• 반도체디스플레이기술학회지
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• 제23권2호
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• pp.123-128
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• 2024

Major countries are trying to expand the construction of smart factories by introducing ICT such as the Internet of Things, cloud, and big data into the manufacturing sector to secure national-level manufacturing competitiveness in the era of the 4th industrial revolution. In addition, Germany is pushing for Industry 4.0 to build a fully automatic production system through the Internet of Things, and China is pushing for the expansion of smart factories to enhance the country's industrial competitiveness through Made in China 2025, Japan's intelligent manufacturing system, and the Korean government's manufacturing innovation 3.0. In this study, considering the increasing security connectivity of smart factories, we would like to identify security threats in the external connection part of smart factories and suggest security enhancement measures based on domestic and international standard security models to respond to the identified security threats. Eventually the proposed method can be applied by accurately identifying the smart factory security status, diagnosing vulnerabilities, establishing appropriate improvement plans, and expanding security strategies to respond to security threats.

• Journal of Information Technology Applications and Management
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• 제29권6호
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• pp.145-157
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• 2022

Climate crisis is one of the most urgent and serious threats to the right to life. As AR picture books are particularly effective for safety education, this study aimed to produce an AR picture book featuring animals that are endangered due to the climate crisis. In order to increase the educational effect and enhance the climate sensitivity, this study developed a children's activity workbook (with follow-up activities) and a teacher's guide (with lesson plans) as a package. To this end, market research and surveys were first conducted. Next, through the management and support of the Korea Institute of Startup & Entrepreneurship Development, this research team produced a climate crisis themed AR picture book package through expert advice, help from outsourcing companies, and field application. The package was promoted through publicity in various forms of media. The contents of the AR-using picture book package of this case study were introduced and then advantages and disadvantages were discussed.

• International Journal of Naval Architecture and Ocean Engineering
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• 제12권1호
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• pp.440-454
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• 2020

To prevent pollution from ships, the Energy Efficiency Design Index (EEDI) is a mandatory guideline for all new ships. The Ship Energy Efficiency Management Plan (SEEMP) has also been applied by MARPOL to all existing ships. SEEMP provides the Energy Efficiency Operational Indicator (EEOI) for monitoring the operational efficiency of a ship. By monitoring the EEOI, the shipowner or operator can establish strategic plans, such as routing, hull cleaning, decommissioning, new building, etc. The key parameter in calculating EEOI is Fuel Oil Consumption (FOC). It can be measured on board while a ship is operating. This means that only the shipowner or operator can calculate the EEOI of their own ships. If the EEOI can be calculated without the actual FOC, however, then the other stakeholders, such as the shipbuilding company and Class, or others who don't have the measured FOC, can check how efficiently their ships are operating compared to other ships. In this study, we propose a method to estimate the EEOI without requiring the actual FOC. The Automatic Identification System (AIS) data, ship static data, and environment data that can be publicly obtained are used to calculate the EEOI. Since the public data are of large capacity, big data technologies, specifically Hadoop and Spark, are used. We verify the proposed method using actual data, and the result shows that the proposed method can estimate EEOI from public data without actual FOC.

• Journal of Information Technology Applications and Management
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• 제22권3호
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• pp.83-103
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• 2015

The rapid development of internet technologies and social media over the last few years has generated a huge amount of unstructured text data, which contains a great deal of valuable information and issues. Therefore, text mining-extracting meaningful information from unstructured text data-has gained attention from many researchers in various fields. Topic analysis is a text mining application that is used to determine the main issues in a large volume of text documents. However, it is difficult to identify related issues or meaningful insights as the number of issues derived through topic analysis is too large. Furthermore, traditional issue-clustering methods can only be performed based on the co-occurrence frequency of issue keywords in many documents. Therefore, an association between issues that have a low co-occurrence frequency cannot be recognized using traditional issue-clustering methods, even if those issues are strongly related in other perspectives. Therefore, in this research, a methodology to reorganize social issues from a research and development (R&D) perspective using social network analysis is proposed. Using an R&D perspective lexicon, issues that consistently share the same R&D keywords can be further identified through social network analysis. In this study, the R&D keywords that are associated with a particular issue imply the key technology elements that are needed to solve a particular issue. Issue clustering can then be performed based on the analysis results. Furthermore, the relationship between issues that share the same R&D keywords can be reorganized more systematically, by grouping them into clusters according to the R&D perspective lexicon. We expect that our methodology will contribute to establishing efficient R&D investment policies at the national level by enhancing the reusability of R&D knowledge, based on issue clustering using the R&D perspective lexicon. In addition, business companies could also utilize the results by aligning the R&D with their business strategy plans, to help companies develop innovative products and new technologies that sustain innovative business models.

• 한국ITS학회 논문지
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• 제21권5호
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• pp.133-148
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• 2022

본 연구에서는 세종시의 도로포장 구간을 대상으로 도로포장의 균열률 파손모델을 개발하였다. 파손모델개발에 필요한 모니터링 데이터는 딥러닝 기반의 도로자산 모니터링 시스템을 활용하여 취득하였다. 모니터링 조사는 동일 구간을 대상으로 2021년도와 2022년도에 수행하였다. 도로포장 파손모델은 연평균 파손량을 추정하기 위한 방법론과 계층적 베이지안 마르코프 혼합 해저드 (Bayesian Markov Mixture Hazard) 모델을 활용한 방법론으로 구분하여 분석을 수행하였다. 분석결과, 기존 전문조사장비에서 취득된 데이터를 기반으로 개발된 균열률 파손모델과 유사한 분석 값을 도출할 수 있었다. 본 연구의 결과는 향후 지자체의 도로관리계획수립을 위한 기초자료로 활용될 것으로 기대된다.

• Journal of Information Technology Applications and Management
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• 제16권1호
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• pp.137-148
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• 2009

Knowledge management becomes the key point for organizations to survive and maintain competitive advantages in the knowledge economy era. E-learning plays a vital role for the organizational learning. How to share the experience of knowledge and the success of the knowledge management has great connection with the organizational culture. This study focuses on the factors of effective E-learning as well as its relation to the organizational culture. A successful e-learning system should not only aim at different statistical variables but emphasize on : course contents, variety of teaching methods and establishes a stable network environment. A stable E-learning platform and speedy bandwidth is a must to achieve the non-barrier communication and built an interactive learning environment. To achieve success in E-learning, it is not necessary to divide the organizational culture to strengthen the course content multiplication and plans the E-learning supervisory work by the sole responsibility unit. It should establish an ample teaching frequency width and platform and also must establish the appropriate study network frequency width and hardware equipment to achieve the best E-learning effect. The interaction in different organizational culture in adapting E-learning, those Ad-hoc and Marketing Culture, are mostly influence by the external environment and have more interactive content. Those in Clan and Hierarchy Culture are affected by traditional conception and lack of interaction. Meanwhile, under the cost consideration, Clan and Ad-hoc Culture on the dynamic side prefer to spend more cost on E-Learning while the stable side, Hierarchy and Marketing culture are willing to pay more expenses on E-Learning.

• 융합정보논문지
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• 제8권5호
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• pp.145-152
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• 2018

이 논문은 빅데이터가 중심이 되는 새로운 시대를 맞이하여 회계업무의 전문성을 높이기 위해 회계교육이 나아가야 할 방향을 제시하고자 한다. 빅데이터의 정의와 분석방법을 살펴보고, 회계전문분야에서 빅데이터 개발을 통한 효용성을 구체적인 언급과 함께 검토한다. 또한, 회계교육과정에 빅데이터라는 주제를 다루기 위하여 회계전문가 모임과 대학이 선택한 몇 가지 계획을 제시한다. 그 계획에 따르면 빅데이터는 회계와 재무전문가의 미래역할에 대한 청사진을 제시할 수 있을 것으로 본다. 그러므로 이 연구가 제안하는 바는 다음과 같다. 미래세대의 회계전문가들이 빅데이터 분석과 관련된 기술을 미리 준비할 수 있도록 빅데이터 주제를 현재의 회계 교육과정에 추가하여 교육내용이 개선시키는 것이다.

• 한국주거학회논문집
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• 제17권4호
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• pp.65-72
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• 2006

Most of buildings have been deteriorated with time-elapse by reflection of the building location, material, environmental circumstances and so on. The performance would go down and be demolished if anything could not be done after constructed. The maintenance should be required to preserve a decent living condition or improve a inferior condition by various plans and practices. The maintenance plan needs various data such as a repair scope, a repair time, a forecasted cost, a plan of management and so forth. Among the above required data for planning the maintenance, the deterioration characteristics of the building components would be first analyzed. The deterioration pattern would be a key role to affect and make a maintenance plan. In this paper, it aimed at classifying the deterioration patterns of building components. A deterioration pattern would be analyzed between the cumulative repair cost and time-elapse and modeled with these relations. A deterioration patterns are classified into 4 types-a accelerated type, a straight type, a temporary type and a slowly type. As a result of this research, a accelerated type includes window, window frame, general paintings, general water proofing in building components. A straight type includes the lacquer paintings, furnishings in building components and water supply pipe, boiler, sanitaries in mechanical facilities and lighting in electric facilities. Based on these research results, further study should be conducted to include any other components and an estimating model.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 춘계학술대회논문집
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• pp.517-520
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• 2005

Noise mapping covers the whole mapping process from the collection of raw data, storage and retrieval of the data for computation/modeling, to the presentation of information related to outdoor sound levels, sound exposure, noise effects or numbers of affected person. This presentation can be in either a graphical or numerical form. In Europe, the Directive 2002/49/EC of the European Parliament and of the Council relating to the assessment and management of environmental noise is now being implemented in the EU Member States. Here, The first maps for major areas are required by mid 2007, and action plans required one year later. These activities are repeated at five yearly intervals and all defined areas are incorporated in the following round of deadlines starting in 2012. The above are minimum requirements and some countries are expected to go further and faster. In this study, present status of domestic and international noise maps has been introduced to implemente the Korean noise map standard. This will help to get more convenient and, more fair result, and produce correct map at domestic level.

• 대한산업공학회지
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• 제39권1호
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• pp.30-45
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• 2013

Predicting monthly electricity price has been a significant factor of decision-making for plant resource management, fuel purchase plan, plans to plant, operating plan budget, and so on. In this paper, we propose a sophisticated prediction model in terms of the technique of modeling and the variety of the collected variables. The proposed model hybridizes the semi-supervised learning and the artificial neural network algorithms. The former is the most recent and a spotlighted algorithm in data mining and machine learning fields, and the latter is known as one of the well-established algorithms in the fields. Diverse economic/financial indexes such as the crude oil prices, LNG prices, exchange rates, composite indexes of representative global stock markets, etc. are collected and used for the semi-supervised learning which predicts the up-down movement of the price. Whereas various climatic indexes such as temperature, rainfall, sunlight, air pressure, etc, are used for the artificial neural network which predicts the real-values of the price. The resulting values are hybridized in the proposed model. The excellency of the model was empirically verified with the monthly data of electricity price provided by the Korea Energy Economics Institute.