• Title/Summary/Keyword: 산업로봇

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국내 우수 연구자의 글로벌 공동연구 활동도 분석 연구 : 신산업 분야를 중심으로

  • Yu, Hwa-Seon;Kim, Yun-Myeong;Yang, Chi-Seung
    • Proceedings of the Korea Technology Innovation Society Conference
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    • 2017.11a
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    • pp.1167-1188
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    • 2017
  • 최근 4차 산업혁명 등 대외적 R&D 환경의 급속한 변화와 이로 인한 과학기술의 융 복합 및 첨단화가 가속화됨에 따라 이에 대응하기 위해 신산업분야를 중심으로 국가 간 공동협력이 점차 활발해짐에도 불구하고, 우리나라는 연구개발 주체의 연구역량 열위, 연구주체의 폐쇄성, 국가 R&D 제도적 미흡 등으로 인해 국가 간 공동연구 활동도가 매우 미흡한 편이다. 2016년 국가과학 기술혁신역량평가 국제협력 항목에서도 우리나라의 국제협력 항목지수는 0.206으로 2015년(0.182) 대비 0.024p 상승하였으나, 여전히 OECD 30개국 중 16위에 머무르는 것으로 나타났으며, 국제협력 상위 3개국에 대한 상대수준에서도 평균 10.3% 수준에 불과하여 국제 공동연구 활동도를 높이기 위한 다각적인 개선방안 확립에 대한 요구가 점차 증대되고 있는 실정이다. 이에 본 연구에서는 2015년 연구에 이어 미래 신산업 분야에서 우리나라와 해외 주요국의 국제 공동연구 현황을 중심으로 핵심연구자 간(연구 활동도 상위 5위 이하) 국제공동연구에 대한 활동도 비교 분석을 통해 정확한 현황을 진단하고, 향후 우리나라 연구주체의 연구개발 개방화, 국제 협력 전략적 분야 및 대상 발굴, 국제공동연구 활성화 등에 대한 발전방안을 고찰하고자 하였다. 국내 및 글로벌 핵심 연구자 간 글로벌 공동연구 현황을 분석하기 위해서 KDD/KM 방법론을 활용한 공동연구자 분석(Co-author analysis)네트워크 기법을 활용하였으며, 동 방법론의 활용을 통해서 신산업 분야 중 가사로봇분야의 상위 10개 국가, 기관, 연구자에 대해 분석하고, 논문 활동도가 높은 글로벌 및 한국의 상위 5위까지의 핵심 연구자를 대상으로 연구자 간 국제공동연구에 대한 현황 및 활동도에 대한 공동연구 네트워크 분석을 수행하였다.

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Image Filter Optimization Method based on common sub-expression elimination for Low Power Image Feature Extraction Hardware Design (저전력 영상 특징 추출 하드웨어 설계를 위한 공통 부분식 제거 기법 기반 이미지 필터 하드웨어 최적화)

  • Kim, WooSuk;Lee, Juseong;An, Ho-Myoung;Kim, Byungcheul
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.10 no.2
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    • pp.192-197
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    • 2017
  • In this paper, image filter optimization method based on common sub-expression elimination is proposed for low-power image feature extraction hardware design. Low power and high performance object recognition hardware is essential for industrial robot which is used for factory automation. However, low area Gaussian gradient filter hardware design is required for object recognition hardware. For the hardware complexity reduction, we adopt the symmetric characteristic of the filter coefficients using the transposed form FIR filter hardware architecture. The proposed hardware architecture can be implemented without degradation of the edge detection data quality since the proposed hardware is implemented with original Gaussian gradient filtering algorithm. The expremental result shows the 50% of multiplier savings compared with previous work.

A Study on the Seam tracking for container box manufacture (컨테이너 제작을 위한 용접선 추적에 관한 연구)

  • Pyo, Jong-Woo;An, Byong-Won;Eom, Han-Sung;Nam, Taek-Kun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.195-199
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    • 2005
  • Semi automatic welding method to use carriage for welding at large size block manufacture welding process of present shipbuilding industry is used much. Carriage is device that transfer welding torch in horizontal fillet weld here, but because it is no function that chase welding like robot welding method, use can be impossible in curved line welding, and simply use in straight line welding. Also, because it is no function that chase welding, though welding mistake corrects this happening often in straight line welding, much times and expense are cost. Added welding chase sensor and 80C196KC microcontroller that use strain gauge to carriage that is using present in paper that see hereupon and manufacture a private line model and container box model welding because developing system that can chase welding automatically straight line and curved line welding establishing and investigate about chase phenomenon.

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Noise Removal using Canny Edge Detection in AWGN Environments (AWGN 환경에서 캐니 에지 검출을 이용한 잡음 제거)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.8
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    • pp.1540-1546
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    • 2017
  • Digital image processing is widely used in various fields including the military, medical, image recognition system, robot and commercial sectors. But in the process of acquiring and transmitting digital images, noise is generated by various external causes. There are various types of general noise depending on the cause and form, but AWGN and impulse noise is one of the leading methods. Removing noise during image processing is essential to the pre-treatment process such as segmentation, image recognition and characteristic extraction. As such, this paper suggests an algorithm that distinguishes the non-edge area and edge area using the Canny edge to apply different filters to different areas in order to effectively remove noise from the image. To verify the effectiveness of the suggested algorithm, it was compared against existing methods using zoom images, edge images and PSNR(peak signal to noise ratio).

A Study on Multi-Object Tracking Method using Color Clustering in ISpace (컬러 클러스터링 기법을 이용한 공간지능화의 다중이동물체 추척 기법)

  • Jin, Tae-Seok;Kim, Hyun-Deok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.11
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    • pp.2179-2184
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    • 2007
  • The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. This paper described appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

Comparison of Unplugged Activities at Home and Abroad using Semantic Network Analysis (시맨틱 네트워크 분석을 이용한 국내외 언플러그드 활동 관련 연구 비교)

  • Kang, Doo Bong
    • The Journal of Korean Association of Computer Education
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    • v.22 no.4
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    • pp.21-34
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    • 2019
  • SW education is being implemented in all the school due to the application of the 2015 Curriculum. The purpose of SW education is to improve Computational Thinking by using Unplugged Activities, Educational Programming Language, and Physical Computing. Among them, 73 domestic and 85 overseas researches related to 'Unplugged Activities' were compared and analyzed using semantic network analysis techniques. As a result, the research on 'Unplugged Activities' has been started from 1998, and the research has started in Korea since 2006. As the CT is recognized as a core competence for the future society in line with the 4th Industrial Revolution, researches have been rapidly increasing in both the domestic and overseas countries since 2016. In Korean studies, it was analyzed that many main words related to the elemental factors such as 'unplugged activity', 'robot utilization', 'educational programming language' were found. This suggests that future research should move toward research for the promotion of 'CT' which is the purpose of computer science.

A Review on Deep Learning Platform for Artificial Intelligence (인공지능 딥러링 학습 플랫폼에 관한 선행연구 고찰)

  • Jin, Chan-Yong;Shin, Seong-Yoon;Nam, Soo-Tai
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.169-170
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    • 2019
  • Lately, as artificial intelligence becomes a source of global competitiveness, the government is strategically fostering artificial intelligence that is the base technology of future new industries such as autonomous vehicles, drones, and robots. Domestic artificial intelligence research and services have been launched mainly in Naver and Kakao, but their size and level are weak compared to overseas. Recently, deep learning has been conducted in recent years while recording innovative performance in various pattern recognition fields including speech recognition and image recognition. In addition, deep running has attracted great interest from industry since its inception, and global information technology companies such as Google, Microsoft, and Samsung have successfully applied deep learning technology to commercial products and are continuing research and development. Therefore, we will look at artificial intelligence which is attracting attention based on previous research.

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Configuration Method of AWS Security Architecture for Cloud Service (클라우드 서비스 보안을 위한 AWS 보안 아키텍처 구성방안)

  • Park, Se-Joon;Lee, Yong-Joon;Park, Yeon-Chool
    • Journal of Convergence for Information Technology
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    • v.11 no.7
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    • pp.7-13
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    • 2021
  • Recently, due to the many features and advantages of cloud computing, cloud service is being introduced to countless industries around the world at an unbelievably rapid pace. With the rapid increase in the introduction of multi-cloud based services, security vulnerabilities are increasing, and the risk of data leakage from cloud computing services are also expected to increase. Therefore, this study will propose an AWS Well-Architected based security architecture configuration method such as AWS standard security architecture, AWS shared security architecture model that can be applied for personal information security including cost effective of cloud services for better security in AWS cloud service. The AWS security architecture proposed in this study are expected to help many businesses and institutions that are hoping to establish a safe and reliable AWS cloud system.

Analysis of the Valuation Model for the state-of-the-art ICT Technology (첨단 ICT 기술에 대한 가치평가 모델 분석)

  • Oh, Sun-Jin
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.4
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    • pp.705-710
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    • 2021
  • Nowadays, cutting-edge information communication technology is the genuine core technology of the fourth Industrial Revolution and is still making great progress rapidly among various technology fields. The biggest issue in ICT fields is the machine learning based Artificial Intelligence applications using big data in cloud computing environment on the basis of wireless network, and also the technology fields of autonomous control applications such as Autonomous Car or Mobile Robot. Since value of the high-tech ICT technology depends on the surrounded environmental factors and is very flexible, the precise technology valuation method is urgently needed in order to get successful technology transfer, transaction and commercialization. In this research, we analyze the characteristics of the high-tech ICT technology and the main factors in technology transfer or commercialization process, and propose the precise technology valuation method that reflects the characteristics of the ICT technology through phased analysis of the existing technology valuationmodel.

Weighted Filter Algorithm based on Distribution Pattern of Pixel Value for AWGN Removal (AWGN 제거를 위한 화소값 분포패턴에 기반한 가중치 필터 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.1
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    • pp.44-49
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    • 2022
  • Abstract Recently, with the development of IoT technology and communication media, various video equipment is being used in industrial fields. Image data acquired from cameras and sensors are easily affected by noise during transmission and reception, and noise removal is essential as it greatly affects system reliability. In this paper, we propose a weight filter algorithm based on the pixel value distribution pattern to preserve details in the process of restoring images damaged in AWGN. The proposed algorithm calculates weights according to the pixel value distribution pattern of the image and restores the image by applying a filtering mask. In order to analyze the noise removal performance of the proposed algorithm, it was simulated using enlarged image and PSNR compared to the existing method. The proposed algorithm preserves important characteristics of the image and shows the performance of efficiently removing noise compared to the existing method.