• Anatomy and Cell Biology
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• v.57 no.1
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• pp.45-60
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• 2024

Morphologic changes in the brain through aging, as a physiologic process, may involve a wide range of variables including ventricular dilation, and sulcus widening. This study reports normal ranges of these changes as standard criteria. Normal brain computed tomography scans of 400 patients (200 males, 200 females) in every decade of life (20 groups each containing 20 participants) were investigated for subcortical/cortical atrophy (bicaudate width [BCW], third ventricle width [ThVW], maximum length of lateral ventricle at cella media [MLCM], bicaudate index [BCI], third ventricle index [ThVI], and cella media index 3 [CMI3], interhemispheric sulcus width [IHSW], right hemisphere sulci diameter [RHSD], and left hemisphere sulci diameter [LHSD]), ventricular symmetry. Distribution and correlation of all the variables were demonstrated with age and a multiple linear regression model was reported for age prediction. Among the various parameters of subcortical atrophy, BCW, ThVW, MLCM, and the corresponding indices of BCI, ThVI, and CMI3 demonstrated a significant correlation with age (R²≥0.62). All the cortical atrophy parameters including IHSW, RHSD, and LHSD demonstrated a significant correlation with age (R²≥0.63). This study is a thorough investigation of variables in a normal brain which can be affected by aging disclosing normal ranges of variables including major ventricular variables, derived ventricular indices, lateral ventricles asymmetry, cortical atrophy, in every decade of life introducing BW, ThVW, MLCM, BCI, ThVI, CMI3 as most significant ventricular parameters, and IHSW, RHSD, LHSD as significant cortical parameters associated with age.

• Clinical Endoscopy
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• v.55 no.2
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• pp.240-247
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• 2022

Background/Aims: Few studies have measured the accuracy of prognostic scores for upper gastrointestinal bleeding (UGIB) among cancer patients. Thereby, we compared the prognostic scores for predicting major outcomes in cancer patients with UGIB. Secondarily, we developed a new model to detect patients who might require hemostatic care. Methods: A prospective research was performed in a tertiary hospital by enrolling cancer patients admitted with UGIB. Clinical and endoscopic findings were obtained through a prospective database. Multiple logistic regression analysis was performed to gauge the power of each score. Results: From April 2015 to May 2016, 243 patients met the inclusion criteria. The AIMS65 (area under the curve [AUC] 0.85) best predicted intensive care unit admission, while the Glasgow-Blatchford score best predicted blood transfusion (AUC 0.82) and the low-risk group (AUC 0.92). All scores failed to predict hemostatic therapy and rebleeding. The new score was superior (AUC 0.74) in predicting hemostatic therapy. The AIMS65 (AUC 0.84) best predicted in-hospital mortality. Conclusions: The scoring systems for prognostication were validated in the group of cancer patients with UGIB. A new score was developed to predict hemostatic therapy. Following this result, future prospective research should be performed to validate the new score.

• Journal of Korean society of Dental Hygiene
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• v.24 no.4
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• pp.343-352
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• 2024

Objectives: This study aimed to assess the relationship between electric toothbrush use and the presence of community periodontal index (CPI) code calculus among Korean adults. Methods: Data from the 7th Korea National Health and Nutrition Examination Survey were analyzed. Multiple logistic regression analysis with a complex sampling design was conducted, adjusting for general characteristic factors. Analyses were performed using SPSS Statistics 29.0. Results: Among the participants, the prevalence of electric toothbrush users was 5.3%. Within this group, 4.7% had periodontal disease, whereas 5.9% did not (p=0.025). Even after adjusting for general characteristics factors in model II of electric toothbrush use, the odds ratio remained statistically significant at 0.791 (95% CI: 0.631-0.992) in all cases. Conclusions: Electric toothbrush use appears to be associated with potential benefits in managing the CPI code calculus distribution; however, evidence supporting this notion remains insufficient. The study findings suggest that these results could be a basis for future studies related to oral hygiene products and the design of oral health promotion programs.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.97-108
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• 2024

Ethical and technical problems are becoming serious as the industrialization of artificial intelligence robots becomes active, research on risk is insufficient. In this situation, the researcher developed 52 verified indicators that can measure the body, rights, property, and social risk of artificial intelligence robots. In order to develop measurement indicators for each type of risk of artificial intelligence robots, 11 experts were interviewed in-depth after IRB deliberation. IIn addition, 328 workers in various fields where artificial intelligence robots can be introduced were surveyed to verify their fieldwork, and statistical verification such as exploratory factor analysis, reliability analysis, correlation analysis, and multiple regression analysis was verifyed to measure validity and reliability. It is expected that the measurement indicators presented in this paper will be widely used in the development, certification, education, and policies of standardized artificial intelligence robots, and become the cornerstone of the industrialization of artificial intelligence robots that are socially sympathetic and safe.

• The Journal of Korean Academic Society of Nursing Education
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• v.30 no.3
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• pp.212-221
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• 2024

Purpose: This study aimed to identify the mediating effect of social phobia between social interaction anxiety and endemic blue among university students who experienced the coronavirus disease 2019 (COVID-19) pandemic. Methods: This study employed a descriptive correlational design. The participants were 196 university students from 10 universities located in four major regions across the Republic of Korea. Data were collected from July 12 to 31, 2022, through an online self-reported questionnaire and were then analyzed using an independent t-test, one-way ANOVA with Scheffé test, Pearson's correlation coefficient, and multiple regression. The mediating effect was analyzed using PROCESS macro model 4 with a bootstrapping method using IBM SPSS 27.0. Results: There were significant positive correlations among social interaction anxiety, social phobia, and endemic blue. Social interaction anxiety had significant effects on social phobia (β=0.77, p<.001) and social interaction anxiety (β=0.33, p<.001) and social phobia had a significant effect on endemic blue (β=0.29, p=.001). Concerning the influence of social interaction anxiety on endemic blue, a significant indirect mediating effect of social phobia was confirmed, and the size of the indirect effect was 0.14 (0.04~0.24). Conclusion: In order to manage the social and psychological health of university students who experienced the COVID-19 pandemic period, it is necessary to develop strategies to overcome endemic blue that reduce social interaction anxiety and take into account the mediating effect of social phobia.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.39-57
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• 2012

Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of Hospice and Palliative Care
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• v.18 no.2
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• pp.128-135
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• 2015

Purpose: As the National Health Insurance Service (NHIS) began to cover home oxygen therapy (HOT) services from 2006, it is expected that the new services have contributed to overall positive outcome of patients with chronic obstructive pulmonary disease (COPD). We examined whether the usage of HOT has helped slow down the progression of COPD. Methods: We examined hospital claim data (N=10,798) of COPD inpatients who were treated in 2007~2012. We performed ${\chi}^2$ tests to analyze the differences in the changes to respiratory impairment grades. Multiple logistic regression analysis was used to identify factors that are associated with the use of HOT. Finally, a generalized linear mixed model was used to examine association between the HOT treatment and changes to respiratory impairment grades. Results: A total of 2,490 patients had grade 1 respiratory impairment, and patients with grades 2 or 3 totaled 8,308. The OR for use of HOT was lower in grade 3 patients than others (OR: 0.33, 95% CI: 0.30~0.37). The maintenance/mitigation in all grades, those who used HOT had a higher OR than non-users (OR: 1.41, 95% CI: 1.23~1.61). Conclusion: HOT was effective in maintaining or mitigating the respiratory impairment in COPD patients.

• Korean Journal of Social Welfare
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• v.57 no.2
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• pp.5-40
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• 2005

Social welfare centers and residential care facilities where provide the socially disadvantaged with proper social services, face financial difficulties. This is because not only of the lack of governmental support, but also of social welfare centers and residential care facilities' lack of skills in developing abundant resources from the private sector. In this context, this study tried to find factors affecting resource mobilization of the social welfare facilities to devise policies in resource development. Mail survey was conducted with the structured questionnaire. Employees in charge of community resource development were asked to answer the questionnaire. The study population were welfare centers and residential care facilities. A total of 293 community welfare centers and 632 residential care facilities responded to the survey. The response rate was about 62%. The dependent variables of the study were the amount of resource mobilization in the year 2001 which was measured as the number of donors, the total amount of donation, and estimated amount of gift-in-kind. Three types models were constructed per each welfare institution. Independent variables were selected based on the previous research findings: community environment factor, structural factor, and resource development factor. Multiple regression was utilized to analyze the data. The resource development factor turned out to be significant variable in various models. In the models of donors, the amount of donation, and the amount of gift-in-kind (except for the welfare center model), at least one out of six variables of the resource development factors was significant welfare center. Welfare centers which establish the resource development department or hire employees to take care of resource development, utilize computer softwares to file donors, and utilize donor management programs, have more donors and/or donations than their counterparts. In addition, residential care facilities located in urban area have more donors and donations, and among residential facilities those for the disables, those with longer history and more employees, receive more donations than their counterparts. As for the gift-in-kind model, the welfare centers located in high income area and residential care facilities for the elderly, children and mentally retarded receive less gift-in-kind than their counterparts Based on the above findings, this study suggested that to mobilize resources the welfare centers as well residential care facilities need to have community resource development department or resource development staffs, adopt computer software to systematically organize donors, and utilize donor mobilizing and maintaining programs.

• Journal of Environmental Science International
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• v.23 no.12
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• pp.2045-2056
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• 2014

In this study, pressure drop was measured in the pulse jet bag filter without venturi on which 16 numbers of filter bags (Ø$140{\times}850{\ell}$) are installed according to operation condition(filtration velocity, inlet dust concentration, pulse pressure, and pulse interval) using coke dust from steel mill. The obtained 180 pressure drop test data were used to predict pressure drop with multiple regression model so that pressure drop data can be used for effective operation condition and as basic data for economical design. The prediction results showed that when filtration velocity was increased by 1%, pressure drop was increased by 2.2% which indicated that filtration velocity among operation condition was attributed on the pressure drop the most. Pressure was dropped by 1.53% when pulse pressure was increased by 1% which also confirmed that pulse pressure was the major factor affecting on the pressure drop next to filtration velocity. Meanwhile, pressure drops were found increased by 0.3% and 0.37%, respectively when inlet dust concentration and pulse interval were increased by 1% implying that the effects of inlet dust concentration and pulse interval were less as compared with those changes of filtration velocity and pulse pressure. Therefore, the larger effect on the pressure drop the pulse jet bag filter was found in the order of filtration velocity($V_f$), pulse pressure($P_p$), inlet dust concentration($C_i$), pulse interval($P_i$). Also, the prediction result of filtration velocity, inlet dust concentration, pulse pressure, and pulse interval which showed the largest effect on the pressure drop indicated that stable operation can be executed with filtration velocity less than 1.5 m/min and inlet dust concentration less than $4g/m^3$. However, it was regarded that pulse pressure and pulse interval need to be adjusted when inlet dust concentration is higher than $4g/m^3$. When filtration velocity and pulse pressure were examined, operation was possible regardless of changes in pulse pressure if filtration velocity was at 1.5 m/min. If filtration velocity was increased to 2 m/min. operation would be possible only when pulse pressure was set at higher than $5.8kgf/cm^2$. Also, the prediction result of pressure drop with filtration velocity and pulse interval showed that operation with pulse interval less than 50 sec. should be carried out under filtration velocity at 1.5 m/min. While, pulse interval should be set at lower than 11 sec. if filtration velocity was set at 2 m/min. Under the conditions of filtration velocity lower than 1 m/min and high pulse pressure higher than $7kgf/cm^2$, though pressure drop would be less, in this case, economic feasibility would be low due to increased in installation and operation cost since scale of dust collection equipment becomes larger and life of filtration bag becomes shortened due to high pulse pressure.