• 제목/요약/키워드: Weighted Support

검색결과 204건 처리시간 0.026초

YCbCr 컬러공간에서 구성성분간의 상관관계를 이용한 축소된 채도 정보의 다중 모드 재구성 (Multi-Mode Reconstruction of Subsampled Chrominance Information using Inter-Component Correlation in YCbCr Colorspace)

  • 김영주
    • 한국콘텐츠학회논문지
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    • 제8권2호
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    • pp.74-82
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    • 2008
  • 본 논문은 압축된 영상의 복원 과정에서 축소된 채도 정보를 휘도와 채도 성분의 상관관계를 이용하여 효율적으로 재구성하는 기법들에 대해 살펴보고, 기존에 계산 복잡도 측면에서 효율성을 보인 적응적 가중치를 가진 2차원 선형 보간법에 대해 문제점을 분석하였다. 그리고 본 논문은 2차원 선형 보간법에 대해 영상의 공간 주파수 분포를 고려하지 않는 문제점을 개선하고 저성능 시스템에 적용하기 위해 휘도 성분의 에지 반응도에 따라 계산 복잡도가 서로 다른 재구성 기법을 적용하는 다중 모드 재구성 기법을 제안하였으며, 임베디드 시스템 개발 플랫폼에서의 성능 평가 실험을 통해 유사한 수준의 복원 영상의 품질을 지원하면서 채도 재구성을 위한 계산 시간을 상대적으로 줄이고 있음을 확인하였다.

BeanFS: 대규모 이메일 서비스를 위한 분산 파일 시스템 (BeanFS: A Distributed File System for Large-scale E-mail Services)

  • 정욱;이대우;박은지;이영재;김상훈;김진수;김태웅;전성원
    • 한국정보과학회논문지:시스템및이론
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    • 제36권4호
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    • pp.247-258
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    • 2009
  • 저가의 하드웨어를 이용하는 분산 파일 시스템은 대용량의 저장 장치를 경제적으로 제공해주는 해법으로 많은 인터넷 서비스 업체에 의해 주목받고 있다. 본 논문에서는 대규모 이메일 서비스를 위한 분산 파일 시스템인 BeanFS의 설계와 구현에 대해 소개한다. BeanFS는 다음과 같이 이메일 서비스에 최적화되었다. 첫째, 이메일 서비스에서 이용되는 작고 많은 파일을 효과적으로 처리하기 위해서, 볼륨 기반의 복제 기법을 도입하여 중앙 서버의 병목현상을 완화시킨다. 둘째, 이메일 메시지의 단순한 접근 패턴을 고려하여 일관성 유지 기법을 경량화시킨다. 셋째, 재복제시에 발생하는 오버헤드를 줄이기 위해 일시적인 장애를 영구적인 장애와 분리하여 대처한다.

생물학적으로 의미 있는 특질에 기반한 베이지안 네트웍을 이용한 microRNA의 예측 (cmicroRNA prediction using Bayesian network with biologically relevant feature set)

  • 남진우;박종선;장병탁
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2006년도 가을 학술발표논문집 Vol.33 No.2 (A)
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    • pp.53-58
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    • 2006
  • MicroRNA (miRNA)는 약 22 nt의 작은 RNA 조각으로 이루어져 있으며 stem-loop 구조의 precursor 형태에서 최종적으로 만들어 진다. miRNA는 mRNA의 3‘UTR에 상보적으로 결합하여 유전자의 발현을 억제하거나 mRNA의 분해를 촉진한다. miRNA를 동정하기 위한 실험적인 방법은 조직 특이적인 발현, 적은 발현양 때문에 방법상 한계를 가지고 있다. 이러한 한계는 컴퓨터를 이용한 방법으로 어느 정도 해결될 수 있다. 하지만 miRNA의 서열상의 낮은 보존성은 homology를 기반으로 한 예측을 어렵게 한다. 또한 기계학습 방법인 support vector machine (SVM) 이나 naive bayes가 적용되었지만, 생물학적인 의미를 해석할 수 있는 generative model을 제시해 주지 못했다. 본 연구에서는 우수한 miRNA 예측을 보일 뿐만 아니라 학습된 모델로부터 생물학적인 지식을 얻을 수 있는 Bayesian network을 적용한다. 이를 위해서는 생물학적으로 의미 있는 특질들의 선택이 중요하다. 여기서는 position weighted matrix (PWM)과 Markov chain probability (MCP), Loop 크기, Bulge 수, spectrum, free energy profile 등을 특질로서 선택한 후 Information gain의 특질 선택법을 통해 예측에 기여도가 높은 특질 25개 와 27개를 최종적으로 선택하였다. 이로부터 Bayesian network을 학습한 후 miRNA의 예측 성능을 10 fold cross-validation으로 확인하였다. 그 결과 pre-/mature miRNA 각 각에 대한 예측 accuracy가 99.99% 100.00%를 보여, SVM이나 naive bayes 방법보다 높은 결과를 보였으며, 학습된 Bayesian network으로부터 이전 연구 결과와 일치하는 pre-miRNA 상의 의존관계를 분석할 수 있었다.

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Analysis of 3D Building Construction Applications in Augmented Reality

  • Khan, Humera Mehfooz;Waseemullah, Waseemullah;Bhutto, Muhammad Aslam;Khan, Shariq Mahmood;Baig, Mirza Adnan
    • International Journal of Computer Science & Network Security
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    • 제22권10호
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    • pp.340-346
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    • 2022
  • Construction industry is considered as one of the oldest industries in the world since human came into being and the need of their own space is realized. All this led to make the world a space of many beautiful constructive ventures. As per the requirements of today's world, every industry is recognizing the need for use and adoption of modern as well as innovative technologies due to their benefits and timely production. Now construction industry has also started adopting the use of modern and innovative technologies during their projects but still the rate of adoption is so slow. From design to completion, construction projects take a lot to manage for which technology based solutions have continuously been proposed. These include Computer Aided Design (CAD), building information modeling (BIM) and cloud computing have been proved to be much successful until now. The construction projects are high budgeted, and direly require timely and successful completion with quality, resource and other constraints. So, the researchers observe the need of more clear and technology based communication between the construction projects and its constructors and other stakeholders is required before and during the construction to take timely precautions for expected issues. This study has analyzed the use of Augmented Reality (AR) technology adopting GammaAR, and ARki applications in construction industry. It has been found that both applications are light-weighted, upgradable, provide offline availability and collaborative environment as well as fulfil most of the requirements of the construction industry except the cost. These applications also support different screen size for better visualization and deep understanding. Both applications are analyzed, based on construction's application requirements, usability of AR and ratings of applications user collected from application's platform. The purpose of this research is to provide a detail insight of construction applications which are using AR to facilitate both the future developers and consumers.

한국의 그린 비즈니스/IT 실태분석을 통한 추진전략 우선순위 도출에 관한 연구 (Development of Korean Green Business/IT Strategies Based on Priority Analysis)

  • 김재경;최주철;최일영
    • Asia pacific journal of information systems
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    • 제20권3호
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    • pp.191-204
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    • 2010
  • Recently, the CO2 emission and energy consumption have become critical global issues to decide the future of nations. Especially, the spread of IT products and the increased use of internet and web applications result in the energy consumption and CO2 emission of IT industry though information technologies drive global economic growth. EU, the United States, Japan and other developed countries are using IT related environmental regulations such as WEEE(Waste Electrical and Electronic Equipment), RoHS(Restriction of the use of Certain Hazardous Substance), REACH(Registration, Evaluation, Authorization and Restriction of CHemicals) and EuP(Energy using Product), and have established systematic green business/IT strategies to enhance the competitiveness of IT industry. For example, the Japan government proposed the "Green IT initiative" for being compatible with economic growth and environmental protection. Not only energy saving technologies but energy saving systems have been developed for accomplishing sustainable development. Korea's CO2 emission and energy consumption continuously have grown at comparatively high rates. They are related to its industrial structure depending on high energy-consuming industries such as iron and steel Industry, automotive industry, shipbuilding industry, semiconductor industry, and so on. In particular, export proportion of IT manufacturing is quite high in Korea. For example, the global market share of the semiconductor such as DRAM was about 80% in 2008. Accordingly, Korea needs to establish a systematic strategy to respond to the global environmental regulations and to maintain competitiveness in the IT industry. However, green competitiveness of Korea ranked 11th among 15 major countries and R&D budget for green technology is not large enough to develop energy-saving technologies for infrastructure and value chain of low-carbon society though that grows at high rates. Moreover, there are no concrete action plans in Korea. This research aims to deduce the priorities of the Korean green business/IT strategies to use multi attribute weighted average method. We selected a panel of 19 experts who work at the green business related firms such as HP, IBM, Fujitsu and so on, and selected six assessment indices such as the urgency of the technology development, the technology gap between Korea and the developed countries, the effect of import substitution, the spillover effect of technology, the market growth, and the export potential of the package or stand-alone products by existing literature review. We submitted questionnaires at approximately weekly intervals to them for priorities of the green business/IT strategies. The strategies broadly classify as follows. The first strategy which consists of the green business/IT policy and standardization, process and performance management and IT industry and legislative alignment relates to government's role in the green economy. The second strategy relates to IT to support environment sustainability such as the travel and ways of working management, printer output and recycling, intelligent building, printer rationalization and collaboration and connectivity. The last strategy relates to green IT systems, services and usage such as the data center consolidation and energy management, hardware recycle decommission, server and storage virtualization, device power management, and service supplier management. All the questionnaires were assessed via a five-point Likert scale ranging from "very little" to "very large." Our findings show that the IT to support environment sustainability is prior to the other strategies. In detail, the green business /IT policy and standardization is the most important in the government's role. The strategies of intelligent building and the travel and ways of working management are prior to the others for supporting environment sustainability. Finally, the strategies for the data center consolidation and energy management and server and storage virtualization have the huge influence for green IT systems, services and usage This research results the following implications. The amount of energy consumption and CO2 emissions of IT equipment including electrical business equipment will need to be clearly indicated in order to manage the effect of green business/IT strategy. And it is necessary to develop tools that measure the performance of green business/IT by each step. Additionally, intelligent building could grow up in energy-saving, growth of low carbon and related industries together. It is necessary to expand the affect of virtualization though adjusting and controlling the relationship between the management teams.

한국 아동 미술치료중재 프로그램 연구 동향 (The Trends of Research on Children Art Therapy Program Intervention in Korea)

  • 김원순
    • 한국임상보건과학회지
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    • 제5권1호
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    • pp.790-802
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    • 2017
  • Purpose. This study was designed to analyze recent trends in Children Art Therapy Program Intervention research in Korea and suggest future research directions in this area. Methods. Studies(29) selected from http://www.riss4u.net for last 15 year were used. They were analyzed by publication type, field and design of the study, study participants and outcome variables used in intervention studies. Results. 1. As for academic field, there are 15 art therapy academic journals(51.72%), which made up the largest proportion. 2. As for subjects of the study, there are 17 articles of Elementary (58.6%) education, which made up the largest proportion. As for the subjects of sex, 8 articles (27.59%) are for male students, 7 (24.14%) articles are for female students and 14 articles (48.28.%) are for both male and female students. 3. As for 7 articles of Art therapy(24.14%), 7 articles of Group Art therapy (24.14%) made up the largest proporton 4. As for the intervention study method according to the subjects of suicide intervention program, there are 15 articles of monoclonal Pre and post design (51.72%),which made up the largest proportion. 5. As for the sample size, there were 16.79 persons in the treatment group on average, 13.28 persons in the control group have average and the total persons were 10 on average. The treatment period was 12 weeks on average and the average number of treatment times was 18. The places of treatment were 3 schools (10.38%), which made up the largest proportion. 19. The results of the experimental study support the research hypothesis of all 29 programs. Conclusions. As the above, the studies on the art therapy intervention program for children are increasing but the subjects are overly weighted toward elementary school students. Although the content of the art therapy intervention program was varied, it was found that the development of the program using various art media which can induce the motivation of the child was lacking. In addition, the place of experimental mediation was concentrated on psychology center as 12(41.38%), indicating that there are not enough places to connect with community organizations such as schools and hospitals. The variables of experimental study were focused on psychological variables and it was found that there were insufficient application of various variables including coping method, social support, and physiological variables.

아동의 간호중재 연구현황 및 간호중재 효과에 대한 메타 분석 (The Metaanalysis of Trends and Contents of Child Nursing Intervention Research)

  • 김은주;조경미
    • Child Health Nursing Research
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    • 제6권2호
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    • pp.119-131
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    • 2000
  • The purpose of this study was to identify the trends and contents of intervention towards children using meta analysis, to support the basis for using in the field and research method about nursing intervention. We used 27 materials which was reported from 1970 to August, 1999 : dissertation study and Korean Nurses' Academic society Journals, the Journal of Korean Academic society of Adult Nursing, The Korea Journal of Maternal and Child Health Nursing. The types of intervention we used came from 3 different researchers. Snyder showed cognitive, movement, social sensory intervention. McCloskey & Bulechek categorized as the following : self-care assistance, acute care management, life-style alteration, health promotion, life support intervention, Craft & Denehy classified psychosocial intervention and biophysiological intervention. Some findings are summarized as follow : Out of the 27 researches sensory intervention had the most in there thesis, recently cognitive intervention research has a tendency to increase. 18 researches has acute care management in there theses, and health promotion was found the least. Out of the 27 thesis 15 thesis was classified as biophysiological intervention and 12 had psychosocial. 27 thesis had 11 types of interventions which originally was categorized by Snyder, therefore sensory intervention thesis had the most. 11 types of intervention which originally was classified by McClosky & Bulechek, teaching and information had the most out of acute care management. Out of 27 thesis, 14 had dealt with newborns, especially newborns with sensory intervention. Therefore school age and above had cognitive intervention which was used for teaching and information. Infants, preschool, schoolage children received acute care management the most, health promotion intervention was used towards adolescences. Depending on the characteristics of dependent variables, it was analysed using meta however 17 thesis are possible except primary experimental research. Mean effect size comparison by Snyder classification, cognitive intervention was the largest mean(1.51), sensory intervention was larger(0.71) also, movement intervention was in the middle(0.56) as shown. Comparison done by McClosky & Bulechek, the intervention leading to life style alteration was the largest mean(1.97), teaching was used the most. Comparison by Craft & Denehy classification, psychosocial intervention was larger(1.15) than biophysiological intervention (0.67). The result of nursing intervention through age classification, the largest weighted mean effect size in the research was towards infants and neonates. The research which was focused on nursing intervention, has important meaning in nursing practice and knowledge development. When we know that children's nursing intervention is necessary and overcome our biased view, efficiency of children's nursing intervention are increased and professionalized. Therefore results will be important basic data to guide a development of child nursing intervention & classification.

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Development and Validation of MRI-Based Radiomics Models for Diagnosing Juvenile Myoclonic Epilepsy

  • Kyung Min Kim;Heewon Hwang;Beomseok Sohn;Kisung Park;Kyunghwa Han;Sung Soo Ahn;Wonwoo Lee;Min Kyung Chu;Kyoung Heo;Seung-Koo Lee
    • Korean Journal of Radiology
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    • 제23권12호
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    • pp.1281-1289
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    • 2022
  • Objective: Radiomic modeling using multiple regions of interest in MRI of the brain to diagnose juvenile myoclonic epilepsy (JME) has not yet been investigated. This study aimed to develop and validate radiomics prediction models to distinguish patients with JME from healthy controls (HCs), and to evaluate the feasibility of a radiomics approach using MRI for diagnosing JME. Materials and Methods: A total of 97 JME patients (25.6 ± 8.5 years; female, 45.5%) and 32 HCs (28.9 ± 11.4 years; female, 50.0%) were randomly split (7:3 ratio) into a training (n = 90) and a test set (n = 39) group. Radiomic features were extracted from 22 regions of interest in the brain using the T1-weighted MRI based on clinical evidence. Predictive models were trained using seven modeling methods, including a light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, with radiomics features in the training set. The performance of the models was validated and compared to the test set. The model with the highest area under the receiver operating curve (AUROC) was chosen, and important features in the model were identified. Results: The seven tested radiomics models, including light gradient boosting machine, support vector classifier, random forest, logistic regression, extreme gradient boosting, gradient boosting machine, and decision tree, showed AUROC values of 0.817, 0.807, 0.783, 0.779, 0.767, 0.762, and 0.672, respectively. The light gradient boosting machine with the highest AUROC, albeit without statistically significant differences from the other models in pairwise comparisons, had accuracy, precision, recall, and F1 scores of 0.795, 0.818, 0.931, and 0.871, respectively. Radiomic features, including the putamen and ventral diencephalon, were ranked as the most important for suggesting JME. Conclusion: Radiomic models using MRI were able to differentiate JME from HCs.

멀티 모달리티 데이터 활용을 통한 골다공증 단계 다중 분류 시스템 개발: 합성곱 신경망 기반의 딥러닝 적용 (Multi-classification of Osteoporosis Grading Stages Using Abdominal Computed Tomography with Clinical Variables : Application of Deep Learning with a Convolutional Neural Network)

  • 하태준;김희상;강성욱;이두희;김우진;문기원;최현수;김정현;김윤;박소현;박상원
    • 한국방사선학회논문지
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    • 제18권3호
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    • pp.187-201
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    • 2024
  • 골다공증은 전 세계적으로 주요한 건강 문제임에도 불구하고, 골절 발생 전까지 쉽게 발견되지 않는 단점을 가지고 있습니다. 본 연구에서는 골다공증 조기 발견 능력 향상을 위해, 복부 컴퓨터 단층 촬영(Computed Tomography, CT) 영상을 활용하여 정상-골감소증-골다공증으로 구분되는 골다공증 단계를 체계적으로 분류할 수 있는 딥러닝(Deep learning, DL) 시스템을 개발하였습니다. 총 3,012개의 조영제 향상 복부 CT 영상과 개별 환자의 이중 에너지 X선 흡수 계측법(Dual-Energy X-ray Absorptiometry, DXA)으로 얻은 T-점수를 활용하여 딥러닝 모델 개발을 수행하였습니다. 모든 딥러닝 모델은 비정형 이미지 데이터, 정형 인구 통계 정보 및 비정형 영상 데이터와 정형 데이터를 동시에 활용하는 다중 모달 방법에 각각 모델 구현을 실현하였으며, 모든 환자들은 T-점수를 통해 정상, 골감소증 및 골다공증 그룹으로 분류되었습니다. 가장 높은 정확도를 갖는 모델 우수성은 비정형-정형 결합 데이터 모델이 가장 우수하였으며, 수신자 조작 특성 곡선 아래 면적이 0.94와 정확도가 0.80를 제시하였습니다. 구현된 딥러닝 모델은 그라디언트 가중치 클래스 활성화 매핑(Gradient-weighted Class Activation Mapping, Grad-CAM)을 통해 해석되어 이미지 내에서 임상적으로 관련된 특징을 강조했고, 대퇴 경부가 골다공증을 통해 골절 발생이 높은 위험 부위임을 밝혔습니다. 이 연구는 DL이 임상 데이터에서 골다공증 단계를 정확하게 식별할 수 있음을 보여주며, 조기에 골다공증을 탐지하고 적절한 치료로 골절 위험을 줄일 수 있는 복부 컴퓨터 단층 촬영 영상의 잠재력을 제시할 수 있습니다.

특허권 취득 공시와 한국유가증권시장의 실시간 정보효율성에 관한 연구 (Real-time information effect of patent listing disclosure)

  • 이종욱;김종윤
    • 경영과정보연구
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    • 제35권3호
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    • pp.195-212
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    • 2016
  • 이 연구는 1분 단위의 거래량가중평균가격(VWAP)을 이용하여 한국 유가증권시장에 상장된 기업을 대상으로 특허권 취득 공시의 초과수익률 및 누적초과수익률 및 이벤트 차익거래 전략을 이용하였을 경우의 실현수익률을 분석하였다. 이상의 연구목표에 대한 결과는 다음과 같다. 첫째, 연구결과 특허권 취득공시 후 1분 뒤 평균 0.92%의 누적초과수익률이 유의하게 발생하여 한국유가증권시장이 실시간으로 효율적인 준강형 시장임을 확인하였다. 또한 기업규모(size)에 따라 3개 패널로 분류하여 연구한 결과, 소형주의 초과수익률이 중형주보다 적어 한국유가증권시장에서 규모효과가 더 이상 존재하지 않는다는 최근의 자산가격결정모형과 관련한 연구결과를 부분적으로 지지하였다. 둘째, 공시 시점에 매입하는 이벤트 차익거래 전략의 실현수익은 마켓 메이킹 전략이 가장 우수한 실현수익률을 보였으며 시장가로 매수 매도하는 전략은 음(-)의 수익률을 실현하였다. 이와 같은 결과는 즉각적으로 시장가 매수주문을 하는 전략보다 시장가주문과 지정가주문의 유입률, 주문의 취소율과 같은 주문흐름(order flow)과 체결확률을 고려한 마켓 메이킹 전략을 병행할 때 실현수익률이 향상될 수 있음을 시사한다.

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