• Journal of Korean Elementary Science Education
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• v.33 no.4
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• pp.762-772
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• 2014

The purpose of this study was to investigate the effects of science lesson applying STEAM education on the creative thinking activities and emotional intelligence of elementary school students. The study subjects were two classes of the $3^{th}$ grade of S elementary school in B Metropolitan City. One class including 26 students was experimental group and the other including 27 students was comparison group. For the purpose of study, the lesson unit 'The world of animals' was practised, the reorganized unit applying STEAM was applied to experimental group, whereas comparison group was taught traditional science lesson. The results of this study were as follows. First, the science lesson applying STEAM education influenced significantly the improvement of the creative thought activities of elementary school students. Second, the science lesson applying STEAM education influenced significantly the improvement of the emotional intelligence of elementary school students.

• Korean journal of food and cookery science
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• v.25 no.4
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• pp.506-512
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• 2009

The principal objective of this study is to determine the most appropriate methods to increase global recognition of Korean food. In service of this objective, interviews were conducted with Korean food specialists who worked for a Korean culinary educational institute in Seoul, as well as cooking experts who worked for restaurants in super deluxe hotels. The study was conducted for 10 days from Feb $21^{st}$ to March $2^{nd}$ in 2009. The results of the study were summarized and synthesized into some key opinions. First, one of the main concepts in Korean culinary education should involve the selection of a small group of the best members and training them to a world class level at a traditional HanOk style institute. Second, to establish a standard for trainee recruitment, we selected a group of members consisting of about 20 persons over the age of 18 years who had earned a degree or were scheduled to graduate from university chef training and had also worked for over 5 years in the field, additionally, foreigners were allowed to apply to the institute. The educational term is one year and some benefits, such as a fixed amount of subsidies to help in daily living, free dormitory housing a certificate of course completion, and an employment guarantee. Third, the educational program consisted of two stages one was the specialist course in which traditional foods were covered and the other was the menu development course, which dealt with the creation of new Korean foods. Fourth, unique programs, including specialized foreign foods experience halls or commission education, were instituted in an effort to raise the level of world recognition of the superiority of Korean food.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.19-30
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• 2021

Diabetes Mellitus (DM) is one of common chronic diseases leading to severe health complications that may cause death. The disease influences individuals, community, and the government due to the continuous monitoring, lifelong commitment, and the cost of treatment. The World Health Organization (WHO) considers Saudi Arabia as one of the top 10 countries in diabetes prevalence across the world. Since most of the medical services are provided by the government, the cost of the treatment in terms of hospitals and clinical visits and lab tests represents a real burden due to the large scale of the disease. The ability to predict the diabetic status of a patient without the laboratory tests by performing screening based on some personal features can lessen the health and economic burden caused by diabetes alone. The goal of this paper is to investigate the prediction of diabetic and prediabetic patients by considering factors other than the laboratory tests, as required by physicians in general. With the data obtained from local hospitals, medical records were processed to obtain a dataset that classified patients into three classes: diabetic, prediabetic, and non-diabetic. After applying three machine learning algorithms, we established good performance for accuracy, precision, and recall of the models on the dataset. Further analysis was performed on the data to identify important non-laboratory variables related to the patients for diabetes classification. The importance of five variables (gender, physical activity level, hypertension, BMI, and age) from the person's basic health data were investigated to find their contribution to the state of a patient being diabetic, prediabetic or normal. Our analysis presented great agreement with the risk factors of diabetes and prediabetes stated by the American Diabetes Association (ADA) and other health institutions worldwide. We conclude that by performing class-specific analysis of the disease, important factors specific to Saudi population can be identified, whose management can result in controlling the disease. We also provide some recommendations learnt from this research.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.14-20
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• 2024

Traffic sign recognition is an essential feature of intelligent transportation systems and Advanced Driver Assistance Systems (ADAS), which are necessary for improving road safety and advancing the development of autonomous cars. This research investigates the incorporation of the YOLOv9 model into traffic sign recognition systems, utilizing its sophisticated functionalities such as Programmable Gradient Information (PGI) and Generalized Efficient Layer Aggregation Network (GELAN) to tackle enduring difficulties in object detection. We employed a publically accessible dataset obtained from Roboflow, which consisted of 3130 images classified into five distinct categories: speed_40, speed_60, stop, green, and red. The dataset was separated into training (68%), validation (21%), and testing (12%) subsets in a methodical manner to ensure a thorough examination. Our comprehensive trials have shown that YOLOv9 obtains a mean Average Precision (mAP@0.5) of 0.959, suggesting exceptional precision and recall for the majority of traffic sign classes. However, there is still potential for improvement specifically in the red traffic sign class. An analysis was conducted on the distribution of instances among different traffic sign categories and the differences in size within the dataset. This analysis aimed to guarantee that the model would perform well in real-world circumstances. The findings validate that YOLOv9 substantially improves the precision and dependability of traffic sign identification, establishing it as a dependable option for implementation in intelligent transportation systems and ADAS. The incorporation of YOLOv9 in real-world traffic sign recognition and classification tasks demonstrates its promise in making roadways safer and more efficient.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.69-76
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• 2020

This paper presents direction for efficient software education. Due to the impact of the Fourth Industrial Revolution, the whole world is interested in software education. However, simply teaching how to code is not software education. The thinking abilities used in coding for software implementation are even more important. Therefore, computational thinking is getting great attention. Several institutions suggest factors for computational thinking and encourage to teach in a relevant way based on the suggestion. In this study, the verification of the factors they suggested was conducted through a questionnaire. The total of 419 freshman students of the College of Social Sciences who were taking "Computational Thinking and Software Coding" class participated in the survey at the beginning and the end of the semester. We first analyzed Wing's proposal that summarized the concept of computational thinking, and reviewed the proposal of ISTE (International Society for Technology in Education) for defining computational thinking factors for coding education, also checked on the suggestion of Google for factors necessary for software coding. As a result of research analysis, this paper suggests a direction for efficient software education.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.5
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• pp.39-48
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• 2002

long with the rapid spread of the Internet, a new class of commercial applications which process transactions with respect to electronic dictionaries become popular Typical examples are Internet search engines. In this paper, we present a new approach to achieving high performance electronic dictionaries. Different from the conventional approach which use Trie data structures for the implementation of electronic dictionaries, our approach used multi-dimensional binary trees. In this paper, we present the implementation of our electronic dictionary ED-MBT(Electronic Dictionary based on Multidimensional Binary Tree). Exhaustive performance study is also presented to assess the performance impact of ED-MBT on the real world applications.

• Proceedings of the KSRS Conference
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• v.2
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• pp.706-709
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• 2006

Cancer is one of the major causes of death; however, the survival rate can be increased if discovered at an early stage for timely treatment. According to the statistics of the World Health Organization of 2002, breast cancer was the most prevalent cancer for all cancers occurring in women worldwide, and it account for 16.8% of entire cancers inflicting Korean women today. In order to classify the type of breast cancer whether it is benign or malignant, this study was conducted with the use of the discriminant analysis and the decision tree of data mining with the breast cancer data disclosed on the web. The discriminant analysis is a statistical method to seek certain discriminant criteria and discriminant function to separate the population groups on the basis of observation values obtained from two or more population groups, and use the values obtained to allow the existing observation value to the population group thereto. The decision tree analyzes the record of data collected in the part to show it with the pattern existing in between them, namely, the combination of attribute for the characteristics of each class and make the classification model tree. Through this type of analysis, it may obtain the systematic information on the factors that cause the breast cancer in advance and prevent the risk of recurrence after the surgery.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.217-234
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• 2018

Copulas are a tool for constructing multivariate distributions and formalizing the dependence structure between random variables. From copula literature review, there are a few asymmetric copulas available so far while data collected from the real world often exhibit asymmetric nature. This necessitates developing asymmetric copulas. In this study, we discuss a method to construct a new class of bivariate asymmetric copulas based on products of symmetric (sometimes asymmetric) copulas with powered arguments in order to determine if the proposed construction can offer an added value for modeling asymmetric bivariate data. With these newly constructed copulas, we investigate dependence properties and measure of association between random variables. In addition, the test of symmetry of data and the estimation of hyper-parameters by the maximum likelihood method are discussed. With two real example such as car rental data and economic indicators data, we perform the goodness-of-fit test of our proposed asymmetric copulas. For these data, some of the proposed models turned out to be successful whereas the existing copulas were mostly unsuccessful. The method of presented here can be useful in fields such as finance, climate and social science.

• Korean Journal of Applied Biomechanics
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• v.21 no.1
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• pp.57-65
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• 2011

This research was conducted to biomechanically analyze Tippelt motion in parallel bars, and establish technical understanding. To achieve that goal, the performances of the Tippelt acts carried out by five world top-class national gymnasts in the parallel bars 3-dimensional cinematographic analysis and EMG analysis were conducted and following conclusion were obtained. The Tippelt motions of excellent national gymnasts perform tap motion through the down swing of a large circular movements, and perform kick-out motion rapidly extending shoulder joint angle and hip joint angle with the trunk in a position close to perpendicular position at the vertical downwardness of the grasping the bars. At this time, if handstand starting the movement is too delayed or rapidly down swung, it was shown that from the initial falling, unnecessary muscular power was wasted in trapezius, anterior deltoid, erector spinae, latissimus dorsi, upper rectus abdominis, lower rectus abdominis. The muscular parts in tap motion generating muscle action potential were pectoralis major, rectus femoris, upper rectus abdominis, lower rectus abdominis, and those in kick-out motion were upper rectus abdominis, lower rectus abdominis, trapezius and anterior deltoid.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.977-985
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• 2013

Many situations are classified into more than two categories in real world. In this work, we consider ROC surface and VUS, which are graphical representation methods for classification models with three categories. The standard criteria of AUC for the probability of default based on Basel II is extended to the VUS for ROC surface; therefore, the standardized criteria of VUS for the classification model is proposed. The ranges of AUC, K-S and mean difference statistics corresponding to VUS values for each class of the standard criteria are obtained. The standard criteria of VUS for ROC surface can be established by exploring the relationships of these statistics.