• Title/Summary/Keyword: 흐름 패턴

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A Study on the Application of Information Design to Korean Cultural Heritage Education (한국 문화유산 교육의 정보디자인 적용 방법 고찰)

  • Barng, Keeung
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.9 no.11
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    • pp.475-489
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    • 2019
  • This study seeks to explore the method of imagination through creative new thinking in cultural heritage education and the most effective model of education in education. Research methods were organized by the methods of reviewing literature, browsing the Internet, and comparative analysis of prior research. We hope to realize the need for differentiated Korean cultural heritage and make efforts to incorporate our identity in the design. Through this study, we hope to realize the need for differentiated Korean cultural heritage and make efforts to incorporate our identity in the design. In the process of visualizing information, the focus should be on identifying the structure, characteristics, and the correlation between pattern and trend analysis, and the heterogeneity analysis, and should be made with the characteristics considered. Texting, graphics, sound, animation, lighting, and Navigation are often used as the expressive elements of information visualization for educational models. To facilitate the understanding of learners, accurate information transmission visuals should be presented. To do so, the use of infographic can be the answer. It is necessary to develop appropriate multimedia visual data, such as the use of infographic to be applied, and to develop various infographic multimedia visuals. These work should not be merely a research dimension, but should be carried out with the aim of helping develop actual cultural heritage educational content.

The Improvement of the Area Estimation of the Metropolitan Railway Station Platforms (도시철도 및 광역철도 승강장 면적산정식의 개선방안 연구)

  • Kim, Jinho;Shin, Minjung;You, Soyoung;Kim, Taewan
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.38 no.6
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    • pp.991-999
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    • 2018
  • In urban areas, the proportion of railway traffic in public transport is increasing. The congestion situation is repeated as the passengers concentrate on station and transfer facilities and the inconvenience of the passengers is increasing in terms of safety and convenience. Therefore, the importance of estimating the appropriate area of the station has been emphasized. The area estimation formula used in the metropolitan railway stations currently is a partial modification of the area estimation formula of Japan in the 1970s. It does not reflect changes in the social and cultural environment and patterns of passengers. The technical basis for major decision variables is insufficient. Therefore, the theoretical basis of the area estimation formula and the pedestrian environment satisfaction of the design guideline of metropolitan railway stations were analyzed in order to suggest improvement formula. The improved area estimation formula was verified by conducting field surveys on 5 stations of metropolitan railways and 15 stations of urban railways. The existing area estimation formula is LOS E grade for the main space. However, the LOS D grade is implemented when the improved area estimation formula is applied. Based on the results, the design factors for the area estimation formula are suggested.

Estimation of Road Surface Condition during Summer Season Using Machine Learning (기계학습을 통한 여름철 노면상태 추정 알고리즘 개발)

  • Yeo, jiho;Lee, Jooyoung;Kim, Ganghwa;Jang, Kitae
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.6
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    • pp.121-132
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    • 2018
  • Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

Flow Pattern Change of Dished Bottom Vessel with Dual Impeller in Transition Region (전이영역에서의 2단 날개가 있는 접시형 바닥 교반조의 유동 상태 변화)

  • Koh, Seung-Tae
    • Korean Chemical Engineering Research
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    • v.59 no.1
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    • pp.94-99
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    • 2021
  • It was found that mixing patterns suddenly changed at an impeller rotation speed in a dished bottom vessel with dual Rushton turbines. Two isolated mixing regions like doughnuts rings generated at a low rotational speed and three isolated mixing regions generated at a higher speed. This phenomenon was observed at the mixing condition in transition area, where the power number with baffle was the same as that without baffle. We found a phenomenon in which the flow state in a dish-bottom agitation tank equipped with a two-stage Rushton turbine blade changes at a certain rotational speed. In the laminar flow region, the isolated stable donut rings were formed even when the rotational speed was changed, and no specific variation in the mixing pattern was observed. In the transition region, the two isolated thick unmixed donut rings do not change even if the rotation speed is changed in the flat bottom vessel, whereas in the dished bottom vessel, when the rotation speed is 450 rpm, the two isolated thick unmixed donut rings are changed to three isolated thin donut rings and then improved mixing. In the dished bottom vessel, in the range of Re=138~178, the isolated ring-shaped unmixed region appeared in three places and the size was also large. But in the flat bottom vessel, the isolated thick ring-shaped unmixed region appeared in two places in Re=116~176 and the size was also small. It appeared in two places, and the size was also small. The condition in which this phenomenon is observed is a transition region, and it was found that when the baffle plate is attached, the power number starts to increase compared to when the baffle plate is not present. In addition, when the mixing Reynolds number exceeded 300 and a slight turbulence was mixed in the flow state, the disconnection of these flow pattern was resolved and the mixture was completely mixed.

A research on the possibility of restoring cultural assets of artificial intelligence through the application of artificial neural networks to roof tile(Wadang)

  • Kim, JunO;Lee, Byong-Kwon
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.1
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    • pp.19-26
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    • 2021
  • Cultural assets excavated in historical areas have their own characteristics based on the background of the times, and it can be seen that their patterns and characteristics change little by little according to the history and the flow of the spreading area. Cultural properties excavated in some areas represent the culture of the time and some maintain their intact appearance, but most of them are damaged/lost or divided into parts, and many experts are mobilized to research the composition and repair the damaged parts. The purpose of this research is to learn patterns and characteristics of the past through artificial intelligence neural networks for such restoration research, and to restore the lost parts of the excavated cultural assets based on Generative Adversarial Network(GAN)[1]. The research is a process in which the rest of the damaged/lost parts are restored based on some of the cultural assets excavated based on the GAN. To recover some parts of dammed of cultural asset, through training with the 2D image of a complete cultural asset. This research is focused on how much recovered not only damaged parts but also reproduce colors and materials. Finally, through adopted this trained neural network to real damaged cultural, confirmed area of recovered area and limitation.

A Study of the Scene-based NUC Using Image-patch Homogeneity for an Airborne Focal-plane-array IR Camera (영상 패치 균질도를 이용한 항공 탑재 초점면배열 중적외선 카메라 영상 기반 불균일 보정 기법 연구)

  • Kang, Myung-Ho;Yoon, Eun-Suk;Park, Ka-Young;Koh, Yeong Jun
    • Korean Journal of Optics and Photonics
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    • v.33 no.4
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    • pp.146-158
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    • 2022
  • The detector of a focal-plane-array mid-wave infrared (MWIR) camera has different response characteristics for each detector pixel, resulting in nonuniformity between detector pixels. In addition, image nonuniformity occurs due to heat generation inside the camera during operation. To solve this problem, in the process of camera manufacturing it is common to use a gain-and-offset table generated from a blackbody to correct the difference between detector pixels. One method of correcting nonuniformity due to internal heat generation during the operation of the camera generates a new offset value based on input frame images. This paper proposes a technique for dividing an input image into block image patches and generating offset values using only homogeneous patches, to correct the nonuniformity that occurs during camera operation. The proposed technique may not only generate a nonuniformity-correction offset that can prevent motion marks due to camera-gaze movement of the acquired image, but may also improve nonuniformity-correction performance with a small number of input images. Experimental results show that distortion such as flow marks does not occur, and good correction performance can be confirmed even with half the number of input images or fewer, compared to the traditional method.

Fabrication of Printed Graphene Pattern Via Exfoliation and Ink Formulation of Natural Graphite (천연흑연 박리를 통한 그래핀 잉크 생산 및 프린팅)

  • Gyuri, Kim;Yeongwon, Kwak;Ho Young, Jun;Chang-Ho, Choi
    • Clean Technology
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    • v.28 no.4
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    • pp.293-300
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    • 2022
  • The remarkable mechanical, electrical, and thermal properties of graphene have recently sparked tremendous interest in various research fields. One of the most promising methods to produce large quantities of graphene dispersion is liquid-phase exfoliation (LPE) which utilizes ultrasonic waves or shear stresses to exfoliate bulk graphite into graphene flakes that are a few layers thick. Graphene dispersion produced via LPE can be transformed into graphene ink to further boost graphene's applications, but producing high-quality graphene more economically remains a challenge. To overcome this shortcoming, an advanced LPE process should be developed that uses relatively cheap natural graphite as a graphene source. In this study, a flow-LPE process was used to exfoliate natural graphite to produce graphene that was three times cheaper and seven times larger than synthetic graphite. The optimal exfoliation conditions in the flow-LPE process were determined in order to produce high-quality graphene flakes. In addition, the structural and electrical properties of the flakes were characterized. The electrical properties of the exfoliated graphene were investigated by carrying out an ink formulation process to prepare graphene ink suitable for inkjet printing, and fabricating a printed graphene pattern. By utilizing natural graphite, this study offers a potential protocol for graphene production, ink formulation, and printed graphene devices in a more industrial-comparable manner.

Imputation of Missing SST Observation Data Using Multivariate Bidirectional RNN (다변수 Bidirectional RNN을 이용한 표층수온 결측 데이터 보간)

  • Shin, YongTak;Kim, Dong-Hoon;Kim, Hyeon-Jae;Lim, Chaewook;Woo, Seung-Buhm
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.34 no.4
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    • pp.109-118
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    • 2022
  • The data of the missing section among the vertex surface sea temperature observation data was imputed using the Bidirectional Recurrent Neural Network(BiRNN). Among artificial intelligence techniques, Recurrent Neural Networks (RNNs), which are commonly used for time series data, only estimate in the direction of time flow or in the reverse direction to the missing estimation position, so the estimation performance is poor in the long-term missing section. On the other hand, in this study, estimation performance can be improved even for long-term missing data by estimating in both directions before and after the missing section. Also, by using all available data around the observation point (sea surface temperature, temperature, wind field, atmospheric pressure, humidity), the imputation performance was further improved by estimating the imputation data from these correlations together. For performance verification, a statistical model, Multivariate Imputation by Chained Equations (MICE), a machine learning-based Random Forest model, and an RNN model using Long Short-Term Memory (LSTM) were compared. For imputation of long-term missing for 7 days, the average accuracy of the BiRNN/statistical models is 70.8%/61.2%, respectively, and the average error is 0.28 degrees/0.44 degrees, respectively, so the BiRNN model performs better than other models. By applying a temporal decay factor representing the missing pattern, it is judged that the BiRNN technique has better imputation performance than the existing method as the missing section becomes longer.

A Sanitizer for Detecting Vulnerable Code Patterns in uC/OS-II Operating System-based Firmware for Programmable Logic Controllers (PLC용 uC/OS-II 운영체제 기반 펌웨어에서 발생 가능한 취약점 패턴 탐지 새니타이저)

  • Han, Seungjae;Lee, Keonyong;You, Guenha;Cho, Seong-je
    • Journal of Software Assessment and Valuation
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    • v.16 no.1
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    • pp.65-79
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    • 2020
  • As Programmable Logic Controllers (PLCs), popular components in industrial control systems (ICS), are incorporated with the technologies such as micro-controllers, real-time operating systems, and communication capabilities. As the latest PLCs have been connected to the Internet, they are becoming a main target of cyber threats. This paper proposes two sanitizers that improve the security of uC/OS-II based firmware for a PLC. That is, we devise BU sanitizer for detecting out-of-bounds accesses to buffers and UaF sanitizer for fixing use-after-free bugs in the firmware. They can sanitize the binary firmware image generated in a desktop PC before downloading it to the PLC. The BU sanitizer can also detect the violation of control flow integrity using both call graph and symbols of functions in the firmware image. We have implemented the proposed two sanitizers as a prototype system on a PLC running uC/OS-II and demonstrated the effectiveness of them by performing experiments as well as comparing them with the existing sanitizers. These findings can be used to detect and mitigate unintended vulnerabilities during the firmware development phase.

Design of an Intellectual Smart Mirror Appication helping Face Makeup (얼굴 메이크업을 도와주는 지능형 스마트 거울 앱의설계)

  • Oh, Sun Jin;Lee, Yoon Suk
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.5
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    • pp.497-502
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    • 2022
  • Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.