• Journal of Korean Home Economics Education Association
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• v.34 no.2
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• pp.129-152
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• 2022

The purpose of this study was to develop a sustainable dietary education program for middle school home economics subject using a teaching strategy to improve the empowerment of adolescents and to verify and evaluate the effectiveness of the program. To achieve the purpose of this study, the program was developed and evaluated according to the ADDIE teaching design model. The contents related to the dietary area were extracted from the technical & home economics curriculum of the 2015 revised middle school and SDGs, and their relevance was analyzed to select the contents of dietary education. The program developed based on the analysis results is 'dietary life together' and consists of five learning topics: 'living together in the global village', 'maintaining healthy diet', 'creating a dietary culture together', 'living with nature and people', and 'maintaining a safe diet'. As a strategy for improving empowerment, we presented four situations, each of which represents value judgment, prediction of results, responsible behavior choice, and decision making. The developed program was reviewed by experts and applied to 17 unit classes for 17 weeks (1 unit hour per week) to the third graders of middle schools in Gyeonggi-do. Significant differences were found between before and after the class measurements of the personal empowerment and the political and social empowerment, which shows the classes were effective in improving empowerment. However, since there was no significant difference in interpersonal empowerment before and after the program, suggestions were made to utilize strategies to facilitate discussion and cooperative learning when implementing the program. The students who participated in the class evaluated the program positively as a whole. The program was evaluated to have helped the students believe they could change society through solving dietary problems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.413-417
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• 2007

2006년 11월 이후 신 차량 번호판 등장 후, 신 차량 번호판 차량이 꾸준히 증가하고 있다. 이에 따라 속도위반, 신호위반 단속, 무인 주차 관리 시스템, 범죄 및 도주 차량 검거, 고속도로 톨게이트에서 통행료 지불로 인한 교통 체증현상을 해소하기 위한 자동 요금 징수와 같은 다양한 경우에서 신 자동차 번호판의 특징에 맞는 인식 시스템이 요구되고 있다. 따라서 본 논문에서는 이러한 문제를 해결하기 위해 지능형 신 자동차 번호판 인식 방법을 제안한다. 무인 카메라에서 획득된 신 차량 영상을 그레이 레벨로 변환한 후에 블록 이진화한다. 블록 이진화된 차량 영상을 대상으로 차량의 형태학적 특징을 적용하여 잡음을 제거한 후, 번호판 영역을 추출한다. 추출된 번호판 영역에 대해 Grassfire 알고리즘을 적용하여 개별 코드를 추출한다. 차량 번호판을 인식하기 위하여 추출된 개별 코드를 퍼지 ART 알고리즘을 적용하여 학습 및 인식한다. 제안된 차량 번호판 추출 및 인식 방법의 성능을 평가하기 위해 100장의 차량 영상을 대상으로 실험한 결과, 제안된 차량 번호판 추출 및 인식 방법이 실험을 통해서 효율적인 것을 확인하였다.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.273-278
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• 2008

Cars attaching new license plates are increasing after introducing the new format of car license plate in Korea. Therefore, a car new license plate recognition system is required for various fields using automatic recognition of car license plates, automatic parking management systems and arrest of criminal or missing vehicles. In this paper, we proposed an intelligent new car license plate recognition method for the various fields. The proposed method is as follows. First of all, an acquired color image from a surveillance camera is converted to a gray level image and binarized by block binarization method. Second, noises of the binarized image removed by morphological characteristics of cars and then license plate area is extracted. Third, individual characters are extracted from the extracted license plate area using Grassfire algorithm. lastly, the extracted characters are learned and recognized by a fuzzy ART algorithm for final car license plate recognition. In the experiment using 100 car images, we could see that the proposed method is efficient.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.594-600
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• 2017

The new design methodology of prediction model and pattern classification, which is based on the dimension reduction algorithm called principal component analysis, is introduced in this paper. Principal component analysis is one of dimension reduction techniques which are used to reduce the dimension of the input space and extract some good features from the original input variables. The extracted input variables are applied to the prediction model and pattern classifier as the input variables. The introduced prediction model and pattern classifier are based on the very simple regression which is the key point of the paper. The structural simplicity of the prediction model and pattern classifier leads to reducing the over-fitting problem. In order to validate the proposed prediction model and pattern classifier, several machine learning data sets are used.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.945-954
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• 2022

Billions of malicious codes are detected every year, of which only 0.01% are new types of malware. In this situation, an effective malware type classification tool is needed, but previous studies have limitations in quickly analyzing a large amount of malicious code because it requires a complex and massive amount of data pre-processing. To solve this problem, this paper proposes a method to classify the types of malicious code based on the similarity hash without complex data preprocessing. This approach trains the XGBoost model based on the similarity hash information of the malware. To evaluate this approach, we used the BIG-15 dataset, which is widely used in the field of malware classification. As a result, the malicious code was classified with an accuracy of 98.9% also, identified 3,432 benign files with 100% accuracy. This result is superior to most recent studies using complex preprocessing and deep learning models. Therefore, it is expected that more efficient malware classification is possible using the proposed approach.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.761-766
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• 2023

In this paper, TI was measured to classify the presence or absence of mild left ventricular diastolic dysfunction. Of the total 306 data, 206 were used as training data and 100 were used as test data, and the machine learning models used for classification used SVM and KNN. As a result, it was confirmed that SVM showed relatively higher accuracy than KNN and was more useful in diagnosing the presence of left ventricular diastolic dysfunction. In future research, it is expected that classification performance can be further improved by adding various indicators that evaluate not only TI but also cardiac function and securing more data. Furthermore, it is expected to be used as basic data to predict and classify other diseases and solve the problem of insufficient medical manpower compared to the increasing number of tests.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.27-35
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• 2023

In this paper, we propose a process of increasing productivity by applying a deep learning-based defect detection and classification system to the prepreg fiber manufacturing process, which is in high demand in the field of producing composite materials. In order to apply it to toe prepreg manufacturing equipment that requires a solution due to the occurrence of a large amount of defects in various conditions, the optimal environment was first established by selecting cameras and lights necessary for defect detection and classification model production. In addition, data necessary for the production of multiple classification models were collected and labeled according to normal and defective conditions. The multi-classification model is made based on CNN and applies pre-learning models such as VGGNet, MobileNet, ResNet, etc. to compare performance and identify improvement directions with accuracy and loss graphs. Data augmentation and dropout techniques were applied to identify and improve overfitting problems as major problems. In order to evaluate the performance of the model, a performance evaluation was conducted using the confusion matrix as a performance indicator, and the performance of more than 99% was confirmed. In addition, it checks the classification results for images acquired in real time by applying them to the actual process to check whether the discrimination values are accurately derived.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.224-233
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• 2023

The purpose of this study is to investigate the effect of environmental classes using EBS program on the environmental sensitivity and environmentally responsible behavior of 6th grade elementary school students. To this end, the 2015 revised elementary school curriculum was reconstructed for 6th grade students, and subject-centered environmental classes were planned, and EBS educational broadcasting environmental contents suitable for each class were applied and utilized. The conclusion of this study is as follows. First, this study analyzed the 2015 revised curriculum and reorganized the 6th grade curriculum and creative experience activities to plan the 22nd environmental class, specifying environmental sensitivity and environmentally responsible behavior that can have a positive impact on learners in each class. EBS educational broadcasting environmental contents that can be utilized were selected and environmental classes were conducted using them. Second, it was found that environmental classes using EBS educational broadcasting had a significant effect on improving the environmental sensitivity of elementary school students. The fact that environmental classes using EBS educational broadcasting goes beyond the spatial limitations of schools and informs that global citizens are interested in environmental problems and are working to solve environmental problems. Third, it was found that environmental classes using EBS educational broadcasting had a significant effect on elementary school students' environmentally responsible behavior. This is because environmental classes using EBS educational broadcasting do not stop at imparting knowledge, but suggest learning that leads to civic behavior, educational behavior, economic behavior, physical behavior, and persuasive behavior related to the environment.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.2
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• pp.211-224
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• 2011

The purpose of this study is to investigate exchange between companies and rural communities in 1 company - 1 village campaign and assess functions of NACF(National Agricultural Cooperative Federation)'s 'I Farm Love' as intermediary organization. The result shows that Korea companies participated in 1 company - 1 village campaign to understand rural area and revitalize economic condition in rural community. Most of exchange programs are volunteer works and direct dealing of farm products. The functions of NACF was highly assessed as an informant and intermediary. However establishing networks or promoting exchanges between corporation and rural village were low assessed. It is necessary of NACF to make up for advanced mediation and intermediary between rural villages and companies so that 1 company - 1 village campaign become corporate community investment. Moreover functions to develop programs suited characteristic of companies and set up networks of multi-stakeholders are needed.

• Journal of Science Education
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• v.38 no.3
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• pp.718-736
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• 2014

This study was intended to determine PCK of the middle school science teachers on Mendelian genetics and factors influenced to form their PCKs. Two science teachers with biology major with a teaching experience over 5 years were chosen as the subject. Data were collected by class observation, semi-structured interview, teacher questionnaire survey, Content Representation and Pedagogical and Professional-experience Repertoire. The collected data were analyzed based on Magnusson's PCK for science teaching consisting of five components: (a) the orientation toward teaching science, (b) the knowledge of science curriculum, (c) the knowledge of students' understanding, (d) the knowledge of assessment, and (e) the knowledge and belief in the instructional strategies to teach science. Teachers could have the orientation toward teaching science served as an assisting role to support students' abilities. Both subject teachers seemed to focus on giving lectures. Their efforts to improve students' exploration methods and abilities were not expressed enough in their real classes and they found that students struggled to understand Mendelian genetics. Therefore, they should have explained them in an easier way and worked harder to make their students understood accurately and applied basic and advanced concepts of Mendelian genetics. They found students' preconception and misconception regarding Mendelian genetics and wished to enhance their learning effects by various teaching strategies such as correcting misconception, adding the history of science and simply assessing students' affirmative domains. It was also found that factors influenced to form PCK regarding Mendelian genetics by both teachers were as follows: teacher's personality and endeavor, textbooks and guidance books, schools and their circumstances, teaching experience, experience as a learner, interaction with their colleagues, and university curriculum. Both teachers said that it was important for teachers to make every efforts to give better classes.