• 정보와 통신
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• 제5권2호
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• pp.245-256
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• 1988

본 논문에서는 적응 데이터 반향제거기(adaptive data-driven echo canceller)의 여러 구조에 대한 성능을 고찰한다. 우선 각 data-driven echo canceller (DDEC)의 시스템식을 일관성 있는 기준에 의하여 분류하고 연관성을 살펴본다. 특히, 본 논문에서 제안된 새로운 DDEC 알고리즘의 기존의 방법과의 차이점을 중점 기술한다. 또한 각 DDEC구조의 성능 및 복잡성을 비교 분석한다. 결과로서, 제안된 새로운 알고리즘이 성능이 우수할 뿐만아니라 복잡성 또한 적음을 입증하였으며 이를 시뮬레이션을 통하여 확인하였다.

• 한국IT서비스학회:학술대회논문집
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• 한국IT서비스학회 2009년도 추계학술대회
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• pp.505-510
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• 2009

전자, 자동차 등 엔지니어링 컨버전스 산업이 발전함에 따라 임베디드 S/W 테스트의 중요성이 증가하고 있다. 그러나, 일반적인 S/W 테스트 방법을 그대로 이용할 경우 임베디드 디바이스의 특성으로 인해 일반적인 품질 수준의 테스트 결과를 얻기 위해 상대적으로 더 많은 비용과 시간을 필요로 하게 된다. 따라서, 다양한 임베디드 시스템의 환경에 적용하기 쉽고, 임베디드 디바이스의 특성에 잘 대응하는 테스트 방법이 요구되는 실정이다. 본 논문에서는 Data-Driven 기법을 이용한 효과적인 임베디드 테스트 자동화 기법을 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권3호
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• pp.235-250
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• 2009

An understanding of performance of database driven network applications is critical in combating slow performance of e-commerce web sites, besides efficient web page design, and high quality and well-maintained web server equipment. This paper describes a method of measuring performance from the user viewpoint, which can help enormously in making realistic assessment of true performance of database driven applications. The performance measurements were taken at user locations by using several specially designed JavaScript functions along with ASP scripts. A performance study is presented in this paper, comparing performance of data access using stored procedures with the traditional way of querying a database. It is generally believed that stored procedures have performance benefits as they are pre-compiled. However, our study shows that the data access approach using stored procedures provides significant benefits(by about 30%) over the traditional approach for querying a commercial MySQL database, only when retrieving a substantial amount of data(at least 10,000 rows of data).

• 스마트미디어저널
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• 제11권11호
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• pp.63-74
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• 2022

Nowadays, lithium-ion battery has become more popular around the world. Knowing when batteries reach their end of life (EOL) is crucial. Accurately predicting the remaining useful life (RUL) of lithium-ion batteries is needed for battery health management systems and to avoid unexpected accidents. It gives information about the battery status and when we should replace the battery. With the rapid growth of machine learning and deep learning, data-driven approaches are proposed to address this problem. Extracting aging information from battery charge/discharge records, including voltage, current, and temperature, can determine the battery state and predict battery RUL. In this work, we first outlined the charging and discharging processes of lithium-ion batteries. We then summarize the proposed techniques and achievements in all published data-driven RUL prediction studies. From that, we give a discussion about the accomplishments and remaining works with the corresponding challenges in order to provide a direction for further research in this area.

• 한국콘텐츠학회논문지
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• 제21권10호
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• pp.103-114
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• 2021

본 연구는 데이터 과학의 분석적 연구 방법을 디자인 연구에 활용할 수 있는 방법을 모색, 실증해봄으로써 빅데이터 기반의 디자인 분야에서 데이터 자원을 효과적으로 활용하고, 빅데이터 기술과 디자인이 상생 발전할 수 있는 디자인 연구 방향을 제시하였다. 본 연구의 방법은 먼저 고전적인 디자인 리서치의 방법들과 데이터를 활용한 디자인 리서치의 연구 방법론, 데이터 과학의 연구 방법론을 고찰하고 디자인과 데이터 과학의 선행연구들을 종합하여 데이터 과학의 연구 방법론과 디자인 프로세스를 통합하는 데이터 기반 디자인의 연구 방법론을 개발 제안하였다. 제안된 연구 모델은 데이터 기반 서비스 앱의 디자인 리서치 사례 연구를 수행하여 제안한 방법론의 적용 가능성을 살펴보았으며, 제시한 연구 방법의 적용을 위하여 데이터 큐레이션 방법에 대한 연구와 디자이너의 데이터 문해력 확보가 향후 연구과제로 도출되었다.

• 지식경영연구
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• 제17권1호
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• pp.49-72
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• 2016

Extant research on firm innovation productivity is limited in measuring the innovation productivity, in which they measured firm innovation productivity by using either inputs or outputs of innovation. The present study complemented the extant research by employing Data Envelopment Analysis (DEA) approach to measure firm innovation productivity. Furthermore, this paper examined the effects of firms' external knowledge search, as one of open innovation practices, on firm innovation productivity, for open innovation activities are regarded as an influencing factor on firm innovation productivity in the previous literatures. Using the data of the Korean Innovation Survey (KIS) of manufacturing industries conducted in 2008, this study developed hypotheses in which we considered not only two dimensions of external knowledge search (breadth and depth) but also two subtypes of external knowledge search (market-driven and science-driven). The results found that searching deeply and market-driven search are positively related to firm innovation productivity, but science-driven search is somewhat negatively related to firm innovation productivity. Furthermore, market-driven search can mitigate the negative effect of science-driven search on innovation productivity.

• Asia pacific journal of information systems
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• 제32권3호
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• pp.477-495
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• 2022

This paper proposes how to design and implement data-driven strategies by investigating how a firm can increase its value using data science. Drawing on prior studies on architectural innovation, a behavioral theory of the firm, and the knowledge-based view of the firm as well as the analysis of field observations, the paper shows how data science is abused in dealing with meso-level data while it is underused in using macro-level and alternative data to accomplish machine-human teaming and risk management. The implications help us understand why some firms are better at drawing value from intangibles such as data, data-science capabilities, and routines and how to evaluate such capabilities.

• Nuclear Engineering and Technology
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• 제52권6호
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• pp.1148-1155
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• 2020

This work presents two different methods for quantifying and propagating the uncertainty associated with fuel composition at end of life for cask criticality calculations. The first approach, the computational approach uses parametric uncertainty including those associated with nuclear data, fuel geometry, material composition, and plant operation to perform forward depletion on Monte-Carlo sampled inputs. These uncertainties are based on experimental and prior experience in criticality safety. The second approach, the data-driven approach relies on using radiochemcial assay data to derive code bias information. The code bias data is used to perturb the isotopic inventory in the data-driven approach. For both approaches, the uncertainty in k_eff for the cask is propagated by performing forward criticality calculations on sampled inputs using the distributions obtained from each approach. It is found that the data driven approach yielded a higher uncertainty than the computational approach by about 500 pcm. An exploration is also done to see if considering correlation between isotopes at end of life affects k_eff uncertainty, and the results demonstrate an effect of about 100 pcm.

• 한국CDE학회논문집
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• 제14권2호
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• pp.96-104
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• 2009

It gradually becomes important to study on how to efficiently integrate and manage plant lifecycle data such as 2D schematic and 3D solid data, logical configuration data, and equipment specifications data. From this point of view, converting plant design data from various systems into neutral data independent from any commercial systems is one of important technologies for the operation and management of plants which usually have a very long period of life. In order to achieve this goal, a neutral model for efficient integration and management of plant data was defined. After schema mapping between one of specification-driven plant design systems and the neutral model was performed, a plant data translator is also implemented according to the mapping result. Finally, by experiments with nuclear power plant design, the feasibility of the translator was demonstrated.

• 대한기계학회논문집A
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• 제31권7호
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• pp.747-755
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• 2007

To improve the reality of motion simulator, the method of data-driven motion generation has been introduced to simply record and replay the motion of real vehicles. We can achieve high quality of reality from real samples, but it has no interactions between users and simulations. However, in character animation, user controllable motions are generated by the database made up of motion capture signals and appropriate control algorithms. In this study, as a tool for the interactive data-driven driving simulator, we proposed a new motion generation method. We sample the motion data from a real vehicle, transform the data into the appropriate data structure(motion block), and store a series of them into a database. While simulation, our system searches and synthesizes optimal motion blocks from database and generates motion stream reflecting current simulation conditions and parameterized user demands. We demonstrate the value of the proposed method through experiments with the integrated motion platform system.