• Title/Summary/Keyword: Cluster Models

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A Development of Hourly Rainfall Simulation Technique Based on Bayesian MBLRP Model (Bayesian MBLRP 모형을 이용한 시간강수량 모의 기법 개발)

  • Kim, Jang Gyeong;Kwon, Hyun Han;Kim, Dong Kyun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.3
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    • pp.821-831
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    • 2014
  • Stochastic rainfall generators or stochastic simulation have been widely employed to generate synthetic rainfall sequences which can be used in hydrologic models as inputs. The calibration of Poisson cluster stochastic rainfall generator (e.g. Modified Bartlett-Lewis Rectangular Pulse, MBLRP) is seriously affected by local minima that is usually estimated from the local optimization algorithm. In this regard, global optimization techniques such as particle swarm optimization and shuffled complex evolution algorithm have been proposed to better estimate the parameters. Although the global search algorithm is designed to avoid the local minima, reliable parameter estimation of MBLRP model is not always feasible especially in a limited parameter space. In addition, uncertainty associated with parameters in the MBLRP rainfall generator has not been properly addressed yet. In this sense, this study aims to develop and test a Bayesian model based parameter estimation method for the MBLRP rainfall generator that allow us to derive the posterior distribution of the model parameters. It was found that the HBM based MBLRP model showed better performance in terms of reproducing rainfall statistic and underlying distribution of hourly rainfall series.

Parallel Rendering of High Quality Animation based on a Dynamic Workload Allocation Scheme (작업영역의 동적 할당을 통한 고화질 애니메이션의 병렬 렌더링)

  • Rhee, Yun-Seok
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.1
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    • pp.109-116
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    • 2008
  • Even though many studies on parallel rendering based on PC clusters have been done. most of those did not cope with non-uniform scenes, where locations of 3D models are biased. In this work. we have built a PC cluster system with POV-Ray, a free rendering software on the public domain, and developed an adaptive load balancing scheme to optimize the parallel efficiency Especially, we noticed that a frame of 3D animation are closely coherent with adjacent frames. and thus we could estimate distribution of computation amount, based on the computation time of previous frame. The experimental results with 2 real animation data show that the proposed scheme reduces by 40% of execution time compared to the simple static partitioning scheme.

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EFFECT OF SECOND GENERATION POPULATIONS ON THE INTEGRATED COLOR OF METAL-RICH GLOBULAR CLUSTERS IN EARLY-TYPE GALAXIES

  • Chung, Chul;Lee, Sang-Yoon;Yoon, Suk-Jin;Lee, Young-Wook
    • The Bulletin of The Korean Astronomical Society
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    • v.38 no.1
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    • pp.30.2-30.2
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    • 2013
  • The mean color of globular cluster (GCs) systems in early-type galaxies (ETGs) is, in general, bluer than the integrated color of field stars in their host galaxies. Recently, Goudfrooij & Kruijssen (2013) reported that even red GCs in the ETGs show bluer colors than their host field stars and suggested the different initial mass function (IMF) for red GCs and field stars to explain the observed offset in color. Here we suggest an alternative scenario that explains the observed color offsets between red GCs in ETGs and the field stars in the parent galaxies without invoking to the variation of the IMF. We find that the inclusion of second-generation (SG) helium-enhanced populations in the model fully explains the observed color offset between red GCs and field stars in the host galaxies. We have also tested the effect of the IMF slope on our models, but the effect is relatively small compared to the effect of the SG population. Our new model suggests that, in order to explain far-UV strong metal-rich GCs in M87 and the observed color offset between metal-rich GCs and the field stars in ETGs simultaneously, the inclusion of the SG populations with enhanced helium abundance is a more natural solution than the model that only adopted variations in the IMF.

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An Exploration of Families Use of Information and Communications Technology: The Case of Korea and the United States

  • Brady, John T.;Lee, Bohan;Rha, Jong-Youn
    • International Journal of Human Ecology
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    • v.16 no.2
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    • pp.79-88
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    • 2015
  • As information and communications technology (ICT) becomes increasingly integrated into the daily lives of people around the world, it is important to know how the technology is influencing the behaviors of individuals and families. This study looked at the ecology of families as it is related to ICT and the changes to processes that occur as ICT devices and services are integrated into the family. A survey of 1084 families was conducted. Five hundred of the families were from the United States and 584 families were from Korea. Significant differences were found in the use of ICT by Korean and American families although the source of this difference was not clearly identified in this study. Three clusters of families were identified based on their use of devices and services. These were labeled as; 'The Tech Savvy', 'The Wireless Users', 'The In-betweeners', 'The Wired', and 'The Just Mobile'. 'The Tech Savvy' used the greatest variety of ICT technologies and 'The Wired' used the fewest. Other clusters fell in the middle with families seemingly using the devices which met their particular needs. Two factors related to ICT integration into the family were identified. These were related to family intimacy and family relationship maintenance. The family cluster identified as 'Tech Savvy' made significantly greater use of ICT in these relationships and 'The Wired' made the least use of ICT in these areas. The other clusters tended to be between the two ends and tended not to be significantly different from each other in their use of ICT. Finally, models for ICT use by families showed that demographics, nation of origin, types of devices and services used, and attitude and interest in ICT all had a significant impact.

A case study on the economic feasibility of different patterns of green care and healing complexes

  • Koo, Seungmo;Kim, Dae Sik;Koo, Hee Dong;Lee, Han Joon;Park, Bum Jin;Kim, Kyoung-Chan
    • Korean Journal of Agricultural Science
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    • v.44 no.3
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    • pp.451-461
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    • 2017
  • Korean agriculture has recently focused on the 6th dimension of industrialization, which includes the functions of healing and care. The green care and healing business is one of the most representative models, satisfying modern consumers' needs for care or healing in rural agricultural environments. Many studies have shown physical and social benefits from green care and healing, but studies regarding economic performance are rarely found. The present study aimed to analyze the economic feasibility of different green care and healing farm complexes proposed in recent domestic research, with various possible combinations of business scenarios. The results show that most of the scenarios are economically feasible as B/C (benefit-cost ratio) and IRR (internal rate of return) are 1.19 and 8.53%, respectively, under scenario 1. This study also performed a break-even analysis for providing more flexible decision-making information. Overall, scenario 1 from green care and healing site and scenario 4 from green care and healing cluster are found to be superior to the other scenarios in terms of B/C and IRR. The scenarios in this study reflect the domestic farms or complexes which have similar functions of care or healing. Therefore, the results of this study provide information on practical policies and business implications in making decisions on the specific size and operational patterns when adopting green care and healing complexes by central or local governments and private sectors in the future.

Metabolic Risk Profile and Cancer in Korean Men and Women

  • Ko, Seulki;Yoon, Seok-Jun;Kim, Dongwoo;Kim, A-Rim;Kim, Eun-Jung;Seo, Hye-Young
    • Journal of Preventive Medicine and Public Health
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    • v.49 no.3
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    • pp.143-152
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    • 2016
  • Objectives: Metabolic syndrome is a cluster of risk factors for type 2 diabetes mellitus and cardiovascular disease. Associations between metabolic syndrome and several types of cancer have recently been documented. Methods: We analyzed the sample cohort data from the Korean National Health Insurance Service from 2002, with a follow-up period extending to 2013. The cohort data included 99 565 individuals who participated in the health examination program and whose data were therefore present in the cohort database. The metabolic risk profile of each participant was assessed based on obesity, high serum glucose and total cholesterol levels, and high blood pressure. The occurrence of cancer was identified using Korean National Health Insurance claims data. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models, adjusting for age group, smoking status, alcohol intake, and regular exercise. Results: A total of 5937 cases of cancer occurred during a mean follow-up period of 10.4 years. In men with a high-risk metabolic profile, the risk of colon cancer was elevated (HR, 1.40; 95% CI, 1.14 to 1.71). In women, a high-risk metabolic profile was associated with a significantly increased risk of gallbladder and biliary tract cancer (HR, 2.05; 95% CI, 1.24 to 3.42). Non-significantly increased risks were observed in men for pharynx, larynx, rectum, and kidney cancer, and in women for colon, liver, breast, and ovarian cancer. Conclusions: The findings of this study support the previously suggested association between metabolic syndrome and the risk of several cancers. A high-risk metabolic profile may be an important risk factor for colon cancer in Korean men and gallbladder and biliary tract cancer in Korean women.

Comparison analysis of big data integration models (빅데이터 통합모형 비교분석)

  • Jung, Byung Ho;Lim, Dong Hoon
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.4
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    • pp.755-768
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    • 2017
  • As Big Data becomes the core of the fourth industrial revolution, big data-based processing and analysis capabilities are expected to influence the company's future competitiveness. Comparative studies of RHadoop and RHIPE that integrate R and Hadoop environment, have not been discussed by many researchers although RHadoop and RHIPE have been discussed separately. In this paper, we constructed big data platforms such as RHadoop and RHIPE applicable to large scale data and implemented the machine learning algorithms such as multiple regression and logistic regression based on MapReduce framework. We conducted a study on performance and scalability with those implementations for various sample sizes of actual data and simulated data. The experiments demonstrated that our RHadoop and RHIPE can scale well and efficiently process large data sets on commodity hardware. We showed RHIPE is faster than RHadoop in almost all the data generally.

Verification Test of High-activity SMEs Using Technology Appraisal Items (기술력 평가항목을 이용한 고활동성 중소기업 판별)

  • Lee, Jun-won
    • Journal of Technology Innovation
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    • v.28 no.1
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    • pp.31-52
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    • 2020
  • This study was started to verify the preliminary(Ex-ante) discrimination power of the firm's high-activity using the 'Forward-looking' oriented technology appraisal model used in technology financing. The analytical firms are classified into the industry (manufacturing / non-manufacturing) and the age of company (initial / non-initial). High-activity SMEs are defined as those that achieve at least twice the average asset turnover ratio of the cluster. As a result of the discriminant model by applying C5.0 method, which is one of decision tree models, classification accuracy is more than 99% in all industries and the age of company, and it is confirmed that the discriminant power of the model is stable. As a result, the management expertise, capital involvement and funding capacity items were identified as a critical variable for the high-activity SMEs. In addition, the technology management capability and technology life cycle were also confirmed to be the items to determine high-activity SMEs in the manufacturing industry. Through this, it was possible to confirm some possibility of prior discrimination and policy utilization of high-activity SMEs by using technology appraisal items.

Data Augmentation Method for Deep Learning based Medical Image Segmentation Model (딥러닝 기반의 대퇴골 영역 분할을 위한 훈련 데이터 증강 연구)

  • Choi, Gyujin;Shin, Jooyeon;Kyung, Joohyun;Kyung, Minho;Lee, Yunjin
    • Journal of the Korea Computer Graphics Society
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    • v.25 no.3
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    • pp.123-131
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    • 2019
  • In this study, we modified CT images of femoral head in consideration of anatomically meaningful structure, proposing the method to augment the training data of convolution Neural network for segmentation of femur mesh model. First, the femur mesh model is obtained from the CT image. Then divide the mesh model into meaningful parts by using cluster analysis on geometric characteristic of mesh surface. Finally, transform the segments by using an appropriate mesh deformation algorithm, then create new CT images by warping CT images accordingly. Deep learning models using the data enhancement methods of this study show better image division performance compared to data augmentation methods which have been commonly used, such as geometric conversion or color conversion.

The Moderating Effect of Learning Strategy Levels on the Relationship between Academic Grit and Career Development Competence Perceived by High School Students (고등학생이 인식하는 학업적 그릿과 진로개발역량 관계에서 학습전략 수준의 조절효과)

  • Kim, Kyu Tae
    • Journal of Digital Convergence
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    • v.17 no.6
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    • pp.27-33
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    • 2019
  • The purpose of this study was to explore the moderating effect of learning strategy levels on the relationship between academic grit and career development competence perceived by high school students. The sample for this study comprised 573 high school students, and data analysis was conducted mainly using reliability analysis, correlation analysis, K-mean cluster analysis, hierarchical regression analysis. The results of the study showed that the learning strategy levels moderated the relationship between academic grit and career development competence. This study suggest it is necessary to provide grit enhancement programs coupled with learning strategy levels in order to facilitate career development competence. The future studies need to explore the literature review for logical relationship between academic grit and career development competence, the qualitative approach for drawing on the theoretical models among the related variables, and the relational research to explore mediating or moderating effect of the individual backgrounds and related variables on the relationship between academic grit and career development competence.