• Title/Summary/Keyword: Web data

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Experiences of Unmet Healthcare Service Utilization in Rural Populations Using Primary Health Care Posts during the COVID-19: A Mixed Method Study Based on Andersen's Behavior Model (COVID-19 기간 동안 보건진료소를 이용하는 마을 주민의 미충족 보건의료서비스 이용 경험: 앤더슨 행동모델을 기반으로 한 혼합연구)

  • Ha, Yeongmi;Kim, Youngnam;Choi, Hyunkyoung;Yang, Seung-Kyoung;Ko, Young-Suk;Jung, Mira;Yi, Jee-Seon;Choi, Youngmi;Shin, Eun Ji;Kim, Younkyoung;Lee, Kowoon;Jung, Aeri;Jang, Ji Hui;Kim, Da Eun;Kim, Kyunghee;Shin, So Young;Park, Song Ran;Yim, Eun Shil
    • Journal of Korean Academy of Rural Health Nursing
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    • v.18 no.2
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    • pp.80-91
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    • 2023
  • Purpose: The purpose of the study quantitatively investigates the experience of unmet healthcare service utilization by rural populations in vulnerable areas during the COVID-19 pandemic based on Andersen's behavior model. At the same time, this study attempts to describe the experiences of unmet healthcare service utilization among participants in vulnerable rural areas by analyzing qualitative contents through open-ended question. Methods: Data were collected from October to November 2022 using Qualtrix, a web-based survey platform. A total of 863 participants completed an online survey. Quantitative data were analyzed using 𝑥2 test and logistic regression analysis. Qualitative data were analyzed using content analysis. Results: The factors affecting participants' unmet healthcare service utilization were type of residential area and underlying disease. The qualitative analysis identified; four categories and nine sub-categories. Conclusion: Based on these findings, it is necessary to develop a disaster nursing response model according to the type of residential areas and the number of people.

A Study on Implementation of Indoor Positioning Simulator through Indoor Positioning API Development (실내측위 API개발을 통한 실내측위 시뮬레이터 구현에 관한 연구)

  • Shin, Chang Soo;Kim, Sung Su
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.6
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    • pp.873-881
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    • 2023
  • The evolution of civil engineering technology, exemplified by recent milestones like the completion of the Gangnam Global Business Center (GBC), has fostered the construction of expansive civil and architectural structures both above and below the earth's surface. This surge in construction necessitates a commensurate advancement in research and technology pertaining to safety protocols applicable to these vast edifices. Such protocols encompass a spectrum of concerns, ranging from the preemptive mitigation of accidents to the effective management of exigencies such as fires. As the trajectory of construction endeavors continues unabated, encompassing both subterranean and elevated domains, a concomitant imperative emerges to refine the methodologies underpinning precise indoor positioning. To address this need, an innovative web-based simulator has been devised to emulate indoor positioning scenarios for rigorous testing. This research further entails the development of an indoor positioning data Application Programming Interface (API) fortified by Geographic Information System (GIS) spatial operation techniques. This API is anchored in the construction of intricate test data, centered on the spatial layout of building 13 at the Electronics and Telecommunications Research Institute (ETRI). Consequently, the study renders feasible the expeditious provisioning of diverse signal-based and image-based spatial information, pivotal for enhancing the navigational acumen of mobile devices. Path delineation, cellular signal mapping, landmark identification, and ancillary navigational aids are among the manifold datasets promptly furnished by the indoor positioning data API. In summation, this study engenders a crucial leap towards the fortification of safety protocols and navigational precision within the expansive confines of modern architectural wonders.

Revisiting the e-Government Maturity Model: Significance, Limitations, and Suggestions (전자정부 성숙도 모델의 재검토: 모델의 의의와 한계, 실증분석을 통한 제언)

  • SUNG, WOOKJOON
    • Informatization Policy
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    • v.30 no.3
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    • pp.3-28
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    • 2023
  • This study aims to analyze the usage behavior of e-government service users based on the e-government maturity model and provide suggestions for advancement of the e-government services. The changes in Korea's e-government services were analyzed as follows; 1) Proportion of use of e-government services in Korean public services, 2) E-government service types/stages use, 3) Service use by platform 4) User response to e-government service 5) Users' requests for future e-government service usage methods. For the analysis, this study used data from Korea's 2012-2020 e-government usage behavior survey data. As a result of the analysis, first, the proportion of e-government service has been continuously increasing, and second, the use of the e-participation stage is relatively low compared to the presenting information, interaction, and transaction stages. Third, by platform, e-government service has been expanded to various access platforms such as mobile, kiosk, and SNS centering on the web. Fourth, users' satisfaction with e-government service is very high. However, to vitalize e-government services, users requested improvements such as providing one-stop integrated services and simplifying authentication procedures. Based on the analysis results, this study 1) reflects the user's point of view in the maturity model of e-government, 2) considers access to various platforms according to the development of digital technology, 3) improves the e-government maturity model through data-based analysis such as user usage behavior suggested the need.

Development of Web-based Construction-Site-Safety-Management Platform Using Artificial Intelligence (인공지능을 이용한 웹기반 건축현장 안전관리 플랫폼 개발)

  • Siuk Kim;Eunseok Kim;Cheekyeong Kim
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.37 no.2
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    • pp.77-84
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    • 2024
  • In the fourth industrial-revolution era, the construction industry is transitioning from traditional methods to digital processes. This shift has been challenging owing to the industry's employment of diverse processes and extensive human resources, leading to a gradual adoption of digital technologies through trial and error. One critical area of focus is the safety management at construction sites, which is undergoing significant research and efforts towards digitization and automation. Despite these initiatives, recent statistics indicate a persistent occurrence of accidents and fatalities in construction sites. To address this issue, this study utilizes large-scale language-model artificial intelligence to analyze big data from a construction safety-management information network. The findings are integrated into on-site models, which incorporate real-time updates from detailed design models and are enriched with location information and spatial characteristics, for enhanced safety management. This research aims to develop a big-data-driven safety-management platform to bolster facility and worker safety by digitizing construction-site safety data. This platform can help prevent construction accidents and provide effective education for safety practices.

Relationships between Job Stress and Burnout of Primary Health Care Practitioners during COVID-19: A Mixed Methods Study (코로나19 기간 동안 보건진료전담공무원의 직무스트레스와 소진의 관계: 혼합연구방법)

  • Ha, Yeongmi;Yim, Eun Shil;Kim, Youngnam;Choi, Hyunkyoung;Ko, Young-suk;Jung, Mira;Yi, Jee-Seon;Choi, Youngmi; Shin, Eun Ji;Kim, Younkyoung;Lee, Kowoon;Jung, Aeri;Jang, Ji hui;Kim, Da Eun;Kim, Kyeonghui;Shin, So Young;Yang, Seung-Kyoung;Park, Songran
    • Journal of Korean Academy of Rural Health Nursing
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    • v.19 no.1
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    • pp.25-34
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    • 2024
  • Purpose: This study investigates the relationship between job stress and burnout among primary healthcare practitioners during COVID-19 pandemic through mixed methods study. Methods: Data were collected from October to November 2022 using Qualtrix, a web-based survey platform. 1,082 primary health care practitioners participated in the survey. Quantitative data were analyzed using correlation analysis using IBM SPSS/WIN 27.0. Qualitative data were analyzed using content analysis through open-ended questions. Results: Job stress and burnout among primary healthcare practitioners during COVID-19 were positively correlated. Four categories and seven subcategories were identified. Conclusion: Based on these findings, it is necessary to develop a support system for primary healthcare practitioners according to the type of residential area and the number of peopleto reduce job stress and burnout.

Sentiment Analyses of the Impacts of Online Experience Subjectivity on Customer Satisfaction (감성분석을 이용한 온라인 체험 내 비정형데이터의 주관도가 고객만족에 미치는 영향 분석)

  • Yeeun Seo;Sang-Yong Tom Lee
    • Information Systems Review
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    • v.25 no.1
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    • pp.233-255
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    • 2023
  • The development of information technology(IT) has brought so-called "online experience" to satisfy our daily needs. The market for online experiences grew more during the COVID-19 pandemic. Therefore, this study attempted to analyze how the features of online experience services affect customer satisfaction by crawling structured and unstructured data from the online experience web site newly launched by Airbnb after COVID-19. As a result of the analysis, it was found that the structured data generated by service users on a C2C online sharing platform had a positive effect on the satisfaction of other users. In addition, unstructured text data such as experience introductions and host introductions generated by service providers turned out to have different subjectivity scores depending on the purpose of its text. It was confirmed that the subjective host introduction and the objective experience introduction affect customer satisfaction positively. The results of this study are to provide various implications to stakeholders of the online sharing economy platform and researchers interested in online experience knowledge management.

Development of an AI Model to Determine the Relationship between Cerebrovascular Disease and the Work Environment as well as Analysis of Consistency with Expert Judgment (뇌심혈관 질환과 업무 환경의 연관성 판단을 위한 AI 모델의 개발 및 전문가 판단과의 일치도 분석)

  • Juyeon Oh;Ki-bong Yoo;Ick Hoon Jin;Byungyoon Yun;Juho Sim;Heejoo Park;Jongmin Lee;Jian Lee;Jin-Ha Yoon
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.34 no.3
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    • pp.202-213
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    • 2024
  • Introduction: Acknowledging the global issue of diseases potentially caused by overwork, this study aims to develop an AI model to help workers understand the connection between cerebrocardiovascular diseases and their work environment. Materials and methods: The model was trained using medical and legal expertise along with data from the 2021 occupational disease adjudication certificate by the Industrial Accident Compensation Insurance and Prevention Service. The Polyglot-ko-5.8B model, which is effective for processing Korean, was utilized. Model performance was evaluated through accuracy, precision, sensitivity, and F1-score metrics. Results: The model trained on a comprehensive dataset, including expert knowledge and actual case data, outperformed the others with respective accuracy, precision, sensitivity, and F1-scores of 0.91, 0.89, 0.84, and 0.87. However, it still had limitations in responding to certain scenarios. Discussion: The comprehensive model proved most effective in diagnosing work-related cerebrocardiovascular diseases, highlighting the significance of integrating actual case data in AI model development. Despite its efficacy, the model showed limitations in handling diverse cases and offering health management solutions. Conclusion: The study succeeded in creating an AI model to discern the link between work factors and cerebrocardiovascular diseases, showcasing the highest efficacy with the comprehensively trained model. Future enhancements towards a template-based approach and the development of a user-friendly chatbot webUI for workers are recommended to address the model's current limitations.

Investigation of Study Items for the Patterns of Care Study in the Radiotherapy of Laryngeal Cancer: Preliminary Results (후두암의 방사선치료 Patterns of Care Study를 위한 프로그램 항목 개발: 예비 결과)

  • Chung Woong-Ki;Kim I1-Han;Ahn Sung-Ja;Nam Taek-Keun;Oh Yoon-Kyeong;Song Ju-Young;Nah Byung-Sik;Chung Gyung-Ai;Kwon Hyoung-Cheol;Kim Jung-Soo;Kim Soo-Kon;Kang Jeong-Ku
    • Radiation Oncology Journal
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    • v.21 no.4
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    • pp.299-305
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    • 2003
  • Purpose: In order to develop the national guide-lines for the standardization of radiotherapy we are planning to establish a web-based, on-line data-base system for laryngeal cancer. As a first step this study was performed to accumulate the basic clinical information of laryngeal cancer and to determine the items needed for the data-base system. Materials and Methods: We analyzed the clinical data on patients who were treated under the diagnosis of laryngeal cancer from January 1998 through December 1999 In the South-west area of Korea. Eligiblity criteria of the patients are as follows: 18 years or older, currently diagnosed with primary epithelial carcinoma of larynx, and no history of previous treatments for another cancers and the other laryngeal diseases. The items were developed and filled out by radiation oncologlst who are members of forean Southwest Radiation Oncology Group. SPSS vl0.0 software was used for statistical analysis. Results: Data of forty-five patients were collected. Age distribution of patients ranged from 28 to 88 years(median, 61). Laryngeal cancer occurred predominantly In males (10 : 1 sex ratio). Twenty-eight patients (62$\%$) had primary cancers in the glottis and 17 (38$\%$) in the supraglottis. Most of them were diagnosed pathologically as squamous cell carcinoma (44/45, 98$\%$). Twenty-four of 28 glottic cancer patients (86$\%$) had AJCC (American Joint Committee on Cancer) stage I/II, but 50$\%$ (8/16) had In supraglottic cancer patients (p=0.02). Most patients(89$\%$) had the symptom of hoarseness. indirect laryngoscopy was done in all patients and direct laryngoscopy was peformed in 43 (98$\%$) patients. Twenty-one of 28 (75$\%$) glottic cancer cases and 6 of 17 (35$\%$) supraglottic cancer cases were treated with radiation alone, respectively. The combined treatment of surgery and radiation was used in 5 (18$\%$) glottic and 8 (47$\%$) supraglottic patients. Chemotherapy and radiation was used in 2 (7$\%$) glottic and 3 (18$\%$) supraglottic patients. There was no statistically significant difference in the use of combined modality treatments between glottic and supraglottic cancers (p=0.20). In all patients, 6 MV X-ray was used with conventional fractionation. The iraction size was 2 Gy In 80$\%$ of glottic cancer patients compared with 1.8 Gy in 59$\%$ of the patients with supraglottic cancers. The mean total dose delivered to primary lesions were 65.98 ey and 70.15 Gy in glottic and supraglottic patients treated, respectively, with radiation alone. Based on the collected data, 12 modules with 90 items were developed or the study of the patterns of care In laryngeal cancer. Conclusion: The study Items for laryngeal cancer were developed. In the near future, a web system will be established based on the Items Investigated, and then a nation-wide analysis on laryngeal cancer will be processed for the standardization and optimization of radlotherapy.

Efficient Topic Modeling by Mapping Global and Local Topics (전역 토픽의 지역 매핑을 통한 효율적 토픽 모델링 방안)

  • Choi, Hochang;Kim, Namgyu
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.69-94
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    • 2017
  • Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

A Digital Library Prototype for Access to Diverse Collections (다양한 장서 접근을 위한 디지털 도서관의 프로토타입 구축)

  • Choi Won-Tae
    • Journal of the Korean Society for Library and Information Science
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    • v.32 no.2
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    • pp.295-307
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    • 1998
  • This article is an overview of the digital library project, indicating what roles Koreas diverse digital collections may play. Our digital library prototype has simple architecture, consisting of digital repositories, filters, indexing and searching, and clients. Digital repositories include various types of materials and databases. The role of filters is to recognize a format of a document collection and mark the structural components of each of its documents. We are using a database management system (ORACLE and ConText) supporting user-defined functions and access methods that allows us to easily incorporate new object analysis, structuring, and indexing technology into a repository. Clients can be considered browsers or viewers designed for different document data types, such as image, audio, video, SGML, PDF, and KORMARC. The combination of navigational tools supports a variety of approaches to identifying collections and browsing or searching for individual items. The search interface was implemented using HTML forms and the World Wide Web's CGI mechanism.

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