• Journal of Engineering Education Research
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• v.12 no.3
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• pp.79-95
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• 2009

Women engineering education programs in the United States, Europe and Australia were analyzed. From 1970s, these countries focused on the low representation of women in engineering, and carried out extensive research and programs. Numerous studies identified the causes of low representation as low interests in mathematics and science during K-12 years, classroom environments which treat women differently (often referred as chilly climate), and the masculine culture in engineering. Comprehensive approaches were taken in the development of the programs: the programs utilized the schools and universities as well as various local institutes, and the programs were designed not only for female students from elementary to graduate levels, but also for parents, teachers, professors, and school administrators. In order to adopt these programs in Korea, the problems that Korean female engineering students are facing in the education environment must be investigated first. Then, unified efforts to change the educational system, environments and culture are needed by all in engineering fields, along with nation-wide policies and funding.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.9-21
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• 2015

The support vector machine has been successfully applied to various classification areas due to its flexibility and a high level of classification accuracy. However, when analyzing imbalanced data with uneven class sizes, the classification accuracy of SVM may drop significantly in predicting minority class because the SVM classifiers are undesirably biased toward the majority class. The weighted $L_2$-norm SVM was developed for the analysis of imbalanced data; however, it cannot identify irrelevant input variables due to the characteristics of the ridge penalty. Therefore, we propose the weighted $L_1$-norm SVM, which uses lasso penalty to select important input variables and weights to differentiate the misclassification of data points between classes. We demonstrate the satisfactory performance of the proposed method through simulation studies and a real data analysis.

• Communications of Mathematical Education
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• v.24 no.1
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• pp.1-27
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• 2010

This study intends to provide implications about sluggish use of calculators in our case by analyzing the math textbook of U.S. Macmillan/McGraw-Hill along with the tendency of paying more attention to math class using technologies. From the results of analysis, this textbook deals with various methods over around 3.3% of all pages, using calculators across all grades from 1st to 6th grade. In particular, it offers guidance into three types such as 'Choose a Computation Method', 'You can also use a calculator.', and 'TECHNOLOGY LINK', while particularly it is impressive in the perspective of using calculators as one of calculation strategies. And case studies of usage in textbooks describe 8 different perspectives as an example-represent; solve problems or equations; develope or demonstrate conceptual understanding; analyze; compute or estimate; describe, explain or justify; choose appropriate calculation method; determine a calculated answer's reasonableness. Reflecting on the fact that we still use calculators in a passive way, there are considerable implications to us.

• Education of Primary School Mathematics
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• v.21 no.4
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• pp.397-413
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• 2018

The purpose of this study is to analyze the level of statistical literacy among fifth and sixth graders in the data presentation task based on the speculative data generation process. For the research, the data presentation tasks based on the speculative data generation process was designed and statistical literacy standards for evaluating the student's level was presented based on prior studies. It is meaningful that the stepwise presentation of the students' statistical literacy and analysis of their developmental patterns can help them to find their current position and reach a higher level of performance. In this study, the standard of statistical literacy level was clarified based on the previous research, and a new perspective was presented about the data presentation instruction in the statistical education by analyzing the students' responses by each level.

• Steel and Composite Structures
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• v.25 no.6
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• pp.717-726
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• 2017

In this paper, a new simple shear deformation theory for bending analysis of functionally graded plates is developed. The present theory involves only three unknown and three governing equation as in the classical plate theory, but it is capable of accurately capturing shear deformation effects, instead of five as in the well-known first shear deformation theory and higher-order shear deformation theory. A shear correction factor is, therefore, not required. The material properties of the functionally graded plates are assumed to vary continuously through the thickness, according to a simple power law distribution of the volume fraction of the constituents. Equations of motion are obtained by utilizing the principle of virtual displacements and solved via Navier's procedure. The elastic foundation is modeled as two parameter elastic foundation. The results are verified with the known results in the literature. The influences played by transversal shear deformation, plate aspect ratio, side-to-thickness ratio, elastic foundation, and volume fraction distributions are studied. Verification studies show that the proposed theory is not only accurate and simple in solving the bending behaviour of functionally graded plates, but also comparable with the other higher-order shear deformation theories which contain more number of unknowns.

• Geomechanics and Engineering
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• v.22 no.5
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• pp.397-414
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• 2020

In this paper, practical predictive models for soil shear strength parameters are proposed. As cohesion and internal friction angle are of essential shear strength parameters in any geotechnical studies, we try to predict them via artificial neural network (ANN) and neuro-imperialism approaches. The proposed models was based on the result of a series of consolidated undrained triaxial tests were conducted on reinforced sandy soil. The experimental program surveys the increase in internal friction angle of sandy soil due to addition of polypropylene fibers with different lengths and percentages. According to the result of the experimental study, the most important parameters impact on internal friction angle i.e., fiber percentage, fiber length, deviator stress, and pore water pressure were selected as predictive model inputs. The inputs were used to construct several ANN and neuro-imperialism models and a series of statistical indices were calculated to evaluate the prediction accuracy of the developed models. Both simulation results and the values of computed indices confirm that the newly-proposed neuro-imperialism model performs noticeably better comparing to the proposed ANN model. While neuro-imperialism model has training and test error values of 0.068 and 0.094, respectively, ANN model give error values of 0.083 for training sets and 0.26 for testing sets. Therefore, the neuro-imperialism can provide a new applicable model to effectively predict the internal friction angle of fiber-reinforced sandy soil.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.54-61
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• 2019

Recently, IITS (intelligent integrated transportation system) has been important topic in Smart City related industry. As a main objective of IITS, prevention of traffic jam (due to car accidents) has been attempted with help of advanced sensor and communication technologies. Studies show that car accident has certain correlation with some factors including characteristics of location, weather, driver's behavior, and time of day. We concentrate our study on observing auto correlativity of car accidents in terms of time of day. In this paper, we performed the ARIMA tests including ADF (augmented Dickey-Fuller) to check the three factors determining auto-regressive, stationarity, and lag order. Summary on forecasting of hourly car crash counts is presented, we show that the traffic accident data obtained in Korea can be applied to ARIMA model and present a result that traffic accidents in Korea have property of being recurrent daily basis.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.721-732
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• 2018

Latent class analysis (LCA) is an important tool to explore unseen latent groups in multivariate categorical data. In practice, it is important to select a suitable set of variables because the inclusion of too many variables in the model makes the model complicated and reduces the accuracy of the parameter estimates. Dean and Raftery (Annals of the Institute of Statistical Mathematics, 62, 11-35, 2010) proposed a headlong search algorithm based on Bayesian information criteria values to choose meaningful variables for LCA. In this paper, we propose a new variable selection procedure for LCA by utilizing posterior probabilities obtained from each fitted model. We propose a new statistic to measure the adequacy of LCA and develop a variable selection procedure. The effectiveness of the proposed method is also presented through some numerical studies.

• Education of Primary School Mathematics
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• v.22 no.3
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• pp.149-166
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• 2019

The purpose of this study is to analyze the statistical literacy in elementary school students when they beginning inference. Picto-graphs provide statistical information and often data-related arguments they certainly qualify as objects for interpretation, for critical evaluation, and for discussion or communication of the conclusions presented. For research, the inference from pictograph task was designed and statistical literacy standards for evaluating the student's level was presented based on prior studies. Evaluating student's statistical literacy is meaningful in that it can check their current level. To know the student's current level can help them achieve a higher level of performance. The outcomes of this research indicate that pictograph can provide a basis for rich tasks displaying not only student's counting skills but also their appreciation of variation and uncertainty in prediction. Raising statistical thinking by students is an important goal in statistical education, and the experience of informal statistical reasoning can help with formal statistical reasoning that will be learned later. Therefore, the task about the inference from a pictograph, discussions on statistical learning of elementary school children are expected to present meaningful implications for statistical education.

• Journal of Contemporary Eastern Asia
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• v.18 no.1
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• pp.7-29
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• 2019

This study describes an approach for comparative bibliometric analysis of scientific publications related to (i) individual or several departments comprising a university, and (ii) broader integrated subject areas using multiple disciplinary schemes. It uses a custom dataset of scientific publications (ca. 15,000 articles and reviews, published during 2009-2013, and recorded in the Web of Science Core Collections) with author affiliations to the research departments, dedicated to science, technology, engineering, mathematics, and medicine (STEMM), of a comprehensive university. The dataset was subjected, at first, to the department level and discipline level analyses using the newly available KAKEN-L3 classification (based on MEXT/JSPS Grants-in-Aid system), hierarchical clustering, correspondence analysis to decipher the major departmental and disciplinary clusters, and visualization of the department-discipline relationships using two-dimensional stacked bar diagrams. The next step involved the creation of subsets covering integrated subject areas and a comparative analysis of departmental contributions to a specific area (medical, health and life science) using several disciplinary schemes: Essential Science Indicators (ESI) 22 research fields, SCOPUS 27 subject areas, OECD Frascati 38 subordinate research fields, and KAKEN-L3 66 subject categories. To illustrate the effective use of the science mapping techniques, the same subset for medical, health and life science area was subjected to network analyses for co-occurrences of keywords, bibliographic coupling of the publication sources, and co-citation of sources in the reference lists. The science mapping approach demonstrates the ways to extract information on the prolific research themes, the most frequently used journals for publishing research findings, and the knowledge base underlying the research activities covered by the publications concerned.