• 제목/요약/키워드: Data Asset

검색결과 841건 처리시간 0.023초

응집물질물리분야 연구데이터 관리 방안 연구 (A Study on the Research Data Management Methods for the Condensed Matter Physics)

  • 김성욱;김선태
    • 정보관리학회지
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    • 제37권3호
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    • pp.77-106
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    • 2020
  • 본 연구에서는 학제 간 연구가 가장 활발하고 응용가능성이 가장 높은 응집물질물리분야의 연구데이터를 체계적으로 관리하기 위한 개선방안을 제안하였다. 이를 위해 연구데이터 관리 도구인 Data Asset Framework (DAF)와 데이터 공유 및 재사용을 위한 FAIR원칙을 바탕으로 설문 내용을 구성하여 14명의 연구자를 대상으로 응집물질물리분야의 연구데이터 관리 현황을 수집하였다. 수집된 데이터는 설문에 응답한 연구자의 특성 및 기초정보, 데이터 보존 및 관리, 데이터 공유 및 접근에 관한 데이터로 구성되었다. 수집된 설문결과를 분석하여 응집물질물리분야의 연구데이터 특징과 데이터 수집과 생산, 데이터 보존과 관리, 데이터 공유 및 접근에 대한 9가지 문제점을 도출하였으며, 각 측면에서 도출된 문제점에 대한 개선방안을 제언하였다.

디지털 데이터 가치의 정량적 측정에 대한 개념적 연구 (A Conceptual Study on the Quantitative Measurement of Digital Data Value)

  • 최성호;이상곤
    • 한국IT서비스학회지
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    • 제21권5호
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    • pp.1-13
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    • 2022
  • With the rapid development of computer technology and communication networks in modern society, human economic activities in the almost every field of our society depend on various electronic devices. The huge amount of digital data generated in these circumstances is refined by technologies such as artificial intelligence and big data, and its value has become larger and larger. However, until now, it is the reality that the digital data has not been clearly defined as an economic asset, and the institutional criteria for expressing its value are unclear. Therefore, this study organizes the definition and characteristics of digital data, and examines the matters to be considered when considering digital data in terms of accounting assets. In addition, a method that can objectively measure the value of digital data was presented as a quantitative calculation model considering the time value of profits and costs.

베이비붐세대 가계의 자산.부채상태 분석: 2006년과 2011년 비교 (Asset-Liability Analysis of Baby-Boomer Households: Comparison of year 2006 and 2011)

  • 차경욱
    • 가족자원경영과 정책
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    • 제16권3호
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    • pp.153-176
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    • 2012
  • This study gives an account of the state of baby-boomer households in regard to assets and liabilities utilizing the 2006 Household Asset Survey and the 2011 Survey of Household Finances. Using the data gathered from each year, this study examined the proportion of households who had each type of asset and liability, and the amount of them. This study also compared the amount of assets and liabilities of baby-boomer households with those of non baby-boomer households in 2006 and 2011 respectively. Finally, this study examined the amount of change and composition ratio of assets and liabilities of baby-boomer households between 2006 and 2011. Selected financial ratios were also presented for both years. Major findings are as follows. The average asset amount for baby-boomer households was approximately 296 million in 2006 and 392 million in 2011. Of total assets, 78% and 76.5% were real assets in 2006 and 2011 respectively. The average financial assets of 2006 baby-boomer households were approximately 66 thousand and the average amount of debt was 42 thousand. For 2011 baby-boomer households, the average amount of financial assets was 92 thousand and the average amount of debt was 73 thousand. Results from the 2011 survey showed that baby-boomer households had a significantly higher proportion of total assets, total debt, and net worth than non baby-boomer households. The proportion of savings, saving insurance, stocks, and mutual funds were significantly higher for baby-boomer households than non baby-boomer households in 2011. In regard to financial ratios, the emergency fund index and debt burden index were appropriate to the guidelines of asset quality, although the propensity to investment indexes were not.

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기계학습을 활용한 상품자산 투자모델에 관한 연구 (A Study on Commodity Asset Investment Model Based on Machine Learning Technique)

  • 송진호;최흥식;김선웅
    • 지능정보연구
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    • 제23권4호
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    • pp.127-146
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    • 2017
  • 상품자산(Commodity Asset)은 주식, 채권과 같은 전통자산의 포트폴리오의 안정성을 높이기 위한 대체투자자산으로 자산배분의 형태로 투자되고 있지만 주식이나 채권 자산에 비해 자산배분에 대한 모델이나 투자전략에 대한 연구가 부족한 실정이다. 최근 발전한 기계학습(Machine Learning) 연구는 증권시장의 투자부분에서 적극적으로 활용되고 있는데, 기존 투자모델의 한계점을 개선하는 좋은 성과를 나타내고 있다. 본 연구는 이러한 기계학습의 한 기법인 SVM(Support Vector Machine)을 이용하여 상품자산에 투자하는 모델을 제안하고자 한다. 기계학습을 활용한 상품자산에 관한 기존 연구는 주로 상품가격의 예측을 목적으로 수행되었고 상품을 투자자산으로 자산배분에 관한 연구는 찾기 힘들었다. SVM을 통한 예측대상은 투자 가능한 대표적인 4개의 상품지수(Commodity Index)인 골드만삭스 상품지수, 다우존스 UBS 상품지수, 톰슨로이터 CRB상품지수, 로저스 인터내셔날 상품지수와 대표적인 상품선물(Commodity Futures)로 구성된 포트폴리오 그리고 개별 상품선물이다. 개별상품은 에너지, 농산물, 금속 상품에서 대표적인 상품인 원유와 천연가스, 옥수수와 밀, 금과 은을 이용하였다. 상품자산은 전반적인 경제활동 영역에 영향을 받기 때문에 거시경제지표를 통하여 투자모델을 설정하였다. 주가지수, 무역지표, 고용지표, 경기선행지표 등 19가지의 경제지표를 이용하여 상품지수와 상품선물의 등락을 예측하여 투자성과를 예측하는 연구를 수행한 결과, 투자모델을 활용하여 상품선물을 리밸런싱(Rebalancing)하는 포트폴리오가 가장 우수한 성과를 나타냈다. 또한, 기존의 대표적인 상품지수에 투자하는 것 보다 상품선물로 구성된 포트폴리오에 투자하는 것이 우수한 성과를 얻었으며 상품선물 중에서도 에너지 섹터의 선물을 제외한 포트폴리오의 성과가 더 향상된 성과를 나타남을 증명하였다. 본 연구에서는 포트폴리오 성과 향상을 위해 기존에 널리 알려진 전통적 주식, 채권, 현금 포트폴리오에 상품자산을 배분하고자 할 때 투자대상은 상품지수에 투자하는 것이 아닌 개별 상품선물을 선정하여 자체적 상품선물 포트폴리오를 구성하고 그 방법으로는 기간마다 강세가 예측되는 개별 선물만을 골라서 포트폴리오를 재구성하는 것이 효과적인 투자모델이라는 것을 제안한다.

e-Commerce 상에서 빅데이터 서비스제공 기대가 이용의도에 미치는 영향 연구 (A Study on the Influence of Expectation of Big Data Service on e-Commerce on the Use Intension)

  • 김영국;염수환;김진형;배석민;정재진
    • 한국멀티미디어학회논문지
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    • 제22권9호
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    • pp.1132-1139
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    • 2019
  • Big data is prominently used as a prediction method in achieving a goal, because it can analyze the regularities to predict future results from a vast amount of past data. Furthermore, big data has huge influence in very diverse academic fields. On such awareness, this study analyzed the regular effect of e-Commerce usefulness from the effects which expectations on big-data service affect the usage purpose of e-Commerce usefulness. This study categorized e-Commerce usefulness into quality recognition, service, and ease, and studied how each category works between the relationship of big-data service expectation and the use intention.

민간병원의 유동성 관련요인 분석 (Liquidity Determinants of Private Hospitals in Korea)

  • 최만규;이윤석;이윤현
    • 보건행정학회지
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    • 제12권4호
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    • pp.1-17
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    • 2002
  • This study was attempted to identify the liquidity trends and determinants of private hospitals in Korea different. Data used in this study were collected from 98 hospitals with complete general data of present conditions as well as financial statements(balance sheets, income statements). They were chosen from hospitals that passed the standardization audit undertaken by the Korean Hospital Association from 1996 to 2000 for the purpose of accrediting training hospitals. The dependent variables in this study were used current ration and quick ratio as a proxy indicator for liquidity. The independent variables were ownership type, hospital type, location, bed size, period of establishment, short-term liabilities to total assets, long-term liabilities to total assets, borrowings to total assets, fixed asset ration, net profit to total assets, operating margin to gross revenue, growth rate of net worth to total assets, total asset turnover, and business risk(volatility of profit). The major findings of this study were as follows. Trends of liquidity(current ratio, quick ratio) had been continuously decreased. Especially, There were very distinct decreasing trends of personal hospitals and less than 300beds, which weakened liquidity. The factors had significant effect on current ratio were short-term debt to total assets(-), fixed asset ratio(-), business risk(+). High short-term debt to total assets, high fixed asset ratio and high business risk significantly decreased in liquidity. The factors that significantly affected on quick ratio were short-term debt to total assets(-), borrowings to total assets(+), fixed asset ratio(-), business risk(+).

Jensen's Alpha Estimation Models in Capital Asset Pricing Model

  • Phuoc, Le Tan
    • The Journal of Asian Finance, Economics and Business
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    • 제5권3호
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    • pp.19-29
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    • 2018
  • This research examined the alternatives of Jensen's alpha (α) estimation models in the Capital Asset Pricing Model, discussed by Treynor (1961), Sharpe (1964), and Lintner (1965), using the robust maximum likelihood type m-estimator (MM estimator) and Bayes estimator with conjugate prior. According to finance literature and practices, alpha has often been estimated using ordinary least square (OLS) regression method and monthly return data set. A sample of 50 securities is randomly selected from the list of the S&P 500 index. Their daily and monthly returns were collected over a period of the last five years. This research showed that the robust MM estimator performed well better than the OLS and Bayes estimators in terms of efficiency. The Bayes estimator did not perform better than the OLS estimator as expected. Interestingly, we also found that daily return data set would give more accurate alpha estimation than monthly return data set in all three MM, OLS, and Bayes estimators. We also proposed an alternative market efficiency test with the hypothesis testing Ho: α = 0 and was able to prove the S&P 500 index is efficient, but not perfect. More important, those findings above are checked with and validated by Jackknife resampling results.

스마트 팩토리 환경에서 제조 데이터 수집을 위한 AAS 설계 (ASS Design to Collect Manufacturing Data in Smart Factory Environment)

  • 정진욱;진교홍
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2022년도 추계학술대회
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    • pp.204-206
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    • 2022
  • 스마트 팩토리(Smart Factory) 고도화의 핵심으로 평가되는 디지털 트윈(Digital Twin)은 현실 세계의 자산과 동일한 속성 및 기능을 가지는 디지털 복제본을 가상의 세계에 구현하는 기술이다. 디지털 트윈 기술이 적용된 스마트팩토리는 생산공정의 실시간 모니터링, 생산공정 시뮬레이션, 생산설비 예지보전 등의 서비스를 지원할 수 있어 생산비용 절감 및 생산성 향상에 기여할 것으로 기대된다. AAS(Asset Administration Shell)는 디지털 트윈을 구현하기 위한 필수 기술로, 현실의 물리적 자산을 디지털로 표현하는 방법을 제공한다. 본 논문에서는 스마트팩토리 내 생산설비를 자산으로 간주하여, 운용 중인 실시간 CNC(Computer Numerical Control) 모니터링 시스템에서 활용할 제조 데이터 수집을 위한 AAS를 설계하였다.

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우리나라 공공건물의 내용연수 추정: RCC를 중심으로 (An Estimation on Average Service Life of Public Buildings in South Korea: In Case of RCC)

  • 권정훈;조진형;오현승;이세재
    • 산업경영시스템학회지
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    • 제46권1호
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    • pp.84-90
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    • 2023
  • ASL estimation of public building is based on how appropriate the maximum age of the asset is derived based on the age record of the asset in the statistical data owned by public institutions. This is because we get a 'constrained' ASL by that number. And it is especially true because other studies have assumed that the building is an Iowa curve R3. Also, in this study, the survival rate is 1% as the threshold value at which the survival curve and the predictable life curve almost coincide. Rather than a theoretical basis, in the national statistical survey, the value of residual assets was recognized from the net value of 10% of the acquisition value when the average service life has elapsed, and 1% when doubling the average service life has elapsed. It is based on the setting mentioned above. The biggest constraint in fitting statistical data to the Iowa curve is that the maximum ASL is selected at R3 150%, and the 'constrained' ASL is calculated by the proportional expression on the assumption that the Iowa curve is followed. In like manner constraints were considered. First, the R3 disposal curve for the RCC(reinforced cement concrete) building was prepared according to the discarding method in the 2000 work, and it was jointly worked on with the National Statistical Office to secure the maximum amount of vintage data, but the lacking of sample size must be acknowledged. Even after that, the National Statistical Office and the Bank of Korea have been working on estimating the Iowa curve for each asset class in the I-O table. Another limitation is that the asset classification uses the broad classification of buildings as a subcategory. Second, if there were such assets with a lifespan of 115 years that were acquired in 1905 and disposed of in 2020, these discarded data would be omitted from this ASL calculation. Third, it is difficult to estimate the correct Iowa curve based on the stub-curve even if there is disposal data because Korea has a relatively shorter construction history, accumulated economic wealth since the 1980's. In other words, "constrained" ASL is an under-estimation of its ASL. Considering the fact that Korea was an economically developing country in the past and during rapid economic development, environmental factors such as asset accumulation and economic ability should be considered. Korea has a short period of accumulation of economic wealth, and the history of 'proper' architectures faithful to building regulations and principles is short and as a result, buildings 'not built properly' and 'proper' architectures are mixed. In this study, ASL of RCC public building was estimated at 70 years.