• Journal of Intelligence and Information Systems
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• v.13 no.2
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• pp.43-53
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• 2007

e-Learning education system as the next educational trend supporting remote and multimedia education. However, the students stay mainly at remote place and it is hard to certificate whether he is really studying now or not. To solve this problem, some solutions were proposed such as instructor's supervision by real time motion picture or message exchanging. Unhappily, as you can see, it needs much cost to establish the motion exchanging system and trampling upon human rights could occasion to reduce the student's will. Accordingly, we propose the new intelligent system based on face recognition to reduce the system cost. The e-Learning system running on the web page can check the student's status by motion image, and the images transfer to the instructor. For this study, 20 students and one instructor takes part in capturing and recognizing the face images. And the result produces the prevention the leave of students from lecture and improvement of attention.

• Journal of the Korean Society of Earth Science Education
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• v.14 no.2
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• pp.173-192
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• 2021

The purpose of this study is to analyze the previous research on geological fieldwork from 2000 to 2020, examine the tasks that have been focused on, and suggest directions and implications for future geological fieldwork research. The data was conducted for the thesis searched on ScienceON and RISS in relation to geological fieldwork and journals listed in the Korean Citation Index(KCI), and the study title was analyzed using the semantic network analysis. For analysis, the data that had been pre-processed was visualized as a network by semantic network analysis, and frequency and centrality were analyzed. The centrality analysis was based on degree centrality and eigenvector centrality, and all analyzes were performed by dividing the entire study period into four periods: 2000-2005, 2006-2010, 2011-2015, and 2016-2020. As a result, research on geological fieldwork focused more on the development of geological field courses, and in particular, jeju island was actively discussed as a learning site. Also, the study was conducted on students rather than teachers, and among them, high school students showed high frequency and centrality. In addition, it can be seen that studies on the educational effect of geological fieldwork were discussed, either in connection with programs such as STEAM, free-semester program, or indirect geological fieldwork methods such as web, flash panorama, and 3D. This study is meaningful in that it suggests the direction of future research by looking back on the research on geological fieldwork that has been done so far.

• Journal of Korean Medicine Rehabilitation
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• v.31 no.4
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• pp.49-63
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• 2021

Objectives This study aimed to investigate the trend in treating fracture with acupuncture and to evaluate the quality of case reports. Methods All case reports of fractures treated with acupuncture were extracted from four Korean web databases. We classified these studies by five fracture sites and investigated frequently used meridian and acupoint, outcome measurements, treatment period. And we assessed the quality of the case reports by the STandards for Reporting Interventions in Clinical Trials of Acupuncture (STRICTA) guidelines. Results A total of 33 case reports were included. The outcome measurements were divided into six categories, and the outcome measurements used in more than three studies showed improvement in patient symptoms. The mainly used meridians for each fracture site were as follows: chest and abdomen (GB, LR, CV), back (BL, GB), upper limb (LI, TE), lower Limb (GB, ST, BL, SP). The most commonly used acupoints for each fracture site were as follows: chest and abdomen (Ashi points, GB24, GB25, GB26, LR13, LR14, CV16, CV17, CV18, CV19), back (BL23, BL24, BL25, BL26, BL40, BL51, BL52, BL60, GB34), upper limb (LI4, LI10, LI11, TE3), lower limb (GB34, GB40). According to the STRICTA guidelines, more than 54.54% of the reports were found to be 'not reported' or 'not sufficient' in the following categories: 'response sought', 'description of participating acupuncturist', and 'number of needle insertions per subject per session'. Conclusions The meridians and acupuncture points frequently used for acupuncture treatment of fractures were near the fracture site. Future clinical studies involving acupuncture must be reported in accordance with the STRICTA guidelines to improve transparency and uniformity.

• Journal of Korean Medicine Rehabilitation
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• v.31 no.1
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• pp.119-135
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• 2021

Objectives This review aims to analyze the current research trend in the usage of bee venom (BV) acupuncture for articular diseases of single type joint. Methods We collected 74 articles on BV acupuncture clinical study for articular diseases of single joint by searching Korean web databases 'Journal of Korean Medicine Rehabilitation', 'Oriental Medicine Advanced Searching Integrated System', 'Korean Traditional Knowledge Portal' from 1999 to 2020 August. Results We summarized the most frequent clinical treatment methods of BV acupuncture for articular diseases of single type joint. Research focused on specific diseases in application of BV acupuncture about some articular type diseases of single joint. It is assumed that the details of treatment for each joint are not related to the type of joint. In clinical study of BV acupuncture, reproducibility was mostly insufficient. Conclusions BV acupuncture clinical study for articular diseases of single joint should be proceed for a number of subjects, to treat various types of disease, by using more safe and detailed treatments.

• Korean Journal of Acupuncture
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• v.38 no.1
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• pp.16-31
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• 2021

Objectives : The purpose of this study was to investigate the current status of clinical practice for gout in Korean Medicine (KM). Methods : On-line survey was adopted for this study, targeted at KM Doctors who were registered in the Association of Korean Medicine. The questionnaire included the general status of treatment, pattern identification and treatment method according to three stages given: acute, chronic and asymptomatic hyperuricemia stage. Results : Data from a total of 384 respondents was analyzed. Participants who responded most were in their 40s, working in KM clinics located in Seoul. Acupuncture and herbal medicines were the top priority treatments in preparing recommendations in clinical practice guidelines for gout, and where clinical trials were considered essential. As of the past year, the average number of first visits per month was 86.7%, and the average treatment duration was less than 1 month, accounting for 72.9%. As for the diagnostic method used for gout patients, the "diagnosed by clinical pattern" response was the highest, and the "blood and urine test" response was the highest as the diagnostic equipment used. As for the evaluation scale being used, the "VAS/NRS" response was the highest. Regardless of the gout stage, acupuncture was the most commonly used treatment method for gout patients, and bee venom pharmacopuncture was the highest for the pharmacopuncture used. In the case of herbal medicine, it was found that a wider variety of herbal medication uninsured in health insurance and herbal prescription were used for the staged treatment of gout than herbal medication in national health insurance coverage. In clinical practice, "acupuncture treatment three times a week" was the most common, and the "acupoints in the limb" were the most frequently used; LR3 and SP3 were the most frequently used acupoints. Conclusions : It is suggested that this survey should be helpful to develop clinical practice guideline for gout that reflects actual clinical practice.

• 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.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.313-325
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• 2022

The purpose of this study is to examine the changes in the elderly healthcare app market through text mining analysis and to present basic data for activating elderly healthcare apps. Data collection was conducted on Naver, Daum, blog web, and cafe. As for the research method, text mining, TF-IDF(Term frequency-inverse document frequency), emotional analysis, and semantic network analysis were conducted using Textom and Ucinet6, which are big data analysis programs. As a result of this study, a total of six categories were finally derived: resolving the healthcare app information gap, convergence healthcare technology, diffusion media, elderly healthcare app industry, social background, and content. In conclusion, in order for elderly healthcare apps to be accepted and utilized by the elderly, they must have a good diffusion infrastructure, and the effectiveness of healthcare apps must be maximized through the active introduction of convergence technology and content development that can be easily used by the elderly.

• Journal of Korean Foot and Ankle Society
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• v.25 no.4
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• pp.149-156
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• 2021

Purpose: Given the lack of definite evidence-based guidelines in clinical practice, there may be a wide variation in treatment protocols for osteochondral lesions of the talus (OLT). Based on the Korean Foot and Ankle Society (KFAS) member survey, this study aimed to report the current trends in the management of OLT. Materials and Methods: A web-based questionnaire containing 30 questions was sent to all KFAS members in September 2021. The questions were mainly related to clinical experience and preferences in diagnosis, conservative, and surgical treatments for patients with OLT. Answers with a prevalence of ≥50% of respondents were considered a tendency. Results: Sixty-two (11.3%) of the 550 surgeons queried responded to the survey. The responses to 9 (30.0%) of the total of 30 questions established a tendency. Answers exhibiting a tendency were as follows; additional diagnostic tools except for plain radiograph (magnetic resonance imaging), most common conservative treatment method (oral medication, rest), most important radiological factor in decision making for surgical treatment and method (size of the lesion, ankle instability, loose bodies), most important patient factors in decision making for surgical treatment and method (age, activity or occupation), infrequently requiring posterior arthroscopy (less than 3%), most common revision surgery for failed bone marrow stimulation procedure (osteochondral autograft transplantation [OAT]), not requiring additional procedure for donor site in OAT, the main reason for unsatisfactory result after OAT (persistent pain without radiological abnormality), no generalization of autologous chondrocyte implantation or chondrogenesis using stem cells. Conclusion: This study presents updated information on current trends in the management of OLT in Korea. Both consensus and variations in the approach to patients with OLT were revealed through this survey. Since recent biologic efforts to regenerate cartilage have been unsuccessful, further studies to identify clinical evidence would be needed.

• Information Systems Review
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• v.24 no.1
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• pp.21-37
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• 2022

Drug repositioning, one of the methods of developing new drugs, is a useful way to discover new indications by allowing drugs that have already been approved for use in people to be used for other purposes. Recently, with the development of machine learning technology, the case of analyzing vast amounts of biological information and using it to develop new drugs is increasing. The use of machine learning technology to drug repositioning will help quickly find effective treatments. Currently, the world is having a difficult time due to a new disease caused by coronavirus (COVID-19), a severe acute respiratory syndrome. Drug repositioning that repurposes drugsthat have already been clinically approved could be an alternative to therapeutics to treat COVID-19 patients. This study intends to examine research trends in the field of drug repositioning using machine learning techniques. In Pub Med, a total of 4,821 papers were collected with the keyword 'Drug Repositioning'using the web scraping technique. After data preprocessing, frequency analysis, LDA-based topic modeling, random forest classification analysis, and prediction performance evaluation were performed on 4,419 papers. Associated words were analyzed based on the Word2vec model, and after reducing the PCA dimension, K-Means clustered to generate labels, and then the structured organization of the literature was visualized using the t-SNE algorithm. Hierarchical clustering was applied to the LDA results and visualized as a heat map. This study identified the research topics related to drug repositioning, and presented a method to derive and visualize meaningful topics from a large amount of literature using a machine learning algorithm. It is expected that it will help to be used as basic data for establishing research or development strategies in the field of drug repositioning in the future.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.91-121
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• 2008

Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.