• The Journal of the Convergence on Culture Technology
• /
• v.5 no.4
• /
• pp.251-258
• /
• 2019

This study proposed a system that can improve the employment rate and maintenance employment rate by filtering information related to employment in analyzing big data for students who want to find employment. The subject was a two-year female university, the existing employment strategy participated in the job search with simple information such as school grades and personality. As a result, the maintenance employment rate was relatively low due to the decrease in the satisfaction of students seeking employment and the incompatibility with the post-employment aptitude. In order to solve these problems, we propose a system that determines and filters whether the input data in the process of analyzing big data such as employment-related information to improve employment and maintenance employment rates.

• Clinical and Experimental Pediatrics
• /
• v.64 no.3
• /
• pp.96-102
• /
• 2021

This study aimed to investigate the effect of maternal smoking during pregnancy (MSDP) on the risk of bone fractures in the offspring through a systematic review and meta-analysis. The PubMed, Web of Science, and Scopus databases were systematically searched for relevant articles published through July 2019. According to heterogeneity, the pooled risk ratio (RR) and odds ratio (OR) and their corresponding 95% confidence interval (CI) were obtained using fixed or random effects models. The heterogeneity and quality of the included studies were assessed by the I-squared (I²) statistic and the Newcastle-Ottawa scale, respectively. Sensitivity analyses were performed to test the effect of MSDP misclassification on the results. The review of 842 search records yielded 5 studies including 8,746 mother-child pairs that were included in the meta-analysis. Pooling adjusted effect measures showed that MSDP was not associated with a later risk of bone fractures in the offspring (pooled RR, 1.15; 95% CI, 0.84-1.58; I²=66.8%; P=0.049). After the adjustment for misclassification, MSDP may be associated with a 27% increased risk of bone fracture (pooled OR, 1.27; 95% CI, 1.00-1.62; I²=0%; P=0.537). After the adjustment for misclassification, MSDP is associated with an increased risk of bone fractures among children whose mothers smoked during pregnancy.

• The Korean Journal of Health Service Management
• /
• v.12 no.3
• /
• pp.119-129
• /
• 2018

Objectives: The purpose of this study was to provide basic data for the improvement of healthy habits and development of an oral health promotion program among Korean youth. Therefore, this study investigated adolescent health risk factors, oral health risk factors, and oral disease symptoms. Methods: This study used data from the Korea youth web-based survey, 2016. The subjects selected for the study were 61,086 persons who did not exhibit health risk factors, oral health risk factors, and oral disease symptoms. The statistical analyses were conducted by applying a complex sample analysis technique. Results: Those who drank carbonated beverages at least once a day were 1.15 times more likely to experience oral disease symptoms. The more sweet drinks they drank, the higher the risk of experiencing oral disease symptoms. Subjects who consumed alcohol had a 1.30 times greater risk of experiencing oral disease symptoms while subjects with smoking experience had a 1.13 times greater risk of experiencing oral disease symptoms. Conclusions: As a result, in order to maintain the physical and mental health of Korean adolescents, it is necessary to develop an oral health program for the prevention of unhealthy eating habits and oral diseases.

• International Journal of Advanced Culture Technology
• /
• v.9 no.2
• /
• pp.86-90
• /
• 2021

Sentiment refers to a person's thoughts, opinions, and feelings toward an object. Sentiment analysis is a process of collecting opinions on a specific target and classifying them according to their emotions, and applies to opinion mining that analyzes product reviews and reviews on the web. Companies and users can grasp the opinions of public opinion and come up with a way to do so. Recently, natural language processing models using the Transformer structure have appeared, and Google's BERT is a representative example. Afterwards, various models came out by remodeling the BERT. Among them, the Facebook AI team unveiled the XLM-R (XLM-RoBERTa), an upgraded XLM model. XLM-R solved the data limitation and the curse of multilinguality by training XLM with 2TB or more refined CC (CommonCrawl), not Wikipedia data. This model showed that the multilingual model has similar performance to the single language model when it is trained by adjusting the size of the model and the data required for training. Therefore, in this paper, we study the improvement of Korean sentiment analysis performed using a pre-trained XLM-R model that solved curse of multilinguality and improved performance.

• The Journal of Korean Society for School & Community Health Education
• /
• v.22 no.3
• /
• pp.1-15
• /
• 2021

Objectives: The purpose of this study was to examine whether demographic and socio-economic characteristics, health behaviors are related overweight and obesity in Korean adolescents. Methods: Data from the 15^th Korea Youth Risk Behaviors web-based Survey(KYRBWS) administered in 2019 were analyzed: 60,100 students in middle and high school participated in the survey. But except 1,555 missing value, 55,748 students were analyzed. It was conducted frequency analysis, Rao-Scott chi-square test and multiple logistic regression analysis. Results: The significant influencing factors on overweight and obesity of adolescents were gender, economic status, father's educational background, alcohol experience, fastfood consumption, muscle strengthening exercise, stress perception(p<.001). The odds ratio for overweight and obesity of male adolescents compared to female adolescents were 1.19(p<.001). and The odds ratio for overweight and obesity of perceived stress adolescents compared to those who without stress were 1.13(p<.001). Conclusions: I found that adolescents' some undesirable health behaviors affect their overweight and obesity, I recommend that school health promotion programmes should be implemented in schools to form good health behaviors such as healthy eating habits, physical exercise and managing stress.

• International Journal of Advanced Culture Technology
• /
• v.10 no.3
• /
• pp.220-225
• /
• 2022

The purpose of this study is to develop an e-teaching portfolio to perform a teaching portfolio of an instructor on the web. I order to carry out this study, an initial model of the e-teaching portfolio was developed through systematic literature review, and the final e-teaching portfolio was developed by selecting and applying five students, then modifying and supplementing them. The study period was from May 1 to May 20, 2022. As a result of the study, the components of the finally developed e-teaching portfolio are Step 1: Understanding oneself, Step 2: Goal setting, Step 3: Learning strategy, Step 4: Self-check. In conclusion, the program developed through this study is a convenient function that can process everything in one place by connecting the fragmented teaching results, and the developed e-teaching portfolio can promote interaction between individuals by building a community. It has possible characteristics. In order to systematically activate the e-teaching portfolio developed through this study, it is necessary to establish an online management system for systematic operation. Furthermore, an institutional device is needed to guarantee the result of the developed e-teaching portfolio. In order to continuously manage the quality of the teaching portfolio, extrinsic rewards that stimulate the instructor's intrinsic motivation should be provided.

• International Journal of Advanced Culture Technology
• /
• v.9 no.4
• /
• pp.288-294
• /
• 2021

There are various ways to be infected with malicious code due to the increase in Internet use, such as the web, affiliate programs, P2P, illegal software, DNS alteration of routers, word processor vulnerabilities, spam mail, and storage media. In addition, malicious codes are produced more easily than before through automatic generation programs due to evasion technology according to the advancement of production technology. In the past, the propagation speed of malicious code was slow, the infection route was limited, and the propagation technology had a simple structure, so there was enough time to study countermeasures. However, current malicious codes have become very intelligent by absorbing technologies such as concealment technology and self-transformation, causing problems such as distributed denial of service attacks (DDoS), spam sending and personal information theft. The existing malware detection technique, which is a signature detection technique, cannot respond when it encounters a malicious code whose attack pattern has been changed or a new type of malicious code. In addition, it is difficult to perform static analysis on malicious code to which code obfuscation, encryption, and packing techniques are applied to make malicious code analysis difficult. Therefore, in this paper, a method to detect malicious code through dynamic analysis and static analysis using Trojan-type Downloader/Dropper malicious code was showed, and suggested to malicious code detection and countermeasures.

• Journal of Wellbeing Management and Applied Psychology
• /
• v.5 no.3
• /
• pp.7-17
• /
• 2022

Purpose: With the introduction of Web 2.0, the advent of smartphones, and the recent outbreak of COVID-19 worldwide, interest in online shopping has soared. In an online shopping environment, the desire for impulse buying increases compared to offline shopping. Research design, data and methodology: In this study, three marketing stimulating factors such as product factor, price factor, and facilitating factor were selected which affect impulse buying for clothing and accessory products in the Korean online shopping environment. The mechanism of causal relationship among them, and the role customer value between marketing stimulating factor and impulse buying was analyzed. Results: The analysis results are as follows. First, the product factor had a significant positive effect on consumer value and impulse buying. Second, the price factor also had a significant positive effect on consumer value and impulse buying. Conclusions: Although the facilitating factor had no significant influence on consumer value and impulse buying, the indirect effect through consumer value was positively significant. Consumer value had a positive mediating effect on impulse purchase in the order of price factor, product factor, and promotion factor.

• International Journal of Advanced Culture Technology
• /
• v.10 no.2
• /
• pp.201-212
• /
• 2022

With the development of sequencing technology, there is a need for technology to predict the function of the protein sequence. Enzyme Commission (EC) numbers are becoming markers that distinguish the function of the sequence. In particular, many researchers are researching various methods of predicting the EC numbers of protein sequences based on deep learning. However, as studies using various methods exist, a problem arises, in which the exact prediction result of the sequence is unknown. To solve this problem, this paper proposes an All Enzyme Commission (AEC) algorithm. The proposed AEC is an algorithm that executes various prediction methods and integrates the results when predicting sequences. This algorithm uses duplicates to give more weights when duplicate values are obtained from multiple methods. The largest value, among the final prediction result values for each method to which the weight is applied, is the final prediction result. Moreover, for the convenience of researchers, the proposed algorithm is provided through the AllEC web services. They can use the algorithms regardless of the operating systems, installation, or operating environment.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.1
• /
• pp.613-618
• /
• 2023

In this paper, a monitoring program that can automatically determine whether a patient admitted to an isolation room acts out of a stable state through a screen photographed in real time is described. The motion recognition model of this program was built by learning through transfer learning. 900 images were used for the three movements, and this program was developed for the web to support all environments. The model was determined with high accuracy to determine the state of the subject hospitalized in the isolation room, and can be applied by applying it to the existing isolation room monitoring system.