• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.447-454
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• 2022

In the era of the 4th industrial revolution, we are living in a flood of information. It is very difficult and complicated to find the information people need in such an environment. Therefore, in the flood of information, a recommendation system is essential. Among these recommendation systems, many studies have been conducted on each recommendation system for movies, music, food, and clothes. To date, most personalized recommendation systems have recommended clothes, books, or movies by checking individual tendencies such as age, genre, region, and gender. Future generations will want to be recommended clothes, books, and movies at once by checking age, genre, region, and gender. In this paper, we propose a recommendation system that recommends personalized clothes and food at once according to the user's emotions and weather. We obtained user data from Twitter of social media and analyzed this data as user's basic emotion according to Paul Eckman's theory. The basic emotions obtained in this way were converted into colors by applying Hayashi's Quantification Method III, and these colors were expressed as recommended clothes colors. Also, the type of clothing is recommended using the weather information of the visualcrossing.com API. In addition, various foods are recommended according to the contents of comfort food according to emotions.

• Journal of Korean Home Economics Education Association
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• v.33 no.4
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• pp.1-13
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• 2021

The purpose of this study is to identify trends and potential themes of research on consumption of children and adolescents for 20 years by analyzing keywords. The keywords of 869 studies on consumption of children and adolescents published in journals listed in Korean Citation Index were analyzed using text mining techniques. The most frequent keywords were found in the order of youth, youth consumers, consumer education, conspicuous consumption, consumption behavior, and character. As a result of analyzing the frequency of keywords by dividing into five-year periods, it was confirmed that the frequency of consumer education was significantly higher betwn 2006 and 2010. Research on ethical consumption has been active since 2011, and research has been conducted on various topics instead of without a prominent keyword during the most recent 5-year period. Looking at the keywords based on the TF-IDF, the keywords related to the environment and the Internet were the main keywords between 2001 and 2005. From 2006 to 2010, the TF-IDF values of media use, advertisement education, and Internet items were high. From 2011 to 2015, fair trade, green growth, green consumption, North Korean defector youths, social media, and from 2016 to 2020, text mining, sustainable development education, maker education, and the 2015 revised curriculum appeared as important themes. As a result of topic modeling, eight topics were derived: consumer education, mass media/peer culture, rational consumption, Hallyu/cultural industry, consumer competency, economic education, teaching and learning method, and eco-friendly/ethical consumption. As a result of network analysis, it was found that conspicuous consumption and consumer education are important topics in consumption research of children and adolescents.

• Journal of the Korea Computer Graphics Society
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• v.28 no.2
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• pp.1-9
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• 2022

In this paper, we propose a vector-based augmentation technique that can generate data required for crack detection and a ConvNet(Convolutional Neural Network) technique that can learn it. Detecting cracks quickly and accurately is an important technology to prevent building collapse and fall accidents in advance. In order to solve this problem with artificial intelligence, it is essential to obtain a large amount of data, but it is difficult to obtain a large amount of crack data because the situation for obtaining an actual crack image is mostly dangerous. This problem of database construction can be alleviated with elastic distortion, which increases the amount of data by applying deformation to a specific artificial part. In this paper, the improved crack pattern results are modeled using ConvNet. Rather than elastic distortion, our method can obtain results similar to the actual crack pattern. By designing the crack data augmentation based on a vector, rather than the pixel unit used in general data augmentation, excellent results can be obtained in terms of the amount of crack change. As a result, in this paper, even though a small number of crack data were used as input, a crack database can be efficiently constructed by generating various crack directions and patterns.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.2
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• pp.285-298
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• 2022

This study is to investigate the effects and characteristics of science and engineering integrated lessons on elementary students' creative engineering problem solving propensity (CEPSP). The science and engineering integrated lessons used in this study was a 10 lesson-hours STEM program, co-developed by University of Minnesota and Purdue University. The program was implemented in the 6th grade science class of H Elementary School located in P Metropolitan city. The main data of this study are the pre-post CEPSP result and interview with 5 students collected before and after the research. The CEPSP result was analyzed by a paired-sample t-test and hierarchical cluster analysis. As a result of the t-test, it was found that overall, the program has a positive effect on the students' CEPSP score. As a result of cluster analysis, it was confirmed that studnets' CEPSP could be classified into two groups (lower and higher score cluster). Five students whose, CEPSP score has significantly improved after the lessons were interviewed to find out what the characteristics of the program that contribute the significant change are. As a result of conducting centroid analysis of the interview transcription and the hybrid analysis method, it was found that the meaningful experiences that the five students commonly shared were 'problem solving through collaboration' and 'through repeated experiments (redesign)', problem solving' and 'utilization of scientific knowledge'. As minor reactions, 'choice of the best experimental method' and 'difference between science and engineering' appeared.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.5
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• pp.54-68
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• 2022

This study proposes urban development concept and strategies for Garden City, focused on Solaseado, Yeongam Heanam Tourism-Leisure Type Enterprise City in Korea. Understanding that an essential element of a garden is the endless care performed by gardeners, the Garden City development concept suggests applying this idea to making planned cities by cultivating the potential natural landscape of the site in the long run. The meaning of Garden City can be defined in three aspects; an attitude and process of planning a city, a system for constructing the spatial structure of a city, and city branding. A Garden City is a city structured with the spirit of a garden, a city where open space networks become the urban structure, and a city that builds its identity through the landscape, respectively. From this point of view, the research draws development strategies with spatial design examples to embody the Garden City concept in Solaseado by following three steps; establishing the main urban axes, creating city networks through the conjunction of the axes, and categorizing and systematizing open spaces within the city. Consequently, the study shows an alternative urban planning model that extends the concept of a Garden City while maintaining the intrinsic landscape as an urban resource. In addition, the conceptual master plan of Solaseado will structure the urban landscape and park system according to the Garden City strategies.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.187-192
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• 2023

In this study, trends in ICT education were investigated by analyzing the frequency of appearance of keywords related to machine learning and using conversion of iteration correction(CONCOR) techniques. A total of 304 papers from 2018 to the present published in registered sites were searched on Google Scalar using "ICT education" as the keyword, and 60 papers pertaining to ICT education were selected based on a systematic literature review. Subsequently, keywords were extracted based on the title and summary of the paper. For word frequency and indicator data, 49 keywords with high appearance frequency were extracted by analyzing frequency, via the term frequency-inverse document frequency technique in natural language processing, and words with simultaneous appearance frequency. The relationship degree was verified by analyzing the connection structure and centrality of the connection degree between words, and a cluster composed of words with similarity was derived via CONCOR analysis. First, "education," "research," "result," "utilization," and "analysis" were analyzed as main keywords. Second, by analyzing an N-GRAM network graph with "education" as the keyword, "curriculum" and "utilization" were shown to exhibit the highest correlation level. Third, by conducting a cluster analysis with "education" as the keyword, five groups were formed: "curriculum," "programming," "student," "improvement," and "information." These results indicate that practical research necessary for ICT education can be conducted by analyzing ICT education trends and identifying trends.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.87-96
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• 2022

The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.139-149
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• 2010

Internet was designed for network scalability and best-effort service which makes all hosts connected to Internet to be vulnerable against attack. Many papers have been proposed about attack detection algorithms against the attack using IP spoofing and DoS/DDoS attack. Purpose of DoS/DDoS attack is achieved in short period after the attack begins. Therefore, DoS/DDoS attack should be detected as soon as possible. Attack detection algorithms using false alarm rates consist of the false negative rate and the false positive rate. Moreover, they are important metrics to evaluate the attack detections. In this paper, we analyze the performance of the attack detection algorithms using the impact of false negative rate and false positive rate variation to the normal traffic and the attack traffic by simulations. As the result of this, we find that the number of passed attack packets is in the proportion to the false negative rate and the number of passed normal packets is in the inverse proportion to the false positive rate. We also analyze the limits of attack detection due to the relation between the false negative rate and the false positive rate. Finally, we propose a solution to minimize the limits of attack detection algorithms by defining the network state using the ratio between the number of packets classified as attack packets and the number of packets classified as normal packets. We find the performance of attack detection algorithm is improved by passing the packets classified as attacks.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.77-87
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• 2010

Currently, our society has been changed from the industrial society to the information society. As the war progresses to Information Warfare, Network-Centric Warfare, Long-Range Precision Engagement and Robot Warfare, the military should advance to High-tech Scientific force. For this creation of the war potential, it is regarded as the warfighting experiment is a critical method. Surely it is rational that LVC(Live Virtual Constructive simulation) is desirable to make the warfighting experiment. But because it is limited by the cost, the time, the place and the resource, the constructive simulation(M&S : Modeling&Simulation) is a good tool to solve those problems. There are some studies about the evaluation process for developing the model, but it is unsatisfying in the process of the constructive simulations' operation. This study focuses on the way of constructive simulation operation, which is supplied with the evaluation process(VV&A : Verification Validation & Accreditation). We introduce the example of the rear area operation simulation for "appropriateness evaluation to the organization of logistic corps" by the AWAM(Army Weapon Analysis Model). This study presents the effective methods of the constructive simulations, which is based on the reliable evaluation process, so it will contribute to the warfighting experiments.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.103-109
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• 2023

In this paper, we propose a smart wall switch based on IEEE 802.11b/g/n standard 2.4GHz band communication. As the 4th industrial era evolves, smart home solution development is actively underway, and application cases for smart wall switches are increasing. Most of the Chinese products that preoccupy the market through price competitiveness use Bluetooth and Zigbee communication switches. However, while ZigBee communication is low power, communication speed is slower than Bluetooth and network configuration through a separate hub is additionally required. The Bluetooth method has problems in that the communication range and speed are lower than Wi-Fi communication, the communication standby time is relatively long, and security is weak. In this study, an IEEE 802.11b/g/n smart wall switch applied with Wi-Fi communication technology was developed. In addition, through the two-wire structure, it is designed so that no additional cost is incurred through the construction of a separate neutral line in the building. The result of the study is more than 30% cheaper than the existing wall switch, so it is judged that it will be able to preoccupy the market not only in terms of technological competitiveness but also price competitiveness.