• Title/Summary/Keyword: tabular data

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A New Importance Measure of Association Rules Using Information Theory (정보이론에 기반한 연관 규칙들의 새로운 중요도 측정 방법)

  • Lee, Chang-Hwan;Bae, Joohyun
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.1
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    • pp.37-42
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    • 2014
  • The abstract should concisely state what was done, how it was done, principal results, and their significance. It should be less than 300 words for all forms of publication. The abstract should be written as one paragraph and should not contain tabular material or numbered references. At the end of abstract, keywords should be given in 3 to 5 words or phrases.

Study on the revision of Heating Degree-days for Korea (국내 난방도일의 재정립에 관한 연구)

  • Kim, Seong-Su;Cho, Sung-Hwan;Choi, Chang-Yong;Kim, Sang-Ho;Kim, Youn-Hong
    • Proceedings of the SAREK Conference
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    • 2007.11a
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    • pp.17-22
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    • 2007
  • Global average temperature rise accelerates by global warming in the three decades of the 20th century. But now we use heating degree days which was established 20 years ago. Therefore new heating degree days for 15 district areas of korea was determined using long-term measured data. Five different base temperatures ranging from 24 to $16^{\circ}C$ were chosen in the calculation of heating degree days. And yearly heating degree days were given in the tabular form.

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Development of Educational Simulator for Novel Network Reduction (송전망 축약을 위한 교육용 시뮬레이터 개발)

  • Kim, Hyun-Houng;Lee, Woo-Nam;Kim, Wook;Park, Jong-Bae;Shin, Joong-Rin
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.10
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    • pp.1902-1910
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    • 2009
  • This paper presents a graphical windows-based program for the education and training for novel network reduction. The object of developed simulator is to provide users with a simple and useable tool for gaining an intuitive feel for power system analysis. The developed simulator consists of the main module (MMI,GUI), the location marginal price module (LMP), the clustering module and network reduction module. Each module has a separate graphical and interactive interfacing window. The developed simulator needs with the PSS/E input data format, generator cost function, location information. Line admittances of reduced network was determined by using the power flow method(Newton-Raphson). So line flow of reduced network is almost same to original power system. Results of reduced network are compared on the window in the tabular format. Therefore, the developed simulator can be utilized as a useful tool for effective education and training for power system analysis.

A Modi ed Entropy-Based Goodness-of-Fit Tes for Inverse Gaussian Distribution (역가우스분포에 대한 변형된 엔트로피 기반 적합도 검정)

  • Choi, Byung-Jin
    • The Korean Journal of Applied Statistics
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    • v.24 no.2
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    • pp.383-391
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    • 2011
  • This paper presents a modified entropy-based test of fit for the inverse Gaussian distribution. The test is based on the entropy difference of the unknown data-generating distribution and the inverse Gaussian distribution. The entropy difference estimator used as the test statistic is obtained by employing Vasicek's sample entropy as an entropy estimator for the data-generating distribution and the uniformly minimum variance unbiased estimator as an entropy estimator for the inverse Gaussian distribution. The critical values of the test statistic empirically determined are provided in a tabular form. Monte Carlo simulations are performed to compare the proposed test with the previous entropy-based test in terms of power.

The Effect of Economic Growth and Urbanization on Poverty Reduction in Vietnam

  • NGUYEN, Huyen Thi Thanh;NGUYEN, Chau Van;NGUYEN, Cong Van
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.7
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    • pp.229-239
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    • 2020
  • This article aims to measure the impact of economic growth and urbanization on poverty reduction in Vietnam, and verify whether economic growth and urbanization will help reduce poverty rates. Data for this study are tabular data related to growth, urbanization and poverty at the provincial level for the period of nine years, from 2006 to 2014 provided by the Vietnam General Statistics Office and the Vietnam General Department of Customs. The level of economic growth and urbanization mentioned in the study is reflected in such indicators as GDP value, exports value, imports value, urbanization rate and employment rate. The authors used logistic regression models with fixed-effects and logistic regression models with random effects. With 5% confidence level tested by the Chi-Square test of Hausman trial with the fixed-effect model, research results show that: (1) factors with significant negative impact on the poverty rate include imports value, urbanization rate and, employment rate; (2) factors that do not affect the poverty rate include exports value and GDP value. Based on the research results, this study proposes a number of policy recommendations to help promote economic growth, to sustain the urbanization process, and to contribute directly and positively to poverty reduction in Vietnam.

Uncertainty Study of Added Resistance Experiment (부가저항 실험의 불확실성 연구)

  • Park, Dong-Min;Lee, Jaehoon;Kim, Yonghwan
    • Journal of the Society of Naval Architects of Korea
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    • v.51 no.5
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    • pp.396-408
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    • 2014
  • In this study, uncertainty analysis based on ITTC(International Towing Tank Conference) Recommended Procedures is carried out in the towing-tank experiment for motion responses and added resistance. The experiment was conducted for KVLCC2 model in head sea condition. The heave, pitch and added resistance were measured in different wave conditions, and the measurement was repeated up to maximum 15 times in each wave condition in order to observe the uncertainty of measured data. The uncertainty analysis was carried out by adopting the ISO-GUM(International Organization for Standardization, Guide to the Expression of Uncertainty in Measurements) method recommended by ITTC. This paper describes the details about the analysis method, uncertainty and the measured uncertainty for each source. The uncertainty analysis results are summarized as a tabular form. To validate the accuracy of the present measurement, the experimental results are compared with the results of numerical computation and other experiment. From the present uncertainty analysis, the main sources of uncertainty are identified, which can be very useful to improve the accuracy for added resistance experiment.

A Personalized Health Training System Using 3D Animation (3D 애니메이션을 이용한 맞춤형 헬스 트레이닝 시스템)

  • Kim, Jai-Hyun;Park, Jun-Sung;Jung, Il-Hong
    • Journal of Digital Contents Society
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    • v.11 no.4
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    • pp.589-595
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    • 2010
  • In this paper, we have designed and implemented a personalized health training system which provides health training methods using 3D animation based on the data from a professional trainer, after a trainee inputs individual physical characteristics. Many trainers at fitness centers provide only sketchy training method and usage of fitness machines not appropriate training method for trainee's physical characteristics. Individual characteristics. Individual characteristics prepared tabular input which consists of exercise goals, exercise areas, whether or not the normal movement, and RM. The system provides the training methods, the effects of exercise, and the health training motions through searching the database more accurately.

Flow and Heat Transfer Analysis of Copper-water Nanofluid with Temperature Dependent Viscosity Past a Riga Plate

  • Ahmad, A.;Ahmed, S.;Abbasi, F.M.
    • Journal of Magnetics
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    • v.22 no.2
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    • pp.181-187
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    • 2017
  • Flow of electrically conducting nanofluids is of pivotal importance in countless industrial and medical appliances. Fluctuations in thermophysical properties of such fluids due to variations in temperature have not received due attention in the available literature. Present investigation aims to fill this void by analyzing the flow of copper-water nanofluid with temperature dependent viscosity past a Riga plate. Strong wall suction and viscous dissipation have also been taken into account. Numerical solutions for the resulting nonlinear system have been obtained. Results are presented in the graphical and tabular format in order to facilitate the physical analysis. An estimated expression for skin friction coefficient and Nusselt number are obtained by performing linear regression on numerical data for embedded parameters. Results indicate that the temperature dependent viscosity alters the velocity as well as the temperature of the nanofluid and is of considerable importance in the processes where high accuracy is desired. Addition of copper nanoparticles makes the momentum boundary layer thinner whereas viscosity parameter does not affect the boundary layer thickness. Moreover, the regression expressions indicate that magnitude of rate of change in effective skin friction coefficient and Nusselt number with respect to nanoparticles volume fraction is prominent when compared with the rate of change with variable viscosity parameter and modified Hartmann number.

Domain-agnostic Pre-trained Language Model for Tabular Data (도메인 변화에 강건한 사전학습 표 언어모형)

  • Cho, Sanghyun;Choi, Jae-Hoon;Kwon, Hyuk-Chul
    • Annual Conference on Human and Language Technology
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    • 2021.10a
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    • pp.346-349
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    • 2021
  • 표 기계독해에서는 도메인에 따라 언어모형에 필요한 지식이나 표의 구조적인 형태가 변화하면서 텍스트 데이터에 비해서 더 큰 성능 하락을 보인다. 본 논문에서는 표 기계독해에서 이러한 도메인의 변화에 강건한 사전학습 표 언어모형 구축을 위한 의미있는 표 데이터 선별을 통한 사전학습 데이터 구축 방법과 적대적인 학습 방법을 제안한다. 추출한 표 데이터에서 구조적인 정보가 없이 웹 문서의 장식을 위해 사용되는 표 데이터 검출을 위해 Heuristic을 통한 규칙을 정의하여 HEAD 데이터를 식별하고 표 데이터를 선별하는 방법을 적용했으며, 구조적인 정보를 가지는 일반적인 표 데이터와 엔티티에 대한 지식 정보를 가지는 인포박스 데이터간의 적대적 학습 방법을 적용했다. 기존의 정제되지 않는 데이터로 학습했을 때와 비교하여 데이터를 정제하였을 때, KorQuAD 표 데이터에서 f1 3.45, EM 4.14가 증가하였으며, Spec 표 질의응답 데이터에서 정제하지 않았을 때와 비교하여 f1 19.38, EM 4.22가 증가한 성능을 보였다.

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Deep Interpretable Learning for a Rapid Response System (긴급대응 시스템을 위한 심층 해석 가능 학습)

  • Nguyen, Trong-Nghia;Vo, Thanh-Hung;Kho, Bo-Gun;Lee, Guee-Sang;Yang, Hyung-Jeong;Kim, Soo-Hyung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.805-807
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    • 2021
  • In-hospital cardiac arrest is a significant problem for medical systems. Although the traditional early warning systems have been widely applied, they still contain many drawbacks, such as the high false warning rate and low sensitivity. This paper proposed a strategy that involves a deep learning approach based on a novel interpretable deep tabular data learning architecture, named TabNet, for the Rapid Response System. This study has been processed and validated on a dataset collected from two hospitals of Chonnam National University, Korea, in over 10 years. The learning metrics used for the experiment are the area under the receiver operating characteristic curve score (AUROC) and the area under the precision-recall curve score (AUPRC). The experiment on a large real-time dataset shows that our method improves compared to other machine learning-based approaches.