• Journal of Korean Home Economics Education Association
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• v.32 no.1
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• pp.51-76
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• 2020

The purpose of this research was to develop the education program on traditional living culture for home economics(HE) based on the 2015 revised national curriculum. The existing school curriculum for traditional living culture tends to overly focus on the theories about traditional culture and suffer from absence of continuity in learning activities. It can be argued that HE is an ideal subject for dealing with traditional living culture as it aims to develop students' ability to recreate the traditional culture, meeting present needs and trends. This study, thus, attempted to present the practical ways of improving the quality of education on traditional living culture by developing HE education program for high school students. To fulfill the purpose, this research, as a teaching topic, selected the traditional patterns and the "Obangsaek"(Korean traditional five colors) which can commonly be dealt with in the subjects of traditional Korean food, Korean costume and Korean style house. In particular, the program was developed following the ADDE process. In the stage of analysis, this article analyzed the HE curriculum and making activities included in HE textbooks based on the 2015 revised national curriculum, as well as the needs of teachers and students regarding traditional living culture education. In the stage of design, this study developed the instructional model, selecting class topics, tools and materials. In the stage of development, the programs on traditional living culture including costume, food and house were developed. In the evaluation phase, this research conducted the validity test and received the feedbacks from 12 HE educators in order to complete the programs. This study finally suggested that future studies in this area examine the effect of the presented programs on enhancing the students' perception of traditional culture and the will of developing and succeeding the traditional living culture.

• Journal of the Korean Chemical Society
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• v.65 no.3
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• pp.209-218
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• 2021

This study investigated the condition of chemistry teacher's student competency assessment based on the inquiry report. To this end, an inquiry report was collected for chemistry teachers who took the training at two universities that conducted the 2020 first-class chemistry teacher training. The science subject competencies presented in NAEA analysis framework was used to analyze what kind of competencies teachers assess students through inquiry reports. A total of 63 chemistry teachers submitted inquiry reports, which were analyzed by competency, sub-element of each competency, and detail element to analyze the actual situation. As a result of the study, most chemistry teachers reflected their 'scientific inquiry and problem-solving ability' in their evaluation through inquiry reports. 'Ability to understand and apply scientific principles', which is mainly evaluated through paper-based evaluation, was partially used as confirmation of prerequisite learning at the beginning of the inquiry and the weight of evaluating 'scientific communication skill' was not large. In 'scientific inquiry and problem-solving ability' through inquiry report, 'design and conduct explorations', 'data analysis and interpretation' and 'drawing conclusion and suggesting solution' were mainly assessed. However, 'discover and recognize problems' and 'development and use of model' were hardly assessed.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.217-242
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• 2022

With the launch of Artificial Intelligence(AI)-based intelligent products on the market, innovative changes are taking place not only in business but also in consumers' daily lives. Intelligent products have the potential to realize technology differentiation and increase market competitiveness through advanced functions of artificial intelligence. However, there is no new product development methodology that can sufficiently reflect the characteristics of artificial intelligence for the purpose of developing intelligent products with high market acceptance. This study proposes a KANO-QFD integrated model as a methodology for intelligent product development. As a specific example of the empirical analysis, the types of consumer requirements for hair loss prediction and treatment device were classified, and the relative importance and priority of engineering characteristics were derived to suggest the direction of intelligent medical product development. As a result of a survey of 130 consumers, accurate prediction of future hair loss progress, future hair loss and improved future after treatment realized and viewed on a smartphone, sophisticated design, and treatment using laser and LED combined light energy were realized as attractive quality factors among the KANO categories. As a result of the analysis based on House of Quality of QFD, learning data for hair loss diagnosis and prediction, micro camera resolution for scalp scan, hair loss type classification model, customized personal account management, and hair loss progress diagnosis model were derived. This study is significant in that it presented directions for the development of artificial intelligence-based intelligent medical product that were not previously preceded.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.262-268
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• 2017

The energy consumption of buildings is approximately 20.5% of the total energy consumption, and the interest in energy efficiency and low consumption of the building is increasing. Several studies have performed energy analysis and evaluation. Energy analysis and evaluation are effective when applied in the initial design phase. In the initial design phase, however, the energy performance is evaluated using general level information, such as glazing area and surface area. Therefore, the evaluation results of the detailed design stage, which is based on the drawings, including detailed information of the materials and facilities, will be different. Thus far, most studies have reported the analysis and evaluation at the detailed design stage, where detailed information about the materials installed in the building becomes clear. Therefore, it is possible to improve the accuracy of the energy environment analysis if the energy environment information generated during the life cycle of the building can be established and accurate information can be provided in the analysis at the initial design stage using a probability / statistical method. On the other hand, historical data on energy use has not been established in Korea. Therefore, this study performed energy environment analysis to construct the energy environment historical data. As a result of the research, information classification system, information model, and service model for acquiring and providing energy environment information that can be used for building lifecycle information of buildings are presented and used as the basic data. The results can be utilized in the historical data management system so that the reliability of analysis can be improved by supplementing the input information at the initial design stage. If the historical data is stacked, it can be used as learning data in methods, such as probability / statistics or artificial intelligence for energy environment analysis in the initial design stage.

• Journal of Korean Society of Steel Construction
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• v.19 no.6
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• pp.695-702
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• 2007

The Thermal Prestressing Method for continuous composite girder bridges is a new design and construction method developed to induce initial composite stresses in the concrete slab at negative bending regions. Due to the induced initial stresses, prevention of tensile cracks at the concrete slab, reduction of steel girder section, and reduction of reinforcing bars are possible. Thus, the construction efficiency can be improved and the construction can be made more economical. The method for determining the optimum heating region of the thermal prestressing method has not been established although such method is essential for improving the efficiency of the design process. The trial-and-error method used in previous studies is far from efficient, and a more rational method for computing optimal heating region is required. In this study, an efficient method for determining the optimum heating region in using the thermal prestressing method was developed based on the neural network algorithm, which is widely adopted to pattern recognition, optimization, diagnosis, and estimation problems in various fields. Back-propagation algorithm, commonly used as a learning algorithm in neural network problems, was used for the training of the neural network. Through case studies of two-span and three-span continuous composite girder bridges using the developed procedure, the optimal heating regions were obtained.

• Journal of Korean Tunnelling and Underground Space Association
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• v.4 no.4
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• pp.277-286
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• 2002

Most of the problems in dealing with the tunnel construction are the uncertainties and complexities of the stress conditions and rock strengths in ahead of the tunnel excavation. The limitations on the investigation technology, inaccessibility of borehole test in mountain area and public hatred also restrict our knowledge on the geologic conditions on the mountainous tunneling area. Nevertheless an extensive and superior geophysical exploration data is possibly acquired deep within the mountain area, with up to the tunnel locations in the case of alternative design or turn-key base projects. An appealing claim in the use of artificial neural networks (ANN) is that they give a more trustworthy results on our data based on identifying relevant input variables such as a little geotechnical information and biological learning principles. In this study, error back-propagation algorithm that is one of the teaching techniques of ANN is applied to presupposition on Rock Mass Ratings (RMR) for unknown tunnel area. In order to verify the applicability of this model, a 4km railway tunnel's field data are verified and used as input parameters for the prediction of RMR, with the learned pattern by error back propagation logics. ANN is one of basic methods in solving the geotechnical uncertainties and helpful in solving the problems with data consistency, but needs some modification on the technical problems and we hope our study to be developed in the future design work.

• Journal of The Korean Association of Information Education
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• v.12 no.4
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• pp.437-448
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• 2008

As the importance of knowledge is emphasized and the environment of battlefields is changing, the military also demands competent people equipped with creativity, cooperativeness and communication ability, and in this situation it is required to apply PBL to education in the navy. The present study went through three stages in order to develop a prototype to implement a naval e PBL support system for knowledge creation. First, databases in Korea Education and Research Information Service, National Assembly Library, etc. were searched using keywords such as PBL, e-PBL, knowledge creation and knowledge ecosystem. In addition, we selected and analyzed frequently quoted literature and recent research reports related to this study among domestic and foreign theses, books, research papers, etc. recommended by specialists in contents, and derived the key values of a knowledge creation type e-PBL support system and design strategies. Second, we developed a primary prototype based on the contents of analysis and, revising it according to teaching design specialists' opinions, we proposed the final prototype of knowledge creation type naval e PBL support system and it has values as follows. First, the knowledge creation type naval e PBL support system provides learners with opportunities to apply e PBL and helps them improve their creativity, cooperativeness and communication ability and accumulate know how of services. Second, it improves work efficiency by circulating knowledge through sharing among individuals or groups, and produces synergy that promotes the organizational culture of learning. Third, the knowledge creation type naval e-PBL support system enables teachers who apply PBL to school education to find new applications of PBL in constructing knowledge bases.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.135-141
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• 2018

In this paper, we describe design and implementation of optimal smart home control system. Recent developments in technologies such as sensors and communication have enabled the Internet of Things to control a wide range of objects, such as light bulbs, socket-outlet, or clothing. Many businesses rely on the launch of collaborative services between them. However, traditional IoT systems often support a single protocol, although data is transmitted across multiple protocols for end-to-end devices. In addition, depending on the manufacturer of the Internet of things, there is a dedicated application and it has a high degree of complexity in registering and controlling different IoT devices for the internet of things. ARIoT system, special marking points and edge extraction techniques are used to detect objects, but there are relatively low deviations depending on the sampling data. The proposed system implements an IoT gateway of object based on OneM2M to compensate for existing problems. It supports diverse protocols of end to end devices and supported them with a single application. In addition, devices were learned by using deep learning in the artificial intelligence field and improved object recognition of existing systems by inference and detection, reducing the deviation of recognition rates.

• The Journal of Korean Association of Computer Education
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• v.5 no.4
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• pp.134-145
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• 2002

The purpose of this study is to present the functional and technical solutions for text learning of web-based textbook in which each letter has its own focal point. The solutions help learners not to lose the main focus when eye moves to the next letter or line. The text screen of the electronic textbook automatically scrolls the text to up and down or left and right directions which are preassigned by learner. It doesn't need the operation of mouse or keyboard. And learner can change scroll speed and types anytime during scrolling. Automatic text scroll function is a solution for controlling data and screen to reflect the personal favor and ability. It contains the content structure of the text(characteristics, categorizations etc.), the appearance of the text(density, size, font etc.), scroll options(scroll, speed etc.), program control type(ram resident program etc.), and the application of the screen design principles(legibility etc.). To resolve these functional problems, technical 8 phases are provided, which are environment setting, scroll option setting, copy, data analysis, scroll coding, centered focus coding, left and right focus coding, implementation. The learner can focus on text without dispersion because the text focal points stay in the fixed area of screen. 1bey read the text following their preferences for fonts, sizes, line spacing and so on.