• Journal of Industrial Convergence
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• v.19 no.1
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• pp.53-63
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• 2021

As tourists travel to other regions, they encounter numerous facts that conflict with their views. At that time, we change our view of coping with life. In this respect, tourism is a new way of learning. As a new learning method, tourism experience research is a new approach. In this study, the relationship between experience and learning experienced in tourist destinations was analyzed by applying the activity theory. The analysis units applied in the activity theory were set as subjects, goals, communities, roles, methods and rules, outcomes, and relevance to local communities. Based on this, in-depth interviews were conducted with commentators and guides who had a great influence on the tourism experience to analyze the learning process of tourists. As a result of the analysis, the experiences of tourists during the tour were interactive in various forms within the unit as well as the unit of the activity system of the commentator and guide. This interaction induces changes in the tourism experience activity system, enabling tourists to learn. The content is that the value of learning increases as the role of guide and commentator increases, that the social and cultural dimension of tourism experience is included in the learning effect, and the contradictions that arise from interactions within or between activity systems. The fact that they find the solution process themselves, and that tourism activity is not an isolated unit, but exists at the intersection of hierarchies and networks, is affected by the activities and environments of others.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.285-293
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• 2021

Politics and conflicts within organizations are natural phenomena found in any type of organization, affecting organizational outcomes and output variables. Nevertheless, there are not many previous studies on politics and conflict within nursing organizations. Therefore, in this study, we would like to analyze how the internal politics and conflicts, which have been excluded from the previous studies related to nursing organizations, affect the quality of communication between nurses. Data were collected from 310 nurses in an university hospital. Using SPSS21, the data were analyzed by descriptive statistics, Pearson's correlation analysis, and multiple regression analyses. As results of the analyses, the organizational politics and relationship conflict have negative effect on the quality of vertical and horizontal communication, and task conflict has a positive effect on them. Organizational politics and relationship conflict have negative effects on quality of formal communication. Organizational politics and conflicts did not significantly affect the quality of informal communication. These results suggest that active, managerial efforts should be executed to overcome the negative effects of organizational politics and emotional conflicts among nurses. Furthermore, empirical research on organizational politics and conflicts within nurses organizations should be expanded.

• Physical Therapy Korea
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• v.28 no.1
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• pp.18-26
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• 2021

Previous studies have reported that deep neck flexor (DNF) exercise can improve neck problems, including neck pain, forward head posture, and headache, by targeting the deep and superficial muscles of the neck. Despite the prevailing opinion across studies, the benefits of DNF can vary according to the type of neck problems and the outcome measures adopted, ranging from positive outcomes to non-significant benefits. A meta-analysis was conducted in this study to assess conclusive evidence of the impact of DNF exercise on individuals with neck problems. We used PUBMED, MEDLINE, NDSL, EMBASE, and Web of Science to search for primary studies and the key terms used in these searches were "forward head posture (FHP)," "biofeedback," "pressure biofeedback unit," "stabilizer," "headache," and "neck pain." Twenty-four eligible studies were included in this meta-analysis and were coded according to the type of neck problems and outcome measures described, such as pain, endurance, involvement of neck muscle, craniovertebral angle (CVA), neck disability index (NDI), cervical range of motion (CROM), radiographs of the neck, posture, strength, endurance, and headache disability index. The overall effect size of the DNF exercise was 0.489. The effect sizes of the neck problems were 0.556 (neck pain), -1.278 (FHP), 0.176 (headache), and 1.850 (mix). The effect sizes of outcome measures were 1.045 (pain), 0.966 (endurance), 0.894 (deep neck flexor), 0.608 (superficial neck flexor), 0.487 (CVA), 0.409 (NDI), and 0.252 (CROM). According to the results of this study, DNF exercise can effectively reduce neck pain. Thus, DNF exercise is highly recommend as an effective exercise method for individuals suffering from neck pain.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.3
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• pp.219-237
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• 2021

Visual information is widely used to deliver health information more effectively on social media, but there is lack of research on how effectively visual information delivers health information on social media. This study reports Facebook users' reading patterns and cognitive tests (recall and recognition tests) results using health-related Facebook posts. For this study, 21 college students participated in online questionnaire, eye tracking experiment, and recall and recognition tests. First, users paid their attention to the area that contains information (i.e., users focused on the main text rather than photos that do not contain information). Second, in the case of Facebook posts containing infographics, users paid their attention on the infographics, but the recall and recognition test results of the posts with infographics were lower than the posts containing photos. Particularly, when the infographics are in a complex collage format, recall and recognition tests result lower scores. Third, regarding the length of the text, the Facebook posts with short text resulted in higher recall and recognition test scores than the posts with medium or long texts. This study suggested to Facebook health information providers and distributors how to design Facebook posts for delivering health information more effectively.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.3
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• pp.87-97
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• 2021

Purpose : The purpose of this meta-analysis was to evaluate the effects of transcranial direct current stimulation on the lower extremity function of stroke patients. Methods : Domestic data were gathered from studies that conducted clinical trials associated with transcranial direct current stimulation and its impact on lower extremity function of stroke patients. A total of 592 studies published between 2012 and 2020 were identified, with 7 studies satisfying the inclusion data. The studies consisted of patient, intervention, comparison, and outcome (PICO) data. The search outcomes were items associated with muscle activity, balance, muscle strength and walking ability. Cochrane risk of bias (ROB) was used to evaluate the quality of 3 randomized control trials. The quality of 4 non-randomized control trials was evaluated using risk of bias assessment tool for non-randomized studies (RoBANS). Effect sizes in this study were computed as the corrected standard mean difference (SMD). A random-effect model was used to analyze the effect size because of the high heterogeneity among the studies. Egger's regression and 'trim-and-fill' tests were carried out to analyze the publishing bias. Results : The following factors had a large total effect size (Hedges's g=2.10, 95 %CI=1.54~2.66) involving transcranial direct current stimulation on stroke patients: muscle activity (Hedges's g=2.38, 95 %CI=1.08~3.68), balance (Hedges's g4=2.41, 95 %CI=1.33~3.60), walking ability (Hedges's g=1.54, 95 %CI=0.49~2.59), and muscle strength (Hedges's g=2.45, 95 % CI: 0.85~4.05). Egger's regression test showed that the publishing bias had statistically significant differences but 'trim-and-fill' test showed that there was still statistical difference. Conclusion : This study provides evidence for the effectiveness of transcranial direct current stimulation on the lower extremity in terms of muscle activity, balance, walking ability, and muscle strength in stroke patients. However, due to the low quality of studies and high heterogeneity factors, the results of our study should be interpreted cautiously.

• Therapeutic Science for Rehabilitation
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• v.10 no.3
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• pp.7-22
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• 2021

Objective : The purpose of this study was to verify the effect of virtual reality interventions (VRIs) on cognitive function in individuals with stroke through a systematic literature review and meta-analysis. Methods : We reviewed randomized controlled trials (RCTs) the last 10 years using academic databases. PubMed, MEDLINE, and CINAHL were used for international studies, and DBpia, KISS, Kyoboscholar, and e-article were used for Korean studies. For the quantitative meta-analysis, subgroups of outcomes were classified into general cognitive function (G-CF), attention and memory (A&M), and executive function (EF). Results : Nine RCTs were analyzed. The total number of participants was 271 (140 in the experimental group). The effect size (Cohen's d) was estimated using a random effects model. The effect sizes of the outcome subgroups of were as follows: small to medium for G-CF (d=0.422; 95% CI: 0.101~0.742; p=0.010), small for A&M (d=0.249; 95% CI: -0.107~0.605; p=0.170), and medium for EF (d=0.666; 95% CI: 0.136~1.195; p=0.014). Conclusion : Considering the various stimuli provided by the virtual environment and the results from available research, virtual reality should be applied to interventions for integrated cognitive functions. In addition, it would be appropriate to be used as an additional intervention to traditional cognitive rehabilitation for stroke.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.830-860
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• 2022

[Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.

• Tuberculosis and Respiratory Diseases
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• v.85 no.1
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• pp.74-79
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• 2022

Background: The effect of underlying chronic obstructive pulmonary disease (COPD) on coronavirus disease 2019 (COVID-19) during a pandemic is controversial. The purpose of this study was to examine the prognosis of COVID-19 according to the underlying COPD. Methods: COVID-19 patients were assessed using nationwide health insurance data. Comorbidities were evaluated using the modified Charlson Comorbidity Index (mCCI) which excluded COPD from conventional CCI scores. Baseline characteristics were assessed. Univariable and multiple logistic and linear regression analyses were performed to determine effects of variables on clinical outcomes. Ages, sex, mCCI, socioeconomic status, and underlying COPD were selected as variables. Results: COPD patients showed older age (71.3±11.6 years vs. 47.7±19.1 years, p<0.001), higher mCCI (2.6±1.9 vs. 0.8±1.3, p<0.001), and higher mortality (22.9% vs. 3.2%, p<0.001) than non-COPD patients. The intensive care unit admission rate and hospital length of stay were not significantly different between the two groups. All variables were associated with mortality in univariate analysis. However, underlying COPD was not associated with mortality unlike other variables in the adjusted analysis. Older age (odds ratio [OR], 1.12; 95% confidence interval [CI], 1.11-1.14; p<0.001), male sex (OR, 2.29; 95% CI, 1.67-3.12; p<0.001), higher mCCI (OR, 1.30; 95% CI, 1.20-1.41; p<0.001), and medical aid insurance (OR, 1.55; 95% CI, 1.03-2.32; p=0.035) were associated with mortality. Conclusion: Underlying COPD is not associated with a poor prognosis of COVID-19.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.269-279
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• 2022

Purpose: The purpose of this study is to develop a deep learning-based personal protective equipment detection model for disaster prevention at construction sites, and to apply it to actual construction sites and to analyze the results. Method: In the method of conducting this study, the dataset on the real environment was constructed and the developed personal protective equipment(PPE) detection model was applied. The PPE detection model mainly consists of worker detection and PPE classification model.The worker detection model uses a deep learning-based algorithm to build a dataset obtained from the actual field to learn and detect workers, and the PPE classification model applies the PPE detection algorithm learned from the worker detection area extracted from the work detection model. For verification of the proposed model, experimental results were derived from data obtained from three construction sites. Results: The application of the PPE recognition model to construction site brings up the problems related to mis-recognition and non-recognition. Conclusions: The analysis outcomes were produced to apply the object recognition technology to a construction site, and the need for follow-up research was suggested through representative cases of worker recognition and non-recognition, and mis-recognition of personal protective equipment.

• Journal of Korean Medicine Rehabilitation
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• v.32 no.3
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• pp.131-140
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• 2022

Objectives This study aimed to investigate whether the concurrent use of conventional and herbal medications affects liver and kidney function, by examining blood test data. Methods We retrospectively reviewed the electronic medical records of 590 inpatients with musculoskeletal diseases between 2013 and 2017. We investigated cases of drug-induced liver injury (DILI) according to the Roussel Uclaf Causality Assessment Method criteria and cases of drug-induced kidney injury (DIKI) based on the Kidney Disease Improving Global Outcomes definition. Results One case (0.17%) of DILI and one case (0.17%) of DIKI were identified. Significant improvements in serum laboratory data were observed after the concurrent use of both types of medications (p<0.05). The kappa coefficients ranged from 0.26 to 0.72, indicating that the values after the concurrent use of conventional and herbal medications showed a fair similarity to the baseline values of the patients. The linear regression test showed that female sex and high body mass index (BMI) were risk factors for an increase in the serum blood levels of liver function parameters. Conclusions The concurrent use of conventional and herbal medications for musculoskeletal disorders is relatively safe; however, clinicians should exercise caution when prescribing these medications to female patients and patients with a high BMI because of their potential effect on hepatic function.