengthen by two months at the end of the $21^{st}$ century compared to the present. The annual highest temperature and its fluctuation is expected to increase. Accordingly, the heat damage is also expected to increase. The result of this study can be used as an information on damage prevention measures due to temperature extreme events.

Diagnosis of Low-Level Aviation Turbulence Using the Korea Meteorological Administration Post Processing (KMAPP) (고해상도 규모상세화 수치자료 산출체계(KMAPP)를 이용한 저고도 항공난류 진단)

  • Seok, Jae-Hyeok;Choi, Hee-Wook;Kim, Yeon-Hee;Lee, Sang-Sam
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.28 no.4
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    • pp.1-11
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    • 2020
  • In order to diagnose low-level turbulence in Korea, diagnostic indices of low-level turbulence were calculated from Aug 2016 to Jul 2019 using a Korea Meteorological Administration Post Precessing (KMAPP) developed by the National Institute Meteorological Sciences (NIMS), and the indices were evaluated using Aircaft Meteorological Data Relay (AMDAR). In the mean horizontal distribution of diagnostic indices calculated, severe turbulence was simulated along major domestic mountains, including near the Taebaek Mountains, the Sobaek Mountains and Hallasan Mountain on Jeju Island due to geographical factors. Later, detection performance was evaluated by calculating the KMAPP Low-Level Turbulencd index (KLT) on combined index, using AUC value of Individual diagnostic indices as a weight. The result showed that the AUC value of KLT was 0.73, and the detection performance was improved (0.02-0.13) when the index was combined. Also, when looking for the AMDAR data is divided into years, seasons, and altitudes, up to 0.94 AUC values were found in winter (DJF) and the surface (surface-1,000ft). By using high-resolution numerical data reflecting detailed terrain data, local turbulence distribution was well demonstrated and high detection performance was shown at low-level.

Analysis of Importance of Damaged Area Assessment Indices using Analytic Hierarchy Process (AHP 기법을 활용한 훼손지 평가항목의 중요도 분석)

  • Song, Ki-Hwan;Choi, Yun-Eui;Seok, Young-Sun;Jeon, Seong-Woo;Sung, Hyun-Chan;Seo, Jung-Young;Chon, Jin-Hyung
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.23 no.6
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    • pp.15-28
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    • 2020
  • Urbanization and industrialization have caused increasing damage to national lands, and ecological restoration has proceeded without any specific assessment of this damage. The purpose of this study is to select indices to assess damaged areas through literature review and panel discussions, and to derive the importance of damaged area assessment indices by analyzing them through the Analytic Hierarchy Process (AHP). This study has derived, via literature review, six types of damage and a total of 18 related assessment indices. A total of 51 responses were collected from surveys and given to experts, and an AHP analysis conducted. As a result of the analysis, "Landform change (0.268)" was of the highest importance, with associated damage types as follows: "Soil contamination (0.193)", "Vegetation damaged (0.149)", "Surface soil loss (0.143)", "Change in soil physiochemical property (0.125)", and "Vegetation decline (0.122)". The analysis determined that the item of the highest importance in the overall assessment of damage was "Slope occurred area (0.100)", and that "Conductivity (0.022)" was of the lowest importance. This study can be presented as a criterion in determining the type and degree of damage in setting priorities for future ecological restoration projects.