• Title/Summary/Keyword: 분위별 수요

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Inference of natural flood frequency for the region affected by dams in Nam Han River (남한강 유역 댐 영향 지역의 기본홍수량 추론)

  • Kim, Nam Won;Lee, Jeong Eun;Lee, Jeongwoo
    • Journal of Korea Water Resources Association
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    • v.49 no.7
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    • pp.599-606
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    • 2016
  • The objective of this study is to estimate the unregulated flood frequency from Chungju dam to Yangpyung gauging station for the region affected by dams based on the peak discharges simulated by storage function routing model. From the flood frequency analyses, the quantiles for the unregulated flood frequency at 6 sites have similar pattern to each other, and their averaged quantile almost matched to the result from the regional flood frequency analysis. The quantile and annual mean discharge for the unregulated flood frequency for the downstream of Chungju dam show the similar behaviour to those for the upstream area. While the quantile and the annual mean discharge for the regulated flood frequency are significantly different from those for the unregulated flood frequency. In particular, the qunatile shows severe difference as the return period increases, and the annual mean discharge has a tendency to approach to the natural flood as the distance from dam increases.

Performance Analysis of Directors, Producers, Main Actors in Korean Movie Industry using Deciles Distribution (2004-2017) (평균 관객 수 10분위를 활용한 감독, 제작자, 배우 흥행성과 분석)

  • Kim, Jung-Ho;Kim, Jae Sung
    • The Journal of the Korea Contents Association
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    • v.18 no.10
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    • pp.78-98
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    • 2018
  • On the 855 pure Korean commercial fictional movies, excluding diversity films, released in Korea from 2004 to August 2017, I conducted deciles distribution analysis of box office performance of those movies and average box office performance of directors, producers and lead actors who involved in making them. Deciles distribution analysis of average box office performance might be helpful to predict their next box office performance of newly produced Korean movies and to evaluate their contribution to box office performance. In baseball, the various index such as winning rate, on-base percentage, slugging percentage, stolen base percentage, battling average, earned run average is used for predicting and reviewing of professional players. In this study, I evaluate the script's narrative quality by the indirect method of insight and judgment of creative manpower involved in making the movies. For the more productive prediction, direct statistical analysis method on the narrative of the script needs to develop. Time series analysis is required to evaluate the rise and fall of creative manpower and network analysis is also necessary to see the interaction among creative people.

집단화된 자료의 분위수를 계산하는 수정된 방법

  • Kim, Hyeok-Ju;Yu, Ji-Seon
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.05a
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    • pp.147-154
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    • 2005
  • 본 논문에서는 집단화된 자료의 분위수들을 계산하는 수정된 방법을 제시하였다. 제시된 방법은 각 계급구간 안의 자료들이 그 구간에 걸쳐 균등한 간격으로, 그리고 구간의 중간점에 관하여 대칭으로 분포하고 있다고 가정하고 분위수들을 계산하는 방법이다. 개개의 자료값들이 주어진 자료를 통하여, 제시된 방법과 기존의 방법을 비교하였다.

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Correlation of Korean Elderly Dental Health Capacity and Preferred Foods (한국 노인의 치아건강도와 선호식품과의 관련성)

  • Ju, On-Ju;Kim, In-Ja
    • Journal of dental hygiene science
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    • v.15 no.6
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    • pp.712-720
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    • 2015
  • The purpose of this study is to examine whether any correlation exists between the dental health capacity and preferred foods of Korean senior citizens over the age of 65 years. The 5th Korean National Health and Nutrition Survey were used. Tissue health index (T-health), Sound teeth (ST), Functioning teeth index (FS-T), Present teeth (PT), and Missing teeth (MT) were used as variables to assess the dental health capacity of the elderly. Preferred foods of the elderly included 63 foods that were categorized as cereals, pulses and roots, meat and poultry, fish, vegetables, sea algae, fruits, milk and dairy products, cream and sugar, and other foods. For data analysis, the weighted average was taken into consideration to generate planning files, and then complex sample analysis were conducted. For statistical analysis, frequency analysis, t-test, one-way ANOVA, and compound specimen linear regression analysis were conducted. T-health score was significantly high in the group with high preference for cereals, fruits, and other foods. In terms of age and economic status, 65~69 years, 70~74 years, and mid to low range in the income ranges scored high in T-health. ST score was significant in the group that preferred cereals, other foods; the corresponding demographic profiles represent 65~69 years, 70~74 years, and the mid-range income communities. FS-T was significant in relation with a preference for fruits, creams and sugars, other foods; the scores were also high for 65~69 years, 70~74 years, and mid-low to low income groups. PT and MT were significant in the group that preferred cereals and fruits; the same applied for 65~69 years, 70~74 years, and mid-low to low income individuals (p<0.05). Food preferences seemed to vary depending on the dental health state of the elderly, and the dental health state of the elderly may act as a risk factor for nutritional imbalance.

Analysis of AI interview data using unified non-crossing multiple quantile regression tree model (통합 비교차 다중 분위수회귀나무 모형을 활용한 AI 면접체계 자료 분석)

  • Kim, Jaeoh;Bang, Sungwan
    • The Korean Journal of Applied Statistics
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    • v.33 no.6
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    • pp.753-762
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    • 2020
  • With an increasing interest in integrating artificial intelligence (AI) into interview processes, the Republic of Korea (ROK) army is trying to lead and analyze AI-powered interview platform. This study is to analyze the AI interview data using a unified non-crossing multiple quantile tree (UNQRT) model. Compared to the UNQRT, the existing models, such as quantile regression and quantile regression tree model (QRT), are inadequate for the analysis of AI interview data. Specially, the linearity assumption of the quantile regression is overly strong for the aforementioned application. While the QRT model seems to be applicable by relaxing the linearity assumption, it suffers from crossing problems among estimated quantile functions and leads to an uninterpretable model. The UNQRT circumvents the crossing problem of quantile functions by simultaneously estimating multiple quantile functions with a non-crossing constraint and is robust from extreme quantiles. Furthermore, the single tree construction from the UNQRT leads to an interpretable model compared to the QRT model. In this study, by using the UNQRT, we explored the relationship between the results of the Army AI interview system and the existing personnel data to derive meaningful results.

Nonparametric estimation of conditional quantile with censored data (조건부 분위수의 중도절단을 고려한 비모수적 추정)

  • Kim, Eun-Young;Choi, Hyemi
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.2
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    • pp.211-222
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    • 2013
  • We consider the problem of nonparametrically estimating the conditional quantile function from censored data and propose new estimators here. They are based on local logistic regression technique of Lee et al. (2006) and "double-kernel" technique of Yu and Jones (1998) respectively, which are modified versions under random censoring. We compare those with two existing estimators based on a local linear fits using the check function approach. The comparison is done by a simulation study.

Analysis of Efficacy of The National Scholarship System and Policy Suggestions (국가장학금의 효과성 분석과 개선방안에 대한 고찰)

  • Park, Seung-Ryel;Han, Byung-Suk
    • Journal of the Korea Convergence Society
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    • v.9 no.12
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    • pp.259-264
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    • 2018
  • This study analyzes whether the national scholarship system achieves the policy goal to provide the half-tuition and suggests ways to improve the policy. The study finds that the national scholarship system provides free education for students from under 2nd decile income and the half-tuition for students from under 6th decile. However, since students don't feel fully the effect of the policy, this study proposes policy improvements on new approaches to public communications. Also is suggested the necessity to change the policy tool from debt-like to equity-like investment.

Redundant and Abnormal Data Processing Scheme in Large-scale IoT Environment (대규모 IoT 환경에서의 중복 및 비정상 데이터 처리 기법)

  • Kim, Min-Woo;Lee, Tae-Ho;Lee, Byung-Jun;Kim, Kyung-Tae;Youn, Hee-Yong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.07a
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    • pp.109-110
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    • 2019
  • 최근 IoT 환경에서는 고밀도로 노드가 분포되어진다. 이러한 센서 노드들은 데이터 전송 시 혼잡을 초래하는 중복 데이터를 생성하여 데이터의 정확도를 저하시킨다. 이에 따라 본 연구에서는 데이터 집중으로 인해 발생하는 네트워크의 정체 문제를 해결하기 위해 제안 기법은 사 분위(Interquatile, IRQ) 분석과 코사인 유사도 함수를 통해 데이터의 이상치와 중복성을 측정하여 중복 데이터 및 특이치를 제거한다. 본 연구를 통하여 최적의 데이터 전송을 통하여 IoT의 통신 성능을 향상시킬 수 있으며 결과적으로 데이터 감소율, 네트워크 수명 및 에너지의 효율성을 높일 수 있다.

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CTE with weighted portfolios (가중 포트폴리오에서의 CTE)

  • Hong, Chong Sun;Shin, Dong Sik;Kim, Jae Young
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.1
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    • pp.119-130
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    • 2017
  • In many literatures on VaR and CTE for multivariate distribution, these are estimated by using transformed univariate distribution with a specific ratio of many kinds of portfolios. Even though there are lots of works to define quantiles for multivariate distributions, there does not exist a quantile uniquely. Hence, it is not easy to define the VaR and CTE. In this paper, we propose the weighted CTE vectors corresponding to various ratio combinations of many kinds of portfolios by extending the researches on the alternative VaR and integrated multivariate CTE based on multivariate quantiles. We extend relation equations about univariate CTEs to multivariate CTE vectors and discuss their characteristics. The proposed weighted CTEs are explored with some data from multivariate normal distribution and illustrative examples.

Assessing the Utility of Rainfall Forecasts for Weekly Groundwater Level Forecast in Tampa Bay Region, Florida (주단위 지하수위 예측 모의를 위한 강우 예측 자료의 적용성 평가: 플로리다 템파 지역 사례를 중심으로)

  • Hwang, Syewoon;Asefa, Tirusew;Chang, Seungwoo
    • Journal of The Korean Society of Agricultural Engineers
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    • v.55 no.6
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    • pp.1-9
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    • 2013
  • 미래 기후 정보를 이용한 수문 환경의 단기 미래 예측은 안정적 수자원 공급을 위한 필수적 과제이다. 미국 플로리다 주 중서부 템파지역에서는 주요 수자원 중 하나인 지하수의 효과적 활용을 위해 지하수위 인공신경망 모델 (GWANN)을 개발하여 피압 대수층과 비피압 대수층에 대한 주 단위 평균 지하수위를 월별로 예측하고 그 결과를 수자원 공급 의사 결정에 반영하고 있다. 본 논문은 템파지역에 대한 GWANN 모델을 이용한 지하수위 예측 시스템을 소개하고 모델의 기후 입력 자료의 민감도를 분석함으로써 양질의 기후 정보에 대한 현 시스템의 활용성을 검토하였다. 2006년과 2007년에 대한 연구 결과, 관측 자료를 최적 예측 시나리오 (the best forecast)로 가정하여 적용한 결과는 지하수위 관측 지점에 따라 큰 차이를 보였지만 일반적으로 현 시스템 (현 시점의 실시간 주 단위 평균 강우량을 향후 4주간 동일하게 적용함) 에 비해 예측 성능이 개선되는 것으로 나타났다. 더불어 강우 관측 자료의 백분위 (percentile forecast; 20분위, 50분위, 80분위)를 강우 예측 자료로 활용한 경우에도 현 시스템과 비교하여 일부 나은 결과를 보여주었다. 그러나 지하수위 예측 모델을 활용하지 않고 현 시점의 지하 수위가 지속된다고 가정하는 경우 (na$\ddot{i}$ve model) 향후 2주간의 예측 결과가 best forecast 경우에 비해 높은 정확도를 보이는 등, GWANN 모델의 단기 예측에 대한 양질의 강우 예측 정보의 활용성은 낮으며, 향후 3주 이상에 대한 예측 성능에 있어 best forecast결과가 na$\ddot{i}$ve model 결과에 비해 높은 정확도를 보이기 시작하는 것으로 나타났다. 또한 GWANN 모델의 예측 성능은 적용 기간과 지역 및 지하대수층의 특성에 따라 큰 다양성을 가지는 단점을 보여 강우 예측 자료 활용에 앞서 모델 개선의 필요성이 있다고 판단된다. 본 연구는 단기수자원 공급 계획 수립을 위하여 사용되는 지역 모델링 시스템에 대한 기후 예측정보의 활용성 평가를 위한 방법론으로 고려될 수 있을 것으로 기대된다.