• Journal of the Korea Safety Management & Science
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• v.24 no.4
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• pp.61-70
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• 2022

In spite of lab safety act for over 10 years, over 100 safety accidents in the laboratory have been constantly occurring. The ideal safety management system is to prevent accidents by differential classifying and managing laboratory regulatory materials according to the risk level. In order to approach this system, in-depth interviews with safety managers were first conducted to identify the current status of safety management in domestic university laboratories. And then through comparative analysis of safety management systems in domestic and foreign laboratories, a new regulatory substance classification standard based on the analysis of the hazards and the classification of risk grades, and a safety management system are proposed. From this study, it will contribute to the creation of a safe laboratory environment by differential classification and management laboratory regulatory materials based on the risk level.

• Journal of the Korea Safety Management & Science
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• v.25 no.3
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• pp.17-22
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• 2023

As the importance of artificial intelligence grows rapidly and emerges as a leader in technology, it is becoming an important variable in the next-generation industrial system along with the robot industry. In this study, a safety system was developed using deep learning technology to provide worker safety in a robot workplace environment. The implemented safety system has multiple cameras installed with various viewing directions to avoid blind spots caused by interference. Workers in various scenario situations were detected, and appropriate robot response scenarios were implemented according to the worker's risk level through IO communication. For human detection, the YOLO algorithm, which is widely used in object detection, was used, and a separate robot class was added and learned to compensate for the problem of misrecognizing the robot as a human. The performance of the implemented system was evaluated by operator detection performance by applying various operator scenarios, and it was confirmed that the safety system operated stably.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.3
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• pp.483-497
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• 2023

This study aims to provide strategic recommendations for promoting the development of the global satellite data services industry by analyzing the startup landscape. Based on the analysis of startup data, such as number of startups, market segment, and funding amount, we examined the paradigm shift in the global satellite data services market, particularly its convergence with other market segments. To this end, we derived the cumulative funding-convergence dynamics matrix, which classifies the converging areas into four quadrants by considering the growth rate of converging segments and the cumulative funding amount. In this way, we can specify converging areas in the satellite data services market that bear potential importance for the creation of new markets. The findings of this study are expected to contribute to the advancement of the satellite data services industry and facilitate the exploration of new market opportunities. Furthermore, they can serve as a valuable reference for policy makers, industry stakeholders, government officials, and researchers involved in the satellite data services industry in capitalizing on the emerging space economy.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.833-844
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• 2023

As technology convergence is recognized as a driver of innovation, the identification of technology convergence opportunities is critical to expanding a firm's technology portfolio. Recently, wearable technology has emerged as an important factor in creating new business opportunities and providing technology investment alternatives for firms in the era of Industry 4.0. Against this background, this study provides a new patent analysis framework for identifying and proposing technology convergence opportunities in the wearable field. Using 8,621 patents filed between 2011 and 2021, a case study was conducted to identify technological convergence opportunities by applying Word2Vec algorithm. The analysis framework can be divided into four stages, with the final stage recommending potential technology convergence opportunities for a specific candidate firm's technology area by calculating similarities between technology codes. This study aims to better understand the current status of wearable technology development as well as to propose a new methodology for capturing technology convergence opportunities in the wearable industry. The case study result suggests that the convergence of healthcare and ICT may provide new development opportunities. Furthermore, the results are expected to provide alternative perspectives on the development of new markets and technologies using wearable technology and can support the strategic decision-making on future technology planning in the wearable field.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.635-644
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• 2024

Although the business model(BM) patents act as a creative bridge between technology and the marketplace, limited scholarly attention has been paid to the content analysis of BM patents. This study aims to contextualize converging BM patents by employing topic modeling technique and clustering highly marketable topics, which are expressed through a topic-market impact matrix. We relied on BM patent data filed between 2010 and 2022 to derive empirical insights into the commercial potential of emerging business models. Subsequently, nine topics were identified, including but not limited to "Data Analytics and Predictive Modeling" and "Mobile-Based Digital Services and Advertising." The 2x2 matrix allows to position topics based on the variables of topic growth rate and market impact, which is useful for prioritizing areas that require attention or are promising. This study differentiates itself by going beyond simple topic classification based on topic modeling, reorganizing the findings into a matrix format. T he results of this study are expected to serve as a valuable reference for companies seeking to innovate their business models and enhance their competitive positioning.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.925-933
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• 2024

Identification of potential technology convergence opportunities is crucial to drive innovation and growth in modern enterprises. In this study, we proposed a framework to explore technological convergence opportunities based on CPC code sequences from patents by utilizing the BERT model. We relied on the BERT architecture to train a new model using about 1.3 million patents registered at the Korean Intellectual Property Office, and achieved an accuracy of approximately 73% based on HitRate@10 metric. A case study using patents related to wearable technologies was conducted to demonstrate practicability and effectiveness of the proposed framework. The key contributions of this research include: (1) enabling in-depth analysis that takes into account the complex interactions between CPC codes and contextual variability; (2) enabling the exploration of diverse technology convergence scenarios beyond simple sequential patterns. This study is one of the first studies to apply the BERT model for exploring technology convergence opportunities, and is expected to contribute to the establishment of technology innovation and R&D strategies by providing a more accurate and practical tool for enhancing the speed and efficiency of technology opportunity-related decision-making processes.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.356-360
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• 2007

디지털 생태계에 대한 관심이 작년 다보스 세계경제 포럼(WEF)과 최근의 이론적 문헌을 통해 국내외에서 주목을 받고 있다. 국내에 관련 전담 연구조직이 생기고 일정한 성과물을 시현하기 시작하고 있다. 이와 관련, 이 연구는 최근 이슈가 되고 있는 디지털 생태계에 대한 이론적 연구를 토대로 국내 IPTV 영역에서의 동향과 응용가능성에 대해 살펴보고자 한다. 우선, 기존의 통방융합의 한 형태인 IPTV에서의 주주 중심(Share-holderism)에서 이해관계자 중심관점(Stake-holderism)으로의 이론적 연구를 바탕으로 한다. 또한 디지털 생태계의 생태중심 관점(Eco-holderism)으로의 상호 공존과 공진화(Co-evolution)를 위한 연구로 외연 확장을 모색 하고자 한다. 이 연구를 통해 아직 법적 문제, 서비스 내용과 사업 영역에 있어서 방송계와 통신계의 이해가 상충되고 있는 IPTV의 원활한 서비스를 위한 토대를 마련 하고자 한다. 국내외 문헌연구를 바탕으로 국내에서 IPTV의 선행 형태로 서비스중인 하나TV와 메가TV 등의 사례 분석을 통해 디지털 생태계 연구에서 의미있는 시사점을 추가하고자 한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.523-526
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• 2004

가입자단에서의 병목현상 해결과 통신방송융합서비스의 제공을 위해 가입자망 기술은 디지털화된 HFC와 상하향 100Mbps이상의 속도를 제공하는 FTTH(Fiber To The Home)로 진화될 것으로 예측되며, 궁극적으로는 FTTH로 수렴될 것으로 전망되고 있다. FTTH는 통신과 방송이 융합된 다양한 신규서비스로 새로운 수익을 창출할 것으로 기대되나, 대규모 투자가 필요한 상황에서 정확한 수요 예측은 통신 회사들의 네트워크 구축 관련 의사결정에 필수적인 요인이다. 이를 위해 본 논문에서는 경쟁서비스로 천이가 용이한 통신서비스의 특징을 고려하여 FTTH의 수요예측을 실시하였다. 1차 전문가 설문을 통해 서비스간 전이형태를 모형화하였으며, 이를 토대로 FTTH 서비스로의 천이에 의해 추가적인 확산이 일어나는 변형된 Bass모형을 제안하였다. FTTH 서비스의 확산요인을 분석한 후 이를 토대로 2차 전문가 설문을 통해 각 계수를 추정하였다.

• Knowledge Management Research
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• v.19 no.4
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• pp.149-170
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• 2018

Healthcare lifelog, a personal record relating to disease treatment and healthcare, plays an important role in healthcare paradigm shifts in which medical and information technology converge. Healthcare services based on various healthcare lifelogs are being launched domestically by both large corporations and small and medium enterprises, however, they are being built on an individual platform that is dependent on each company. Therefore, the terms of lifelog data are different as well as the measurement specifications are not uniform. This study proposes a reference model for minimum common data required for sharing and utilization of healthcare lifelog. Literature study and expert survey derived 3 domain, 17 essential items, and 51 sub-items. The model provides definition, measurement data format, measurement method, and precautions for each detailed measurement item, and provides necessary guidelines for data and service design and construction for healthcare service. This study has its significance as a basic research supporting the activation of ecosystem by ensuring interoperability of data between heterogeneous healthcare devices linked to digital healthcare platform.

• The Journal of Economics, Marketing and Management
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• v.10 no.6
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• pp.9-16
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• 2022

Purpose: This research investigates the differences in knowledge exchange activities and performances between startups and large companies in software industry clusters. Research design, data, and methodology: Six independent factors of human resource information, R&D and technology, marketing knowledge, government support information, strategic knowledge, and cooperation information were extracted to test the firm size effect in the relationships with two performance factors such as satisfaction with industry cluster location and satisfaction with financial performances. Data were collected through a survey of entrepreneurs, managers, and employees and tested by statistical analysis methodologies. Results: Three independent factors of human resource information, R&D and technology, and cooperation information were particularly significant in the relationship with both dependent factors. Strategic knowledge significantly affected financial performance. Knowledge exchange activities were more important in startups than in large companies for all eight factors. Conclusion: Policies for software industry clusters need a different approach for startups and large companies.