• Journal of Biomedical Engineering Research
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• v.43 no.3
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• pp.131-135
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• 2022

Due to COVID-19, Correct method of wearing mask is important to prevent COVID-19 and the other respiratory tract infections. And the deep learning technology in the image processing has been developed. The purpose of this study is to create the type of mask wearing dataset for deep learning models and select the deep learning model to detect the wearing mask correctly. The Image dataset is the 2,296 images acquired using a web crawler. Deep learning classification models provided by tensorflow are used to validate the dataset. And Object detection deep learning model YOLOs are used to select the detection deep learning model to detect the wearing mask correctly. In this process, this paper proposes to validate the type of mask wearing datasets and YOLOv5 is the effective model to detect the type of mask wearing. The experimental results show that reliable dataset is acquired and the YOLOv5 model effectively recognize type of mask wearing.

• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.272-280
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• 2022

During last few years, pandemic of COVID-19 has been a global issue. Under the COVID-19, global events have been restricted or canceled to secure public hygiene and safety. Since one of the largest global events is Olympic Games, we selected recent Olympic Games as our case of analysis. Tokyo Olympic Games (TOG) was held in 2021, but it encountered a millennium disaster, the pandemic of COVID-19. In such a special period, it is of great significance to explore the emotional tendency of global views before and TOG via artificial intelligence. This paper vastly collects the TOG comment data of mainstream websites in South Korea, China, and the United States by implementing crawler program for sentiment analysis (SA). And we use a variety of sentiment analysis models to compare the accuracy of the experimental results, to obtain more reliable SA results. In addition, in the prediction results, to reduce the distortion of opinion by a minority, we introduce an algorithm called "Removing Biased Minority Opinions (RBMO)" and provide how to apply this method to the interpretation domain. Through our method, more authoritative SA results were obtained, which in turn provided a basis for predicting the sentiment tendency of countries around the world in TOG during the COVID-19 epidemic.

• The Journal of Information Systems
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• v.31 no.3
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• pp.19-45
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• 2022

Purpose Since COVID-19, the demand for online class platforms has increased. However, those platforms have not been clearly defined, and related research is also limited. In the context of the knowledge marketplace (KMs), this study examined the effects of class information and trust in creators on class preferences from the perspective of consumption value theory. Design/methodology/approach By establishing a web crawler through Python, this study collected 1,174 class data in Korea's leading knowledge marketplace, Class 101, focusing on diverse class-related information and the number of Instagram followers for individual class creators. Based on class information, this research analyzed the effects of consumers' utilitarian value, social value, and hedonic value on class preference. In addition, this study examined whether consumers' trust in creators moderates the relationship between class information and class preference. Findings According to analysis results, it was found that the higher the consumers' consumption value for each class on KMs, the more positive their preference for the class. Also, it was confirmed that consumers' trust in creators moderates the relationship between class information and class preference.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2571-2586
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• 2022

The rapid popularity of government social media has generated huge amounts of text data, and the analysis of these data has gradually become the focus of digital government research. This study uses Python language to analyze the big data of the Chinese provincial government Weibo. First, this study uses a web crawler approach to collect and statistically describe over 360,000 data from 31 provincial government microblogs in China, covering the period from January 2018 to April 2022. Second, a word separation engine is constructed and these text data are analyzed using word cloud word frequencies as well as semantic relationships. Finally, the text data were analyzed for sentiment using natural language processing methods, and the text topics were studied using LDA algorithm. The results of this study show that, first, the number and scale of posts on the Chinese government Weibo have grown rapidly. Second, government Weibo has certain social attributes, and the epidemics, people's livelihood, and services have become the focus of government Weibo. Third, the contents of government Weibo account for more than 30% of negative sentiments. The classified topics show that the epidemics and epidemic prevention and control overshadowed the other topics, which inhibits the diversification of government Weibo.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.281-282
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• 2021

본 논문에서는 항공 수요예측을 위한 빅데이터 기반 플랫폼의 설계 및 실증 결과를 제시한다. 항공 수요예측 통합 플랫폼은 항공산업 관련 데이터를 Open API, RSS Feed, 웹크롤러(Web Crawler) 등을 이용하여 수집 및 분석하여 자체 개발한 항공 수요예측 알고리즘을 기반으로 결과를 시각화하여 보여주도록 구현되어 있다. 또한, 제안하는 플랫폼의 사용자 인터페이스를 통해 변수 설정을 하여 단위별(Global, National 등), 기간별(단기, 중장기 등), 유형별(여객, 화물 등) 예측 통계 자료를 도출할 수 있다. 플랫폼의 성능 검증을 위해 정형화된 데이터를 비롯하여 소셜네트워크서비스(SNS), 검색엔진 등에서 수집한 비정형 데이터까지 활용하여 특정 키워드의 빈도와 특정 노선에 대한 항공 수요간 상관관계를 분석하였다. 개발한 통합 플랫폼의 지능형 항공 수요예측 알고리즘을 통해 전반적인 공항 운영 및 공항 운영 정책 수립에 기여할 것으로 예상한다.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.151-160
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• 2024

Artificial Neural Networks that enabled Artificial Intelligence are being used in many fields. However, the application to mechanical structures has several problems and research is incomplete. One of the problems is that it is difficult to secure a large amount of data necessary for learning Artificial Neural Networks. In particular, it is important to detect and recognize external forces and forces for safety working and accident prevention of mechanical structures. This study examined the possibility by applying the Current Neural Network of Artificial Neural Networks to detect and recognize the load on the machine. Tens of thousands of data are required for general learning of Recurrent Neural Networks, and to secure large amounts of data, this paper derives load data from ANSYS structural analysis results and applies a stacked auto-encoder technique to secure the amount of data that can be learned. The usefulness of Stacked Auto-Encoder data was examined by comparing Stacked Auto-Encoder data and ANSYS data. In addition, in order to improve the accuracy of detection and recognition of load data with a Recurrent Neural Network, the optimal conditions are proposed by investigating the effects of related functions.

• The Journal of the Convergence on Culture Technology
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• v.3 no.4
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• pp.177-180
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• 2017

Recently, as aging progresses rapidly around the world, studies using light (UV-LED, etc.) as a method which is harmless to the human body and less burden on the treatment are continuously being carried out. Especially, in some fields, it is not used in a limited way but it is advantageous to be used in various medical fields such as dermatology, dentistry, otorhinolaryngology, etc. In many advanced countries, various studies using it have been carried out. However, Are far behind in developed countries. Therefore, in this paper, we propose a technology that can provide good quality services to human patients by effectively controlling light module that can be used for medical use by using IoT crawler-based middleware platform.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.3
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• pp.275-282
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• 2015

Recently, Vecna BEAR type robot to save injured individuals from inaccessible areas has been developed to minimize the loss of life. Because this robot is driven on rough terrain, there is a risk of rollover and vibration, which could impact the injured. In order to guarantee its stability, an algorithm is required that can estimate the speed limits for various environments in real time. Therefore, a dynamic model for real-time analysis is needed for this algorithm. Because the tracks used as the driving component of Vecna BEAR type robot consist of many parts, it is impossible to analyze the multibody tracks in real time. Thus, a lumped track model that satisfies the requirements of a short computation time and adequate accuracy is required. This study performed lumped track modeling, and the traction force was verified using RecurDyn, which is a dynamic commercial program.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.269-281
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• 2010

The cone penetration test(CPT) has been increasingly used for in situ site characterization. However, the use of CPT is often limited due to specific site conditions depending on the cone size, geometry, and capacity of the CPT system used. In South Korea, it has generally been considered that the CPT could be satisfactorily performed only in soft soils. Louisiana State University/ Louisiana Transportation Research Center has implemented a field-rugged continuous intrusion miniature cone penetration test (CIMCPT) system since the 1990s. The miniature cone penetrometer of the CIMCPT system has a cross-sectional cone area of $2cm^2$ allowing finer soil profiles compared to the standard $10cm^2$. The reduced cross-sectional area also enables a system capacity reduction leading to cost saving and ease in maintenance. In addition, the continuous intrusion mechanism allows fast and economic site investigations. Samsung C&T Corporation has recently implemented a similar CIMCPT system. In this study, case studies on the field application of Samsung CIMCPT system for the last 2 years are presented to illustrate its performance investigation and its usefulness and limitation. Results of the case studies show that the CIMCPT system can be applied to soils with cone tip resistance($q_c$) values up to about 30MPa and allows a reliable and useful way to characterize soft soils. The results also show that the rod buckling limits the investigation depth by the system and the large contact pressure of the CIMCPT truck prevents the use of the system at sites with soft surface soils. According to the results of the case studies, the Samsung CIMCPT system has been being upgraded with a miniature cone with a longer rod, a crawler-type transportation system, a pre-boring system, and so on.

• Explosives and Blasting
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• v.8 no.1
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• pp.3-16
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• 1990

The cautious blasting works had been used with emulsion explosion electric M/S delay caps. Drill depth was from 3m to 6m with Crawler Drill $\varphi{70mm}$ on the calcalious sand stone(sort-moderate-semi hard Rock). The total numbers of feet blast were 88. Scale distance were induces 15.52-60.32. It was applied to propagation Law in blasting vibration as follows. Propagtion Law in Blasting Vibration $V=K(\frac{D}{W^b})^n$ where V : Peak partical velocity(cm/sec) D : Distance between explosion and recording sites (m) W : Maximum Charge per delay-period of eighit milliseconds or more(Kg) K : Ground transmission constant, empirically determind on th Rocks, Explosive and drilling pattern ets. b : Charge exponents n : Reduced exponents Where the quantity $D/W^b$ is known as the Scale distance. Above equation is worked by the U.S Bureau of Mines to determine peak particle velocity. The propagation Law can be catagrorized in three graups. Cabic root Scaling charge per delay Square root Scaling of charge per delay Site-specific Scaling of charge per delay Charge and reduction exponents carried out by multiple regressional analysis. It's divided into under loom and over loom distance because the frequency is verified by the distance from blast site. Empirical equation of cautious blasting vibration is as follows. Over 30m----under l00m----- $V=41(D/3\sqrt{W})^{-1.41}$ -----A Over l00m-----$V= 121(D/3\sqrt{W})^{-1.66}$-----B K value on the above equation has to be more specified for furthur understang about the effect of explosives, Rock strength. And Drilling pattern on the vibration levels, it is necessary to carry out more tests.