• Child Health Nursing Research
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• v.13 no.2
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• pp.157-165
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• 2007

Purpose: This study was done to investigate internet addiction, sexual attitudes and gender egalitarianism in middle school students, and to identify the differences of sexual attitude and gender egalitarianism according to the level of internet addiction. Method: The participants were 344 students from two middle schools in Seoul. Data were collected through self-report questionnaires which included an internet addiction test, a sexual attitude scale, and a Korean gender egalitarianism scale for adolescents. The data were analyzed using the SPSS program. Results: Of the students, 63.1% reported being average on-line users, 33.4%, heavy on-line users, and 3.5%, internet addicted. Sexual attitudes and gender egalitarianism of average on-line users were different from those addicted to the internet. Internet addiction, sexual attitudes and gender egalitarianism of students were different according to general characteristics, time spent on-line, and exposure and contact to cyber obscenities. Conclusion: Sexual attitudes and gender egalitarianism in middle school students were influenced by internet addiction. Therefore nursing interventions to prevent and manage internet addiction need to be developed and provided to middle school students. Also a variety of programs for teaching sexuality to adolescents should be developed.

• Korean Journal of Health Education and Promotion
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• v.30 no.2
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• pp.1-10
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• 2013

Objectives: The objective of this study was to assess the relationship between internet addiction and health behaviors & mental health among Korean adolescents. Methods: Data from the 2010 Korean Youth Risk Behavior Web-based Survey was analyzed. Using the Korean Internet Addiction Proneness Scale for Youth-Short Form: Self Report developed by the Korean National Information Society Agency in 2008, subjects were classified into 3 groups for internet addiction including general user, potential-risk group, and high-risk group. The health behaviors and mental health were compared among the groups for internet addiction by gender. Results: There was significantly higher prevalence of internet addiction including potential-risk group and high-risk group in boys(14.1%) than in girls(8.8%). There were significant odds ratios of perceived stress, perceived depression, perceived health and happiness, and satisfaction of sleeping in both genders at potential-risk group and high-risk group compared to general user for the internet addiction. The odds ratios of smoking at high risk group, alcohol drinking at potential risk group, eating breakfast at high risk group, and moderate physical activity at both risk groups among boys were significant. Among girls at both risk group, the odds ratios of smoking, alcohol drinking, and eating breakfast were significant. Conclusions: This study reveals a significant association among internet addiction, and health behaviors, and mental health in Korean adolescents.

• Child Health Nursing Research
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• v.11 no.4
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• pp.405-414
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• 2005

Purpose: This study was a cross-sectional descriptive survey to identify school nurses' knowledge, educational needs and providing education about Internet addiction. Method: A total of 198 school nurses working in schools located in Gyunggi Province and the cities of Ulsan, Daegu, and Pohang participated in the study A self-report scale was used to collect data. It included 53 items measuring school nurses' knowledge, their educational needs and performing related to Internet addiction. Results: The mean score for knowledge of Internet addiction was 13.12 (SD=3.13), indicating a moderate level of knowledge. The highest frequency, $24.7\%$ of the school nurses agreed that the computer teacher is the appropriate person to do educate on Internet addiction, followed by the school nurse with another teacher ($24.2\%$). Only $40.4\%$ of the nurses had any experience in providing students with education about Internet addiction. The main reason for not providing education about Internet addiction was that there was no time ($57.6\%$). Education was reported most frequently as being provided by the class teacher ($36.3\%$), followed by school nurse ($31.3\%$). Conclusions: It is important to expand the role of school nurses in preventing and responding to Internet addiction and to develop training programs designed to further develop their abilities in teaching and counseling.

• Korean Parent-Child Health Journal
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• v.8 no.2
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• pp.112-122
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• 2005

Purpose: This study was done to investigate the relation to perceived maternal child rearing behaviors and the level of internet addiction in the upper year grade students. Method: Data was collected through self-report questionnaires in which perceived maternal child rearing behaviors and internet addiction. This study population was comprised of 668 students who enrolled 4~6 year-grade in Kwangwon-Do. The data collected was analyzed by the SPSS program. Results: The level of internet addiction of subjects was rather low. Of the children, 88.2% reported being average on-line users, 7.3%, heavy on-line users, and 4.5%, internet addicted. Gender, existence of father, mother's attitude when child overuse on-line, average playing time of on-line per day, frequency of on-line visits per week and purpose of on-line use for average on-line users were different from that of heavy on-line users. The level of perceived maternal child rearing behaviors were abbreviate positively correlated to the level of internet addiction in subjects. Conclusion: We suggest these results be used to develop a internet addiction prevention program.

• Journal of East-West Nursing Research
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• v.21 no.1
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• pp.78-84
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• 2015

Purpose: The purpose of this study was to investigate the relationship between self-esteem, social support, smartphone dependency and internet game dependency of college students. Methods: This was a descriptive study. The survey participants were 299 college students in M city and I city. The data were collected from June 2 to June 20, 2014 and self-report questionnaires including Self-Esteem Scale, Multidimensional Scale of Perceived Social Support, Smartphone Dependency Sale, Internet Game Dependency Scale. Data were analyzed by descriptive statistics, independent-sample t-test, ANOVA, stepwise multiple regression. Results: Social support & smartphone dependency showed significant differences according to gender. Smartphone dependency was found to have a statistically negative correlation with self-esteem, social support and positive correlation with internet game dependency. Internet game dependency was found to have a statistically negative correlation with self-esteem, social support. Social support was found to have a statistically negative correlation with self-esteem. Stepwise multiple regression analysis revealed that the significant predictors of smartphone dependency were internet game dependency, gender, self-esteem, accounted for 16.6% of the variance. Conclusion: It is necessary for reduction program of college students' smartphone dependency that consider their internet game dependency, gender, self-esteem.

• The Korean Journal of Rehabilitation Nursing
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• v.14 no.2
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• pp.145-152
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• 2011

Purpose: The study was to identify the influences of stress, social support and impulsiveness on the internet addiction of adolescents. Methods: A cross-sectional study was conducted with 243 male middle and high school students in D city. Data were collected from March to April in 2009 using self-report questionnaires such as internet addiction test, perceived stress, social support appraisal scale and Barratt impulsiveness scale. Data were analyzed using frequency, mean, Pearson's corelation coefficient, & hierarchial multiple regression. Results: The results showed that adolescents who had poor social support or higher stress and impulsiveness were more likely to have higher levels of internet addiction. The internet addiction was positively related to the stress and impulsiveness and negatively related to the social support. And education, record at school, stress, social support and impulsiveness had influence on the depression. Conclusion: Based on the findings, school nurses need to screen the risk of the internet addiction for adolescents who are in serious stress and have poor social support and impulsiveness. It is necessary to develop some preventive programs for those in high risk of internet addiction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4183-4204
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• 2018

The existing en-route filtering schemes only consider some simple false data injection attacks, which results in lower safety performance. In this paper, we propose an efficient geographical information-based en-route filtering scheme (EGEFS), in which each forwarding node verifies not only the message authentication codes (MACs), but also the report identifier and the legitimacy and authenticity of locations carried in a data report. Thus, EGEFS can defend against not only the simple false data injection attacks and the replay attack, but also the collusion attack with forged locations proposed in this paper. In addition, we propose a new method for electing the center-of-stimulus (CoS) node, which can ensure that only one detecting node will be elected as the CoS node to generate one data report for an event. The simulation results show that, compared to the existing en-route filtering schemes, EGEFS has higher safety performance, because it can resist more types of false data injection attacks, and it also has higher filtering efficiency and lower energy expenditure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1583-1598
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• 2019

Recently, software has increased in complexity and been applied in various industrial fields. As a result, the presence of software bugs cannot be avoided. Various bug severity prediction methodologies have been proposed, but their performance needs to be further improved. In this study, we propose a novel technique for bug severity prediction in cross projects such as Eclipse, Mozilla, WireShark, and Xamarin by using topic modeling and similarity (i.e., KL-divergence). First, we construct topic models from bug repositories in cross projects using Latent Dirichlet Allocation (LDA). Then, we find topics in each project that contain the most numerous similar bug reports by using a new bug report. Next, we extract the bug reports belonging to the selected topics and input them to a Naïve Bayes Multinomial (NBM) algorithm. Finally, we predict the bug severity in the new bug report. In order to evaluate the performance of our approach and to verify the difference between cross projects and single project, we compare it with the Naïve Bayes Multinomial approach; the Lamkanfi methodology, which is a well-known bug severity prediction approach; and an emotional similarity-based bug severity prediction approach. Our approach exhibits a better performance than the compared methods.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.29-37
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• 2019

As software development technology evolves, the quality of software has increased. But software created through sophisticated technology is still defective. The developer will be aware of the defect through a bug report and the reported defect must be fixed as soon as possible for the software to function correctly. It is important to know which component of the program is related to the reported defect and should be fixed. However, even though the developer understands the developed software, the task of tracing faults is a time-consuming task and requires effort. Therefore, if there is a way for developers to support tracing faults, they could fix defects more quickly. Because fixing defects rapidly is a factor of software reliability, fault traceability is essential and an effective method is needed. Therefore, in this paper, we propose a model-based fault traceability enhancement technique by using bug report and commit information and verify the effectiveness of the proposed technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2768-2787
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• 2023

As an important research direction of the application of computer science in the medical field, the automatic generation technology of radiology report has attracted wide attention in the academic community. Because the proportion of normal regions in radiology images is much larger than that of abnormal regions, words describing diseases are often masked by other words, resulting in significant feature loss during the calculation process, which affects the quality of generated reports. In addition, the huge difference between visual features and semantic features causes traditional multi-modal fusion method to fail to generate long narrative structures consisting of multiple sentences, which are required for medical reports. To address these challenges, we propose a multi-feature optimization Transformer (MFOT) for generating radiology reports. In detail, a multi-dimensional mapping attention (MDMA) module is designed to encode the visual grid features from different dimensions to reduce the loss of primary features in the encoding process; a feature pre-fusion (FP) module is constructed to enhance the interaction ability between multi-modal features, so as to generate a reasonably structured radiology report; a detail enhanced attention (DEA) module is proposed to enhance the extraction and utilization of key features and reduce the loss of key features. In conclusion, we evaluate the performance of our proposed model against prevailing mainstream models by utilizing widely-recognized radiology report datasets, namely IU X-Ray and MIMIC-CXR. The experimental outcomes demonstrate that our model achieves SOTA performance on both datasets, compared with the base model, the average improvement of six key indicators is 19.9% and 18.0% respectively. These findings substantiate the efficacy of our model in the domain of automated radiology report generation.