Purpose: The purpose of this study is to develop innovation index of hospital service integrating 6 sigma and SERVQUAL. Methods: This study used DMA(Define, Measure and Analysis) from 6 sigma and 5 Factors from SEVQUAL. To test data, chi-squire text, association analysis and behavior analysis was conducted. Results: This study indicated the management index through CTQ (Critical to Quality) and Chosen few X using 6 sigma process. Finally, And this study developed 5 Factors; Equipment Utilization in Tangibility, Ratio of Patients/Disease/Behavior/Treatment in Reliability, Survival RAte, Canselation Rate of Reservation, Churn Rate, Interval of Treatment and Confidence in Responsiveness, Frequency of Patients/Disease/Behavior/Treatment in Assurance and Contrast to Best Department/Best Doctor/Best Doctor in Faculty/Average of Mine in Empathy. Conclusion: This study developed innovation index of hospital service. Managing this index, hospital is able to achieve the decline of total treatment cycle, adjustment of patients behavior and increase of equipment utilization. Ultimately, hospital is able to accomplish innovation of healthcare service.
International Journal of Advanced Culture Technology
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v.4
no.3
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pp.62-68
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2016
This study explores evaluative linguistic expressions in news reporting about the 2016 general election outcome in Korean newspapers. In particular, we have examined the evaluative linguistic expressions quoted from the three Western news media -New York Times, Washington Post, and BBC, both quantitatively and qualitatively in Korean news stories in order to know how journalists frame the news stories to persuade news consumers to accept their ideologies. This is based on the assumption that quotation can be a tool in conveying ideologies to news consumers (van Dijk, 1988, Jullian, 2011). To achieve this purpose, we selected ten Korean newspapers which included quotations from the news stories of the three Western media and then analyzed the quoted expressions quantitatively and qualitatively. For a qualitative analysis, evaluative linguistic expressions were analyzed to examine the journalistic stances of the Western news stories, following Martin's (2003) appraisal theory. For a quantitative analysis, a word frequency analysis was conducted to figure out the ratio of quoted words to the whole news texts in Korean newspapers. As a result, it was found that the news stories of BBC and Washington Post were more frequently quoted than that of New York Times when journalists conveyed neutral or positive attitude to the election outcome, thus confirming that evaluative linguistic expressions were functionally employed to convey journalists' ideologies or stances to news readers.
Background: Sex influences is important to understand behavioral manifestations in a large number of neuropsychiatric disorders. We found electrophysiological differences specifically related to the influence of sex on psychopathic traits. Methods: The resting electroencephalography (EEG) activity and low-resolution brain electromagnetic tomography (LORETA) for the EEG spectral bands were evaluated in 38 teenagers with conduct disorder (CD). The 25 male and 13 female subjects had psychopathic traits as diagnosed using the Antisocial Process Screening Device. All of the included adolescents were assessed using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) criteria. The visually inspected EEG characteristics and the use of frequency-domain quantitative analysis techniques are described. Results: Quantitative EEG (QEEG) analysis showed that the slow-wave activities in the right frontal and left central regions were higher and the alpha-band powers in the left central and bitemporal regions were lower in the male than the female psychopathic traits group. The current source density showed increases in paralimbic areas at 2.73 Hz and decreases in the frontoparietal area at 9.37 Hz in male psychopathics relative to female psychopathics. Conclusions: These findings indicate that QEEG analysis and techniques of source localization can reveal sex differences in brain electrical activity between teenagers with CD and psychopathic traits that are not obvious in visual inspections.
Purpose: This study identified words closely associated with the keyword "dietary supplement" (DS) using big data in Korean social media and investigated consumer perceptions and trends related to DSs before (2019) and after the coronavirus disease 2019 (COVID-19) pandemic (2021). Methods: A total of 37,313 keywords were found for the 2019 period, and 35,336 keywords were found for the 2021 period using blogs and cafes on Daum and Naver. Results were derived by text mining, semantic networking, network visualization analysis, and sentiment analysis. Results: The DS-related keywords that frequently appeared before and after COVID-19 were "recommend", "vitamin", "health", "children", "multiple", and "lactobacillus". "Calcium", "lutein", "skin", and "immunity" also had high frequency-inverse document frequency (TF-IDF) values. These keywords imply a keen interest in DSs among Korean consumers. Big data results also reflected social phenomena related to DSs; for example, "baby" and "pregnant woman" had lower TD-IDF values after the pandemic, suggesting lower marriage and birth rates but higher values for "joint", indicating reduced physical activity. A network centered on vitamins and health care was produced by semantic network analysis in 2019. In 2021, values were highest for deficiency and need, indicating that individuals were searching for DSs after the COVID-19 pandemic due to a lack an awareness of the need for adequate nutrient intake. Before the pandemic, DSs and vitamins were associated with healthcare and life cycle-related topics, such as pregnancy, but after the COVID-19 pandemic, consumer interests changed to disease prevention and treatment. Conclusion: This study provides meaningful clues regarding consumer perceptions and trends related to DSs before and after the COVID-19 pandemic and fundamental data on the effect of the pandemic on consumer interest in dietary supplements.
This study aims to conduct a comprehensive meta-study from the perspective of content analysis to explore trends in Korean academic research on the sharing economy by using the big data analytics. Comprehensive meta-analysis methodology can examine the entire set of research results historically and wholly to illuminate the tendency or properties of the overall research trend. Academic research related to the sharing economy first appeared in the year in which Professor Lawrence Lessig introduced the concept of the sharing economy to the world in 2008, but research began in earnest in 2013. In particular, between 2006 and 2008, research improved dramatically. In order to grasp the overall flow of domestic academic research of trends, 8 years of papers from 2013 to the present have been selected as target analysis papers, focusing on titles, keywords, and abstracts using database of electronic journals. Big data analysis was performed in the order of cleaning, analysis, and visualization of the collected data to derive research trends and insights by year and type of literature. We used Python3.7 and Textom analysis tools for data preprocessing, text mining, and metrics frequency analysis for key word extraction, and N-gram chart, centrality and social network analysis and CONCOR clustering visualization based on UCINET6/NetDraw, Textom program, the keywords clustered into 8 groups were used to derive the typologies of each research trend. The outcomes of this study will provide useful theoretical insights and guideline to future studies.
This study used big data to analyze visitors' experiences in Fishing Experience Recreation Village. Through the portal site posting data for the past six years, the experience of visiting Fishing Experience Villages in Baekmi and Susan was analyzed. The analysis method used Text mining and Social Network Analysis which are Big data analysis techniques. Data was collected using Textom, and experience keywords were extracted by analyzing the frequency and importance of experience texts. Afterwards, the characteristics of the experience of visiting the Fishing Experience Village were identified through the analysis of the interaction between the experience keywords using 'U cinet 6.0' and 'NetDraw'. First, through TF and TF-IDF values, keywords such as "Gungpyeong Port", "Susan Port", and "Yacht Marina" that refer to the name of the port and the port facilities appeared at the top. This is interpreted as the name of the port has the greatest impact on the recognition of the Fishing Experience Villages, and visitors showed a lot of interest in the port facilities. Second, focusing on the unique elements of port facilities and fishing villages such as "mud flat experience", "fishing village experience", "Gungpyeong port", "Susan port", "yacht marina", and "beach" through the values of degree, closeness, and betweenness centrality interpreted as having an interaction with various experiences. Third, through the CONCOR analysis, it was confirmed that the visitor's experience was focused on the dynamic behavior, the experience program had the greatest influence on the experience of the visitor, and that the experience of the static and the dynamic behavior was relatively balanced. In conclusion, the experience of visitors in the Fishing Experience Villages is most affected by the environment of the fishing village such as the tidal flats and the coast and the fishing village experience program conducted at the fishing port facilities. In particular, it was found that fishing port facilities such as ports and marinas had a high influence on the awareness of the Fishing Experience Villages. Therefore, it is important to actively utilize the scenery and environment unique to fishing villages in order to revitalize the Fishing Experience Villages experience and improve the quality of the visitor experience. This study is significant in that it studied visitors' experiences in fishing village recreation villages using big data and derived the connection between fishing village and fishing village infrastructure in fishing village experience tourism.
The Journal of the Convergence on Culture Technology
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v.10
no.3
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pp.97-109
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2024
In the field of domestic tourism, tourism trend analysis of tourism consumers, both international tourists and domestic tourists, is essential not only for the Korean tourism market but also for local and governmental tourism policy makers. e will explore the keywords and sentiment analysis on social media to establish a marketing strategy plan and revitalize the domestic tourism industry through communication and information from tourism consumers. This study utilized TEXTOM 6.0 to analyze recent trends in Korean tourism. Data was collected from September 31, 2022, to August 31, 2023, using 'Korean tourism' and 'domestic tourism' as keywords, targeting blogs, cafes, and news provided by Naver, Daum, and Google. Through text mining, 100 key words and TF-IDF were extracted in order of frequency, and then CONCOR analysis and sentiment analysis were conducted. For Korean tourism keywords, words related to tourist destinations, travel companions and behaviors, tourism motivations and experiences, accommodation types, tourist information, and emotional connections ranked high. The results of the CONCOR analysis were categorized into five clusters related to tourist destinations, tourist information, tourist activities/experiences, tourism motivation/content, and inbound related. Finally, the sentiment analysis showed a high level of positive documents and vocabulary. This study analyzes the rapidly changing trends of Korean tourism through text mining on Korean tourism and is expected to provide meaningful data to promote domestic tourism not only for Koreans but also for foreigners visiting Korea.
The purpose of this exploratory study is to compare the differences in public perceptual characteristics of Korean and Chinese societies regarding the metaverse using big data analysis. Due to the environmental impact of the COVID-19 pandemic, technological progress, and the expansion of new consumer bases such as generation Z and Alpha, the world's interest in the metaverse is drawing attention, and related academic studies have been also in full swing from 2021. In particular, Korea and China have emerged as major leading countries in the metaverse industry. It is a timely research question to discover the difference in social awareness using big data accumulated in both countries at a time when the amount of mentions on the metaverse has skyrocketed. The analysis technique identifies the importance of key words by analyzing word frequency, N-gram, and TF-IDF of clean data through text mining analysis, and analyzes the density and centrality of semantic networks to determine the strength of connection between words and their semantic relevance. Python 3.9 Anaconda data science platform 3 and Textom 6 versions were used, and UCINET 6.759 analysis and visualization were performed for semantic network analysis and structural CONCOR analysis. As a result, four blocks, each of which are similar word groups, were driven. These blocks represent different perspectives that reflect the types of social perceptions of the metaverse in both countries. Studies on the metaverse are increasing, but studies on comparative research approaches between countries from a cross-cultural aspect have not yet been conducted. At this point, as a preceding study, this study will be able to provide theoretical grounds and meaningful insights to future studies.
The purpose of this study was to investigate the factors influence the outbuying behavior of the consumers reside in middle sized cities adjacent to Kwangju. a metropolitan city of Korea. Data were collected by using questionnaire from 570 female consumers in Suncheon and Yeosu city from 8 September to 16. 1999. Data from 513 respondents were analyzed. Factor analysis. t-text. $x^2$test and cross analysis were used. Respondents were divided by two groups, outbuying group/resident purchasing group, based on the frequency of purchasing and intention of purchasing in local stores. and the differences between two groups were analyzed. The results were as follows : 1. There were significant differences in the residence. levels of education and Income. age. job. automobile possession, numbers of children, clothing expenditure Per month between outbuying group and resident purchasing group(p<.001, respectively) . 2. Outbuying group had significant higher tendency toward pursuing fashionability and pleasure, and symbolism in clothing than resident purchasing group(p<.001. respectively) 3. Outbuying group considered store services. assortments. shopping convenience significantly more important than resident purchasing group(p<.001. respectively) 4. Outbuying group obtained information from media sources and non-media sources significantly more often than resident purchasing group(p<.001, respectively) .
Hussain, Muzamal;Naeem, Muhammad Nawaz;Tounsi, Abdelouahed;Taj, Muhammad
Advances in nano research
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v.7
no.6
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pp.431-442
/
2019
Vibration analysis of carbon nanotubes (CNTs) is very essential field owing to their many promising applications in tiny instruments. In current study, the Eringen's nonlocal elasticity theory with clamped-clamped and clamped-free end conditions is utilized for the vibration analysis of armchair and zigzag SWCNTs. The Fourier method is utilized to solve the ordinary differential equation. The motion equation for this system is developed using a novel wave propagation method. Complex exponential functions have been used and the axial model depends on BCs that has been described at the edges of CNTs. The behavior of different nonlocal parameters is considered to find the vibrational frequency of SWCNTs. It is exhibited that the effect of frequencies against aspect ratio by varying the bending rigidity. It has been investigated that by increasing the nonlocal parameter decreases the frequencies and on increasing the aspect ratio increases the frequencies for both the tubes. To generate the fundamental natural frequencies of SWCNTs, computer software MATLAB engaged. The numerical results are validated with existing open text. Since the percentage of error is negligible, the model has been concluded as valid.
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