• 정보과학회 논문지
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• 제42권11호
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• pp.1452-1458
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• 2015

한국어 형태소 분석은 교착어 특성상 난이도가 높은 작업이다. 그 중에서 형태소의 원형 복원 작업은 규칙이나 기분석 사전 정보 등을 활용하는 방법이 주로 연구되었다. 그러나 이러한 방법들은 어휘 수준의 문맥 정보를 보지 못하기 때문에 원형 복원에 한계가 있다. 본 논문에서는 최근 자연어처리에 연구되고 있는 기계학습 방법인 딥 러닝(deep learning)을 사용하여 형태소의 원형 복원 문제의 해결을 시도하였다. 문맥 정보를 보기 위해 단어 표현(word embedding)을 사용하여 기존의 방법들 보다 높은 성능을 보였다. 실험 결과, '들/VV'과 '듣/VV'의 복원 문제에 대해서 97.97%로 기존의 자연어처리에 쓰이는 기계학습 방법 중 하나인 SVM(Support Vector Machine)의 96.22% 보다 1.75% 높은 성능을 보였다.

• 태양에너지
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• 제18권3호
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• pp.81-87
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• 1998

Solar energy has been experiencing renewed interest because of the recent economical crisis in Korea. Absorption cooling is one of the promising solar energy utilization technologies. In this study the dynamic performance of a solar driven absorption cooling machine(SDACM) was numerically investigated. The simulated machine is a commercially available water/LiBr single effect absorption chillers driven by hot water from solar collectors. The present study has been directed to investigate the dynamic behavior of a solar cooling system including an absorption chiller, solar collector, a hot water storage tank, fan coil units, and the air-conditioned space. The operation of the system was simulated for 9 hours in varying operation conditions. The variation of temperature and concentration in the system components, and that of heat transfer rates in the system were obtained. It was also found that the room temperature was maintained near the desired value by controlling the mass flow rate of hot water.

• 한국기계가공학회지
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• 제12권6호
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• pp.175-181
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• 2013

The primary element of machining automation is to maximize the utilization of machine tools, which determines the output and lead-time. In particular, 95% of raw materials for wing ribs are cut into chips and 0.6 ton of chips are generated every hour from each machine tool. In order to verify the chip recycling system that controls the chips from the machines in five-axis FMS line, a simulation of the virtual model is constructed using the QUEST simulation program. The optimum speed of the chip conveyor and its operating conditions that directly affect the efficiency of the FMS line are presented including the chip conveyor speed, the maximum capacity of the hopper, and the number of chip compressors.

• Earthquakes and Structures
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• 제25권6호
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• pp.469-479
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• 2023

A probabilistic seismic damage analysis is an essential procedure to identify seismically vulnerable structures, prioritize the seismic retrofit, and ultimately minimize the overall seismic risk. To assess the seismic risk of multiple structures within a region, a large number of nonlinear time-history structural analyses must be conducted and studied. As a result, each assessment requires high computing resources. To overcome this limitation, we explore a deep learning-based metamodel to enable the prediction of the mean and the standard deviation of the seismic damage distribution of track-on steel-plate girder railway bridges in Korea considering the geometric variation. For machine learning training, nonlinear dynamic time-history analyses are performed to generate 800 high-fidelity datasets on the seismic response. Through intensive trial and error, the study is concentrated on developing an optimal machine learning architecture with the pre-identified variables of the physical configuration of the bridge. Additionally, the prediction performance of the proposed method is compared with a previous, well-defined, response surface model. Finally, the statistical testing results indicate that the overall performance of the deep-learning model is improved compared to the response surface model, as its errors are reduced by as much as 61%. In conclusion, the model proposed in this study can be effectively deployed for the seismic fragility and risk assessment of a region with a large number of structures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권6호
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• pp.1518-1539
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• 2024

Artificial intelligence-enabled business models aim to improve decision-making, operational efficiency, innovation, and productivity. The presented systematic literature review is conducted to highlight elucidating the utilization of artificial intelligence (AI) methods and techniques within AI-enabled businesses, the significance and functions of AI-enabled organizational models and frameworks, and the design parameters employed in academic research studies within the AI-enabled business domain. We reviewed 39 empirical studies that were published between 2010 and 2023. The studies that were chosen are classified based on the artificial intelligence business technique, empirical research design, and SLR search protocol criteria. According to the findings, machine learning and artificial intelligence were reported as popular methods used for business process modelling in 19% of the studies. Healthcare was the most experimented business domain used for empirical evaluation in 28% of the primary research. The most common reason for using artificial intelligence in businesses was to improve business intelligence. 51% of main studies claimed to have been carried out as experiments. 53% of the research followed experimental guidelines and were repeatable. For the design of business process modelling, eighteen AI mythology were discovered, as well as seven types of AI modelling goals and principles for organisations. For AI-enabled business models, safety, security, and privacy are key concerns in society. The growth of AI is influencing novel forms of business.

• 한국콘텐츠학회논문지
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• 제14권2호
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• pp.409-420
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• 2014

본 연구는 직업분류 및 고용분류별 스트레스, 스트레스 상담, 우울증상, 우울증상 상담 정도를 파악하기 위해 지역사회건강조사 자료를 이차 분석하였다. 직업분류별 및 고용분류별 확실한 비교를 위해 기준 직업군으로 '무직(직업분류 기준항목)'과 '무급가족종사자(고용분류 기준항목)'를 포함하여 한국표준직업분류(6차 개정)에 의한 총 13개의 직업군을 이용하였다. 직업분류 및 고용분류별 스트레스, 스트레스 상담, 우울증상, 우울증상 상담 여부의 교차비에서는 '무직'과 '무급가족종사자'의 스트레스 정도가 대체적으로 더 낮게 나타난 반면, 스트레스 상담, 우울증상, 우울증상 상담에서는 '무직'과 '무급가족종사자'가 오히려 더 높은 교차비를 보였다. '관리직'을 포함한 7개의 직업군은 '무직'보다 스트레스를 많이 받지만(OR > 1), 의료기관 이용률은 낮게 나타났다(OR < 1). '고용주 및 자영업자'와 '임금근로자'가 '무급가족종사자'에 비해 높은 교차비를, 스트레스 상담 및 우울상담에서는 낮은 교차비를 보였다. 본 연구는 정신건강문제 선별 및 관리를 위해 특정 인구집단에 대한 접근을 통해 직장 내 정신보건서비스 제공에 대한 필요성을 시사하고 있다.

• 대한원격탐사학회지
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• 제37권6_3호
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• pp.1923-1929
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• 2021

지구관측위성은 다양한 분야에서 활용되고 있으며 높은 활용성과 시장성으로 인해 많은 국가에서 개발 하고 있다. 우리나라는 국가 우주개발 계획에 따라 다양한 지구관측위성을 개발하고 있으며, 그 중에서 다목적 실용위성 시리즈는 가장 대표적인 저궤도 위성이다. 지금까지 총 5기의 다목적실용위성이 발사되어 국가 영상 수요를 충족하고 있으며, 국가기관을 비롯하여 다양한 분야에서 활용되고 있다. 본 특별호에서는 다목적실용 위성 시리즈의 다양한 영상자료를 이용한 자료처리, 분석 및 활용과 관련된 연구에 대해서 소개하고자 한다. 한편 후속 다목적실용위성 영상자료의 차질 없는 활용을 위해서는 고해상도 영상에 적합한 자료처리 및 활용 연구가 계속되어야 하며, 특별호를 통해서 관련 연구 내용이 지속적으로 공유될 수 있도록 할 예정이다.

• 인터넷정보학회논문지
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• 제21권6호
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• pp.133-139
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• 2020

Big data, artificial intelligence (AI), and machine learning are keywords that represent the Fourth industrial Revolution. In addition, as the development of science and technology, the Korean government, public institutions and industries want professionals who can collect, analyze, utilize and predict data. This means that data analysis and utilization education become more important. Education on data analysis and utilization is increasing with trends in other academy. However, it is true that not many academy run long-term and systematic education. Korea Institute of Science and Technology Information (KISTI) is a data ecosystem hub and one of its performance missions has been providing data utilization and analysis education to meet the needs of industries, institutions and governments since 1966. In this study, KISTI's data education was analyzed using the number of curriculum trainees per year from 2001 to 2019. With this data, the change of interest in education in information and data field was analyzed by reflecting social and historical situations. And we identified the characteristics of KISTI and trainees. It means that the identity, characteristics, infrastructure, and resources of the institution have a greater impact on the trainees' interest of data-use education.In particular, KISTI, as a research institute, conducts research in various fields, including bio, weather, traffic, disaster and so on. And it has various research data in science and technology field. The purpose of this study can provide direction forthe establishment of new curriculum using data that can represent KISTI's strengths and identity. One of the conclusions of this paper would be KISTI's greatest advantages if it could be used in education to analyze and visualize many research data. Finally, through this study, it can expect that KISTI will be able to present a new direction for designing data curricula with quality education that can fulfill its role and responsibilities and highlight its strengths.

• 한국엔터테인먼트산업학회논문지
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• 제15권4호
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• pp.349-357
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• 2021

최근 급속히 보편화되고 확대되는 드론의 비행 데이터가 엔터테인먼트 기술 분석 자료로 활용이 가능한지의 검증이 매우 필요하다. 특히, 자율화, 지능화의 방법으로 발전하는 엔터테인먼트 드론의 비행과 운용과정을 데이터 분석과 기계학습을 통해서 분석 및 활용할 수 있는지를 확인해야 한다. 본 논문에서는 엔터테인먼트용 드론의 평가에 FC의 데이터를 이용하여 머신러닝 기법으로 활용할 수 있는지를 확인하였다. 그 결과 매빅2나 아나피와 같은 DJI나 Parrot의 FC 데이터는 엔터테인먼트를 위한 머신러닝 분석이 불가능하였다. 이는 데이터가 0.1초 이상의 간격으로 수집됨으로써 GCS와의 다른 데이터들과의 상관성을 찾기 불가능하기 때문이다. 이에 반하여 ARM 프로세서를 채용하여 Nuttx 운영체제로 작동하는 픽스호크의 경우에는 머신러닝 기법의 적용이 가능함을 알 수 있었다. 앞으로 고정익과 회전익 비행 정보들을 구분하여 엔터테인먼트의 특성 분석이 가능한 기술들을 발전시켜야 한다. 이를 위해서는 모델을 개발하고 체계적인 데이터 수집과 연구가 진행되어야 할 것이다.

• 한국프랜차이즈경영연구
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• 제12권4호
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• pp.1-11
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• 2021

Purpose: The franchise system started by Singer Sewing Machine in the US is acting as a national economic growth engine in terms of job creation and economic growth. In China, the franchise system was introduced in the mid-1980s. And since joining the WTO, it has grown by 5-6% every year. However, compared to the growth rate of franchises, studies on shared growth between the chain headquarters and franchisees were insufficient. Accordingly, recent studies related to shared growth between the chain headquarters and franchisees have been active in China. The purpose of this study is to examine the knowledge transfer system between the knowledge creation, knowledge sharing, and the use of knowledge by franchise chain headquarters in China. In addition, the relationship between franchise satisfaction and performance is identified. Research design, data, and methodology: The data were collected from franchise stores in Sichuan, China, and were conducted with the help of ○○ Incubation, a Sichuan Province-certified incubator. From November 2020 to January 2021, 350 copies of the questionnaire were distributed in China, and 264 copies were returned. Of these, 44 copies with insincere answers and response errors were excluded, and 222 copies were used for analysis. The data were analyzed with SPSS 22.0 and AMOS 22.0 statistical packages. Result: The results of this study are as follows. First, knowledge creation has been shown to have a statistically significant impact on knowledge sharing and knowledge utilization. In particular, the effectiveness of knowledge creation was higher in knowledge sharing than in knowledge utilization. And we can see that knowledge sharing also has a statistically significant e ffect on knowledge utilization. Second, knowledge sharing was not significant for transaction satisfaction and business performance, and knowledge utilization was significant for transaction satisfaction and business performance. These results can be said to mean less interdependence of the Chinese franchise system. Finally, transaction satisfaction was statistically significant to business performance. The purpose of this study was to examine the importance of knowledge management to secure long-term competitive advantage for Chinese franchises. This study shows that knowledge sharing is important for long-term franchise growth. And we can see that there is a lack of knowledge sharing methods in the case of franchises in China. I n addition, it was found that the growth of Chinese franchises requires systematization of communication, information sharing measures and timing, help from chain headquarters, and mutual responsibility awareness.