• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

• Journal of the Korean Chemical Society
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• v.67 no.5
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• pp.378-392
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• 2023

The purpose of this study is to analyze the pre-service chemistry teachers' cognition of the nature of model in process of designing and developing models using technology. For this purpose, 19 pre-service chemistry teachers' in the 3rd grade of a education college located in the central region observe experimental phenomena related to Boyle's law presented in the 7th grade science textbook and researchers required the design and development of a model related to the observed experimental results using technology. Based on previous studies, the nature of model were classified into two aspect: 'Representational aspect' and 'Explanatory aspect'. The 'Representational aspect' was classified into 'Representation', 'Abstraction', and 'Simplification', and the 'Explanatory aspect' was classified into 'Analysis', 'Interpretation', 'Reasoning', 'Explanation', and 'Quantification'. The pre-service chemistry teachers' cognition were analyzed by the classification. As a result of the study, the 'Representation' of the 'expressive aspect' was uniformized in the form of space that changes in volume, and the pressure was expressed as the Brightness inside the cylinder or frequency of color change of particles for 'Abstraction'. In the case of 'Simplification', the particle collision was expressed as a perfectly elastic collision, but there was a group that could not simply indicate the type of particle. In the 'Explanatory aspect', in the case of 'Analysis', volume was classified as a manipulated variable, and in the case of 'Interpretation', most groups analyzed the change in pressure through the collision of gas particles. However, the cognition involved in 'Reasoning' was not observed much. In the case of 'Explanation', there were groups that did not succeed in explanation because the area where the particles collided was not set or incorrectly set, and in the case of 'Quantification', there was a group that formulated the number of collisions per unit time, and on the contrary, there was a group that could not quantify the number of collisions because they could not be expressed in numbers.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.73-82
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• 2009

Due to the many advantages including low price, low power consumption, and miniaturization, the CMOS camera has been utilized in many applications, including mobile phones, the automotive industry, medical sciences and sensoring, robotic controls, and research in the security field. In particular, the 360 degree omni-directional camera when utilized in multi-camera applications has displayed issues of software nature, interface communication management, delays, and a complicated image display control. Other issues include energy management problems, and miniaturization of a multi-camera in the hardware field. Traditional CMOS camera systems are comprised of an embedded system that consists of a high-performance MCU enabling a camera to send and receive images and a multi-layer system similar to an individual control system that consists of the camera's high performance Micro Controller Unit. We proposed the SL-AVS (Small Size/Low power Around-View System) to be able to control a camera while collecting image data using a high speed synchronization technique on the foundation of a single layer low performance MCU. It is an initial model of the omni-directional camera that takes images from a 360 view drawing from several CMOS camera utilizing a 110 degree view. We then connected a single MCU with four low-power CMOS cameras and implemented controls that include synchronization, controlling, and transmit/receive functions of individual camera compared with the traditional system. The synchronization of the respective cameras were controlled and then memorized by handling each interrupt through the MCU. We were able to improve the efficiency of data transmission that minimizes re-synchronization amongst a target, the CMOS camera, and the MCU. Further, depending on the choice of users, respective or groups of images divided into 4 domains were then provided with a target. We finally analyzed and compared the performance of the developed camera system including the synchronization and time of data transfer and image data loss, etc.

• Journal of the korean academy of Pediatric Dentistry
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• v.50 no.1
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• pp.65-74
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• 2023

This study compared the surface roughness and microbial adhesion characteristics of Omnichroma, a novel composite resin developed using "smart chromatic technology", with those of two other conventional composite resins with different filler compositions. A total of 144 specimens were fabricated using 3 types of composite resins: Omnichroma (nano-spherical), Filtek Z350XT (nanofill), and Tetric N-Ceram (nanohybrid) and, divided into 3 groups of 48. Finishing was performed using tungsten carbide burs. Specimens were then divided into 3 subgroups using different polishing methods: Control, SofLex, and PoGo. Surface roughness was analyzed quantitatively and qualitatively using an atomic force microscope and a scanning electron microscope. Microbial adhesion was assessed by culturing Streptococcus mutans on the specimens for 24 hours and then measuring colony-forming units attached to the upper surface. The surface roughness (Ra) of Omnichroma was 0.123 ㎛ after finishing, and it exhibited a smooth surface compared to the other resins. However, after polishing, there were no significant differences in the surface roughness between the three composite groups, regardless of the polishing methods. The surfaces of the Control subgroups were significantly rougher than those of the SofLex subgroups in all 3 composite groups. However, except for Tetric N-Ceram, there were no significant differences between the Control and PoGo subgroups in the other composite groups. Microbial adhesion assessment showed no significant differences between any of the 3 composite resin subgroups; however, Omnichroma exhibited higher microbial adhesion than the other two composites. No significant correlation was observed between surface roughness and microbial adhesion.

• Journal of the korean academy of Pediatric Dentistry
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• v.50 no.2
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• pp.205-216
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• 2023

This study aimed to compare the color stability and surface roughness of three-dimensional (3D) printing resin according to polishing methods. 3D-printed resin specimens were fabricated at TC-80DP (Graphy, Seoul, Korea) with a stereolithography 3D printer, and the specimens were divided into three groups, each of which was not polished, was polished using Enhance^®, and was polished using a Sof-Lex^TM disc. The CIE L^*a^*b^* value and the surface roughness of each group were measured and immersed in artificial saliva and orange juice after 0, 1, 7, 30, and 60 days, and the color difference (ΔE^*) was calculated. As a result of the study, no noticeable color change was observed in artificial saliva, but a noticeable color change was demonstrated in orange juice after 60 days of immersion, and the difference was significant. In the Sof-Lex^TM group, surface roughness according to the solution was found to be significantly higher in the orange juice than that in artificial saliva. No significant difference in color change was found according to the polishing method, but surface roughness was significantly lower in the Sof-Lex^TM group than both that of the unpolished group and that of the Enhance^® group. Nevertheless, all groups exhibited clinically acceptable properties regardless of their higher surface roughness than the threshold for plaque accumulation. Overall, this study recommends utilizing Sof-Lex^TM for polishing 3D printing resin when used in primary anterior tooth coverage.

• Journal of Korean Home Economics Education Association
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• v.35 no.1
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• pp.1-14
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• 2023

The objective of the study was to examine the associations of dietary carbohydrate and fat intake with the prevalence of metabolic syndrome in Korean women. A cross-sectional study was employed based on data from the Korea National Health and Nutrition Examination (2007-2016). A total of 22,850 women aged 19 to 69 years were studied after excluding responses from pregnant or lactating women and those with missing metabolic values. Dietary intake data were collected with a 24-hour recall method. Dietary carbohydrate and fat intakes were divided into quintiles. After controlling for confounding variables, a multivariable logistic regression and general linear model were used. The findings indicated that HDL cholesterol levels were lower (p for trend<0.01), while triglyceride levels (p for trend=0.04), waist circumference (p for trend<0.01), and systolic blood pressure (p for trend<0.01) were higher among participants in the highest quintile of carbohydrate intake compared to those in the lowest quintile. Participants in the highest quintile of fat intake had lower waist circumference (p for trend=0.02), triglyceride level (p for trend<0.01), and systolic blood pressure (p for trend<0.01), while higher HDL cholesterol level (p for trend<0.01) compared to those in the lowest fat intake quintile. Metabolic syndrome was more likely to be present in the highest quintile of carbohydrates intake than in the lowest quintile (5^th quintile vs. 1^st quintile, OR: 1.32; 95% CI: 1.11 to 1.57). However, metabolic syndrome was less likely to be present in the highest quintile of fat intake than in the lowest quintile (5^th quintile vs. 1^st quintile, OR: 0.73; 95% CI: 0.61 to 0.86). This study revealed that high dietary carbohydrate intake and low dietary fat intake were associated with metabolic syndrome in Korean women.

• The Mathematical Education
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• v.62 no.3
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• pp.435-455
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• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.

• Journal of Korean Dental Hygiene Science
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• v.6 no.1
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• pp.37-50
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• 2023

Background: This study investigated the structural relationships among justice, test anxiety, and school reliability s non-face-to-face tests of dental hygiene students. Methods: A survey was conducted with 267 dental hygiene students. The survey items included general characteristics, opinions on evaluation, the fairness of non-face-to-face tests (distributive, procedural, and interactional justice), school satisfaction, and school reliability. For statistical analysis, independent-sample t-tests, one-way ANOVA, and structural modeling analyses were performed. Results: Among factors that directly affected distributive justice and reliability towards non-face-to-face tests, the higher the interactional justice (β=0.401, p<0.001) and distributive justice (β=0.232, p=0.002) levels, the higher the school satisfaction. The higher the school satisfaction (β=0.606, p<0.001) and procedural justice (β=0.299, p<0.001) levels, the higher the perceived reliability of the school. Factors that indirectly affected school reliability included interactional justice (β=0.243, p=0.010) and distributive justice (β=0.141, p=0.010). Interactional justice (β=0.592, p=0.010) and distributive justice (β=0.208, p=0.010) were the factors affecting school satisfaction. Moreover, factors that influenced school reliability were distributive justice (β=0.56, p=0.010), interactional justice (β=0.332, p=0.010), procedural justice (β=0.229, p=0.010), and distributive justice (β=0.116, p=0.010). Conclusions: Students will trust and be satisfied with schools when schools and professors sufficiently provide information on face-to-face tests and ensure proper procedures to achieve reasonable grades as rewards for exerted time and effort. Furthermore, this study provides a reference base for developing a variety of content for fair, non-face-to-face tests, thereby allowing students to trust their schools.

• Korean Journal of Culture and Social Issue
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• v.29 no.3
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• pp.361-404
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• 2023

This study utilized a cross-temporal meta-analysis to explore shifts in self-efficacy levels among Korean college students from 1999 to 2022. We expected that increases in authoritative parenting styles, narcissism levels among students, and individualism in Korea might have positively influenced the self-efficacy of college students over the years. Conversely, growing economic disparities, decreasing class mobility, and the increasing instability of job markets might have had negative effects on self-efficacy. To investigate this, we analyzed 293 self-efficacy studies involving Korean college students published between 1999 and 2022, encompassing a total of 88,904 participants. Our criteria included studies that used the three most prevalent self-efficacy scales in Korea, focused solely on Korean college students, were cross-sectional with a one-time self-efficacy measurement, and provided essential statistics for our analysis. The results indicated no significant change in the self-efficacy levels of Korean college students over the observed period from 1999 to 2022. Additionally, we examined correlations between self-efficacy and various social indicators from different time points (20, 15, 10, and 5 years prior, as well as the year of data collection). Findings revealed that both birth rate and consumer price fluctuation rate were consistently negatively correlated with self-efficacy, while gross national income was positively correlated. This study is the first to assess Korean college students' self-efficacy levels using a cross-temporal meta-analysis, offering foundational knowledge for implementing such analytical methods for subsequent research and providing an indirect assessment of the generational gap theory. Finally, the limitations of the study and the direction for future research were discussed.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.210-223
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• 2023

This study developed elementary and middle school career education programs linked to science subjects and local natural resources, and explored learning effects and implications for developing and operating career programs. In order to achieve the research purpose, a 10-hour career education program using local natural and social resources was developed and applied to 25 elementary and middle school students in rural areas. As a result of the study, most of the elementary and middle school students who participated in this study were not well aware of the natural and social resource value of the area where they lived. Therefore, when developing and operating a regional-based career education program for elementary and middle school students in rural areas, it is necessary to operate a separate teaching/learning activity time so that students can fully know the natural and social information and resource values of the region. In addition, in order to enhance students' participation and interest in career education programs, it is necessary to organize the operation of the program in groups, not individuals, and to guide students in detail by dividing the program's performance process into several sub-steps. Finally, the core material of regional-linked career education-related programs focused more on their own content, that is, agricultural products grown by parents, and future job settings were higher in start-ups that directly operate companies such as travel agencies and manufacturing companies. Given the recent emphasis on career education in the curriculum, it is suggested that local students should pay more attention to finding materials with local resource value in the field of geoscience, which is closely related to natural resources, and developing and operating them as career education programs linked to local resources.