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A Study on the Development Direction of Medical Image Information System Using Big Data and AI (빅데이터와 AI를 활용한 의료영상 정보 시스템 발전 방향에 대한 연구)

  • Yoo, Se Jong;Han, Seong Soo;Jeon, Mi-Hyang;Han, Man Seok
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.9
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    • pp.317-322
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    • 2022
  • The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

Performance Optimization of Numerical Ocean Modeling on Cloud Systems (클라우드 시스템에서 해양수치모델 성능 최적화)

  • JUNG, KWANGWOOG;CHO, YANG-KI;TAK, YONG-JIN
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.27 no.3
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    • pp.127-143
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    • 2022
  • Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

Development of Coaching Model to Enhance Teaching Capability of Lifelong Educator (평생교육교수자의 교수역량 강화를 위한 코칭모델 개발)

  • Son, Sung Hwa;Kim, Jin Sook
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.4
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    • pp.369-376
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    • 2021
  • The purpose of this study is to develop a coaching model which can enhance teaching ability of lifelong educator. To achieve this purpose, this study verifies and analyzes several documentary records related with diverse teaching capabilities, operation reality and coaching method run by lifelong educator. Furthermore, an in-depth interview about teaching capability was undertaken for field experts who have worked at the institutions of lifelong education for more than 10 years. As a result, the study could develop a coaching model to identify teaching capability of lifelong educator by conducting matrix analysis. First, according to the documentary studies, the paradigm for lifelong education has been shifted to centralize learner's demand with the advent of 4th industrial revolution and it suggests coaching capability which could enhance educator's capability should come first. A lifelong educator should have capabilities including identification of vision and goal, creation of mission declaration, development of coaching skill and procedure, management of crisis and coaching capability as an expert in the lifelong education field. Second, a model which can centralize learners could be developed for lifelong teaching capability by adopting a teaching capability suggested by field experts, According to the experts, it is essential to develop a program model to acquire professional knowledge, communication capability, understanding of adult learner, personal relations capability. If there is a model which can develop such capabilities, it is able to strengthen lifelong teaching capability to focus on learner's demand, mainly adult learners, a major consumer of the field. Third, a coaching model to enhance teaching capability for an educator is to acquire and implement sufficient step-by-step teaching capability which has been suggested from a procedure comprised of entrance, progress, critique and return. This, present study suggests, after the critique, a lifelong educator oneself can newly develop and extend a teaching capability basis on pursuing teaching capability as a lifelong educator through the return process.

An Exploratory study on derivation and Improvement of Kano Quality Attributes in Untact Classes (비대면 수업의 Kano 품질속성 도출과 개선에 관한 탐색적 연구)

  • Daeho Byun;Jaehoon Yang
    • Journal of Service Research and Studies
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    • v.12 no.2
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    • pp.65-79
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    • 2022
  • Non-face-to-face classes continue due to Covid-19. There have been e-learning classes since the past, but the difference is that the current non-face-to-face classes are blended classes that combine real-time and recording classes or combine face-to-face and non-face classes. It is also characterized by being able to self-filmed or choose various lecture platforms in a place other than a dedicated studio. The advantages of non-face-to-face classes can be learned beyond time and space, and repetitive viewing and learning speed can be adjusted. Greening classes have no time and place constraints, and real-time classes have the advantage of high communication effects with learners. Evaluating whether non-face-to-face classes provide sufficient quality compared to face-to-face classes or e-learning will be necessary if branded classes are considered for post Covid. In this paper, for the evaluation of the service quality of non-face-to-face classes, the essential attributes desired by the instructors were derived from the viewpoint of Kano quality attributes and a quality improvement plan was proposed. After expressing the degree of functions that non-face-to-face classes should have on the X-axis and the satisfaction of learners on the Y-axis, 23 quality attributes were classified into 6 quality dimensions. In addition, satisfaction coefficient, dissatisfaction coefficient, and customer satisfaction improvement index were derived. As a result, 50% of learners were satisfied with non-face-to-face classes, but the preference was slightly higher than satisfaction, suggesting the sustainability of non-face-to-face classes. In terms of the customer satisfaction improvement index, the ranking of attributes with the largest increase in satisfaction when improving class quality was as follows. Professors' quick answers to learners' questions, content that can fully explain the subject, what the professor explains easily, develop high-quality content that can be learned on mobile phones, fairness of attendance checks, and real-time classes should start on time.

An Qualitative Study on Correctional institution Counselors' Perception of Ex-Offender's Experience regarding Reintegration into Family (수감자의 출소 후 가족복귀 경험에 관한 교정기관 상담자의 인식)

  • Dong Hun Lee ;Su Eun Kang ;Seung Hee Jee
    • Korean Journal of Culture and Social Issue
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    • v.22 no.4
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    • pp.595-622
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    • 2016
  • This study aims to understand the process of family reunion of the ex-offenders. To this end, Korea Rehabilitation Agency under Ministry of Justice and Healthy Family Support Center conducted intensive interviews with ex-offenders, their families and with 8 counselors who are in charge of ex-offenders and their families' residential, psychological, and educational support. The data collected through the interviews were analyzed by Consensus Qualitative Research(COR). The followings are the results: the counselors found out that most of ex-offenders had experienced unhappy childhood which was lack of healthy relationship with their parents. Secondly, counselors noticed a common feature among the families of ex-offenders. The common feature was that they keep the fact that one of their parents was imprisoned to their children as a secret. Thirdly, through the data analysis, counselors could understand various factors that affect reunion of ex-offenders' families: the factors that helped successful reunion were ex-offenders' sense of responsibility, open and healthy communication among family members, and mutual understanding of being a good family member, whereas, irresponsible dependance to other family members, denier and avoidance from the family members against ex-offenders, and lost sense of being a family member were the factors that discouraged the reunion. It turned out that the kinds of crime that ex-offenders committed also affected family reunion. The processes of reunion were easier for those who served their time with fraud, embezzlement, whereas, it was much more challenging for those who served their time with rape, violence, or murder. Fourthly, counselors learned that "relaxation" is the key factor in the process of reunion of ex-offenders' families. They also emphasized that there should be thorough monitoring process before the intervention in the reunion process. This study contributes in terms of finding healthy ways of intervention with ex-offenders' families and developing programs that help ex-offenders to recover their relationship with their family.

A Study on Human-Robot Interaction Trends Using BERTopic (BERTopic을 활용한 인간-로봇 상호작용 동향 연구)

  • Jeonghun Kim;Kee-Young Kwahk
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.185-209
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    • 2023
  • With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.

A CF-based Health Functional Recommender System using Extended User Similarity Measure (확장된 사용자 유사도를 이용한 CF-기반 건강기능식품 추천 시스템)

  • Sein Hong;Euiju Jeong;Jaekyeong Kim
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.1-17
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    • 2023
  • With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

A Study on Industry-specific Sustainability Strategy: Analyzing ESG Reports and News Articles (산업별 지속가능경영 전략 고찰: ESG 보고서와 뉴스 기사를 중심으로)

  • WonHee Kim;YoungOk Kwon
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.287-316
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    • 2023
  • As global energy crisis and the COVID-19 pandemic have emerged as social issues, there is a growing demand for companies to move away from profit-centric business models and embrace sustainable management that balances environmental, social, and governance (ESG) factors. ESG activities of companies vary across industries, and industry-specific weights are applied in ESG evaluations. Therefore, it is important to develop strategic management approaches that reflect the characteristics of each industry and the importance of each ESG factor. Additionally, with the stance of strengthened focus on ESG disclosures, specific guidelines are needed to identify and report on sustainable management activities of domestic companies. To understand corporate sustainability strategies, analyzing ESG reports and news articles by industry can help identify strategic characteristics in specific industries. However, each company has its own unique strategies and report structures, making it difficult to grasp detailed trends or action items. In our study, we analyzed ESG reports (2019-2021) and news articles (2019-2022) of six companies in the 'Finance,' 'Manufacturing,' and 'IT' sectors to examine the sustainability strategies of leading domestic ESG companies. Text mining techniques such as keyword frequency analysis and topic modeling were applied to identify industry-specific, ESG element-specific management strategies and issues. The analysis revealed that in the 'Finance' sector, customer-centric management strategies and efforts to promote an inclusive culture within and outside the company were prominent. Strategies addressing climate change, such as carbon neutrality and expanding green finance, were also emphasized. In the 'Manufacturing' sector, the focus was on creating sustainable communities through occupational health and safety issues, sustainable supply chain management, low-carbon technology development, and eco-friendly investments to achieve carbon neutrality. In the 'IT' sector, there was a tendency to focus on technological innovation and digital responsibility to enhance social value through technology. Furthermore, the key issues identified in the ESG factors were as follows: under the 'Environmental' element, issues such as greenhouse gas and carbon emission management, industry-specific eco-friendly activities, and green partnerships were identified. Under the 'Social' element, key issues included social contribution activities through stakeholder engagement, supporting the growth and coexistence of members and partner companies, and enhancing customer value through stable service provision. Under the 'Governance' element, key issues were identified as strengthening board independence through the appointment of outside directors, risk management and communication for sustainable growth, and establishing transparent governance structures. The exploration of the relationship between ESG disclosures in reports and ESG issues in news articles revealed that the sustainability strategies disclosed in reports were aligned with the issues related to ESG disclosed in news articles. However, there was a tendency to strengthen ESG activities for prevention and improvement after negative media coverage that could have a negative impact on corporate image. Additionally, environmental issues were mentioned more frequently in news articles compared to ESG reports, with environmental-related keywords being emphasized in the 'Finance' sector in the reports. Thus, ESG reports and news articles shared some similarities in content due to the sharing of information sources. However, the impact of media coverage influenced the emphasis on specific sustainability strategies, and the extent of mentioning environmental issues varied across documents. Based on our study, the following contributions were derived. From a practical perspective, companies need to consider their characteristics and establish sustainability strategies that align with their capabilities and situations. From an academic perspective, unlike previous studies on ESG strategies, we present a subdivided methodology through analysis considering the industry-specific characteristics of companies.

A Changes in China's Landscape Scenic Sites System and Suggestions for Application of Major Policies to Scenic Sites of Korea (중국 풍경명승구 제도의 변천과 주요정책의 국내 명승 적용 제언)

  • Kim, Dong-Hyun;Lee, Jian-Feng;Shin, Hyun-Sil
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.41 no.2
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    • pp.11-18
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    • 2023
  • This study aims to distinguish what can be used in consideration of the national situation with Korea for Chinese Scenic and Historic Interest Areas, and the results are as follows; First, the Chinese Scenic and Historic Interest Areas expanded to the existing scenic cruise culture, travel, and tourism culture in the process of the influx of Western culture in the modern and contemporary era, and became popular as a travel destination. Accordingly, the Chinese government developed the tourism industry around the scenic sites, and thanks to the development of transportation and communication, the Scenic and Historic Interest Areas has become an important national heritage. This influenced the establishment of the system related to Scenic and Historic Interest Areas, and today, it is operated around the Scenic and Historic Interest Areas ordinance. Second, the designation of the Scenic and Historic Interest Areas is divided into the size of the site according to the area, and the process of selecting the Scenic and Historic Interest Areas classification, rating evaluation, and comprehensive value evaluation according to evaluation indicators and rating standards is carried out. Accordingly, according to the results of the classification, it is subdivided from the national level to the Scenic and Historic Interest Areas at the local level. Third, the central government is in charge of managing and supervising Scenic and Historic Interest Areas across the country, and the local government's construction department is in charge of supervising Scenic and Historic Interest Areas in the region. The management organization of Scenic and Historic Interest Areas established by local governments above the county level has a system that actually protects, utilizes, and manages Scenic and Historic Interest Areas. In addition, 14 detailed indicators are used to monitor Scenic and Historic Interest Areas. Based on these results, considering the application of the domestic scenic site policy, the method of developing the policy that has established the system from the perspective of the utilization of the people is worth considering. On the other hand, the evaluation of the designation and management system through the setting of various indicators has limitations in that it is difficult to secure objectivity in impressing or evaluating the landscape. Therefore, rather than blindly introducing quantified evaluation, it seems that guidance and promotion on how to expand consensus on scenic values and enjoy heritage should be prioritized.

Multiple SL-AVS(Small size & Low power Around View System) Synchronization Maintenance Method (다중 SL-AVS 동기화 유지기법)

  • Park, Hyun-Moon;Park, Soo-Huyn;Seo, Hae-Moon;Park, Woo-Chool
    • Journal of the Korea Society for Simulation
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    • v.18 no.3
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    • pp.73-82
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    • 2009
  • Due to the many advantages including low price, low power consumption, and miniaturization, the CMOS camera has been utilized in many applications, including mobile phones, the automotive industry, medical sciences and sensoring, robotic controls, and research in the security field. In particular, the 360 degree omni-directional camera when utilized in multi-camera applications has displayed issues of software nature, interface communication management, delays, and a complicated image display control. Other issues include energy management problems, and miniaturization of a multi-camera in the hardware field. Traditional CMOS camera systems are comprised of an embedded system that consists of a high-performance MCU enabling a camera to send and receive images and a multi-layer system similar to an individual control system that consists of the camera's high performance Micro Controller Unit. We proposed the SL-AVS (Small Size/Low power Around-View System) to be able to control a camera while collecting image data using a high speed synchronization technique on the foundation of a single layer low performance MCU. It is an initial model of the omni-directional camera that takes images from a 360 view drawing from several CMOS camera utilizing a 110 degree view. We then connected a single MCU with four low-power CMOS cameras and implemented controls that include synchronization, controlling, and transmit/receive functions of individual camera compared with the traditional system. The synchronization of the respective cameras were controlled and then memorized by handling each interrupt through the MCU. We were able to improve the efficiency of data transmission that minimizes re-synchronization amongst a target, the CMOS camera, and the MCU. Further, depending on the choice of users, respective or groups of images divided into 4 domains were then provided with a target. We finally analyzed and compared the performance of the developed camera system including the synchronization and time of data transfer and image data loss, etc.