• Title/Summary/Keyword: Automated analysis

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Analysis of the Technology Adoption Impact Factors for Automated Construction Equipment (건설 자동화 장비 도입을 위한 기술도입 영향요인 분석)

  • Lee, Chijoo;Lee, Ghang;Sim, Jaekyang
    • Korean Journal of Construction Engineering and Management
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    • v.14 no.2
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    • pp.56-64
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    • 2013
  • New construction technologies, especially automated equipment, are rarely deployed on a construction site where many accidents and claims occur. This study analyzed and derived impact factors for technology adoption to improve the chance of adopting automated construction equipment to the field. First, impact factors were classified into functional and non-functional factors. Then the functional factors were divided into usability and functionality factors, and the non-functional factors into cost, construction property, and organization factors. Next, the importance and realization possibility of each impact factor were analyzed through a survey with experts. Usability and functionality were analyzed to have the highest importance and realization possibility. Lastly, the differences between construction companies and equipment development companies in the importance and realization possibility of each factor were analyzed. Construction companies recognized previous relationship, operator's attitude, members' will, and construction quality more important than equipment development companies.. The equipment development companies should consider these differences between the view of construction companies and that of equipment development companies on the impact factors. The result of this study can be used as a basis for evaluating for automated construction equipment in the preliminary development phase.

Study on the Development of K-City Roadmap through the Standard Analysis of the Test-Bed for Automated Vehicles in China (중국 자율주행차 테스트베드 관련 표준 분석을 통한 K-City 고도화 방안 수립에 관한 연구)

  • Lee, Sanghyun;Ko, Hangeom;Lee, Hyunewoo;Cho, Seongwoo;Yun, Ilsoo
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.1
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    • pp.6-13
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    • 2022
  • The Ministry of Land, Infrastructure and Transport (MoLIT) and the Korean Automobile Testing and Research Institute (KATRI) are supporting the development of Lv.3 automated vehicle (hereinafter, AV) technology by constructing an automated driving pilot city (as known as K-City) equipped with total 5 evaluation environments (urban, motorway, suburban, community road, and autonomous parking facility) which is a test bed exclusively for AV (2017~2018). An upgrade project is in a progress to materialize harsh environments such as bad weather (rain, fog, etc.) and reproduction of communication jamming (GPS blocking, etc.) with the purpose of supporting the development of Lv.4 connected & automated vehicle (hereinafter, CAV) technology (2019~2022). We intend to proactively establish a national level standard for CAV test-bed and test road requirements, test method, etc. for establishment of a road map for the construction of the test bed which is being promoted step by step and analyze and, when required, benchmark the case of China that has announced and is utilizing it. Through this, we plan to define standardized requirements (evaluation facility, evaluation system, etc.) on the test bed for the development of Lv.4/4+ CAV technology and utilize the same for the design and construction of a test bed, establishment of a road map for the construction of a real car-based test environment related to the support for autonomous driving service substantiation, etc. through provision of an evaluation environment utilizing K-City, and the establishment of a K-City upgrade strategies, etc.

Applicability Evaluation of Automated Machine Learning and Deep Neural Networks for Arctic Sea Ice Surface Temperature Estimation (북극 해빙표면온도 산출을 위한 Automated Machine Learning과 Deep Neural Network의 적용성 평가)

  • Sungwoo Park;Noh-Hun Seong;Suyoung Sim;Daeseong Jung;Jongho Woo;Nayeon Kim;Honghee Kim;Kyung-Soo Han
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1491-1495
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    • 2023
  • This study utilized automated machine learning (AutoML) to calculate Arctic ice surface temperature (IST). AutoML-derived IST exhibited a strong correlation coefficient (R) of 0.97 and a root mean squared error (RMSE) of 2.51K. Comparative analysis with deep neural network (DNN) models revealed that AutoML IST demonstrated good accuracy, particularly when compared to Moderate Resolution Imaging Spectroradiometer (MODIS) IST and ice mass balance (IMB) buoy IST. These findings underscore the effectiveness of AutoML in enhancing IST estimation accuracy under challenging polar conditions.

Seismic Analysis of Chemical Pump Using Automatic Mesh Generation System (자동요소생성 시스템을 이용한 케미컬 펌프의 지진해석)

  • Jang, Hyun-Seok;Lee, Joon-Seong
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.24 no.6
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    • pp.685-690
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    • 2011
  • This paper describes a seismic analysis of chemical pump using automated mesh generation system. The use of an automated analysis system, involving FE codes together with CAD systems and FE pre- and post-processors, has provided an important step towards shortening the design process and structural optimization. The FE model, which is a FE mesh accompanied with the analysis condition, is automatically converted from the analysis model. The FE models are then automatically analyzed using the FE analysis code. This integrated FE simulation system is applied to an analysis of three-dimensional complex solid structures such as a chemical pump.

Automated Measurement of Native T1 and Extracellular Volume Fraction in Cardiac Magnetic Resonance Imaging Using a Commercially Available Deep Learning Algorithm

  • Suyon Chang;Kyunghwa Han;Suji Lee;Young Joong Yang;Pan Ki Kim;Byoung Wook Choi;Young Joo Suh
    • Korean Journal of Radiology
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    • v.23 no.12
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    • pp.1251-1259
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    • 2022
  • Objective: T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extracellular volume (ECV) fractions in cardiac magnetic resonance (CMR) imaging with a temporally separated dataset. Materials and Methods: CMR images obtained for 95 participants (mean age ± standard deviation, 54.5 ± 15.2 years), including 36 left ventricular hypertrophy (12 hypertrophic cardiomyopathy, 12 Fabry disease, and 12 amyloidosis), 32 dilated cardiomyopathy, and 27 healthy volunteers, were included. A commercial deep learning (DL) algorithm based on 2D U-net (Myomics-T1 software, version 1.0.0) was used for the automated analysis of T1 maps. Four radiologists, as study readers, performed manual analysis. The reference standard was the consensus result of the manual analysis by two additional expert readers. The segmentation performance of the DL algorithm and the correlation and agreement between the automated measurement and the reference standard were assessed. Interobserver agreement among the four radiologists was analyzed. Results: DL successfully segmented the myocardium in 99.3% of slices in the native T1 map and 89.8% of slices in the post-T1 map with Dice similarity coefficients of 0.86 ± 0.05 and 0.74 ± 0.17, respectively. Native T1 and ECV showed strong correlation and agreement between DL and the reference: for T1, r = 0.967 (95% confidence interval [CI], 0.951-0.978) and bias of 9.5 msec (95% limits of agreement [LOA], -23.6-42.6 msec); for ECV, r = 0.987 (95% CI, 0.980-0.991) and bias of 0.7% (95% LOA, -2.8%-4.2%) on per-subject basis. Agreements between DL and each of the four radiologists were excellent (intraclass correlation coefficient [ICC] of 0.98-0.99 for both native T1 and ECV), comparable to the pairwise agreement between the radiologists (ICC of 0.97-1.00 and 0.99-1.00 for native T1 and ECV, respectively). Conclusion: The DL algorithm allowed automated T1 and ECV measurements comparable to those of radiologists.

Study on Correlation-based Feature Selection in an Automatic Quality Inspection System using Support Vector Machine (SVM) (SVM 기반 자동 품질검사 시스템에서 상관분석 기반 데이터 선정 연구)

  • Song, Donghwan;Oh, Yeong Gwang;Kim, Namhun
    • Journal of Korean Institute of Industrial Engineers
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    • v.42 no.6
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    • pp.370-376
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    • 2016
  • Manufacturing data analysis and its applications are getting a huge popularity in various industries. In spite of the fast advancement in the big data analysis technology, however, the manufacturing quality data monitored from the automated inspection system sometimes is not reliable enough due to the complex patterns of product quality. In this study, thus, we aim to define the level of trusty of an automated quality inspection system and improve the reliability of the quality inspection data. By correlation analysis and feature selection, this paper presents a method of improving the inspection accuracy and efficiency in an SVM-based automatic product quality inspection system using thermal image data in an auto part manufacturing case. The proposed method is implemented in the sealer dispensing process of the automobile manufacturing and verified by the analysis of the optimal feature selection from the quality analysis results.

Aerodynamic Analysis Automation and Analysis Code Verification of an Airfoil in the Transonic Region (천음속영역에서 에어포일의 공력해석 자동화 및 해석코드 검증)

  • Kim, Hyun;Chung, Hyoung-Seog;Chang, Jo-Won;Choi, Joo-Ho
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.14 no.3
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    • pp.7-15
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    • 2006
  • Aerodynamic analysis of an airfoil in the transonic region was automated in order to enable parametric study by using the journal file of the commercial analysis code FLUENT, pre/post process Gambit and computational mathematics code MATLAB. The automated capability was illustrated via NACA 0012 and RAE 2822 airfoils. This analysis was carried out at Mach numbers ranged from 0.70 to 0.80, angles of attack; 1$^{\circ}$, 2$^{\circ}$ and 4$^{\circ}$, Reynolds numbers; 4.0${\times}$106, 6.5${\times}$106. The analysis results of a pressure coefficient were verified by comparing with the experimental data which were measured in terms of chord length because the pressure coefficient of an airfoil surface is a good estimator of flow characteristics. The results of two airfoils show that this analysis code is useful enough to be used in the design optimization of airfoil.

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Automated measurement and analysis of sidewall roughness using three-dimensional atomic force microscopy

  • Su‑Been Yoo;Seong‑Hun Yun;Ah‑Jin Jo;Sang‑Joon Cho;Haneol Cho;Jun‑Ho Lee;Byoung‑Woon Ahn
    • Applied Microscopy
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    • v.52
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    • pp.1.1-1.8
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    • 2022
  • As semiconductor device architecture develops, from planar field-effect transistors (FET) to FinFET and gate-all-around (GAA), there is an increased need to measure 3D structure sidewalls precisely. Here, we present a 3-Dimensional Atomic Force Microscope (3D-AFM), a powerful 3D metrology tool to measure the sidewall roughness (SWR) of vertical and undercut structures. First, we measured three different dies repeatedly to calculate reproducibility in die level. Reproducible results were derived with a relative standard deviation under 2%. Second, we measured 13 different dies, including the center and edge of the wafer, to analyze SWR distribution in wafer level and reliable results were measured. All analysis was performed using a novel algorithm, including auto fattening, sidewall detection, and SWR calculation. In addition, SWR automatic analysis software was implemented to reduce analysis time and to provide standard analysis. The results suggest that our 3D-AFM, based on the tilted Z scanner, will enable an advanced methodology for automated 3D measurement and analysis.

Detail Design and Structural Stability Analysis for Automated PHC Pile Cutting Machine (PHC 파일 원커팅 두부정리 자동화 장비의 상세설계 및 구조적 타당성 분석)

  • Yeom, Dong Jun;Hwang, Ji Young;Park, Yesul;Kim, Young Suk
    • Korean Journal of Construction Engineering and Management
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    • v.19 no.2
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    • pp.117-125
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    • 2018
  • The primary objectives of this study are to develop a detail design of automated PHC pile head cutting machine and structural stability analysis of detail design that improves the conventional head cutting work in safety, quality, and productivity. For this, the following research works are conducted sequentially; 1)literature review and field study, 2)expert survey and interview, 3)selection of core technology using AHP analysis, 4)deduction of detail design 5) verification of structural stability. As an outcome, it is analyzed that gripper and gripper bearing shaft are structurally stable. Their maximum stresses are shown as 15.93%, 10.58% compared to their yield strength respectively. The results of detail design and structural stability analysis in this study will be utilized for the actual development of the automated PHC pile cutting machine prototype.

The Study on an Automated Generation Method of Road Drawings using Road Survey Vehicle (도로교통안전점검차량을 이용한 도로의 자동도면화 생성 연구)

  • Lee, Jun Seok;Yun, Duk Geun;Park, Jae Hong
    • International Journal of Highway Engineering
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    • v.16 no.5
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    • pp.91-98
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    • 2014
  • PURPOSES : This study is to develop a automate road mapping system using ARASEO(Automated Road Analysis and Safety Evaluation TOol) for road management. METHODS : The road survey van named ARASEO(Automated Road Analysis and Safety Evaluation TOol) was used to generate highway drawings for Korea National Road number 37 automatically. In order to generate the highway drawings for purpose of road management, it is required to acquired the information for highway alignment, road width and road facilities such as safety barrier and road sign. Therefore the survey van acquired and analyzed the road width, median and guardrail data using rear side laser sensor of ARASEO and recognized the traffic control sign and chevron sign using foreside camera images. Also the highway alignment which is the basic information for highway drawing can be analyzed by acquisition the every 1m positional and attitude data using GPU and IMU sensor and developed algorithm. Finally, in this research the CAD based drawing software was developed to draw highway drawing using the analysis result from ARASEO. RESULTS : This study showed the comparison result of the surveyed road width and drawing data. To make the drawing of the road, we made the Autocad ARX program witch run in CAD menu interface. CONCLUSIONS : Using this program we can create the road center line, every 500m horizontal and vertical ground plan drawing automatically.