• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.359-367
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• 2022

The purpose of this study was to explore the effect of learning effects by type on college life satisfaction for college students. A total of 250 copies of the survey were distributed, and a total of 219 copies were used for analysis except for 31 copies, excluding questionnaires with many poor or missing questions. The learning effect according to the socio-demographic characteristics of college students showed a significant difference in the form of cohabitation, and it was found that the learning effect was high in the order of alone and friends. Perceptual learning showed significant differences in the form of cohabitation, and it was found that perception learning was high in the order of alone, friends, and seniors and juniors. Cognitive learning showed significant differences in the form of cohabitation, and cognitive learning was found to be high in the order of friends, alone, and seniors and juniors. There was a significant difference in college satisfaction with the type of cohabitation, and it was found that college satisfaction was high in the order of alone, seniors and juniors, and friends. Finally, the higher the discovery learning, perceptual learning, and cognitive learning, the higher the college life satisfaction, and among them, discovery learning was found to have a great influence on college life satisfaction. Overall, the university should provide an environment where students can freely move between individuals and communities and live their university life. In addition, in preparation for problems occurring in the community, it will be necessary to activate the related counseling room.

• Journal of Korea Entertainment Industry Association
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• v.13 no.5
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• pp.203-213
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• 2019

The purpose of this study was to compare the anxiety, sexual attitudes, and sexual behavior according to smartphone use and contacts with obscene materials. 110 university students surveyed demographic characteristics, smartphone use, contacts with obscene materials, anxiety, sexual attitudes, and sexual behavior, and analyzed 102 questionnaires except missing and incomplete responses. The collected data were analyzed by independent t-test or chi-square test. Men were significantly more likely to have contacts with obscene materials, sexual attitudes, and sexual behavior than the women (p<.05). In type of residence, boarding room or lodging was significantly higher at time of smartphone use, anxiety, and sexual behaviors than the home (p<.05). There was no difference in variables according to religion (p>.05). There was no difference in variables according to the level of academic achievement (p>.05). Time of smartphone use over 3 hours was significantly higher for contacts of obscene materials, anxiety, and sexual attitudes and behaviors than less 3 hours (p<.05). Higher levels of time of contacts with obscene materials were significantly higher in anxiety and sexual behaviors than lower level (p<.05). The results of this study can be used as a basis for the development of intervention programs for those who are experiencing excessive smartphone use and contacts with obscene materials.

• Journal of Korea Entertainment Industry Association
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• v.13 no.2
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• pp.243-252
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• 2019

The purpose of this study was to evaluate the effect of emotional intelligence, empathy ability, and calling consciousness of nursing students on happiness. The survey was conducted 217 nursing students attending in G city from September 3th to September 14th, 2018. Data was collected from self-administered questionnaires about happiness, emotional intelligence, empathy ability and calling consciousness. Data were analyzed by SPSS software version 21 using descriptive statistics (frequency) and analytical statistics (t-test, ANOVA, Pearson's correlation coefficient, linear regression). As a result, Happiness was significantly different by gender, grade, satisfaction in major, collegiate-life satisfaction, personal relationship, health status, perceived economic status. Also happiness showed positive correlation with emotional intelligence, empathy ability, and calling consciousness. Multiple regression analysis revealed that the predictors of happiness were grade, collegiate-life satisfaction, health status, empathy ability, calling consciousness, and emotional intelligence accounting for a total of 49.1% of the variance. Results of this study suggest that it is necessary for nursing students to intervention program aimed at enhance the happiness and it would be effective to focus on strengthening emotional intelligence and empathy ability for them.

• Korean Journal of Forensic Psychology
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• v.12 no.2
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• pp.223-251
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• 2021

Statement analysis is a technique that examines the credibility of a statement by scientifically analyzing problems and psychological characteristics that appear in the content of the statement. The statement analysis report is prepared, submitted, and used for legal judgments when there is a suspicion of sexual abuse for children(under 13 years of age) and persons with disabilities since it is usually difficult to secure physical evidence nor eyewitnesses. However, the criteria for evaluating the quality of a statement analysis report or testimony are not available in Korea. Although forensic experts and professional organizations in North America and Europe are providing recommendations and guidelines for preparing forensic assessment reports, qualitative analysis research studies for forensic reports revealed a number of problems such as missing or poorly described essential information and lack of logical connection between evaluation results and forensic opinions. Therefore, forensic evaluation guidelines and forensic reports submitted to the courts in the United States, as well as the Structured Quality assessment of eXpert testimony (SQX-12) developed in Sweden were examined to suggest the Korean version of quality evaluation criteria for statement analysis report and testimony. This criteria can be used to improve effectiveness of forensic reports within criminal justice system and used as a guideline to assess the quality forensic reports or expert testimony prepared by experts. However, this criteria do not guarantee the reliability of the statement itself.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.203-211
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• 2022

This study is to examine the causes of research misconduct such as plagiarism, forgery, redundant publication, unfair author expression, and incapacitation of the research ethics system of university researchers and to suggest improvement plan. It basically relied on literature research. In order to supplement the deficiencies in literature research, I sought advice from an expert professor who had experience working in a research-related field in university or who is currently in a position related to research ethics through the delphi-method. As a result of the study, from the perspective of individual researchers, the complacent attitude, dishonesty, and greed for research funds were identified as the main reasons. In terms of organization, it was analyzed for reasons such as lack of detail and application of regulations, lack of verification system, and performance-oriented research environment. In order to overcome research misconduct caused by the researcher's personal reasons, regularization, increase in the number of research ethics education, and strengthening personal penalties were suggested. As a way to overcome irregularities arising from institutional reasons, the reinforcement of the verification system, the reinforcement of the whistle-blower's personal protection system, the omission of promotion, and the quality and quantitative balance of research evaluation was suggested.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.325-331
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• 2022

As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.

• Korea Trade Review
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• v.43 no.4
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• pp.155-175
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• 2018

This study estimates the technical efficiency and total factor productivity(TFP) of and analyzes the relationship between TFP and exports for Korean manufacturing companies from 2000 to 2016. Specially, TFP is decomposed into Technical Change(TC), Technical Efficiency Change (TEC), and Sale Effect(SE), and compared between large and small enterprises. First, in the case of technical efficiency, the Korean economy has been very vulnerable to external shocks, such as the sharp decline following the 2008 financial crisis. The efficiency of the electronics, automobile, and machinery sectors is low and needs to be improved. In addition, the technological efficiency of large enterprises is higher than that of SMEs in most manufacturing sub-sectors except for non-ferrous metals. In the case of TFP, most changes are due to TC, and the effective combination of labor, capital and the effect of scale have little effect, suggesting that improvement of internal structure is urgent. In addition, volatility due to the impact of the financial crisis in 2008 was much larger in SMEs than in large companies, so external economic impacts are more greater for SMEs than large enterprises. The relationship between TFP decomposition factors and exports shows that TC has a positive effect only on exports of SMEs. Therefore, in order to increase exports, in the case of SMEs, R&D support to promote technological development is needed. In the case of large companies, it is necessary to establish differentiated strategies for each export market, competitor company, and item to link efficiency and scale effect of exports.

• Journal of the Korean Society for information Management
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• v.40 no.2
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• pp.183-209
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• 2023

The purpose of this study is to evaluate the Dublin Core metadata generated by ChatGPT using book covers, title pages, and colophons from a collection of books. To achieve this, we collected book covers, title pages, and colophons from 90 books and inputted them into ChatGPT to generate Dublin Core metadata. The performance was evaluated in terms of completeness and accuracy. The overall results showed a satisfactory level of completeness at 0.87 and accuracy at 0.71. Among the individual elements, Title, Creator, Publisher, Date, Identifier, Rights, and Language exhibited higher performance. Subject and Description elements showed relatively lower performance in terms of completeness and accuracy, but it confirmed the generation capability known as the inherent strength of ChatGPT. On the other hand, books in the sections of social sciences and technology of DDC showed slightly lower accuracy in the Contributor element. This was attributed to ChatGPT's attribution extraction errors, omissions in the original bibliographic description contents for metadata, and the language composition of the training data used by ChatGPT.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.131-146
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• 2023

Smart card data is widely used in the public transportation field. Despite the inevitability of various errors occur during the data collection and storage; however, smart card data errors have not been extensively studied. This paper investigates inherent errors in boarding and alighting station information in smart card data. A comparison smart card data and bus boarding and alighting survey data for the same time frame shows that boarding station names differ by 6.2% between the two data sets. This indicates that the error rate of smart card data is 6.2% in terms of boarding station information, given that bus boarding and alighting survey data can be considered as ground truth. This paper propose 6-step algorithm for correcting errors in smart card boarding station information, linking them to corresponding information in Bus Information System(BIS) Data. Comparing BIS data and bus boarding and alighting survey data for the same time frame reveals that boarding station names correspond by 98.3% between the two data sets, indicating that BIS data can be used as reliable reference for ground truth. To evaluate its performance, applying the 6-step algorithm proposed in this paper to smart card data set shows that the error rate of boarding station information is reduced from 6.2% to 1.0%, resulting in a 5.2%p improvement in the accuracy of smart card data. It is expected that the proposed algorithm will enhance the process of adjusting bus routes and making decisions related to public transportation infrastructure investments.