• Title/Summary/Keyword: design error

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FBX Format Animation Generation System Combined with Joint Estimation Network using RGB Images (RGB 이미지를 이용한 관절 추정 네트워크와 결합된 FBX 형식 애니메이션 생성 시스템)

  • Lee, Yujin;Kim, Sangjoon;Park, Gooman
    • Journal of Broadcast Engineering
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    • v.26 no.5
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    • pp.519-532
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    • 2021
  • Recently, in various fields such as games, movies, and animation, content that uses motion capture to build body models and create characters to express in 3D space is increasing. Studies are underway to generate animations using RGB-D cameras to compensate for problems such as the cost of cinematography in how to place joints by attaching markers, but the problem of pose estimation accuracy or equipment cost still exists. Therefore, in this paper, we propose a system that inputs RGB images into a joint estimation network and converts the results into 3D data to create FBX format animations in order to reduce the equipment cost required for animation creation and increase joint estimation accuracy. First, the two-dimensional joint is estimated for the RGB image, and the three-dimensional coordinates of the joint are estimated using this value. The result is converted to a quaternion, rotated, and an animation in FBX format is created. To measure the accuracy of the proposed method, the system operation was verified by comparing the error between the animation generated based on the 3D position of the marker by attaching a marker to the body and the animation generated by the proposed system.

Analysis of Al-Saggaf et al's Three-factor User Authentication Scheme for TMIS

  • Park, Mi-Og
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.9
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    • pp.89-96
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    • 2021
  • In this paper, we analyzed that the user authentication scheme for TMIS(Telecare Medicine Information System) proposed by Al-Saggaf et al. In 2019, Al-Saggaf et al. proposed authentication scheme using biometric information, Al-Saggaf et al. claimed that their authentication scheme provides high security against various attacks along with very low computational cost. However in this paper after analyzing Al-Saggaf et al's authentication scheme, the Al-Saggaf et al's one are missing random number s from the DB to calculate the identity of the user from the server, and there is a design error in the authentication scheme due to the lack of delivery method. Al-Saggaf et al also claimed that their authentication scheme were safe against a variety of attacks, but were vulnerable to password guessing attack using login request messages and smart cards, session key exposure and insider attack. An attacker could also use a password to decrypt the stored user's biometric information by encrypting the DB with a password. Exposure of biometric information is a very serious breach of the user's privacy, which could allow an attacker to succeed in the user impersonation. Furthermore, Al-Saggaf et al's authentication schemes are vulnerable to identity guessing attack, which, unlike what they claimed, do not provide significant user anonymity in TMIS.

AutoML and Artificial Neural Network Modeling of Process Dynamics of LNG Regasification Using Seawater (해수 이용 LNG 재기화 공정의 딥러닝과 AutoML을 이용한 동적모델링)

  • Shin, Yongbeom;Yoo, Sangwoo;Kwak, Dongho;Lee, Nagyeong;Shin, Dongil
    • Korean Chemical Engineering Research
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    • v.59 no.2
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    • pp.209-218
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    • 2021
  • First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.

A Study on the Meaning of School Space: Criticism and Alternatives (학교 공간에 관한 의미 탐색: 비판과 대안)

  • Kim, Dal-Hyo
    • Journal of the Korean Institute of Educational Facilities
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    • v.26 no.4
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    • pp.3-10
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    • 2019
  • In school facilities, space is the basic framework. The structure and arrangement of space will provide the form and feel of school facilities. In order to become a high-quality school facility, it is necessary to focus on the educational, human and ecological aspects of the instructor and learner until the space is conceived, designed and completed. However, even when public education was introduced in the past, it did not become a school space considering this aspect. The school space, which focuses on efficiency and labor production, is a school space that reflects the characteristics of a factory-type school, which has been occupied by a large number until recently. Although efforts to improve the quality of school facilities have been attempted in recent years, there is also a need to pursue more active changes. Future-oriented and progressive school spaces include flexibility, connectivity, individualization, diversity(creativity). In other words, space should be flexible so that it can be used faithfully according to the educational situation, not the fixed and limited school space as in the past. In the future, the school space should be open and securely linked to the place where it is essential to complete community relations with the community. In addition, space should be flexible so that the school can meet the needs of each student as much as possible. And the school space should be transformed from the space design of the past fixed pattern to reflect the close relationship between spatial, psychological, physiological, and behavioral areas. When school space needs to shift away from the past and change in a new future-oriented direction, the remaining tasks should be presented with specific characteristics and content of the direction. And the function of the consignment should be handled by related research. Although the text of this study reveals the characteristics of future-oriented school space, more concrete and empirical research results should be presented by subsequent research at home and abroad. It is necessary to reduce trial and error in creating a future-oriented school space where both professors and learners can be satisfied by analyzing the common points and differences between the results of the study. In order to do this, it is necessary to make efforts to approach such research based on the participation of the subjects who teach and learn directly at the school site.

Correction Algorithm of Errors by Seagrasses in Coastal Bathymetry Surveying Using Drone and HD Camera (드론과 HD 카메라를 이용한 수심측량시 잘피에 의한 오차제거 알고리즘)

  • Kim, Gyeongyeop;Choi, Gunhwan;Ahn, Kyungmo
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.32 no.6
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    • pp.553-560
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    • 2020
  • This paper presents an algorithm for identifying and eliminating errors by seagrasses in coastal bathymetry surveying using drone and HD camera. Survey errors due to seagrasses were identified, segmentated and eliminated using a L∗a∗b color space model. Bathymetry survey using a drone and HD camera has many advantages over conventional survey methods such as ship-board acoustic sounder or manual level survey which are time consuming and expensive. However, errors caused by sea bed reflectance due to seagrasses habitat hamper the development of new surveying tool. Seagrasses are the flowering plants which start to grow in November and flourish to maximum density until April in Korea. We developed a new algorithm for identifying seagrasses habitat locations and eliminating errors due to seagrasses to get the accurate depth survey data. We tested our algorithm at Wolpo beach. Bathymetry survey data which were obtained using a drone with HD camera and calibrated to eliminate errors due to seagrasses, were compared with depth survey data obtained using ship-board multi-beam acoustic sounder. The abnormal bathymetry data which are defined as the excess of 1.5 times of a standard deviation of random errors, are composed of 8.6% of the test site of area of 200 m by 300 m. By applying the developed algorithm, 92% of abnnormal bathymetry data were successfully eliminated and 33% of RMS errors were reduced.

Preparation of Cosmeceuticals Containing Wheat Sprout Extracts: Optimization of Emulsion Stability Using CCD-RSM (밀싹 추출물이 함유된 Cosmeceuticals의 제조: CCD-RSM을 이용한 유화안정성 최적화)

  • Jang, Hyun Sik;Ma, Xixiang;Lee, Seung Bum
    • Applied Chemistry for Engineering
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    • v.32 no.3
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    • pp.320-325
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    • 2021
  • In this study, an optimization for the production of water emulsion was designed by adding an extract of wheat sprout, which is known to contain a large amount of antioxidants. The central composite design of reaction surface analysis method (CCD-RSM) was used for the optimization process. The amount of emulsifier, emulsification time, and added amount of wheat sprout extract were selected as independent variables based on our preliminary experiments. The mean droplet size (MDS), viscosity, and emulsion stability index (ESI) were set as the responses to evaluate the stability of the emulsion. For each independent variable, the P-value and coefficient of determination were evaluated to verify the reliability of the experiments. From the result of CCD-RSM, optimum conditions for the emulsification were determined as 23.6 min, 7.7 wt.%, and 3.9 wt.% for the emulsification time, amount of emulsifier, and amount of sprout, respectively. From the optimized condition obtained, MDS, viscosity, and ESI after 7 days from reaction were estimated as 252.3 nm, 616.7 cP, and 88.7%, respectively. The overall satisfaction was 0.9137, which supported the validity of the experiments, and the error rate was measured at 0.5% or less by advancing the experiments. Therefore, an optimized process for producing an emulsion by adding the malt extract was designed by the CCD-RSM.

A Study on Prediction of Earth Retaining Work Cost in the Project Planning Stage -Focusing on Apartment Construction Projects in Seoul- (사업기획단계에서 흙막이 공사비 예측에 관한 연구 -서울시내 아파트 건설사업을 중심으로-)

  • Lee, Jin-Kyu;Yang, Kyung-Jin;Park, Ki-Hyeon;Kim, Chan-kee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.1
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    • pp.385-392
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    • 2021
  • In general, earth retaining work in construction works enables the construction of structures, prevents the displacement of the surrounding ground to the maximum extent, and plays an important role in ensuring the safety of the surrounding structures and field workers. The earth retaining work and the construction method differ according to the various ground characteristics, surrounding topographical characteristics, repair environment, and design conditions. In particular, in the case of Seoul city, the environments and ground conditions differ according to the area. This study analyzed the earth retaining work cost mainly for the apartment construction project in Seoul and calculated the approximate earth retaining work cost at the project planning stage. A model was developed to predict the cost of earth retaining work that matches the characteristics of Seoul City and predict the construction cost for earth retaining work. This paper presents the predicted earth retaining work cost using a multiple regression model that applies 10 project outlines as independent variables. The error rate of the prediction result of the earth retaining work cost of the apartment construction project in Seoul using multiple regression models was 10.75%.

Traffic Correction System Using Vehicle Axles Counts of Piezo Sensors (피에조센서의 차량 축 카운트를 활용한 교통량보정시스템)

  • Jung, Seung-Weon;Oh, Ju-Sam
    • The Journal of the Korea Contents Association
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    • v.21 no.1
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    • pp.277-283
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    • 2021
  • Traffic data by vehicle classification are important data used as basic data in various fields such as road and traffic design. Traffic data is collected through permanent and temporary surveys and is provided as an annual average daily traffic (AATD) in the statistical yearbook of road traffic. permanent surveys are collected through traffic collection equipment (AVC), and the AVC consists of a loop sensor that detects traffic volume and a piezo sensor that detects the number of axes. Due to the nature of the buried type of traffic collection equipment, missing data is generated due to failure of detection equipment. In the existing method, it is corrected through historical data and the trend of traffic around the point. However, this method has a disadvantage in that it does not reflect temporal and spatial characteristics and that the existing data used for correction may also be a correction value. In this study, we proposed a method to correct the missing traffic volume by calculating the axis correction coefficient through the accumulated number of axes acquired by using a piezo sensor that can detect the axis of the vehicle. This has the advantage of being able to reflect temporal and spatial characteristics, which are the limitations of the existing methods, and as a result of comparative evaluation, the error rate was derived lower than that of the existing methods. The traffic volume correction system using axis count is judged as a correction method applicable to the field system with a simple algorithm.

Influence of Fluid Height and Structure width ratio on the Dynamic Behavior of Fluid in a Rectangular Structure (사각형 구조물에 저장된 유체의 동적거동에 유체높이와 구조물 폭의 비가 미치는 영향)

  • Park, Gun;Yoon, Hyungchul;Hong, Ki Nam
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.24 no.5
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    • pp.126-134
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    • 2020
  • In the case of an earthquake, the fluid storage structure generates hydraulic pressure due to the fluctuation of the fluid. At this time, the hydraulic pressure of the fluid changes not only the peaked acceleration of the earthquake but also the sloshing height of the fluid free water surface. Factors influencing this change in load include the shape of the seismic wave, the maximum seismic strength, the size of the fluid storage structure, the width of the structure, and the height of the fluid. In this study, the effect of the ratio between the height of the fluid and the width of the structure was investigated on the fluctuation characteristics of the fluid. 200mm and 140mm of fluid were placed in a water storage tank with a width of 500mm, and a real seismic wave was applied to measure the shape of the fluctuation of the fluid free water surface. The similarity between the experiment and the analysis was verified through the S.P.H(Smoothed Particle Hydrodynamic) technique, one of the numerical analysis techniques. It was confirmed that the free water surface of the fluid showed a similar shape, through comparison of experiment and analysis. And based on this results, SPH technique was applied to analyze the fluctuation shape of the fluid free water surface while varying the ratio between the fluid height and the structure width. An equation to predict the maximum and minimum heights of the fluid free water surface during an earthquake was proposed, and it was confirmed that the error between the maximum and minimum heights of the fluid free water surface predicted by the proposed equation was within a maximum of 3%.

A Prediction of N-value Using Regression Analysis Based on Data Augmentation (데이터 증강 기반 회귀분석을 이용한 N치 예측)

  • Kim, Kwang Myung;Park, Hyoung June;Lee, Jae Beom;Park, Chan Jin
    • The Journal of Engineering Geology
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    • v.32 no.2
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    • pp.221-239
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    • 2022
  • Unknown geotechnical characteristics are key challenges in the design of piles for the plant, civil and building works. Although the N-values which were read through the standard penetration test are important, those N-values of the whole area are not likely acquired in common practice. In this study, the N-value is predicted by means of regression analysis with artificial intelligence (AI). Big data is important to improve learning performance of AI, so circular augmentation method is applied to build up the big data at the current study. The optimal model was chosen among applied AI algorithms, such as artificial neural network, decision tree and auto machine learning. To select optimal model among the above three AI algorithms is to minimize the margin of error. To evaluate the method, actual data and predicted data of six performed projects in Poland, Indonesia and Malaysia were compared. As a result of this study, the AI prediction of this method is proven to be reliable. Therefore, it is realized that the geotechnical characteristics of non-boring points were predictable and the optimal arrangement of structure could be achieved utilizing three dimensional N-value distribution map.