• Title/Summary/Keyword: Research Data Sharing

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Analysis on the Status of Joint Forestry Project in National Forest (국유림 공동산림사업 실태분석에 관한 연구)

  • Kim, Dong-Hyeon;Ko, Chi-Ung;Kim, Dong-Geun
    • Journal of agriculture & life science
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    • v.53 no.6
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    • pp.45-53
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    • 2019
  • The purpose of this study is to analyze the status of the joint forest project, which is one of the national forest management system, by using stakeholder participation, transparency of decision making, accountability of actors and stakeholders, The questionnaire survey was conducted using the 5 - point scale and the written form. As a result of the questionnaire survey, various stakeholder participation items had the highest opportunity to participate with an average of 3.3 and the lowest score with 2.3 points for establishing conflict and conflict resolution structures. Transparency was analyzed to be 3.4 points for the project disclosure, 2.7 points for information sharing and education promotion activities for local residents, 3.3 points for the detailed role of the project implementer, and 2.7 points for internal and external monitoring and evaluation of the project with various stakeholders. The results of this research, analyzed through the participatory forest management index, are deemed to be used as basic data for the establishment of a plan for the revitalization of national forest participation management.

Study on Improvements to Domestic Marine HNS Training Curricula through a Case Analysis of Marine Chemical Incidents (해상화학사고 사례 분석을 통한 국내 해상HNS 교육과정 개선에 관한 연구)

  • Kim, Kwang-Soo
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.1
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    • pp.97-112
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    • 2021
  • This study introduces lessons learned from investigation and analysis of major domestic and overseas cases of marine chemical incidents involving hazardous and noxious substances (HNS) during maritime transportation by chemical tankers carrying petrochemical products in bulk. The study then suggests plans to improve domestic marine HNS training curricula based on these lessons. Lessons learned from six incident cases are classified into the following six categories: 1) incident-related information, 2) safety, 3) pollution, 4) response, 5) salvage and 6) others. Based on these six categories, it is suggested that the curriculum provided by the Marine Environment Research & Training Institute for marine pollution prevention managers aboard noxious liquid substance carriers should be changed from the existing two-day training of eight subjects (16 h) to a three-day training of sixteen subjects (24 h). In addition, it is proposed that the marine chemical incident response course of the Korea Coast Guard Academy should be changed from the existing five-day training of fifteen subjects (35 h) to a six-day training of thirty-two subjects (48 h). These results are expected to contribute to sharing experiences and lessons learned about response to marine chemical incidents and to be used as basic data for improving the education and training courses for response personnel in preparedness for marine HNS incidents.

Effects of Organizational Justice on Emotions, Job Satisfaction, and Turnover Intention in Franchise Industry (조직공정성이 감정, 직무만족 그리고 이직의도에 미치는 영향)

  • Han, Sang-Ho;Lee, Yong-Ki;Lee, Jae-Gyu
    • The Korean Journal of Franchise Management
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    • v.9 no.2
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    • pp.7-16
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    • 2018
  • Purpose - Turnover Intention in the franchise industry is becoming a very important issue. This study examines the structural relationships between organizational justice, emotion, job satisfaction, and turnover intention in the franchise industry. In this model, emotion was classified into two sub-dimensions such as positive and negative emotion. Research design, data, methodology - The sample of this study collected from employees of a food-service franchise company is representative. Copies of the questionnaire along with a cover letter were delivered by a research assistant to the human resources manager or the general manager of the selected food-service franchise firms after they agreed to participate in the study. In order to increase the response rate of the respondents, a small gift was provided to the respondents who completed the questionnaire. A total of 300 questionnaires were distributed and 285 returned responses, 9 responses were not usable due to missing information. Thus, a total of 276 responses were used using structural equation modeling with Smartpls 3.0. Results - The results showed that organizational justice had positive significant effects on positive emotion and job satisfaction. Job satisfaction had negative a significant effect on turnover intention. And negative emotion had positive significant effect on turnover intention. Conclusions - The results of this study provide some implications. If employees feel that the franchise headquarters is fair about the methods and procedures of decision making, resource allocation, information sharing, etc., it means that employees feel better. If the franchise's decision-making processes and methods and results are transparently disclosed and processed in accordance with the internal rules of the company, the employees will be able to fully understand and accept them. The results of this study also show that positive and negative emotions of service-based franchise employees have different effects on job attitude and organizational behavior. In particular, when negative emotions of employees are passed on to others and the results are negative, employees may feel that they are disoriented or wrong. Therefore, the franchise headquarters should try to inspire employees' sense of organizational community, and should pay attention to how to relieve the job stress and the fair distribution of work and rewards.

Enhancing Project Integration and Interoperability of GIS and BIM Based on IFC (IFC 기반 GIS와 BIM 프로젝트 통합관리 및 상호 운용성 강화)

  • Kim, Tae-Hee;Kim, Tae-Hyun;Lee, Yong-Chang
    • Journal of Cadastre & Land InformatiX
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    • v.54 no.1
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    • pp.89-102
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    • 2024
  • The recent advancements in Smart City and Digital Twin technologies have highlighted the critical role of integrating GIS and BIM in urban planning and construction projects. This integration ensures the consistency and accuracy of information, facilitating smooth information exchange. However, achieving interoperability requires standardization and effective project integration management strategies. This study proposes interoperability solutions for the integration of GIS and BIM for managing various projects. The research involves an in-depth analysis of the IFC schema and data structures based on the latest IFC4 version and proposes methods to ensure the consistency of reference point coordinates and coordinate systems. The study was conducted by setting the EPSG:5186 coordinate system, used by the National Geographic Information Institute's digital topographic map, and applying virtual shift origin coordinates. Through BIMvision, the results of the shape and error check coordinates' movement in the BIM model were reviewed, confirming that the error check coordinates moved consistently with the reference point coordinates. Additionally, it was verified that even when the coordinate system was changed to EPSG:5179 used by Naver Map and road name addresses, or EPSG:5181 used by Kakao Map, the BIM model's shape and coordinates remained consistently unchanged. Notably, by inputting the EPSG code information into the IFC file, the potential for coordinate system interoperability between projects was confirmed. Therefore, this study presents an integrated and systematic management approach for information sharing, automation processes, enhanced collaboration, and sustainable development of GIS and BIM. This is expected to improve compatibility across various software platforms, enhancing information consistency and efficiency across multiple projects.

2021 Korean Thyroid Imaging Reporting and Data System and Imaging-Based Management of Thyroid Nodules: Korean Society of Thyroid Radiology Consensus Statement and Recommendations

  • Eun Ju Ha;Sae Rom Chung;Dong Gyu Na;Hye Shin Ahn;Jin Chung;Ji Ye Lee;Jeong Seon Park;Roh-Eul Yoo;Jung Hwan Baek;Sun Mi Baek;Seong Whi Cho;Yoon Jung Choi;Soo Yeon Hahn;So Lyung Jung;Ji-hoon Kim;Seul Kee Kim;Soo Jin Kim;Chang Yoon Lee;Ho Kyu Lee;Jeong Hyun Lee;Young Hen Lee;Hyun Kyung Lim;Jung Hee Shin;Jung Suk Sim;Jin Young Sung;Jung Hyun Yoon;Miyoung Choi
    • Korean Journal of Radiology
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    • v.22 no.12
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    • pp.2094-2123
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    • 2021
  • Incidental thyroid nodules are commonly detected on ultrasonography (US). This has contributed to the rapidly rising incidence of low-risk papillary thyroid carcinoma over the last 20 years. The appropriate diagnosis and management of these patients is based on the risk factors related to the patients as well as the thyroid nodules. The Korean Society of Thyroid Radiology (KSThR) published consensus recommendations for US-based management of thyroid nodules in 2011 and revised them in 2016. These guidelines have been used as the standard guidelines in Korea. However, recent advances in the diagnosis and management of thyroid nodules have necessitated the revision of the original recommendations. The task force of the KSThR has revised the Korean Thyroid Imaging Reporting and Data System and recommendations for US lexicon, biopsy criteria, US criteria of extrathyroidal extension, optimal thyroid computed tomography protocol, and US follow-up of thyroid nodules before and after biopsy. The biopsy criteria were revised to reduce unnecessary biopsies for benign nodules while maintaining an appropriate sensitivity for the detection of malignant tumors in small (1-2 cm) thyroid nodules. The goal of these recommendations is to provide the optimal scientific evidence and expert opinion consensus regarding US-based diagnosis and management of thyroid nodules.

Implementation Strategy of Global Framework for Climate Service through Global Initiatives in AgroMeteorology for Agriculture and Food Security Sector (선도적 농림기상 국제협력을 통한 농업과 식량안보분야 전지구기후 서비스체계 구축 전략)

  • Lee, Byong-Lyol;Rossi, Federica;Motha, Raymond;Stefanski, Robert
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.15 no.2
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    • pp.109-117
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    • 2013
  • The Global Framework on Climate Services (GFCS) will guide the development of climate services that link science-based climate information and predictions with climate-risk management and adaptation to climate change. GFCS structure is made up of 5 pillars; Observations/Monitoring (OBS), Research/ Modeling/ Prediction (RES), Climate Services Information System (CSIS) and User Interface Platform (UIP) which are all supplemented with Capacity Development (CD). Corresponding to each GFCS pillar, the Commission for Agricultural Meteorology (CAgM) has been proposing "Global Initiatives in AgroMeteorology" (GIAM) in order to facilitate GFCS implementation scheme from the perspective of AgroMeteorology - Global AgroMeteorological Outlook System (GAMOS) for OBS, Global AgroMeteorological Pilot Projects (GAMPP) for RES, Global Federation of AgroMeteorological Society (GFAMS) for UIP/RES, WAMIS next phase for CSIS/UIP, and Global Centers of Research and Excellence in AgroMeteorology (GCREAM) for CD, through which next generation experts will be brought up as virtuous cycle for human resource procurements. The World AgroMeteorological Information Service (WAMIS) is a dedicated web server in which agrometeorological bulletins and advisories from members are placed. CAgM is about to extend its service into a Grid portal to share computer resources, information and human resources with user communities as a part of GFCS. To facilitate ICT resources sharing, a specialized or dedicated Data Center or Production Center (DCPC) of WMO Information System for WAMIS is under implementation by Korea Meteorological Administration. CAgM will provide land surface information to support LDAS (Land Data Assimilation System) of next generation Earth System as an information provider. The International Society for Agricultural Meteorology (INSAM) is an Internet market place for agrometeorologists. In an effort to strengthen INSAM as UIP for research community in AgroMeteorology, it was proposed by CAgM to establish Global Federation of AgroMeteorological Society (GFAMS). CAgM will try to encourage the next generation agrometeorological experts through Global Center of Excellence in Research and Education in AgroMeteorology (GCREAM) including graduate programmes under the framework of GENRI as a governing hub of Global Initiatives in AgroMeteorology (GIAM of CAgM). It would be coordinated under the framework of GENRI as a governing hub for all global initiatives such as GFAMS, GAMPP, GAPON including WAMIS II, primarily targeting on GFCS implementations.

Deriving adoption strategies of deep learning open source framework through case studies (딥러닝 오픈소스 프레임워크의 사례연구를 통한 도입 전략 도출)

  • Choi, Eunjoo;Lee, Junyeong;Han, Ingoo
    • Journal of Intelligence and Information Systems
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    • v.26 no.4
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    • pp.27-65
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    • 2020
  • Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

Needs analysis for development of training program for newly appointed Home Economics teachers - Focusing on the participants of first-grade teachers qualification training - (초임기 가정과 교사 직무연수 프로그램 개발에 대한 요구 분석 - 1급 정교사 가정 자격연수 대상자 중심으로 -)

  • Lee, Hyunjung
    • Journal of Korean Home Economics Education Association
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    • v.30 no.1
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    • pp.15-28
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    • 2018
  • Teachers are not completed by appointment, but gradually made through self-development and training for a long time. In order to improve a sense of responsibility of home economics teachers, and also to suggest the purpose and direction of program through job training, the needs of training subjects should be preferentially understood. Thus, this study aims to provide basic data for establishing the developmental operation measures of training for home economics teachers, by researching the needs for training performed after the qualification training for first-grade teachers, targeting the teachers participating in the qualification training program for first-grade teachers of home economics in 2017. About the half of the research subjects received the home economics training one time or less for last three years. Through the training for first-grade teachers, the technical improvement of lesson instruction was demanded the most. As professional qualifications that should be cultivated through training, the ability to develop teaching methods and teaching/learning materials was the highest. Regarding the theme of training, the development of teaching/learning materials for home economics was desired the most. They wanted the training method including direct participation with high utilization for lesson, sublation of competition-centered evaluation, preference of instructors with field experience, continuous opportunity of home economics training, and communicative training. Regarding the needs for the 2015 revised curriculum, the demand for the training of 'human development and family' area was the highest. Therefore, in order to improve the professionalism of teachers through home economics training, it would be necessary to improve the educational environment such as temporal room for training and administrative support, and also to provide diverse types of training like group training, remote training, and smartphone app training suitable for changes in the generation of teachers. Also, on top of forming communities of home economics teachers, and sharing great contents of training, there should be individually-customized training for practice and sharing lesson cases.

Analysis of Social Trends for Electric Scooters Using Dynamic Topic Modeling and Sentiment Analysis (동적 토픽 모델링과 감성 분석을 활용한 전동킥보드에 대한 사회적 동향 분석)

  • Kyoungok, Kim;Yerang, Shin
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.1
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    • pp.19-30
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    • 2023
  • An electric scooter(e-scooter), one popularized micro-mobility vehicle has shown rapidly increasing use in many cities. In South Korea, the use of e-scooters has greatly increased, as some companies have launched e-scooter sharing services in a few large cities, starting with Seoul in 2018. However, the use of e-scooters is still controversial because of issues such as parking and safety. Since the perception toward the means of transportation affects the mode choice, it is necessary to track the trends for electric scooters to make the use of e-scooters more active. Hence, this study aimed to analyze the trends related to e-scooters. For this purpose, we analyzed news articles related to e-scooters published from 2014 to 2020 using dynamic topic modeling to extract issues and sentiment analysis to investigate how the degree of positive and negative opinions in news articles had changed. As a result of topic modeling, it was possible to extract three different topics related to micro-mobility technologies, shared e-scooter services, and regulations for micro-mobility, and the proportion of the topic for regulations for micro-mobility increased as shared e-scooter services increased in recent years. In addition, the top positive words included quick, enjoyable, and easy, whereas the top negative words included threat, complaint, and ilegal, which implies that people satisfied with the convenience of e-scooter or e-scooter sharing services, but safety and parking issues should be addressed for micro-mobility services to become more active. In conclusion, this study was able to understand how issues and social trends related to e-scooters have changed, and to determine the issues that need to be addressed. Moreover, it is expected that the research framework using dynamic topic modeling and sentiment analysis will be helpful in determining social trends on various areas.

A Study on the Application of the Smartphone Hiking Apps for Analyzing the User Characteristics in Forest Recreation Area: Focusing on Daegwallyoung Area (산림휴양공간 이용특성 분석을 위한 국내 스마트폰 산행앱(APP)의 적용성 및 활용방안 연구: 대관령 선자령 일대를 중심으로)

  • Jang, Youn-Sun;Yoo, Rhee-Hwa;Lee, Jeong-Hee
    • Journal of Korean Society of Forest Science
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    • v.108 no.3
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    • pp.382-391
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    • 2019
  • This study was conducted to verify whether smartphone hiking apps, which generate social network data including location information, are useful tools for analyzing the use characteristics of a forest recreation area. For this purpose, the study identified the functions and service characteristics of smartphone hiking apps. Also, the use characteristics of the area of Daegwallyoung were analyzed, compared with the results of the field survey, and the applicability of hiking apps was reviewed. As a result, the service types of hiking apps were analyzed in terms of three categories: "information offering," "hiking record," and "information sharing." This study focused on an app that is one of the "hiking record" types with the greatest number of users. Analysis of the data from hiking apps and a field survey in the Daegwallyoung area showed that both hiking apps and the field survey can be used to identify the movement patterns, but hiking apps based on a global positioning system (GPS) are more efficient and objective tools for understanding the use patterns in a forest recreation area, as well as for extracting user-generated photos. Second, although it is advantageous to analyze the patterns objectively through the walking-speed data generated, field surveys and observation are needed as complements for understanding the types of activities in each space. The hiking apps are based on cellphone use and are specific to "hiking" use, so user bias can limit the usefulness of the data. It is significant that this research shows the applicability of hiking apps for analyzing the use patterns of forest recreation areas through the location-based social network data of app users who record their hiking information voluntarily.