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Determining Food Nutrition Information Preference Through Big Data Log Analysis (빅데이터 로그분석을 통한 식품영양정보 선호도 분석)

  • Hana Song;Hae-Jeung, Lee;Hunjoo Lee
    • Journal of Food Hygiene and Safety
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    • v.38 no.5
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    • pp.402-408
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    • 2023
  • Consumer interest in food nutrition continues to grow; however, research on consumer preferences related to nutrition remains limited. In this study, big data analysis was conducted using keyword logs collected from the national information service, the Korean Food Composition Database (K-FCDB), to determine consumer preferences for foods of nutritional interest. The data collection period was set from January 2020 to December 2022, covering a total of 2,243,168 food name keywords searched by K-FCDB users. Food names were processed by merging them into representative food names. The search frequency of food names was analyzed for the entire period and by season using R. In the frequency analysis for the entire period, steamed rice, chicken, and egg were found to be the most frequently consumed foods by Koreans. Seasonal preference analysis revealed that in the spring and summer, foods without broth and cold dishes were consumed frequently, whereas in fall and winter, foods with broth and warm dishes were more popular. Additionally, foods sold by restaurants as seasonal items, such as Naengmyeon and Kongguksu, also exhibited seasonal variations in frequency. These results provide insights into consumer interest patterns in the nutritional information of commonly consumed foods and are expected to serve as fundamental data for formulating seasonal marketing strategies in the restaurant industry, given their indirect relevance to consumer trends.

Comparative Analysis of Low Fertility Response Policies (Focusing on Unstructured Data on Parental Leave and Child Allowance) (저출산 대응 정책 비교분석 (육아휴직과 아동수당의 비정형 데이터 중심으로))

  • Eun-Young Keum;Do-Hee Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.769-778
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    • 2023
  • This study compared and analyzed parental leave and child allowance, two major policies among solutions to the current serious low fertility rate problem, using unstructured data, and sought future directions and implications for related response policies based on this. The collection keywords were "low fertility + parental leave" and "low fertility + child allowance", and data analysis was conducted in the following order: text frequency analysis, centrality analysis, network visualization, and CONCOR analysis. As a result of the analysis, first, parental leave was found to be a realistic and practical policy in response to low fertility rates, as data analysis showed more diverse and systematic discussions than child allowance. Second, in terms of child allowance, data analysis showed that there was a high level of information and interest in the cash grant benefit system, including child allowance, but there were no other unique features or active discussions. As a future improvement plan, both policies need to utilize the existing system. First, parental leave requires improvement in the working environment and blind spots in order to expand the system, and second, child allowance requires a change in the form of payment that deviates from the uniform and biased system. should be sought, and it was proposed to expand the target age.

Analysis of Dog-Related Outdoor Public Space Conflicts Using Complaint Data (민원 자료를 활용한 반려견 관련 옥외 공공공간 갈등 분석)

  • Yoo, Ye-seul;Son, Yong-Hoon;Zoh, Kyung-Jin
    • Journal of the Korean Institute of Landscape Architecture
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    • v.52 no.1
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    • pp.34-45
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    • 2024
  • Companion animals are increasingly being recognized as members of society in outdoor public spaces. However, the presence of dogs in cities has become a subject of conflict between pet owners and non-pet owners, causing problems in terms of hygiene and noise. This study was conducted to analyze public complaint data using the keywords 'dog,' 'pet,' and 'puppy' through text mining techniques to identify the causes of conflicts in outdoor public spaces related to dogs and to identify key issues. The main findings of the study are as follows. First, the majority of dog-related complaints were related to the use of outdoor public spaces. Second, different types of outdoor public spaces have different spatial issues. Third, there were a total of four topics of dog-related complaints: 'Requesting a dog playground', 'Raising safety issues related to animals', 'Using facilities other than dog-only areas', and 'Requesting increased park management and enforcement related to pet tickets'. This study analyzed the perceptions of citizens surrounding pets at a time when the creation and use of public spaces related to pets are expanding. In particular, it is significant in that it applied a new method of collecting public opinions by adopting complaint data that clearly presents problems and requests.

Analysis of major issues in the field of Maritime Autonomous Surface Ships using text mining: focusing on S.Korea news data (텍스트 마이닝을 활용한 자율운항선박 분야 주요 이슈 분석 : 국내 뉴스 데이터를 중심으로)

  • Hyeyeong Lee;Jin Sick Kim;Byung Soo Gu;Moon Ju Nam;Kook Jin Jang;Sung Won Han;Joo Yeoun Lee;Myoung Sug Chung
    • Journal of the Korean Society of Systems Engineering
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    • v.20 no.spc1
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    • pp.12-29
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    • 2024
  • The purpose of this study is to identify the social issues discussed in Korea regarding Maritime Autonomous Surface Ships (MASS), the most advanced ICT field in the shipbuilding industry, and to suggest policy implications. In recent years, it has become important to reflect social issues of public interest in the policymaking process. For this reason, an increasing number of studies use media data and social media to identify public opinion. In this study, we collected 2,843 domestic media articles related to MASS from 2017 to 2022, when MASS was officially discussed at the International Maritime Organization, and analyzed them using text mining techniques. Through term frequency-inverse document frequency (TF-IDF) analysis, major keywords such as 'shipbuilding,' 'shipping,' 'US,' and 'HD Hyundai' were derived. For LDA topic modeling, we selected eight topics with the highest coherence score (-2.2) and analyzed the main news for each topic. According to the combined analysis of five years, the topics '1. Technology integration of the shipbuilding industry' and '3. Shipping industry in the post-COVID-19 era' received the most media attention, each accounting for 16%. Conversely, the topic '5. MASS pilotage areas' received the least media attention, accounting for 8 percent. Based on the results of the study, the implications for policy, society, and international security are as follows. First, from a policy perspective, the government should consider the current situation of each industry sector and introduce MASS in stages and carefully, as they will affect the shipbuilding, port, and shipping industries, and a radical introduction may cause various adverse effects. Second, from a social perspective, while the positive aspects of MASS are often reported, there are also negative issues such as cybersecurity issues and the loss of seafarer jobs, which require institutional development and strategic commercialization timing. Third, from a security perspective, MASS are expected to change the paradigm of future maritime warfare, and South Korea is promoting the construction of a maritime unmanned system-based power, but it emphasizes the need for a clear plan and military leadership to secure and develop the technology. This study has academic and policy implications by shedding light on the multidimensional political and social issues of MASS through news data analysis, and suggesting implications from national, regional, strategic, and security perspectives beyond legal and institutional discussions.

Policies to Manage Drug Shortages in Selected Countries: A Review and Implications (주요국의 수급불안정 의약품 관리제도에 관한 고찰과 한국에의 시사점)

  • Inmyung Song;Sang Jun Jung;Eunja Park;Sang-Eun Choi;Eun-A Lim;Sanghyun Kim;Dongsook Kim
    • Health Policy and Management
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    • v.34 no.2
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    • pp.106-119
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    • 2024
  • Drug shortage is a persistent phenomenon that poses a public health risk worldwide and occurs due to a range of causes. The purpose of this study is to review key policies to prepare for and respond to drug shortages in selected countries, such as the United States, Canada, and some European countries in order to draw implications. This study reviewed the reports and articles derived from search engines and Google Scholar by using keywords such as drug shortage and stock-out. Over the last decade or so, the United States have strengthened requirements on advance notification for disruption and interruption of drug manufacturing, established the Inter-agency Drug Shortages Task Force to promote the communication and coordination of responses, and expedited drug regulatory processes. Similarly, Canada established the Multi-Stakeholder Steering Committee on drug shortages by involving representatives from central and local governments and private sectors. Canada also adopted a tiered approach to the communication of drug shortages based on the assessment of the severity of the shortage problem and released a detailed information guide on communication. In 2019, the joint task force between the European Medicines Agency and the Heads of Medicines Agencies issued guidelines on drug shortage communication in the European Economic Area. The countries reviewed in this paper focus on communication across different stakeholders for the monitoring of and timely response to drug shortages. The efforts to protect public health from the negative impact of the drug shortage crisis would require multi-sectorial and multi-governmental coordination and development of guidelines.

Analysis of blue carbon storage research trends and consideration for definitions of blue carbon: A review (블루카본 저장 연구 동향 분석 및 블루카본의 정의에 대한 고찰: 리뷰)

  • Kyeong-deok Park;Dong-hwan Kang;Won Gi Jo;Jun-Ho Lee;Hoi Soo Jung;Man Deok Seo;Byung-Woo Kim
    • Journal of Wetlands Research
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    • v.26 no.1
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    • pp.82-91
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    • 2024
  • In this study, research cases related to blue carbon storage were collected and analyzed, and various definitions of blue carbon were considered in terms of spatiotemporal scope and scientific aspect. 444 papers were selected as research cases related to blue carbon storage, and analysis of the number of papers published by year/country and keywords was performed. Publication of papers related to blue carbon storage has continued to increase since 2011, and more than 50 papers have been published annually since 2018. The most publications by country were in Australia with more than 100 papers, and the United States and China also published more than 60 papers. Key terms related to "natural environment" and "storage characteristics" were analyzed in the sentences defined in the 23 papers that presented the definition of blue carbon. The natural environments where blue carbon was stored were mostly mangroves, salt marshes, and seagrass beds, and blue carbon repository included sediments and even plants themselves. The existing definition of blue carbon focused on the vegetation environment as the storage environment for blue carbon. However, since blue carbon is stored in the sediments of coastal wetlands, it would be appropriate to define the coastal ecosystem, including non-vegetated mudflats, as the storage environment for blue carbon.

Non-Keyword Model for the Improvement of Vocabulary Independent Keyword Spotting System (가변어휘 핵심어 검출 성능 향상을 위한 비핵심어 모델)

  • Kim, Min-Je;Lee, Jung-Chul
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.7
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    • pp.319-324
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    • 2006
  • We Propose two new methods for non-keyword modeling to improve the performance of speaker- and vocabulary-independent keyword spotting system. The first method is decision tree clustering of monophone at the state level instead of monophone clustering method based on K-means algorithm. The second method is multi-state multiple mixture modeling at the syllable level rather than single state multiple mixture model for the non-keyword. To evaluate our method, we used the ETRI speech DB for training and keyword spotting test (closed test) . We also conduct an open test to spot 100 keywords with 400 sentences uttered by 4 speakers in an of fce environment. The experimental results showed that the decision tree-based state clustering method improve 28%/29% (closed/open test) than the monophone clustering method based K-means algorithm in keyword spotting. And multi-state non-keyword modeling at the syllable level improve 22%/2% (closed/open test) than single state model for the non-keyword. These results show that two proposed methods achieve the improvement of keyword spotting performance.

Understanding Assessment for Feeding Disorders in Autistic Spectrum Disorders: A Literature Review (자폐 스펙트럼 장애 섭식장애 평가의 이해: 문헌 고찰)

  • Min, Kyoung-Chul;Kim, Bo-Kyeong
    • Therapeutic Science for Rehabilitation
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    • v.13 no.2
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    • pp.9-25
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    • 2024
  • Objective : Children with autism spectrum disorder (ASD) commonly suffer from feeding disorders. Major feeding problems include mealtime behavior problems, picky eating, and a lack of food variety can lead to nutritional problems, developmental and social limitations, and stress for the caregivers. A review of the latest literature was conducted to gain an in-depth understanding of assessment tools for feeding disorders in children with ASD. Method : This study analyzed assessments to identify feeding problems in ASD based on previous studies searched through keywords such as ASD, ASD feeding problem, and ASD feeding evaluation. Results : The ASD feeding disorder assessment was divided into direct and indirect assessments. Indirect assessment, in which caregivers measure a child's situation using questionnaires, is mainly used. The assessment of feeding disorders in children with ASD was divided into 1) mealtime behavior, 2) sensory processing, 3) food consumption, and 4) others. Conclusion : As the main feeding disorder characteristics of children with ASD are very diverse, a comprehensive evaluation is necessary but is still limited. Swallowing rehabilitation experts, such as occupational therapists, should apply comprehensive assessment tools based on a basic understanding of the feeding problems, behaviors, and sensations in ASD.

Establishment of Risk Database and Development of Risk Classification System for NATM Tunnel (NATM 터널 공정리스크 데이터베이스 구축 및 리스크 분류체계 개발)

  • Kim, Hyunbee;Karunarathne, Batagalle Vinuri;Kim, ByungSoo
    • Korean Journal of Construction Engineering and Management
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    • v.25 no.1
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    • pp.32-41
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    • 2024
  • In the construction industry, not only safety accidents, but also various complex risks such as construction delays, cost increases, and environmental pollution occur, and management technologies are needed to solve them. Among them, process risk management, which directly affects the project, lacks related information compared to its importance. This study tried to develop a MATM tunnel process risk classification system to solve the difficulty of risk information retrieval due to the use of different classification systems for each project. Risk collection used existing literature review and experience mining techniques, and DB construction utilized the concept of natural language processing. For the structure of the classification system, the existing WBS structure was adopted in consideration of compatibility of data, and an RBS linked to the work species of the WBS was established. As a result of the research, a risk classification system was completed that easily identifies risks by work type and intuitively reveals risk characteristics and risk factors linked to risks. As a result of verifying the usability of the established classification system, it was found that the classification system was effective as risks and risk factors for each work type were easily identified by user input of keywords. Through this study, it is expected to contribute to preventing an increase in cost and construction period by identifying risks according to work types in advance when planning and designing NATM tunnels and establishing countermeasures suitable for those factors.

Identifying the Cause of Speculative Investment in Cryptocurrency Investment: Based on the Theory of Bounded Rationality (암호화폐 투자에서 투자자들의 투기적 행동을 야기하는 원인 규명: 제한된 합리성 이론을 기반으로)

  • Eunyoung Kim;Byungcho Kim
    • Information Systems Review
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    • v.22 no.1
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    • pp.33-57
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    • 2020
  • Although cryptocurrency which can promote innovation in the blockchain ecosystem is published for many useful purposes, in Korea, cryptocurrency is recognized only as a means of investment for the profit. The fact emphasizes only the speculative nature of the cryptocurrency, so investor negates the fundamental purpose of cryptocurrency and hinders innovation in the blockchain ecosystem. The purpose of this study is to investigate the cause of cryptocurrency perception and speculative behavior of domestic cryptocurrency investors from an academic perspective. We use a model that reflects the traditional considerations and cryptocurrency's characteristics in investment. Using the model, we can explain the cause of misperception of cryptocurrency through the theory of bounded rationality. In building the research model, we use variables of venture and angel investor's consideration used in investment decisions and collect the keywords from indexes of whitepaper to reflect the properties of cryptocurrency. This study mentions that, due to the imitations presented by Simon, individuals are forced to perceive cryptocurrency as a means of speculation and to make irrational decisions that impair ecosystem health. We analyze whether there is a significant difference in rationality in decision made by the sample under limited knowledge and imperfect information constraints. As a result, imperfect information constraints led investors to consider only irrational criteria in decision making. From this result, this study suggests that information asymmetry needs to be relaxed so that investment can be pursued together with rational investment and development of blockchain ecosystem. In addition, the industry can capture strategic insights for successful financing through ICO by enabling better understanding of investor decision-making.