• Title/Summary/Keyword: big data service

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A Study on the Security Threat Response in Smart Integrated Platforms (스마트 통합플랫폼 보안위협과 대응방안 연구)

  • Seung Jae Yoo
    • Convergence Security Journal
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    • v.22 no.1
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    • pp.129-134
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    • 2022
  • A smart platform is defined as an evolved platform that realizes physical and virtual space into a hyper-connected environment by combining the existing platform and advanced IT technology. The hyper-connection that is the connection between information and information, infrastructure and infrastructure, infrastructure and information, or space and service, enables the realization and provision of high-quality services that significantly change the quality of life and environment of users. In addition, it is providing everyone with the effect of significantly improving the social safety net and personal health management level by implementing smart government and smart healthcare. A lot of information produced and consumed in these processes can act as a factor threatening the basic rights of the public and individuals by the informations themselves or through big data analysis. In particular, as the smart platform as a core function that forms the ecosystem of a smart city is naturally and continuously expanded, it faces a huge security burden in data processing and network operation. In this paper, platform components as core functions of smart city and appropriate security threats and countermeasures are studied.

Development of Real-Time Optimal Bus Scheduling Models (실시간 버스 운행계획수립 모형 개발)

  • Kim, Wongil;Son, Bongsoo;Chung, Jin-Hyuk;Lee, Jeomho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.5D
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    • pp.587-595
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    • 2008
  • Many studies on bus scheduling optimization have been done from the 1960s to recent years for establishing rational bus schedule plan that can improve convenience of bus passengers and minimize unnecessary runs. After 2000, as part of the Intelligent Transport Systems (ITS), the importance of the schedule management and providing schedule information through bus schedule optimization has become a big issue, and much research is being done to develop optimization models that will increase bus passenger convenience and, on the side of bus management, minimize unnecessary bus operation. The purpose of this study is to calculate the optimal bus frequency and create a timetable for each bus stop by applying DTR or DTRC model that use data for each bus stop and route segment. Model verification process was implemented using data collected from bus management system (BMS) and integrated transit-fare card system for bus route of Seoul's No. 472 line. In order to evaluate the reliability and uncertainty of optimal solution, sensitivity analysis was implemented for the various parameters and assumptions used in the bus scheduling model.

Determinants and Effects of FTA-PASS and ERP System Compatibility (원산지관리시스템(FTA-PASS)과 전사자원관리시스템(ERP)의 연동 수준이 수출 성과에 미치는 영향 분석)

  • Su-Han Hwang;Hyuk-Soo Cho
    • Korea Trade Review
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    • v.45 no.2
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    • pp.1-16
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    • 2020
  • Korea is one of active countries in terms of FTA(Free Trade Agreement) around the globe. Local market is not big enough for Korean companies. This is why Korea is actively participating in FTA with various countries. Individual companies should conform to regulation, policy and system relevant to the agreement. Otherwise, it is not easy for companies to enjoy benefits of FTA. The Korean government is using various FTA programs to support domestic companies, in particular SMEs(Small and Medium-Sized Enterprises). FTA-PASS is a representative program. FTA-PASS is an official program of Korea Customs Service. Korean companies can use the program as free. However, some companies may have difficulties regarding the use of FTA-PASS. The program may cause of compatibility problem related their own ERP(Enterprise Resource Planning) systems. This study is designed to analyze determinants of FTA-PASS and ERP system compatibility. Furthermore this study aims to examine effects of the system compatibility on export performances. This study collected data from Koreas SMEs. In specific, the primary data was based on surveys distributed to 303 SMEs. Based on empirical findings, we could get important determinants to improve compatibility between FTA-PASS and ERP systems. For instance, the government support, product standardization, HS Code clearness and market stability could be considered important determinants. Also, according to empirical findings, a positive relationship between system compatibility an export performance was supported. Analyzing comprehensive determinants of system compatibility can be suggested as an important topic for future research.

A comparative study on eating habits and mental health of Korean middle school students according to their bedtime across regions: using data from the 2020-2022 Korea Youth Risk Behavior Survey

  • Sarim Kim;Jiyoung Jeong;Juyeon Kang;Jihye Kim;Yoon Jung Yang
    • Nutrition Research and Practice
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    • v.18 no.2
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    • pp.269-281
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    • 2024
  • BACKGROUND/OBJECTIVES: The objective of this study was to compare dietary habits and mental health among middle school students in urban and rural areas based on bedtime, and to provide evidence supporting appropriate bedtime for Korean middle school students in relation to their healthy dietary habits and mental well-being. SUBJECTS/METHODS: The study population consisted of 25,681 second-year middle school students who participated in the Korea Youth Risk Behavior Survey in 2020-2022. Participants were asked about their bedtime and wake-up time during the past 7 days and were classified into five categories. The study compared the general characteristics, academic factors, dietary habits, and mental health of urban and rural students based on their bedtime. RESULTS: Bedtime was found to be later in the following order: urban female students, rural female students, urban male students, and rural male students. As bedtime got later, the rates of smoking and alcohol consumption increased. Students who went to bed before 11 p.m. had lower academic performance, while rural male students who went to bed after 2 a.m. had lower academic performance. Later bedtime was associated with increased smartphone usage, skipping breakfast, consuming fast food, and drinking carbonated beverages. Later bedtime was also associated with higher perceived stress levels, particularly among students who went to bed after 2 a.m., higher rates of suicidal ideation, experiencing sadness and despair, as well as the prevalence of clinically significant anxiety disorders. CONCLUSION: These results suggest that middle school students who go to bed too late have higher rates of smoking and alcohol drinking, as well as unhealthy eating habits, stress, suicidal ideation, sadness, and anxiety. Therefore, it is necessary to provide educational and social institutional support to promote adequate sleep for the health of adolescents.

Descriptive Review of Patents in Healthcare and Nursing: Based on Network Analysis (네트워크 분석을 활용한 보건의료 및 간호관련 특허의 특징: 서술적 고찰)

  • Jeon, Misun;Youn, Nayung;Kim, Sanghee
    • Journal of Korean Academy of Nursing
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    • v.54 no.1
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    • pp.1-17
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    • 2024
  • Purpose: The significance of the healthcare industry has grown exponentially in recent years due to the impact of the fourth industrial revolution and the ongoing pandemic. Accordingly, this study aimed to examine domestic healthcare-related patents comprehensively. Big data analysis was used to present the trend and status of patents filed in nursing. Methods: The descriptive review was conducted based on Grant and Booth's descriptive review framework. Patents related to nursing was searched in the Korea Intellectual Property Rights Information Service between January 2016 to December 2020. Data analysis included descriptive statistics, phi-coefficient for correlations, and network analysis using the R program (version 4.2.2). Results: Among 37,824 patents initially searched, 1,574 were selected based on the inclusion criteria. Nursing-related patents did not specify subjects, and many patents (41.4%) were related to treatment in the healthcare delivery phase. Furthermore, most patents (56.1%) were designed to increase effectiveness. The words frequently used in the titles of nursing-related patents were, in order, "artificial intelligence," "health management," and "medical information," and the main terms with high connection centrality were "artificial intelligence" and "therapeutic system." Conclusion: The industrialization of nursing is the best solution for developing the healthcare industry and national health promotion. Collaborations in education, research, and policy will help the nursing industry become a healthcare industry of the future. This will prime the enhancement of the national economy and public health.

Study of major issues and trends facing ports, using big data news: From 1991 to 2020 (뉴스 빅데이터를 활용한 항만이슈 변화연구 : 1991~2020)

  • Yoon, Hee-Young
    • Journal of Korea Port Economic Association
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    • v.37 no.1
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    • pp.159-178
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    • 2021
  • This study analyzed issues and trends related to ports with 86,611 news articles for the 30 years from 1991 to 2020, using BIGKinds, a big data news analysis service. The analysis was based on keyword analysis, word cloud, relationship diagram analysis offered by BIG Kinds. Analysis results of issues and trends on ports for the last 30 years are summarized as follows. First, during Phase 1 (1991-2000), individual ports such as Busan, Incheon, and Gwangyang ports tried to strengthen their own competitiveness. During Phase 2 (2001-2010), efforts were made on gaining more professional and specialized port management abilities by establishing the Busan Port Authority in 2004, the Incheon Port Authority in 2005, and the Ulsan Port Authority in 2007. During Phase 3 (2011-2020), the promotion of future-oriented, eco-friendly, and smart ports was major issues. Efforts to reduce particulate matters and pollutants produced from ports were accelerated, and an attempt to build a smart port driven by port automation and digitalization was also intensified. Lastly, in 2020, when the maritime sector was severely hit by the unexpected shock of the COVID-19 pandemic, a microscopic analysis of trends and issues in 2019 and 2020 was made to look into the impact the pandemic on the maritime industry. It was found that shipping and port industries experienced more drastic changes than ever while trying to prepare for a post-pandemic era as well as promoting future-oriented ports. This study made policy suggestions by analyzing port-related news articles and trends, and it is expected that based on the findings of this research, further studies on enhancing the competitiveness of ports and devising a sustainable development strategy will follow through a comparative analysis of port issues of different countries, thereby making further progress toward academic research on ports.

Recommendation of Best Empirical Route Based on Classification of Large Trajectory Data (대용량 경로데이터 분류에 기반한 경험적 최선 경로 추천)

  • Lee, Kye Hyung;Jo, Yung Hoon;Lee, Tea Ho;Park, Heemin
    • KIISE Transactions on Computing Practices
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    • v.21 no.2
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    • pp.101-108
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    • 2015
  • This paper presents the implementation of a system that recommends empirical best routes based on classification of large trajectory data. As many location-based services are used, we expect the amount of location and trajectory data to become big data. Then, we believe we can extract the best empirical routes from the large trajectory repositories. Large trajectory data is clustered into similar route groups using Hadoop MapReduce framework. Clustered route groups are stored and managed by a DBMS, and thus it supports rapid response to the end-users' request. We aim to find the best routes based on collected real data, not the ideal shortest path on maps. We have implemented 1) an Android application that collects trajectories from users, 2) Apache Hadoop MapReduce program that can cluster large trajectory data, 3) a service application to query start-destination from a web server and to display the recommended routes on mobile phones. We validated our approach using real data we collected for five days and have compared the results with commercial navigation systems. Experimental results show that the empirical best route is better than routes recommended by commercial navigation systems.

The Analysis of Urban Park Catchment Areas - Perspectives from Quality Service of Hangang Park - (한강공원의 질적 서비스와 이용자 영향권의 상관관계 분석)

  • Lee, Seo Hyo;Kim, Harry;Lee, Jae Ho
    • Journal of the Korean Institute of Landscape Architecture
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    • v.49 no.6
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    • pp.27-36
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    • 2021
  • At a time when the equitable use of urban parks is gradually emerging as a social issue, this study was initiated to expand the influence of urban parks by improving the quality of park services, thereby resolving areas not covered by urban park services. This study targeted the Hangang Park in Seoul, where the qualitative service of parks shows the greatest difference. The influence relationship between the qualitative services of the park and the user's sphere of influence, which indicates the distribution of park users, was proposed to assess the influence of improvements in the quality of service. As a research method, the top three districts and the bottom three districts were selected through the Han River Park user satisfaction survey conducted from 2017 to 2019, and a qualitative service evaluation was carried out. It was derived using the data acquired in September. Afterward, by performing a spatial autocorrelation analysis on the user's sphere of influence, additional verification of the user's sphere of influence was performed numerically and visually. As a result of the study, the user influence in the top three districts, with high-quality service, was stronger and wider than that of the lower three districts. It was confirmed that the quality of service of the park affects the user influence. This shows that to realize park equity, it is necessary to improve the quality of services through continuous management and improvement of individual parks and the creation of new parks. This study has significance in that it recognizes the limitations of research on park services from a supplier's point of view and evaluates the qualitative services of parks from the perspective of actual park users. We propose an alternative to deal with the lower the park deprivation index.

Analysis of Success Cases of InsurTech and Digital Insurance Platform Based on Artificial Intelligence Technologies: Focused on Ping An Insurance Group Ltd. in China (인공지능 기술 기반 인슈어테크와 디지털보험플랫폼 성공사례 분석: 중국 평안보험그룹을 중심으로)

  • Lee, JaeWon;Oh, SangJin
    • Journal of Intelligence and Information Systems
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    • v.26 no.3
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    • pp.71-90
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    • 2020
  • Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

Bioinformatics services for analyzing massive genomic datasets

  • Ko, Gunhwan;Kim, Pan-Gyu;Cho, Youngbum;Jeong, Seongmun;Kim, Jae-Yoon;Kim, Kyoung Hyoun;Lee, Ho-Yeon;Han, Jiyeon;Yu, Namhee;Ham, Seokjin;Jang, Insoon;Kang, Byunghee;Shin, Sunguk;Kim, Lian;Lee, Seung-Won;Nam, Dougu;Kim, Jihyun F.;Kim, Namshin;Kim, Seon-Young;Lee, Sanghyuk;Roh, Tae-Young;Lee, Byungwook
    • Genomics & Informatics
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    • v.18 no.1
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    • pp.8.1-8.10
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    • 2020
  • The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/.