• Korean Journal of Health Education and Promotion
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• v.27 no.4
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• pp.123-129
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• 2010

Objectives: The aim of this study is to seek an effective way to support smoking cessation by analyzing any change to the pattern of nicotine dependence according to the change in time. Methods: The study was conducted with 800 male smokers who had participated in smoking cessation programs at public health centers from July 16, 2005 to July 15, 2008. Latent growth curve modeling approach was used for data analysis. Results: From the developmental trajectory of individual nicotine dependence, while nicotine dependence of smokers with high nicotine dependence in the first year was slightly decreased in the third year, smokers with low nicotine dependence in the year showed dramatically lower nicotine dependence in the third year. Compared with those who did not successfully quit smoking, the initial value of nicotine dependence of those who successfully quit smoking in the first and the second year was low. Over the years, nicotine dependence was decreased. Conclusion: From this study it was demonstrated that nicotine dependence was reduced through the practice of smoking cessation and reduced nicotine dependence was a factor which affects successful smoking cessation. These results indicate that multiple attempts to quit smoking finally reduces nicotine dependence. Reduced nicotine dependence is likely to increase the possibility of successful smoking cessation.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.521-526
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• 2017

Data format of Big data is diverse and vast, and its generation speed is very fast, requiring new management and analysis methods, not traditional data processing methods. Textual mining techniques can be used to extract useful information from unstructured text written in human language in online documents on social networks. Identifying trends in the message of politics, economy, and culture left behind in social media is a factor in understanding what topics they are interested in. In this study, text mining was performed on online news related to a given keyword using topic - oriented analysis technique. We use Latent Dirichiet Allocation (LDA) to extract information from web documents and analyze which subjects are interested in a given keyword, and which topics are related to which core values are related.

• Human Ecology Research
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• v.54 no.6
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• pp.565-574
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• 2016

This research examined the trajectories of peer rejection in preschool children. This study also investigated the gender differences in the intercept and slope of the trajectories for peer rejection along with the influences of aggression, withdrawal and language ability on the trajectories of peer rejection. A latent growth curve model investigated peer rejection in 3 to 5 year olds. Three hundred and thirteen 3-year-old children were recruited from five preschools and 14 daycare centers. The children's language ability was measured by a Wechsler Preschool and Primary Scale of intelligence verbal test and teachers completed measurements for aggression and withdrawal. A peer nomination inventory was used to assess peer rejection. Children were asked to nominate three classmates who they do not like to play with. The research findings showed that peer rejection decreased during the preschool years. Compared with girls, boys showed higher levels of peer rejection and a slower change rate of peer rejection. Girls who were aggressive showed high levels of peer rejection and a slow change rate of peer rejection. Moreover, girls who had a high levels language showed low levels of peer rejection and a slow change rate of peer rejection. These findings imply that language ability could be a protective factor of peer rejection for girls.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.3
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• pp.425-436
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• 1987

Accurate predictions of heat transfer coefficient of vertical laminar film-boiling are very important in many engineering applications. There are many predictions, however they are not exact as yet, since they have used the assumption of constant thermodynamic properties in the analysis. In this paper, heat transfer of vertical film boiling was analysized by Runnge Kutta method using veriable thermodynamic properties. 1/4 interval method was exployed for the prediction of unknown wall boundary condition. Numerical computations were performed with varying the wall temperature and the free stream velocity of liquid. Results show that assumption of constant thermodynamic properties induced considerable error in predicting the heat transfer coefficient, friction factor, film thickness, and critical length for transition to turbulent flow. Comparision of the predicted heat transfer coefficient of present analysis with that from Bromley's correlation shows that the use of general latent heat in Bromely equation instead of modified latent heat is more desireable since it makes the coefficient of Bromley equation into constant.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.6
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• pp.372-380
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• 2008

In order to control indoor air quality and save energy, it is needed to install a suitable ventilation system equipped with heat exchanger for heat recovery. Paper heat exchanger can recover $50{\sim}70%$ of the enthalpy difference between supply and exhaust air. The purpose of this research is to obtain the experimental correlations for the friction factor, heat transfer coefficient, mass transfer coefficient and permeance of paper heat exchanger, which can be used to predict the performance of the paper heat exchanger. Pressure drops at various velocities, and sensible and latent heat transfer rates at various dry-bulb temperatures, relative humidities and specific humidities are measured to derive experimental correlations. The results of prediction using correlations show fairly good agreement with the experimental data obtained in the actual operating conditions.

• Journal of Science Education
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• v.43 no.1
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• pp.1-16
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• 2019

This exploratory study is aimed at exploring the validity of the Science Motivation Questionnaire (SMQ) developed for university students, to measure the science motivation of middle school students and analyze the differences on gender and country factors of SMQ. A total of 371 students participated in this study: 171 middle school students from the USA and 200 secondary students from Korea. All participants were enrolled in the STEM program and activities in Utah, USA (for US students) and at a Korean university institute for gifted and talented students (for Korean students). In this study, exploratory and confirmatory factor analyses and latent mean analysis were used to analyze the gender and country differences. The results indicated that the 25 items of SMQ scale were theoretically meaningful and valid for middle school students. The latent mean difference by gender indicated that male students have higher intrinsic motivation, career motivation, grade motivation, and self-determination than female students. Moreover, a significant difference exists in these factors between the two countries. Further findings reveal that Korean students scored higher than US students in terms of the aforementioned factors. This study will provide significant insights in and contribution to science motivation issues in STEM education and the development of design-based engineering programs.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.92-103
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• 2021

With the continuous acceleration of economic and social development, people gradually pay attention to their health, improve their living environment, diet, strengthen exercise, and even conduct regular health examination, to ensure that they always understand the health status. Even so, people still face many health problems, and the number of chronic diseases is increasing. Recently, COVID-19 has also reminded people that public health problems are also facing severe challenges. With the development of artificial intelligence equipment and technology, medical diagnosis expert systems based on big data have become a topic of concern to many researchers. At present, there are many algorithms that can help computers initially diagnose diseases for patients, but they want to improve the accuracy of diagnosis. And taking into account the pathology that varies from person to person, the health diagnosis expert system urgently needs a new algorithm to improve accuracy. Through the understanding of classic algorithms, this paper has optimized it, and finally proved through experiments that the combined classification algorithm improved by latent factors can meet the needs of medical intelligent diagnosis.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.199-214
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• 2020

An important technique of the present invention is primarily to parallel light detection, self-pulse therapy after diagnosis. Herpes zoster is a disease caused by varicella zoster virus, and the virus that has been latent in the dorsal root ganglion that controls the skin segment loses its immune system and physically damages it. It is an acute skin disease in which acute pain and bullous rash occur along the sensory ganglia, which are rehab by inducers such as malignant tumors. Dorsal root ganglion after complete recovery of varicella, relapsed after incubation in brain ganglion, latent virus sometimes suppressed activity by cell mediated immunity, and in cell ganglion with reduced cellular immunity. It proliferates and destroys neurons, causing pain while forming a rash and blisters. This can reduce cell necrosis and increase the phagocytosis and enzymatic activity through the movement of ions through the cell membrane, depolarization and membrane potential change, growth factor secretion, calcium ion transfer, chondrocyte synthesis, etc., And may offer treatment options for lesions of herpes zoster and post-herpetic neuralgia (PHN).Therefore, according to the present research, the diagnosis and treatment device of treating paing for herpes zoster and post-herpetic pain can be implemented in the early stage of herpes zoster, and conventional analgesic regulation, anti-inflammatory effect, post-herpetic neuralgia.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.589-603
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• 2023

Deep generative models target to infer the underlying true data distribution, and it leads to a huge success in generating fake-but-realistic data. Regarding such a perspective, the data attributes can be a crucial factor in the data generation process since non-existent counterfactual samples can be generated by altering certain factors. For example, we can generate new portrait images by flipping the gender attribute or altering the hair color attributes. This paper proposes counterfactual disentangled variational autoencoder generative adversarial networks (CDVAE-GAN), specialized for data attribute level counterfactual data generation. The structure of the proposed CDVAE-GAN consists of variational autoencoders and generative adversarial networks. Specifically, we adopt a Gaussian variational autoencoder to extract low-dimensional disentangled data features and auxiliary Bernoulli latent variables to model the data attributes separately. Also, we utilize a generative adversarial network to generate data with high fidelity. By enjoying the benefits of the variational autoencoder with the additional Bernoulli latent variables and the generative adversarial network, the proposed CDVAE-GAN can control the data attributes, and it enables producing counterfactual data. Our experimental result on the CelebA dataset qualitatively shows that the generated samples from CDVAE-GAN are realistic. Also, the quantitative results support that the proposed model can produce data that can deceive other machine learning classifiers with the altered data attributes.

• Solar Energy
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• v.17 no.2
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• pp.75-89
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• 1997

In this paper, the operating thermal characterictics of liquid-ice was expeimentally investigated in an adiabatic and a non-adiabatic direct contact liquid-ice heat exchanger. Experiments were carried out varing inlet temperature, Ice Packing Factor, and the flow rate of heat transfer fluid. The higher inlet temperature and the more much inlet flow rate, thermal stratification in liquid-ice heat exchanger was established faster. In the case of adiabatic ice storage tank, temperature distribution was a little higher at all conditions than that of non-adiabatic one. The ratio of latent energy to total discharge energy($E_{\lambda}/E_[tot}$) was about 80%, and the discharge of latent heat energy was appeared rapidly as inlet temperature and flow rate were higher.