• Journal of The Korean Association For Science Education
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• v.22 no.5
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• pp.1010-1029
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• 2002

The purpose of this research was to survey middle school students' preference for science and its causal factors, so as to analyze the causal relationships between them. Preference for science and its causal factors were defined theoretically, and a theoretical model was constructed to measure them and analyze the causal relationship by structural equation modeling. According to the theoretical model and a pilot test, a questionnaire was developed with three parts; the background information of a respondent, the preference for science, and the causal factors of preference. The questionnaire was administered to one class per grade of randomly selected 8 middle schools from 4 areas across the country, and 819 students' data were collected. Preference for science was defined as a state of mind. It revealed to what extent, and how, one likes science. It consisted of 3 categories - 'emotional response', 'behavioral volition', 'valuational comprehension', and each category was divided into two subcategories. Causal factors affecting the preference for science consisted of three categories - personal, educational and social factors, and each was divided into 2 or 3 subcategories. Middle school students' preference for science was middling as a total. Curiosity about contents of science and valuation of science were high, comparatively, but behavioral volition about science was especially low. Students' responses to the causal factors were relatively high in every educational factor and sociocultural valuation of social factors, but relatively low in socioeconomic rewards of social factors, and especially low in personal factors. The causal relationship about the preference for science was investigated by multiple regression analysis and path analysis, using the structural equation model. Multiple regression analysis about the preference for science and its causal factors revealed important factors. The important factors were personal ability, the personal traits, rewards in school science, and contents of school science in order of magnitude of standardized regression coefficient ${\beta}$. Stepwise regression analysis with each of the subcategories of the preference for science as dependent variables showed what factors were important in each subcategory. According to the result of structural equation modeling, personal factors affected 'emotional response' and 'behavioral volition' directly, and social factors affected 'valuational comprehension' directly. Educational factors affected all categories of the preference for science by influencing not only 'emotional response' and 'valuational comprehension' directly, but also 'behavioral volition' indirectly. The way to promote middle school students' preference for science was suggested, based on the analysis result.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.339-346
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• 2018

An Industry Foundation Classes(IFC), which is a data schema developed focusing on architecture, is being expanded to civil engineering structures. However, it is difficult to create an information model based on extended IFC since the BIM software cannot provide support functions. To manage a railway track based on the extended IFC, this paper proposed a method to create an alignment-centered separated railway track model and convert it to an extended IFC-based information model. First, railway track elements have been classified into continuous and discontinuous structures. The continuous structures were created by an alignment-based software, and discontinuous structures were created as independent objects through linkage of the discretized alignment. Second, a classification system and extended IFC schema for railway track have been proposed. Finally, the semantic information was identified by using the property of classification code and user interface. The availability of the methods was verified by developing an extended IFC-based information model of the Osong railway site.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.91-117
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• 2022

The number of depressed patients in Korea and around the world is rapidly increasing every year. However, most of the mentally ill patients are not aware that they are suffering from the disease, so adequate treatment is not being performed. If depressive symptoms are neglected, it can lead to suicide, anxiety, and other psychological problems. Therefore, early detection and treatment of depression are very important in improving mental health. To improve this problem, this study presented a deep learning-based depression tendency model using Korean social media text. After collecting data from Naver KonwledgeiN, Naver Blog, Hidoc, and Twitter, DSM-5 major depressive disorder diagnosis criteria were used to classify and annotate classes according to the number of depressive symptoms. Afterwards, TF-IDF analysis and simultaneous word analysis were performed to examine the characteristics of each class of the corpus constructed. In addition, word embedding, dictionary-based sentiment analysis, and LDA topic modeling were performed to generate a depression tendency classification model using various text features. Through this, the embedded text, sentiment score, and topic number for each document were calculated and used as text features. As a result, it was confirmed that the highest accuracy rate of 83.28% was achieved when the depression tendency was classified based on the KorBERT algorithm by combining both the emotional score and the topic of the document with the embedded text. This study establishes a classification model for Korean depression trends with improved performance using various text features, and detects potential depressive patients early among Korean online community users, enabling rapid treatment and prevention, thereby enabling the mental health of Korean society. It is significant in that it can help in promotion.

• Korea Science and Art Forum
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• v.32
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• pp.319-334
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• 2018

This research is a case study to make sure the enhancement of students' imagination and creativity through developing and applying the Literature-Art-Science Integrated Education Program. Its research object was totally 25 persons of 29 students of the 1st to the 4 th Grades from Gunsan Sulsan Elementary School. Its research period lasted for 4 months from September to December, 2017, and I, as the research place, used the art room at Gunsan Sulsan Elementary School. The programs were totally 10 sessions with a unit of 1 session per each grade for 2 hours from 1:00 to 3:00 in the afternoon from Monday through Friday. I fixed ten themes of this program-eight plane modeling, and two solid modeling, and finished the work of storytelling during summer vacation. And I arranged their levels as low:middle:high(3:5:2) ones. The former was 'A Film of Monster Gorilla'(L), 'Learning the Spirit of Gyeongju Choi's Family'(M), 'A Tale of My Friend Made of Natural Materials'(L), 'The Reading of My Dream'(M), 'Gathering the Objects in My Mobile'(M), 'A Mock Trial of Marrying Off'(M), 'Painting My Favorite Children's Poem'(H), and 'Painting My Favorite Children's Song'(H), and the latter was 'Seeking for a Bluebird in My Mind'(L), and 'Making My Cherished Object' (M). Then I used the unique art expression technique per each theme, which were in sequence marbling, Korean paper art, combine painting, collage, imaginary painting, imaginary painting, play dough art, imaginary painting techniques. And I delivered to the students the scientific knowledge in terms of growing or manufacturing processes of materials used for making artworks. Prior to and after the processing this program, I surveyed about the students' ability of integrated thinking and emotional experience by 'Figure B Type' and 'Figure A Type' of The Torrance Tests of Creative Thinking, and took statistics with the resultant data. And I executed a paired t-test in order to verify the significance of mean difference in the result of investigation with those data. From the analyzed result according to the elements of creativity and the mean quotients of creativity, there showed a significant difference (t=3.47, p<.01) in 'fluency', and also a significant difference(t=3.59, p<.01) in 'creativity.' Judging from the statistic values of two fields such as the student's ability of integrated thinking and emotional experience, I estimate that over the majority of the students showed the enhancement in self-confident creative expression as well as higher interest and concern through this program. The result that I arranged and analyzed the making process of artworks, the photos of the resultant, etc. as such is as follows : Firstly, from this program being proceeded as art-centered STEAM class, the student's systematic problem-solving ability was improved in his ability of integrated thinking to transform the literary contents into artistic one. Secondly, the student obtained the emotional experience such as interest in the class, self-confidence, intellectual satisfaction, self-fulfillment, etc. through art-centered STEAM class using ten art expression techniques. Thirdly, the student's mind willing to cooperate, communicate with his friends, and care for them was ripened in the process of problem-solving. Fourth, the student's self-confidence was further instilled when presenting famous artists and their artworks in the introduction and finale of ten art expression techniques. Likewise, the statistic values on the fields of student's ability of integrated thinking and emotional experience illustrate that over the majority of the students showed improvement in the ability of creative expression with confidence as well as higher interest and concern upon this program.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.E
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• pp.1-17
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• 2000

In this study, the concentrations of particulate organic constituents of environmental tobacco smoke(ETS) were determined using an environmental smog chamber, where ETS is the sole source of target compounds. ETS was generated in a 30 ㎥ environmental chamber by a number of different cigarettes, including the Kentucky 1R4F reference cigarette and eight commercial brands. A total of 12 experimental runs was conducted, and target analytes included a group of ETS markers both in vapor and particulate phase and a class of polycylic aromatic hydrocarbos(PAHs) associated with ETS particles. The mass concentrations of PAH in ETS particles were also determined. The average contents of benzo(a) pyrene and benzo(a) anthracene in ETS particles for the commercial brands were 12.8 and 21.5$\mu\textrm{g}$/g, respectively, There values are all somewhat higher than those determined previously by other studies. Results form the chamber study are further used to estimate the average and variability of cigarette yields for target compounds associated with ETS. Finally, ratios of RSP to the surrogate standards of UVPM, FPM and solanesol were calculated for each sample. The average conversion factors factors for the eight commercial brands were 7.3, 38, and 41 for UVPM, EPM, and solanesol, respectively. The UVPM and FPM factors are in good agreement with the recently published values. Whereas there might be a substantial difference in the solanesol content among cigarettes produced in different countries, the variability is somewhat greater than those of UVPM and FPM, Unfortunately, comparison of the PAH yield data from this study with literature values was complicated by a lack of consistency in cigarette smoke generating methodology. Validation of the PAH yields was also difficult due to a lack of information on the ETS related PAH in the literature. From and engineering viewpoint , however, these data on the cigarette yields of ETS components may still provide useful information to studies on the mathematical modeling of indoor air quality management regarding tobacco smoke as a source of interest, or to studies on the assessment of human exposure to ETS.

• The Journal of the Korea Contents Association
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• v.17 no.7
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• pp.144-157
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• 2017

Although student satisfaction is important in university development, there have been many studies in this area. Especially student satisfaction is closely related to emotional aspect, but most studies have tended to study it with cognitive view. To suggest the model of student satisfaction with hedonic view, the model which we present in this study includes professor presence and interaction, PAD(pleasure, arousal, dominance), satisfaction(dependent variable). Through reviewing previous studies, we expect that these professor presence and students' interaction effect PAD, in turn, PAD effect satisfaction. Survey research is employed to test hypotheses involving professor presence, students' interaction, PAD and satisfaction. Previous researches, such as education, marketing, game, have been referenced to measure constructs. We collected data involving students in a university, and used 219 respondents to analyze these data using LISREL structural modeling. Professor presence had positive effects on professor-student interaction, pleasure, arousal, and dominance. Also professor-student interaction had positive effect on pleasure and arousal, and student-student interaction had positive effects on pleasure and arousal, dominance. As a result, PAD had effects on students' satisfaction. In the final section, we discussed several limitations of our study and suggested directions for future research. We concluded with a discussion of managerial implications, including the potential to advance understanding learning in a university.

• Asia pacific journal of information systems
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• v.18 no.4
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• pp.1-26
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• 2008

Rapid progress of information technology and widespread use of the personal computers have brought various conveniences in our life. But this also provoked a series of problems such as hacking, malicious programs, illegal exposure of personal information etc. Information security threats are becoming more and more serious due to enhanced connectivity of information systems. Nevertheless, users are not much aware of the severity of the problems. Using appropriate password is supposed to bring out security effects such as preventing misuses and banning illegal users. The purpose of this research is to empirically analyze a research model which includes a series of factors influencing the effectiveness of passwords. The research model incorporates the concept of risk based on information systems risk analysis framework as the core element affecting the selection of passwords by users. The perceived risk is a main factor that influences user's attitude on password security, security awareness, and intention of security behavior. To validate the research model this study relied on questionnaire survey targeted on evening class MBA students. The data was analyzed by AMOS 7.0 which is one of popular tools based on covariance-based structural equation modeling. According to the results of this study, while threat is not related to the risk, information assets and vulnerability are related to the user's awareness of risk. The relationships between the risk, users security awareness, password selection and security effectiveness are all significant. Password exposure may lead to intrusion by hackers, data exposure and destruction. The insignificant relationship between security threat and perceived risk can be explained by user's indetermination of risk exposed due to weak passwords. In other words, information systems users do not consider password exposure as a severe security threat as well as indirect loss caused by inappropriate password. Another plausible explanation is that severity of threat perceived by users may be influenced by individual difference of risk propensity. This study confirms that security vulnerability is positively related to security risk which in turn increases risk of information loss. As the security risk increases so does user's security awareness. Security policies also have positive impact on security awareness. Higher security awareness leads to selection of safer passwords. If users are aware of responsibility of security problems and how to respond to password exposure and to solve security problems of computers, users choose better passwords. All these antecedents influence the effectiveness of passwords. Several implications can be derived from this study. First, this study empirically investigated the effect of user's security awareness on security effectiveness from a point of view based on good password selection practice. Second, information security risk analysis framework is used as a core element of the research model in this study. Risk analysis framework has been used very widely in practice, but very few studies incorporated the framework in the research model and empirically investigated. Third, the research model proposed in this study also focuses on impact of security awareness of information systems users on effectiveness of password from cognitive aspect of information systems users.

• Journal of the Korean Society of Child Welfare
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• no.59
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• pp.209-234
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• 2017

This study viewed schools as a cause of students dropping out and posited that dropping out of high school would vary depending on the characteristics and influencing factors of the school from which students were dropping out. Therefore, focusing on schools, we longitudinally investigated the change patterns of school dropout across high schools in the country, and the types of changes in dropping out of high school. In addition, we predicted the general characteristics of schools according to the type of school students were dropping out from, looked at the changes in the major factors (i.e., school violence and school counseling) affecting school dropout, and reviewed schools' long-term efforts and outcomes in relation to school dropout. For this purpose, KERIS EDSS's "Secondary School Information Disclosure Data" were used. The final model included data collected five years20122016) from high schools across the country. The results were as follows. First, in order to examine the longitudinal change patterns of dropping out of high schools, a latent growth models analysis was conducted, and it revealed that, as time passed, the dropout rate decreased. Second, growth mixture modeling was used to explore types according to the change patterns of the school students were dropping out from. The results showed three types: the "remaining in school" type, the "gradually decreasing school dropout" type, and the "increasing school dropping out". Third, the multinomial logistic regression was conducted to predict the general characteristics of schools by type. The results showed that public schools, vocational schools, and schools with a large number of students who have below the basic levels in Korean, English and mathematics were more likely to belong to the "increasing school dropout" type. Further, the larger the total number of students, the higher the probability of belonging to the "remaining in school" type or the "gradually decreasing school dropout" type. Lastly, growth mixture modeling was used to analyze the trend of school violence and school counseling according to the three types. The focus was on the "gradually decreasing school dropout" type. In the case of the "gradually decreasing school dropout" type, it was found that as time passed, the number of school violence cases and the number of offenders gradually decreased. In addition, in terms of change in school counseling the results revealed that the number of placement of professional counselors in schools increased every year and peer counseling was continuously promoted, which may account for the "gradually decreasing school dropout" type.

• Korean Journal of Family Social Work
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• no.58
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• pp.97-122
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• 2017

The purpose of this study was to identify the longitudinal patterns of marital satisfaction, characteristics of each pattern, influencing factors and the difference on self-esteem, among married couples who experienced unemployment. To achieve this, the 443 married couples, who were initially employed in the first year but unemployed in next 5 years were extracted from the $2^{nd}$ to $11^{st}$ waves of Korean Welfare Panel Study(KoWePS) data. The results showed that there are five patterns on marital satisfactions of couple who experienced unemployment: maintaining low-level, mid-level, continuous declining, rebound after sharp declining, and maintaining high-level. In addition to this, the groups that maintain the marital satisfaction showed higher self-esteem than the groups that showed positive or negative change in marital relationship. Based on these results, this study suggested political and practical intervention to maintain the satisfaction of marital relationship and their self-esteem in a high level.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1031-1031
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• 2001

The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.