• The Journal of Information Systems
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• v.31 no.1
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• pp.175-195
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• 2022

Purpose The purpose of this study is to examine news articles and analyze trends and key agendas related to artificial intelligence(AI). In particular, this study tried to compare the reporting behaviors of Korea and the United States, which is considered to be a leader in the field of AI. Design/methodology/approach This study analyzed news articles using a big data method. Specifically, main agendas of the two countries were derived and compared through the keyword frequency analysis, topic modeling, and language network analysis. Findings As a result of the keyword analysis, the introduction of AI and related services were reported importantly in Korea. In the US, the war of hegemony led by giant IT companies were widely covered in the media. The main topics in Korean media were 'Strategy in the 4th Industrial Revolution Era', 'Building a Digital Platform', 'Cultivating Future human resources', 'Building AI applications', 'Introduction of Chatbot Services', 'Launching AI Speaker', and 'Alphago Match'. The main topics of US media coverage were 'The Bright and Dark Sides of Future Technology', 'The War of Technology Hegemony', 'The Future of Mobility', 'AI and Daily Life', 'Social Media and Fake News', and 'The Emergence of Robots and the Future of Jobs'. The keywords with high centrality in Korea were 'release', 'service', 'base', 'robot', 'era', and 'Baduk or Go'. In the US, they were 'Google', 'Amazon', 'Facebook', 'China', 'Car', and 'Robot'.

• Journal of dental hygiene science
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• v.21 no.4
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• pp.199-212
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• 2021

Background: Various oral health management programs in Korea affect the oral health improvement in the elderly Several studies have been conducted to date; however, those studies have not shown uniform results due to the differences in research methods or designs. Hence, this study aimed to review the overall research trends of the reported oral health care programs for the elderly in Korea, verify their effects, and clarify them based on the systematic literature review. Methods: The literature search selected intervention studies that applied the oral health care program for the elderly in Korea from 2001 to 2020. Following the COre, Standard, and Ideal (COSI) models presented by the US National Library of Medicine, we selected databases including Korean studies Information Service System (KISS), ScienceOn, Research Information Sharing Service (RISS), DBpia, PubMed, and Google Scholar. Of the 1,335 studies searched using keywords, titles, and abstracts, 21 were finally selected based on primary and secondary exclusion criteria. Results: The most frequent intervention period was 4 weeks, and the number of interventions varied between 2 and 90 times. As for the type of intervention, 14 studies that conducted both theory and practice were the most frequent. Significant differences in the clinical indicators, such as calculus, halitosis, salivation rate, swallowing function, and dry mouth, were found in most oral health care programs. Conclusion: Based on the results of this study, the intervention program needs further verification using multiple indicators in future studies. In addition, a study extending the intervention period and the number of samples is considered necessary for verifying continuous effectiveness of the intervention program.

• Journal of Preventive Medicine and Public Health
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• v.55 no.2
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• pp.134-143
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• 2022

Objectives: Many governments have imposed-and are still imposing-mobility restrictions to contain the coronavirus disease 2019 (COVID-19) pandemic. However, there is no consensus on whether policy-induced reductions of human mobility effectively reduce the effective reproduction number (Rt) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Several studies based on country-restricted data reported conflicting trends in the change of the SARS-CoV-2 Rt following mobility restrictions. The objective of this study was to examine, at the global scale, the existence of regional specificities in the correlations between Rt and human mobility. Methods: We computed the Rt of SARS-CoV-2 using data on worldwide infection cases reported by the Johns Hopkins University, and analyzed the correlation between Rt and mobility indicators from the Google COVID-19 Community Mobility Reports in 125 countries, as well as states/regions within the United States, using the Pearson correlation test, linear modeling, and quadratic modeling. Results: The correlation analysis identified countries where Rt negatively correlated with residential mobility, as expected by policymakers, but also countries where Rt positively correlated with residential mobility and countries with more complex correlation patterns. The correlations between Rt and residential mobility were non-linear in many countries, indicating an optimal level above which increasing residential mobility is counterproductive. Conclusions: Our results indicate that, in order to effectively reduce viral circulation, mobility restriction measures must be tailored by region, considering local cultural determinants and social behaviors. We believe that our results have the potential to guide differential refinement of mobility restriction policies at a country/regional resolution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.32-38
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• 2023

This study investigates the influence of particulate matter concentrations on the incidence of asthma, focusing on the delayed onset of symptoms and subsequent medical consultations. Analysis incorporates a four-day lag from the initiation of fine dust exposure and compares asthma patterns before and after the World Health Organization's (WHO) classification of fine dust as a Group 1 carcinogen in November 2013. Utilizing daily PM10 data and asthma-related medical visit counts in Seoul from 2008 to 2016, the study additionally incorporates Google search frequencies and newspaper article counts on fine dust to assess public awareness. Results reveal a surge in search frequencies and article publications after WHO announcement, indicating heightened public interest. To standardize the long-term asthma occurrence trend, the daily asthma patient numbers are ratio-adjusted based on annual averages. The analysis uncovers an increase in asthma medical visits 2 to 3 days after fine dust events. Additionally, greater public awareness of fine dust hazards correlates with a significant reduction in asthma occurrence after such events, even within 'normal' fine dust concentrations. Notably, behavioral changes, like limiting outdoor activities, contribute to this decrease. This study highlights the importance of analyzing accumulated medical data over an extended period to identify general public behavioral patterns, deviating from conventional survey methods in social sciences. Future research aims to extend data collection beyond 2016, exploring recent trends and considering the potential impact of decreased fine dust awareness amid the COVID-19 pandemic.

• Informatization Policy
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• v.25 no.3
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• pp.3-28
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• 2018

The purpose of this study is to analyze the research trends and present future research directions in the field of Cyber Physical System (CPS), a key element in the 4th Industrial Revolution, Industry 4.0, and Smart Manufacturing that are currently promoted as important innovation agenda both at home and abroad. In this study, (1) the concepts of industry 4.0, smart manufacturing and CPS are summarized; (2) analysis criteria of these fields are established; and 3) analysis results are presented and future research direction is proposed. 74 overseas and 8 domestic literature on manufacturing CPS from 2013 to 2017 are identified through 'Google Scholar Search'. Major results of the analysis are summarized as follows: (1) research on a common methodology and framework for the manufacturing CPS needs to be done based on the analysis of the existing methodologies and frameworks of various perspectives; (2) in order to improve the maturity of the manufacturing CPS, it is necessary to study actual deployment and operations of CPS, including the existing systems; (3) it is necessary to study the diagnostic methodology that can evaluate manufacturing CPS and suggest improvement strategy; and (4) as for the detailed model and tool, it is necessary to reinforce research on SCM production planning and human-machine collaboration while considering the characteristics of CPS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.131-143
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• 2019

The purpose of this study is to analyze the research trend of the dementia prevention program in the elderly. Between 2000 and 2018, the Korean Research Information Service (Riss), Google Scholar Search, DBpia, Korea Academy of Science Information (Dissemination Prevention), Dementia Prevention Program, Dementia, The purpose of this study was to investigate the dementia prevention program for the elderly. Based on the analysis criteria and methods of the 404 papers, 36 papers were finally selected. The results of this study are as follows: First, as a result of analysis of the basic structure of the research data and program implementation structure, And, when applied quantitative research method, 25 cases showed a much higher tendency. As a result of analyzing trends of the implementation structure of dementia prevention program for the elderly, 11 were the most in the nursing home (elderly welfare hospital), and the proportion of elderly women was higher than that of male elderly. 65 years of age or older. Second, as a result of analyzing the type of intervention program for dementia prevention program, Third, the Korean version of the MMSE-K tool, which measures cognitive function, is the most frequently used dementia prevention program measurement tool and the result of analysis of effectiveness, Significant improvement in cognitive function. The results of this study suggest that the prevention of dementia for the elderly should be avoided from a fragmentary program and improve the cognitive function, mental behavior and lifestyle of the elderly, improve the healthy aging and quality of life, Suggesting that a program is required.

• Journal of Oriental Neuropsychiatry
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• v.30 no.3
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• pp.251-263
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• 2019

Objectives: The purpose of this study was to review the clinical research trends in the treatment of post traumatic stress disorder (PTSD) in Korean medicine (KM). Methods: We searched MEDLINE, CENTRAL, EMBASE, Google Scholar and five Korean databases through May 2019, for studies on KM to treat PTSD. Clinical research that conducted KM treatment of PTSD patients were included. Two researchers independently conducted study selection and data extraction process. Results: Totally, eight studies were included in this review. Types of traumatic events that patients experienced included physical violence/threatening, traffic accidents, sexual violence and personal tragic events. KM interventions performed included acupuncture, moxibustion, herbal medicine, physical therapy, and KM-based psychotherapy. Treatment duration varied from two days to more than five months. Follow-up began at least one week to three months after the end of treatments. It was reported that the major psychological and/or somatic symptoms of PTSD, such as anxiety, depression, insomnia, and musculoskeletal pain, subjectively improved, as well as other objective outcomes: Impact Event Scale-Revised Korean version (IES-R-K), Beck's Depression Inventory (BDI), State-Trait Anxiety Inventory, Hwabyung Symptoms/characters, Electroencephalography (EEG) change, etc. Statistical studies were conducted in three studies only. Outcomes such as Visual Analogue Scale (VAS), BDI, and IES-R-K showed statistically significant improvement after KM treatments. There was no study reporting adverse events during or after the interventions. Conclusions: According to this review, diverse types of KM treatments have been used among PTSD patients in eight studies. The KM treatments effectively improved psychological and somatic symptoms of PTSD patients. However, the lack of high quality research as well as the lack of standardization of KM treatments for PTSD are limitations. Further methodologically robust clinical trials should be performed, and the standardization of KM treatments for PTSD should be sought.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.268-278
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• 2021

Technologies that are leading the fourth industrial revolution, such as the Internet of Things (IoT), big data, artificial intelligence (AI), and cyber-physical systems (CPS) are developing and generalizing. The demand to improve productivity, economy, safety, etc., is spreading in various industrial fields by applying these technologies. Digital twins are attracting attention as an important technology trend to meet demands and is one of the top 10 tasks of the Korean version of the New Deal. In this study, papers, magazines, reports, and other literature were searched using Google. In order to investigate the contribution or role of geospatial information in the digital twin application, the definition of a digital twin, we investigated technology trends of domestic and foreign companies; the components of digital twins required in manufacturing, plants, and smart cities; and the core techniques for driving a digital twin. In addition, the contributing contents of geospatial information were summarized by searching for a sentence or word linked between geospatial-related keywords (i.e., Geospatial Information, Geospatial data, Location, Map, and Geodata and Digital Twin). As a result of the survey, Geospatial information is not only providing a role as a medium connecting objects, things, people, processes, data, and products, but also providing reliable decision-making support, linkage fusion, location information provision, and frameworks. It was found that it can contribute to maximizing the value of utilization of digital twins.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.49-58
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• 2019

There have been studies on the satisfaction, preference, and post occupancy evaluation of urban parks in order to reflect users' preferences and activities, suggesting directions for future park planning and management. Despite using questionnaires that are proven to be affective to get users' opinions directly, there haven been limitations in understanding the latest changes in park use through questionnaires. This study seeks to address the possibility of utilizing the thirdgeneration SNS data, Instagram and Google, to compare behavior patterns and trends in park activities. Instagram keywords and photos representing user's feelings with a specific park name were collected. We also examined reviews, peak time, and popular time zones regarding selected parks through Google. This study tries to analyze users' behaviors, emerging activities, and satisfaction using SNS data. The findings are as follows. People using park near residential areas tend to enjoy programs being operated in indoor facilities and to like to use picnic places. In an adjacent park of commercial areas, eating in the park and extended areas beyond the park boundaries is found to be one of the popular park activities. Programs using open spaces and indoor facilities were active as well. Han River Park as a detached park type offers a popular venue for excercises and scenery appreciation. We also identified companionship characteristics of different park types from texts and photos, and extracted keywords of feelings and reviews about parks posted in $3^{rd}$ generation SNS. SNS data can provide basis to grasp behavioral patterns and satisfaction factors, and changes of park activities in real time. SNS data also can be used to set future directions in park planning and management in accordance with new technologies and policies.