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오범석 ( Beom Seok Oh ),박재일 ( Jae Il Park ) 대한설비관리학회 2010 대한설비관리학회지 Vol.15 No.4
Small production companies are demanded improving quality, reducing cost and shortening the lead time for strengthen the competitiveness. Therefore they must have visualization tool which can measure production process. In order to do this, they need to apply Enterprise Resource Planning but ERP that deal with all tasks of corporate activities has many unnecessary functions and is complex to use, so it is hard to apply effectively. Thus suitable application of production information system has a purpose to improve effect of process control using visualization tool. In this research, development of visualization tool for process control was studied using Visio, VB and Excel. Therefore supervisor is able to improve effectiveness of management using visualization tool that should find out overall operation.
정웅열 ( Ungyeol Jung ),오범석 ( Beom Seok Oh ),이찬호 ( Chan Ho Lee ),임재원 ( Jae Won Lim ),장선필 ( Seon Pil Jang ) 한국컴퓨터교육학회 2015 한국컴퓨터교육학회 학술발표대회논문집 Vol.19 No.2
PID 제어는 생명체의 길항작용과 미적분 기반의 수학 모델을 응용한 제어 기술로서, 그 효율이 높기 때문에 실제 응용분야에서 많이 응용된다. 본 연구에서는 LEGO Mindstorms NXT와 LabVIEW를 이용하여 PID 제어 알고리즘의 에너지 효율과 직선과 곡선 구간에서의 P, I, D 상수의 에너지 효율에 대한 기여도를 분석하였다. 그 결과 On/Off 제어와 비교할 때, 직선 구간에서는 PID 제어가 1.5∼2배 정도 더 좋은 효율을 보였고, 직선과 곡선이 혼합된 구간에서는 PID 제어가 3∼4배 정도 더 좋은 효율을 보였다. 상수별 기여도의 경우 직선 구간 주행 시에는 I제어가 많은 영향을 미쳤으며, 곡선 구간 주행 시에는 P, D제어가 많은 영향을 끼친다는 것을 알게 되었다. 또한 본 연구에서 제시한 에너지 효율에 대한 정량적인 분석 방법은 PID 제어 이외에 다양한 제어 기법의 효율을 분석할 때에도 사용할 수 있을 것이라 기대한다
Bezawit Habtamu Nuriye(베자윗),Beom-Seok Oh(오범석) 대한전자공학회 2024 대한전자공학회 학술대회 Vol.2024 No.6
Choosing an optimal window time length is pivotal in time series modeling, as it allows for extracting valuable information by examining local patterns within the data. Unlike traditional methods that rely on fixed windows, our research introduces a novel approach to starting point detection in time series data by searching for an optimal window time length before commencing the start point detection task, which enhances performance. Our experiment on a multivariate time series dataset shows promising results affirming the effectiveness of our method.
Shania Sesilia(샤니아 세실리아),Beom-Seok Oh(오범석) 대한전자공학회 2024 대한전자공학회 학술대회 Vol.2024 No.6
Monocular Metric Depth Estimation (MMDE) is crucial for computer vision applications, and recent progress in this field has been significant. However, the challenge of learning metric depth is complicated by the substantial variations in Monocular Depth Estimation (MDE) datasets, resulting in increased model instability during the training. This paper aims to tackle this challenge by thoroughly investigating the effectiveness of camera intrinsic parameters in MMDE. By conducting a series of experiments, we offer valuable insights into the intricacies of MMDE. Our analysis emphasizes the vital role of camera intrinsic parameters such as focal length, magnification, and focus. By leveraging these insights, we are paving the way for more robust and accurate metric depth models in future works.
고장력 소재로 롤-포밍 공법에 의한 자동차 도어 사이드 임팩트 빔 개발
손희진(Hee-Jin Son),김성육(Sung-Yuk Kim),오범석(Beom-Seok Oh),김기선(Key-Sun Kim) 한국기계가공학회 2012 한국기계가공학회지 Vol.11 No.6
The purpose of this study is to produce a side impact beam with high tensile steel using a roll forming process. The door side impact beam plays an important roll in a car because it protects passengers from external crash. The roll forming process is a continuous bending process wherein a long metal sheet is bended as it continuously passes several rolls. The characteristic of this study is that an impact beam is produced by a continuous process using a ultra high strength steel without a hardening heat treatment. A model was determined by analysing plasticity of a cross section shape considering high strength. Design parameters of the impact beam was determined by crash-analysing the model. Workpiece products were manufactured by designing dies for roll forming and setting them up in a following process line. Results of a bending test and a FEM analysis was considered and reviewed.
모바일 기기에서의 Fine-grained classification을 위한 SR-GNN 모델의 경량화
정민기(Minki Jeong),이예랑(Yerang Lee),한대일(Daeil Han),오범석(Beom-Seok Oh) 대한전자공학회 2024 대한전자공학회 학술대회 Vol.2024 No.6
Fine-grained classification task, which is different from the general classification task, is classifying more detailed class. Common fine-grained classification methods extract detailed features and find the relation between features. Extracting features and finding the relation between them, need more computation cost so it is hard to have high performance on mobile devices. So, we propose a lightweight module that can also have high performance on mobile devices. We reduce the parameters of Spatial Relation-aware Graph Neural Network(SR-GNN) by suggesting overlapped ROI extracting method of fixed size.
객체 분할을 위한 가변 거리 기반의 3D LiDAR 포인트 클라우드 그룹핑
허세빈(Sebin Heo),이예랑(Yerang Lee),김가은(Gaeun Kim),김정연(Jungyeon Kim),오범석(Beom-Seok Oh) 대한전자공학회 2023 대한전자공학회 학술대회 Vol.2023 No.6
In this work, an intuitive yet effective points grouping method is proposed for 3D LiDAR objects segmentation. Particularly, the proposed method consists of two main steps: i) the preprocessing step, in which noise points such as ground clusters are filtered out by the proposed cone-shape filtering, and ii) the grouping step, in which sets of 3D LiDAR points are defined as candidate object groups based on the proposed distance variation analysis technique. Our preliminary experimental study reveals that the proposed method can distinguish object groups effectively.