• Journal of Family Resource Management and Policy Review
• /
• v.27 no.3
• /
• pp.53-65
• /
• 2023

The aim of this study was to identify the factors that sustain the work of women activists with children by examining their work and life experiences and demands. This study focused on community-based institutions whose purpose was to spread gender equality and address gender issues. To achieve the purpose of this study, focus group interviews were conducted with 10 women activists working for women's organizations and grassroots women's organizations. By analyzing their interview responses, five topics were derived: the main activities and statuses of the women's organizations and grassroots women's organizations, the motivations for activities, the positive activity experiences that led to life as an activist, the factors that made it difficult to work, and the social support necessary to continue as an activist. The study results show that the work and life experiences and demands of civil society women activists provide the basis for understanding the lives of and scope of social support for women activists compared with women with jobs protected and supported by formal institutions. However, further analysis and discussion are required to identify the needs of more diverse women activists through continuous research in the future.

• Tunnel and Underground Space
• /
• v.33 no.6
• /
• pp.594-609
• /
• 2023

TBM (Tunnel Boring Machine) method is gaining popularity in urban and underwater tunneling projects due to its ability to ensure excavation face stability and minimize environmental impact. Among the prominent models for predicting disc cutter life, the NTNU model uses the Cutter Life Index(CLI) as a key parameter, but the complexity of testing procedures and rarity of equipment make measurement challenging. In this study, CLI was predicted using multiple linear regression analysis and tree-based machine learning techniques, utilizing rock properties. Through literature review, a database including rock uniaxial compressive strength, Brazilian tensile strength, equivalent quartz content, and Cerchar abrasivity index was built, and derived variables were added. The multiple linear regression analysis selected input variables based on statistical significance and multicollinearity, while the machine learning prediction model chose variables based on their importance. Dividing the data into 80% for training and 20% for testing, a comparative analysis of the predictive performance was conducted, and XGBoost was identified as the optimal model. The validity of the multiple linear regression and XGBoost models derived in this study was confirmed by comparing their predictive performance with prior research.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.17 no.4
• /
• pp.101-114
• /
• 2022

Recently, various studies on the entrepreneurial ecosystem have been conducted. The entrepreneurial ecosystem is composed of various elements such as entrepreneurs, governments, and infrastructure, and these factors interact to contribute to economic development. The purpose of this study was to analyze differences in importance and performance of the entrepreneurial ecosystem for startups using the importance-performance analysis (IPA) method. Based on this, the importance and current level of the components of the entrepreneurial ecosystem were identified and policy implications were presented. The results of the study are as follows. The importance ranking was in the order of startup support program(4.43), startup funding (4.39), market accessibility(4.30). The ranking of performance was startup support program(3.81), ease of starting a business(3.76), support for startup support institutions(3.66), and startup funding(3.66). All elements of the entrepreneurial ecosystem showed higher importance than performance. This means that the components of the entrepreneurial ecosystem in Korea are recognized as important, but do not play a significant role in terms of performance for startups. In addition, the factors with the highest improvement in the importance-performance matrix were 「safety nets for startup failure」, 「culture of acceptance of failure」, 「ease of market entry」, 「ease of startup survival」, and 「ease of exit」. This study suggested improvement measures such as establishing a social safety net, improving awareness of startup failure culture, matching successful startups, strengthening scale-up support by growth stage, easing regulations in new business fields, and diversifying investment recovery strategies.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.2
• /
• pp.119-131
• /
• 2024

Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.25 no.6
• /
• pp.469-478
• /
• 2023

The deep tunnel in urban area is a future-oriented construction plan that allows the above-ground space to be used as an eco-friendly park and transportation infrastructure to be constructed in the underground space. However, tunnel construction is often depicted as to cause ground collapse in some media and movies. In fact, while the construction of a deep tunnel in the urban area is underway, the project face with difficulties due to opposition complaints from residents near the route. In this study, we sought to identify perceptions on deep space development and citizen concerns through a public opinion survey regarding deep tunnels. By analyzing laws relevant with the promotion of deep tunnel construction, we reviewed the possibility of public engagement at each stage of the construction and investigated separated surface rights related to compensation for underground space. Through the results of the public opinion survey, it was identified that the concerns of citizens were problems that current technology could solve. Citizen's concerns were improved into a system that confirmed the stability of tunnel construction through public participation, and improvement measures were presented to encourage cooperation from those concerned regarding the establishment of divided superficies.

• Information Systems Review
• /
• v.25 no.1
• /
• pp.129-143
• /
• 2023

In the era of big data, the field of artificial intelligence is showing remarkable growth, and in particular, the image classification learning methods by deep learning are becoming an important area. Various studies have been actively conducted to further improve the performance of CNNs, which have been widely used in image classification, among which a representative method is the Convolutional Recurrent Neural Network (CRNN) algorithm. The CRNN algorithm consists of a combination of CNN for image classification and RNNs for recognizing time series elements. However, since the inputs used in the RNN area of CRNN are the flatten values extracted by applying the convolution and pooling technique to the image, pixel values in the same phase in the image appear in different order. And this makes it difficult to properly learn the sequence of arrangements in the image intended by the RNN. Therefore, this study aims to improve image classification performance by proposing a novel hybrid method of CNN and RNN applying the concepts of encoder and decoder. In this study, the effectiveness of the new hybrid method was verified through various experiments. This study has academic implications in that it broadens the applicability of encoder and decoder concepts, and the proposed method has advantages in terms of model learning time and infrastructure construction costs as it does not significantly increase complexity compared to conventional hybrid methods. In addition, this study has practical implications in that it presents the possibility of improving the quality of services provided in various fields that require accurate image classification.

• 한국벤처창업학회:학술대회논문집
• /
• 2024.04a
• /
• pp.157-160
• /
• 2024

KAIST는 다수의 성공 창업 사례와 국내 창업생태계에서 기술창업 발생지로 역사적 의미를 이어오고 있다. 최근 KAIST의 교원 창업이 매년 증가하고 있으며 딥테크 분야 창업으로 성장률과 생존율이 매우 높게 나타나 많은 주목을 받고 있다. 국가적으로도 매우 중요한 혁신기술창업 집적지라는 평가를 받고 있다. 대표적인 기업가적 대학인 KAIST는 기술창업 요람이라고 불리며 오랫동안 캠퍼스 창업생태계를 구축해오고 있다. 또한, 대한민국 창업생태계가 발전하면서 창업기업을 가장 많이 배출시킨 기관으로 혁신적인 창업문화를 선도해 오고 있다. 최근 KAIST의 신문화전략 1 Lab 1 Startup 비전을 수립하였고, 과학기술의 우수한 기술력을 바탕으로 연구실 R&D 기술을 혁신창업으로 이어지는 사업화를 위한 변화와 혁신을 주도하고 있다. 신문화전략 이후 몇 년 동안 교원들이 더욱 창업에 많은 관심을 가지기 시작하였고, 실질적으로 KAIST의 혁신 창업기업 수가 증가하였다. 이러한 결과는 신문화 전략 외에도 다양한 교원창업 성공사례 확산, 교원창업 활성화를 위해 제도개선, 아이디어 발굴부터 기술사업화 지원, 자금조달, 비즈니스 모델 고도화, 기술사업화 및 글로벌 창업지원, 창업 인프라를 제공하고 있기 때문이다. 하지만 KAIST의 창업을 한 교수를 대상으로 세부적으로 기술창업 성공 사례와 핵심요인에 대해서 분석한 연구는 매우 부족하다. 이에 본 연구에서는 KAIST에서는 교원창업 분야에서 성공적인 창업기업을 배출되고 있는 현상에 관한 사례, KAIST의 특화된 창업지원프로그램 소개, 교원 창업 성공 사례들이 어떻게 가능한지에 관한 요인과 그 이유를 탐색하고자 한다. 교수 창업 활성화를 위한 규정, 제도, 창업지원프로그램 등에 대해서 분석을 하고자 한다. 그러므로 본 연구에서는 대표성이 있는 KAIST N차(연쇄 창업가) 창업을 한 A 교수의 사례를 중심으로 어떻게 지속해서 창업하고 있는지, 성공 요인이 무엇인지, 어떻게 하면 교원창업이 활성화될 수 있는지 요인들을 파악하고, 연쇄 창업 방법론이 무엇인지 사례조사와 함께 선행연구 문헌 자료 조사, 인터뷰를 중심으로 연구하여 대한민국에서 실질적인 교수창업이 활성화될 수 있는 활성화 모델을 제시하고자 한다. 따라서 본 연구를 통해 교원창업에 있어서 실질적인 애로사항, 현황, 여러 번 인터뷰를 통해 핵심 요인과 원인을 파악하고자 한다. 국가적으로 대학 교원 창업 활성화 모델이 필요한 시점에 실효성이 있고 성과를 창출할 수 있는 활성화 모델을 제시하여 대학의 우수한 연구, 인적 자원을 활용한 혁신 창업 활성화 모델을 새롭게 제시하여 기업가적 대학으로 발전하고 교원들이 적극적으로 창업에 관심을 가지고 성공적인 성과를 창출할 수 있도록 체계를 만들고자 한다. 본 연구에서 제시하는 A교수의 N차(5개 창업) 창업한 사례 연구를 통해 대학 교원들의 혁신창업 활성화를 위한 정책적, 실무적 시사점을 도출하고자 한다.

• Journal of the Korean Society for information Management
• /
• v.41 no.2
• /
• pp.245-268
• /
• 2024

As the recognition of data's value increases, the role of data repositories in managing, preserving, and utilizing data is becoming increasingly important. This study investigates ways to enhance the trustworthiness of data repositories through obtaining CoreTrustSeal (CTS) certification. Trust in data repositories is critical not only for data protection but also for building and maintaining trust between the repository and stakeholders, which in turn affects researchers' decisions on depositing and utilizing data. The study examines the CoreTrustSeal, an international certification for trustworthy data repositories, analyzing its impact on the trustworthiness and efficiency of repositories. Using the example of DataON, Korea's first CTS-certified repository operated by the Korea Institute of Science and Technology Information (KISTI), the study compares and analyzes four repositories that have obtained CTS certification. These include DataON, the Physical Oceanography Distributed Active Archive Center (PO.DAAC) from NASA, Yareta from the University of Geneva, and the DARIAH-DE repository from Germany. The research assesses how these repositories meet the mandatory requirements set by CTS and proposes strategies for improving the trustworthiness of data repositories. Key findings indicate that obtaining CTS certification involves rigorous evaluation of organizational infrastructure, digital object management, and technological aspects. The study highlights the importance of transparent data processes, robust data quality assurance, enhanced accessibility and usability, sustainability, security measures, and compliance with legal and ethical standards. By implementing these strategies, data repositories can enhance their reliability and efficiency, ultimately promoting wider data sharing and utilization in the scientific community.

• Journal of Korean Library and Information Science Society
• /
• v.55 no.1
• /
• pp.193-214
• /
• 2024

This study aimed to propose a method for collecting and applying media platform based materials at the National Library of Korea. Firstly, we analyzed the current status and limitations of data collection based on domestic media platforms, including the National Library of Korea. Secondly, a literature review method was used to investigate the current status and types of digital content based on media platforms. Thirdly, we identified the types of materials based on media platforms that are not currently included in the National Central Library's online material collection guidelines through the examination of cases from major overseas libraries. Fourthly, after reviewing technical and legal elements such as the definition of collection targets and scope for each new media, and collection methods, we established collection criteria. Fifthly, based on the research results, the policies proposed in this study are as follows: 1) there is a need to establish a clear legal basis for the collection of media platform based materials; 2) the development and presentation of collection guidelines for media platform based materials is necessary; 3) the development of collection tools and infrastructure for media platform based materials is required; 4) for the collection of media platform based materials, it is necessary to obtain permission for collection from targeted social media organizations, and to cooperate in linkage with organizations that produce and service extended reality content; 5) for the service activation of media platform based materials, it is necessary to improve accessibility for the usage activation of these materials, to enhance the content extensibility and ease of use of the e-deposit system including extended reality content, and to advance and construct spaces for reproducing extended reality content.

• The Journal of Bigdata
• /
• v.8 no.2
• /
• pp.233-248
• /
• 2023

In the process of building the future of smart cities, innovation in mobility and road infrastructure is one of the most important topics. In particular, with the proliferation of autonomous vehicles and various types of mobility on the road, such as electric bicycles, electric kickboards, and electric wheels, roads have a variety of actors to accommodate, including traditional cars and pedestrians, and conflicts between them need to be resolved. Complete streets, a term coined in the United States in 2003, refers to the design and operation of roads that consider the equitable safety and convenience of all road users, including pedestrians, bicyclists, public transportation users, personal mobility (PM) users, and automobile drivers. Currently, many cities overseas are implementing complete streets, and research is being actively conducted to institutionalize them. However, there is a lack of research and discussion on complete streets in Korea. Therefore, this study aims to formalize the main factors to be considered in the design of complete streets by collecting and analyzing the opinions of academic and practitioner experts through the Delphi method. A total of three Delphi surveys were conducted, collecting free responses from experts through the first open-ended survey and organizing them into keywords to create the second and third closed-ended surveys. The second and third rounds of the survey consisted of a total of 52 questions, and 34 items out of 52 were selected as the final factors.