• The Mathematical Education
• /
• v.57 no.4
• /
• pp.393-412
• /
• 2018

Teacher quality is a key factor that determines quality of education. Being aware of this, the Korean government and teachers have been striving to improve teachers' professionalism. Research about the impacts of efforts to enhance teacher professionalism on students' academic achievement and course satisfaction, however, is extremely limited. This study sought to advance our understanding of the relationship between these factors by analyzing what teacher characteristics impact students' achievement and satisfaction. To this end, the study drew on the middle and high school data from 3rd to 6th year survey of the Seoul Educational Longitudinal Study. Structural equational modeling were used as the main approach. Latent profile analysis, a kind of mixture modeling analysis, were used as needed. This study found that teachers' participation in instruction enhancement activity and professional development impact students' attitude toward mathematics lessons and their perception on class atmosphere, and ultimately impact their academic achievement as well as their overall satisfaction in the course. In addition, teachers' use of EBS textbooks and videos impact 3rd grade high schoolers' academic achievement. These findings suggest that effort to improve teacher professionalism positively impact students' academic achievement and course satisfaction, although there is a difference according to the year grade. This study provides implications for education policy makers and teacher educators.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.63 no.4
• /
• pp.360-377
• /
• 2018

The levels of 12 isoflavones were measured in soybean (Glycine max (L.) Merrill) sprouts of 68 genetic varieties from three countries (China, Japan, and Korea). The isoflavone profile differences were analyzed using data mining methods. A principal component analysis (PCA) revealed that the CSRV021 variety was separated from the others by the first two principal components. This variety appears to be most suited for functional food production due to its high isoflavone levels. Partial least squares discriminant analysis (PLS-DA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA) showed that there are meaningful isoflavone compositional differences in samples that have different countries of origin. Hierarchical clustering analysis (HCA) of these phytochemicals resulted in clusters derived from closely related biochemical pathways. These results indicate the usefulness of metabolite profiling combined with chemometrics as a tool for assessing the quality of foods and identifying metabolic links in biological systems.

• Journal of Information Science Theory and Practice
• /
• v.9 no.2
• /
• pp.47-65
• /
• 2021

This study aims to identify specific topics, trends, and structural characteristics of scholarly communication research, based on 1,435 articles published from 1970 to 2018 in the Scopus database through Latent Dirichlet Allocation topic modeling, serial analysis, and network analysis. Topic modeling, time series analysis, and network analysis were used to analyze specific topics, trends, and structures, respectively. The results were summarized into three sets as follows. First, the specific topics of scholarly communication research were nineteen in number, including research resource management and research data, and their research proportion is even. Second, as a result of the time series analysis, there are three upward trending topics: Topic 6: Open Access Publishing, Topic 7: Green Open Access, Topic 19: Informal Communication, and two downward trending topics: Topic 11: Researcher Network and Topic 12: Electronic Journal. Third, the network analysis results indicated that high mean profile association topics were related to the institution, and topics with high triangle betweenness centrality, such as Topic 14: Research Resource Management, shared the citation context. Also, through cluster analysis using parallel nearest neighbor clustering, six clusters connected with different concepts were identified.

• Journal of Information Technology Services
• /
• v.20 no.3
• /
• pp.57-73
• /
• 2021

Recently, online job websites have been activated as unemployment problems have emerged as social problems and demand for job openings has increased. However, while the online job platform market is growing, users have difficulty choosing their jobs. When users apply for a job on online job websites, they check various information such as job contents and recruitment conditions to understand the details of the job. When users choose a job, they focus on various details related to the job rather than simply viewing and supporting the job title. However, existing online job websites usually recommend jobs using only quantitative preference information such as ratings. However, if recommendation services are provided using only quantitative information, the recommendation performance is constantly deteriorating. Therefore, job recommendation services should provide personalized services using various information about the job. This study proposes a recommended methodology that improves recommendation performance by elaborating on qualitative preference information, such as details about the job. To this end, this study performs a topic modeling analysis on the job content of the user profile. Also, we apply LDA techniques to explore topics from job content and extract qualitative preferences. Experiments show that the proposed recommendation methodology has better recommendation performance compared to the traditional recommendation methodology.

• Journal of Energy Engineering
• /
• v.8 no.2
• /
• pp.224-232
• /
• 1999

Latent heat storage system using micro-encapsuled phase change material is effective method for floor heating of house and building. The temperature profile in capsule block and flow rate of hot water are important parameters for the development of heat storage system. In the present study, a mathematical model based on 3-D, non-steady state, Navier-Stokes equations, scalar conservation equations and turbulence model ($\kappa$-$\varepsilon$), is used to predict the temperature profiles in capsule and the velocity vectors in hot water pipe. The multi-block grids and fine grids embedding are used to join the circle in hot water pipe and square in capsule block. The phase change process of the capsule is quite complex not only because the size of phase change material is very small, but also because phase change material is mixed with the cement to form thermal storage block. In calculation, it's assumed that the phenomena of phase change is limited only the thermal properties of phase change material and the change of boundary is not happened in capsule. The purpose of this study is to calculate the temperature profiles in capsule block and velocity vectors in hot water pipe using the numerical calculation. Two kinds of thermal boundary condition were considered, the first (case 1) is the adiabatic condition for the both outside surfaces of the wall, the second (case 2) is the case in which one surface is natural convection with atmosphere and another surface is adaibatic. Calculation results are shown that the temperature profile in capsule block for case 1 is higher than that for case 2 due to less heat loss in adaibatic surface. Specially, in the domain of near Y=0, the difference of temperature is greater in case 1 than in case 2. The detailed experimental data of capsule block on the temperature profile and the thermal properties such as specific heat and coefficient of heat transfer with the various temperature are required to predict more exact phenomena of heat transfer.

• Therapeutic Science for Rehabilitation
• /
• v.13 no.2
• /
• pp.69-84
• /
• 2024

Objective : This study aimed to categorize the lifestyles of older adults into two types - healthy and unhealthy, and use machine learning to identify the personal values that influence these lifestyles. Methods : This cross-sectional study targeting middle-aged and older adults (55 years and above) living in local communities in South Korea. Data were collected from 300 participants through online surveys. Lifestyle types were dichotomized by the Yonsei Lifestyle Profile (YLP)-Active, Balanced, Connected, and Diverse (ABCD) responses using latent profile analysis. Personal value information was collected using YLP-Values (YLP-V) and analyzed using machine learning to identify the relative importance of personal values on lifestyle types. Results : The lifestyle of older adults was categorized into healthy (48.87%) and unhealthy (51.13%). These two types showed the most significant difference in social relationship characteristics. Among the machine learning models used in this study, the support vector machine showed the highest classification performance, achieving 96% accuracy and 95% area under the receiver operating characteristic (ROC) curve. The model indicated that individuals who prioritized a healthy diet, sought health information, and engaged in hobbies or cultural activities were more likely to have a healthy lifestyle. Conclusion : This study suggests the need to encourage the expansion of social networks among older adults. Furthermore, it highlights the necessity to comprehensively intervene in individuals' perceptions and values that primarily influence lifestyle adherence.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.8
• /
• pp.44-51
• /
• 2020

The purpose of this study was to identify latent profiles of multicultural adolescents' psychological outcomes (school participation, self-esteem, and difficulty related to multicultural identity) depending on their perception of the parent-child relationship. A total of 5,540 samples from the Multicultural Adolescents Panel Study (MAPS) conducted by the National Youth Policy Institute in 2018 were analyzed by using Latent Profile Analysis and one-way ANOVA. The best-fitting model identified five groups according to their perception of the parent-child relationship: (1) father low-mother average (6.5%), (2) father average-mother low (2%), (3) father low-mother low (18.6%), (4) father average-mother average (31.2%), and (5) father high-mother high (41.7%). According to the results of one-way ANOVA, the father high-mother high (41.7%) group of adolescents showed more school participants and higher self-esteem and multicultural identity than the other profiled groups. The father average-mother average (31.2%) group of adolescents also scored higher than the other three groups (father low-mother average (6.5%), father average-mother low (2%), and father low-mother low (18.6%) of adolescents). The results of this study imply that improving multicultural adolescents' perception of their parent-child relationships would be important in improving psychological outcomes.

• Atmosphere
• /
• v.22 no.1
• /
• pp.73-85
• /
• 2012

The collision efficiency data for collision between graupel or hail particles and cloud drops that take into account the differences of particle density are applied to the Takahashi cloud model. The original setting assumes that graupel or hail collision efficiency is the same as that of the cloud drops of the same volume. The Takahashi cloud model is run with the new collision efficiency data and the results are compared with those with the original. As an initial condition, a thermodynamic profile that can initiate strong convection is provided. Three different CCN concentration values and therefore three initial cloud drop spectra are prescribed that represent maritime (CCN concentration = 300 $cm^{-3}$), continental (1000 $cm^{-3}$) and extreme continental (5000 $cm^{-3}$) air masses to examine the aerosol effects on cloud and precipitation development. Increase of CCN concentration causes cloud drop sizes to decrease and cloud drop concentrations to increase. However, the concentration of ice particles decreases with the increase of CCN concentration because small drops are difficult to freeze. These general trends are well captured by both model runs (one with the new collision efficiency data and the other with the original) but there are significant differences: with the new data, the development of cloud and raindrop formation are delayed by (1) decrease of ice collision efficiency, (2) decrease of latent heat from riming process and (3) decrease of ice crystals generated by ice multiplication. These results indicate that the model run with the original collision efficiency data overestimates precipitation rates.

• Journal of Physiology & Pathology in Korean Medicine
• /
• v.23 no.4
• /
• pp.765-771
• /
• 2009

The medical informatics for clustering Sasang types with collected clinical data is important for the personalized medicine, but it has not been thoroughly studied yet. The purpose of this study was to examine the usefulness of neural network data mining algorithm for traditional Korean medicine. We used Kohonen neural network, the Self-Organizing Map (SOM), for the analysis of biomedical information following data pre-processing and calculated the validity index as percentage correctly predicted and type-specific sensitivity. We can extract 12 data fields from 30 after data pre-processing with correlation analysis and latent functional relationship analysis. The profile of Myers-Briggs Type Inidcator and Bio-Impedance Analysis data which are clustered with SOM was similar to that of original measurements. The percentage correctly predicted was 56%, and sensitivity for So-Yang, Tae-Eum and So-Eum type were 56%, 48%, and 61%, respectively. This study showed that the neural network algorithm for clustering Sasang types based on clinical data is useful for the sasang type diagnostic test itself. We discussed the importance of data pre-processing and clustering algorithm for the validity of medical devices in traditional Korean medicine.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.6
• /
• pp.101-109
• /
• 2012

To develop high quality software, quality control plan is required about fault correction that is latent within software. We should describe fault correction profile properly for this. The tank and pipe model performs complex processes to calculate fault that is remove and escapes. Also, we have to know in which phase the faults were inserted, removed and escaped and know the fault detection rate at any phases. To simplify such complex process, this paper presented model to fault filtering concept. Presented model has advantage that can describe fault more shortly because need not to consider whether was involved in fault that escaped fault is inserted at any step at free step. Also, presented effort estimating model that do fetters in function of fault removal quality and productivity measure and is required in fault detection.