• 제목/요약/키워드: Semi-automatic

검색결과 412건 처리시간 0.021초

지적도면 수치화를 위한 정밀 벡터라이징 도구 개발 (Development of Precise Vectorizing Tools for Digitization of Cadastral Maps)

  • 정재준;오재홍;김용일
    • Spatial Information Research
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    • 제8권1호
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    • pp.69-83
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    • 2000
  • 지적도면은 매 필지별로 토지에 대한 지번, 위치, 경RP , 소유권등을 규정하고 있는 토지에 관한 가장 기본적인 자료이다. 지적과 관련된 업무는 그 동안 거의 수작업에 의한 방법을 사용하여 효율성의 문제가 대두되었다. 따라서 정부에서는 지적도면을 전산화하려 하였으며, 토지 및 임야대장에 대한 속성정보를 모두 전산 입력하였다. 그러나 도형정보인 지적도면의 전산화가 이루어지지않아 효율적인 토지정보시스템 구축에 많은 어려움이 있다. 따라서 본 연구에서는 오차가 허용될 수 없는 지적도면의 특성을 감안하여 , 스크린 디지타이징을 원형(prototype) 으로 하고 작업의 효율성을 위해 선의 교점을 찾는 과정을 선추적 방식을 통해 자동화한, 혼합형(hybrid) 벡터라이징 방식을 개발하였다. 개발된 프로그램을 구동한 결과 백터라이징의 정확도에 있어서는 스크린 디지타이징 방법과 동일하였고, 효율성 측면에서는 본 프로그램에 의한 방법이 스크린 디지타이징 방법보다 35분 정도 시간을 단축할 수 있었다.

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H 빔 구조물의 T-Joint에서 용접조건에 따른 용접잔류응력의 영향 (Effects of Residual Stress with Welding Condition in the Steel Structure of H-beam)

  • 석한길
    • Journal of Welding and Joining
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    • 제21권5호
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    • pp.568-574
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    • 2003
  • In the welding for the steel structure of H-beam with mild steel and 490N/$\textrm{mm}^2$ high tensile steel, we applied the fillet weld mostly and 6-8mm weld length(AISC-spec.). And a new developed metal-cored-wire is used in automatic welding as well as semi-automatic welding. In this study we have attempted to raise the welding productivity and to stabilize the quality on horizontal positions of fillet welding with the following items: - We improved the weld productivity using metal based cored wire with a high deposition rate in the steel structure of H-beam. - We tested the weldability and evaluated the quality of the weldmetal by horizontal fillet $CO_2$ welding. The process is carried out in combination with a special purpose metal-based FCW with excellent resistance to porosity and high welding speed. - We studied the micro structure of the weldmetal by the various welding conditions. - We studied the effect of welding residual stress by the welding conditions in T-joint. Therefore, it can be assured that more productive and superior quality of the weldmetal can be taken from this study results.

A Study on the Automatic Pattern Development of Adult Male Basic Pattern Using 3D Body Scan Data

  • Jeong, Mi-E;Nam, Yun-Ja
    • 패션비즈니스
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    • 제11권3호
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    • pp.35-45
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    • 2007
  • This study examined how to create 2D basic pattern of individuals by means of 3-D body figure, which is to develop a flat of individual basic pattern directly from the 3-D body scan data of each subject using that of the upper body of a male adult. In terms of methodology, this study adopted 3D body scan data on system and body to make examinations in the following steps: 1. Standard point and line were set on human body, along with 3-D definition points(feature points). 2. PB was created by modifying horizontal and longitudinal section of scan data. 3. Ways to set reserve were established in the findings of PB planar development. Respective developed flat patterns were compared with pattern findings in previous studies by means of sensory evaluation. As a result, it was found that both system and body model are basic pattern and belong to appropriate pattern as semi-tight-fit basic pattern with overall appropriate tolerances. Thus, this study came to a conclusion that it is feasible and valid to develop theories for flat development as considered herein.

디지털 X선 영상을 이용한 치아 와동 컴퓨터 보조 검출 시스템 연구 (A Study of Computer-aided Detection System for Dental Cavity on Digital X-ray Image)

  • 허창회;김민정;조현종
    • 전기학회논문지
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    • 제65권8호
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    • pp.1424-1429
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    • 2016
  • Segmentation is one of the first steps in most diagnosis systems for characterization of dental caries in an early stage. The purpose of automatic dental cavity detection system is helping dentist to make more precise diagnosis. We proposed the semi-automatic method for the segmentation of dental caries on digital x-ray images. Based on a manually and roughly selected ROI (Region of Interest), it calculated the contour for the dental cavity. A snake algorithm which is one of active contour models repetitively refined the initial contour and self-examination and correction on the segmentation result. Seven phantom tooth from incisor to molar were made for the evaluation of the developed algorithm. They contained a different form of cavities and each phantom tooth has two dental cavities. From 14 dental cavities, twelve cavities were accurately detected including small cavities. And two cavities were segmented partly. It demonstrates the practical feasibility of the dental lesion detection using Computer-aided Detection (CADe).

자유곡면의 NC 황삭가공을 위한 자동 공구 선정과 경로 생성 (Automatic Tool Selection and Path Generation for NC Rough Cutting of Sculptured Surface)

  • 홍성의;이건우
    • 한국정밀공학회지
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    • 제11권6호
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    • pp.28-41
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    • 1994
  • An efficient algorithm is proposed to select the proper tools and generate their paths for NC rough cutting of dies and molds with sculptured surfaces. Even though a milling process consists of roughing, semi-finishing, and finishing, most material is removed by a rough cutting process. Therfore it can be said that the rough cutting process occupy an important portion of the NC milling process, and accordingly, an efficient rough cutting method contributes to an efficient milling process. In order work, the following basic assumption is accepted for the efficient machining. That is, to machine a region bounded by a profile, larger tools should be used in the far inside and the region adjacent to relatively simple portion of the boundary while smaller tools are used in the regions adjacent to the relatively complex protion. Thus the tools are selected based on the complexity of the boundary profile adjacent to the region to be machined. An index called cutting path ratio is proposed in this work as a measure of the relative complexity of the profile with respect to a tool diameter. Once the tools are selected, their tool paths are calculated starting from the largest to the smallest tool.

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Revolutionizing Brain Tumor Segmentation in MRI with Dynamic Fusion of Handcrafted Features and Global Pathway-based Deep Learning

  • Faizan Ullah;Muhammad Nadeem;Mohammad Abrar
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권1호
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    • pp.105-125
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    • 2024
  • Gliomas are the most common malignant brain tumor and cause the most deaths. Manual brain tumor segmentation is expensive, time-consuming, error-prone, and dependent on the radiologist's expertise and experience. Manual brain tumor segmentation outcomes by different radiologists for the same patient may differ. Thus, more robust, and dependable methods are needed. Medical imaging researchers produced numerous semi-automatic and fully automatic brain tumor segmentation algorithms using ML pipelines and accurate (handcrafted feature-based, etc.) or data-driven strategies. Current methods use CNN or handmade features such symmetry analysis, alignment-based features analysis, or textural qualities. CNN approaches provide unsupervised features, while manual features model domain knowledge. Cascaded algorithms may outperform feature-based or data-driven like CNN methods. A revolutionary cascaded strategy is presented that intelligently supplies CNN with past information from handmade feature-based ML algorithms. Each patient receives manual ground truth and four MRI modalities (T1, T1c, T2, and FLAIR). Handcrafted characteristics and deep learning are used to segment brain tumors in a Global Convolutional Neural Network (GCNN). The proposed GCNN architecture with two parallel CNNs, CSPathways CNN (CSPCNN) and MRI Pathways CNN (MRIPCNN), segmented BraTS brain tumors with high accuracy. The proposed model achieved a Dice score of 87% higher than the state of the art. This research could improve brain tumor segmentation, helping clinicians diagnose and treat patients.

Is HAZOP a Reliable Tool? What Improvements are Possible?

  • Park, Sunhwa;Rogers, William J.;Pasman, Hans J.
    • 한국가스학회지
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    • 제22권2호
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    • pp.1-20
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    • 2018
  • Despite many measures, still from time to time catastrophic events occur, even after reviewing potential scenarios with HAZID tools. Therefore, it is evident that in order to prevent such events, answering the question: "What can go wrong?" requires more enhanced HAZID tools. Recently, new system based approaches have been proposed, such as STPA (system-theoretic process analysis) and Blended Hazid, but for the time being for several reasons their availability for general use is very limited. However, by making use of available advanced software and technology, traditional HAZID tools can still be improved in degree of completeness of identifying possible hazards and in work time efficiency. The new HAZID methodology proposed here, the Data-based semi-Automatic HAZard IDentification (DAHAZID), seeks to identify possible scenarios with a semi-automated system approach. Based on the two traditional HAZID tools, Hazard Operability (HAZOP) Study and Failure Modes, Effects, and Criticality Analysis (FMECA), the new method will minimize the limitations of each method. This will occur by means of a thorough systematic preparation before the tools are applied. Rather than depending on reading drawings to obtain connectivity information of process system equipment elements, this research is generating and presenting in prepopulated work sheets linked components together with all required information and space to note HAZID results. Next, this method can be integrated with proper guidelines regarding process safer design and hazard analysis. To examine its usefulness, the method will be applied to a case study.

준지도 학습 기반의 자동 문서 범주화 (Automatic Text Categorization based on Semi-Supervised Learning)

  • 고영중;서정연
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제35권5호
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    • pp.325-334
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    • 2008
  • 자동 문서 범주화란 문서의 내용에 기반하여 미리 정의되어 있는 범주에 문서를 자동으로 할당하는 작업이다. 자동 문서 범주화에 관한 기존의 연구들은 지도 학습 기반으로서, 보통 수작업에 의해 범주가 할당된 대량의 학습 문서를 이용하여 범주화 작업을 학습한다. 그러나, 이러한 방법의 문제점은 대량의 학습 문서를 구축하기가 어렵다는 것이다. 즉, 학습 문서 생성을 위해 문서를 수집하는 것은 쉬우나, 수집된 문서에 범주를 할당하는 것은 매우 어렵고 시간이 많이 소요되는 작업이라는 것이다. 본 논문에서는 이러한 문제점을 해결하기 위해서, 준지도 학습 기반의 자동 문서 범주화 기법을 제안한다. 제안된 기법은 범주가 할당되지 않은 말뭉치와 각 범주의 핵심어만을 사용한다. 각 범주의 핵심어로부터 문맥간의 유사도 측정 기법을 이용한 부스트래핑(bootstrapping) 기법을 통하여 범주가 할당된 학습 문서를 자동으로 생성하고, 이를 이용하여 학습하고 문서 범주화 작업을 수행한다. 제안된 기법은 학습 문서 생성 작업과 대량의 학습 문서 없이 적은 비용으로 문서 범주화를 수행하고자 하는 영역에서 유용하게 사용될 수 있을 것이다.

Deep learning-based post-disaster building inspection with channel-wise attention and semi-supervised learning

  • Wen Tang;Tarutal Ghosh Mondal;Rih-Teng Wu;Abhishek Subedi;Mohammad R. Jahanshahi
    • Smart Structures and Systems
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    • 제31권4호
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    • pp.365-381
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    • 2023
  • The existing vision-based techniques for inspection and condition assessment of civil infrastructure are mostly manual and consequently time-consuming, expensive, subjective, and risky. As a viable alternative, researchers in the past resorted to deep learning-based autonomous damage detection algorithms for expedited post-disaster reconnaissance of structures. Although a number of automatic damage detection algorithms have been proposed, the scarcity of labeled training data remains a major concern. To address this issue, this study proposed a semi-supervised learning (SSL) framework based on consistency regularization and cross-supervision. Image data from post-earthquake reconnaissance, that contains cracks, spalling, and exposed rebars are used to evaluate the proposed solution. Experiments are carried out under different data partition protocols, and it is shown that the proposed SSL method can make use of unlabeled images to enhance the segmentation performance when limited amount of ground truth labels are provided. This study also proposes DeepLab-AASPP and modified versions of U-Net++ based on channel-wise attention mechanism to better segment the components and damage areas from images of reinforced concrete buildings. The channel-wise attention mechanism can effectively improve the performance of the network by dynamically scaling the feature maps so that the networks can focus on more informative feature maps in the concatenation layer. The proposed DeepLab-AASPP achieves the best performance on component segmentation and damage state segmentation tasks with mIoU scores of 0.9850 and 0.7032, respectively. For crack, spalling, and rebar segmentation tasks, modified U-Net++ obtains the best performance with Igou scores (excluding the background pixels) of 0.5449, 0.9375, and 0.5018, respectively. The proposed architectures win the second place in IC-SHM2021 competition in all five tasks of Project 2.

3차원 인체 스캔 데이터의 정확도 검증에 관한 연구 - Cyberware의 WB4 스캐너를 중심으로 - (The Verification of Accuracy of 3D Body Scan Data - Focused on the Cyberware WB4 Whole Body Scanner -)

  • 박선미;남윤자
    • 한국의상디자인학회지
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    • 제14권1호
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    • pp.81-96
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    • 2012
  • The purpose of this study is to provide fundamental information for standardization of 3D body measurement. This research analyzes errors occurring in the process of extracting body size from 3D body scan data. First, as a result of analyzing basic state of the 3D body scanner's calibration, the point number of each section was almost the same, while the right and left as well as the front and back coordinates of the center of gravity are not, showing unstable data. Nevertheless, the latter does not influence on the size of cylinder such as width and circumference. Next, we analyzed point coordinates variations of scan data on a mannequin nude by life casting. The result was great deflection in case of complicated or horizontal sections including the reference point beyond proper distance from centers of four cameras. In case of the mannequin's size, accuracy proves comparatively high in that measurement errors in height, width, depth, and length dimension occurred all within allowable errors, only except chest depth, while there were a lot of measurement errors in a circumference dimension. Secondly, analysis of accuracy of automatic extraction identification program algorithm presented that a semi-automatic measurement program is better than an automatic measurement program. While both of them ate very acute in parts related to crotch, they are not in armpit related parts. Therefore, in extracting of human body size from 3D scan data, what really matters seems to parts related to armpits.

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