• Title/Summary/Keyword: 로봇 보안

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A Study on Issues and Tasks of Humanity and Social Science in a Fourth Industrial Revolution Era (제4차 산업혁명시대 인문사회학적 쟁점과 과제에 관한 연구)

  • Kim, Jin-Young;Heo, Wan-Gyu
    • Journal of Digital Convergence
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    • v.16 no.11
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    • pp.137-147
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    • 2018
  • To prepare for and implement policies for the Fourth Industrial Revolution, which is characterized by convergence, super-connectivity, and AI, this study summarized the effects and characteristics of individual technologies on our society and discussed the issues with humanity and social science perspectives. As a result, in terms of AI technology, the issues of job losses, project-type works, basic income and robot taxes, accountability of AI, and algorithm inequality were dealt with. Security, cyber hacking and privacy infringement issues were highlighted in big-data technology. In the part of block-chain and bioengineering, the society of decentralization, the concentration, digital divide, and ethical issues were discussed. On-demand economic aspects highlighted the problems of civil ethics and human commercialization. Lastly, the development of VR is discussed including side effects such as cyber-syndrom, avoidance of reality, and so on.

Hardware Implementation of the Fuzzy Fingerprint Vault System (지문 퍼지볼트 시스템의 하드웨어 구현)

  • Lim, Sung-Jin;Chae, Seung-Hoon;Pan, Sung-Bum
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.20 no.2
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    • pp.15-21
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    • 2010
  • The user authentication using fingerprint information not only provides the convenience but also high security. However, the fingerprint information for user authentication can cause serious problems when it has been compromised. It cannot change like passwords, because the user only has ten fingers on two hands. Recently, there is an increasing research of the fuzzy fingerprint vault system to protect fingerprint information. The research on the problem of fingerprint alignment using geometric hashing technique carried out. This paper proposes the hardware architecture fuzzy fingerprint vault system based on geometric hashing. The proposed architecture consists of software and hardware module. The hardware module has charge of matching between enrollment hash table and verification hash table. Based on the experimental results, the execution time of the proposed system with 36 real minutiae is 0.2 second when 100 chaff minutiae, 0.53 second when 400 chaff minutiae.

Blockchain and AI-based big data processing techniques for sustainable agricultural environments (지속가능한 농업 환경을 위한 블록체인과 AI 기반 빅 데이터 처리 기법)

  • Yoon-Su Jeong
    • Advanced Industrial SCIence
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    • v.3 no.2
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    • pp.17-22
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    • 2024
  • Recently, as the ICT field has been used in various environments, it has become possible to analyze pests by crops, use robots when harvesting crops, and predict by big data by utilizing ICT technologies in a sustainable agricultural environment. However, in a sustainable agricultural environment, efforts to solve resource depletion, agricultural population decline, poverty increase, and environmental destruction are constantly being demanded. This paper proposes an artificial intelligence-based big data processing analysis method to reduce the production cost and increase the efficiency of crops based on a sustainable agricultural environment. The proposed technique strengthens the security and reliability of data by processing big data of crops combined with AI, and enables better decision-making and business value extraction. It can lead to innovative changes in various industries and fields and promote the development of data-oriented business models. During the experiment, the proposed technique gave an accurate answer to only a small amount of data, and at a farm site where it is difficult to tag the correct answer one by one, the performance similar to that of learning with a large amount of correct answer data (with an error rate within 0.05) was found.

Research on Object Detection Library Utilizing Spatial Mapping Function Between Stream Data In 3D Data-Based Area (3D 데이터 기반 영역의 stream data간 공간 mapping 기능 활용 객체 검출 라이브러리에 대한 연구)

  • Gyeong-Hyu Seok;So-Haeng Lee
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.3
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    • pp.551-562
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    • 2024
  • This study relates to a method and device for extracting and tracking moving objects. In particular, objects are extracted using different images between adjacent images, and the location information of the extracted object is continuously transmitted to provide accurate location information of at least one moving object. It relates to a method and device for extracting and tracking moving objects based on tracking moving objects. People tracking, which started as an expression of the interaction between people and computers, is used in many application fields such as robot learning, object counting, and surveillance systems. In particular, in the field of security systems, cameras are used to recognize and track people to automatically detect illegal activities. The importance of developing a surveillance system, that can detect, is increasing day by day.

Multi-classifier Decision-level Fusion for Face Recognition (다중 분류기의 판정단계 융합에 의한 얼굴인식)

  • Yeom, Seok-Won
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.4
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    • pp.77-84
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    • 2012
  • Face classification has wide applications in intelligent video surveillance, content retrieval, robot vision, and human-machine interface. Pose and expression changes, and arbitrary illumination are typical problems for face recognition. When the face is captured at a distance, the image quality is often degraded by blurring and noise corruption. This paper investigates the efficacy of multi-classifier decision level fusion for face classification based on the photon-counting linear discriminant analysis with two different cost functions: Euclidean distance and negative normalized correlation. Decision level fusion comprises three stages: cost normalization, cost validation, and fusion rules. First, the costs are normalized into the uniform range and then, candidate costs are selected during validation. Three fusion rules are employed: minimum, average, and majority-voting rules. In the experiments, unfocusing and motion blurs are rendered to simulate the effects of the long distance environments. It will be shown that the decision-level fusion scheme provides better results than the single classifier.

Design of an Integrated University Information Service Model Based on Block Chain (블록체인 기반의 대학 통합 정보서비스 실증 모델 설계)

  • Moon, Sang Guk;Kim, Min Sun;Kim, Hyun Joo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.2
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    • pp.43-50
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    • 2019
  • Block-chain enjoys technical advantages such as "robust security," owing to the structural characteristic that forgery is impossible, decentralization through sharing the ledger between participants, and the hyper-connectivity connecting Internet of Things, robots, and Artificial Intelligence. As a result, public organizations have highly positive attitudes toward the adoption of technology using block-chain, and the design of university information services is no exception. Universities are also considering the application of block-chain technology to foundations that implement various information services within a university. Through case studies of block-chain applications across various industries, this study designs an empirical model of an integrated information service platform that integrates information systems in a university. A basic road map of university information services is constructed based on block-chain technology, from planning to the actual service design stage. Furthermore, an actual empirical model of an integrated information service in a university is designed based on block-chain by applying this framework.

Object Detection Based on Hellinger Distance IoU and Objectron Application (Hellinger 거리 IoU와 Objectron 적용을 기반으로 하는 객체 감지)

  • Kim, Yong-Gil;Moon, Kyung-Il
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.2
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    • pp.63-70
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    • 2022
  • Although 2D Object detection has been largely improved in the past years with the advance of deep learning methods and the use of large labeled image datasets, 3D object detection from 2D imagery is a challenging problem in a variety of applications such as robotics, due to the lack of data and diversity of appearances and shapes of objects within a category. Google has just announced the launch of Objectron that has a novel data pipeline using mobile augmented reality session data. However, it also is corresponding to 2D-driven 3D object detection technique. This study explores more mature 2D object detection method, and applies its 2D projection to Objectron 3D lifting system. Most object detection methods use bounding boxes to encode and represent the object shape and location. In this work, we explore a stochastic representation of object regions using Gaussian distributions. We also present a similarity measure for the Gaussian distributions based on the Hellinger Distance, which can be viewed as a stochastic Intersection-over-Union. Our experimental results show that the proposed Gaussian representations are closer to annotated segmentation masks in available datasets. Thus, less accuracy problem that is one of several limitations of Objectron can be relaxed.

Multiple SL-AVS(Small size & Low power Around View System) Synchronization Maintenance Method (다중 SL-AVS 동기화 유지기법)

  • Park, Hyun-Moon;Park, Soo-Huyn;Seo, Hae-Moon;Park, Woo-Chool
    • Journal of the Korea Society for Simulation
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    • v.18 no.3
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    • pp.73-82
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    • 2009
  • Due to the many advantages including low price, low power consumption, and miniaturization, the CMOS camera has been utilized in many applications, including mobile phones, the automotive industry, medical sciences and sensoring, robotic controls, and research in the security field. In particular, the 360 degree omni-directional camera when utilized in multi-camera applications has displayed issues of software nature, interface communication management, delays, and a complicated image display control. Other issues include energy management problems, and miniaturization of a multi-camera in the hardware field. Traditional CMOS camera systems are comprised of an embedded system that consists of a high-performance MCU enabling a camera to send and receive images and a multi-layer system similar to an individual control system that consists of the camera's high performance Micro Controller Unit. We proposed the SL-AVS (Small Size/Low power Around-View System) to be able to control a camera while collecting image data using a high speed synchronization technique on the foundation of a single layer low performance MCU. It is an initial model of the omni-directional camera that takes images from a 360 view drawing from several CMOS camera utilizing a 110 degree view. We then connected a single MCU with four low-power CMOS cameras and implemented controls that include synchronization, controlling, and transmit/receive functions of individual camera compared with the traditional system. The synchronization of the respective cameras were controlled and then memorized by handling each interrupt through the MCU. We were able to improve the efficiency of data transmission that minimizes re-synchronization amongst a target, the CMOS camera, and the MCU. Further, depending on the choice of users, respective or groups of images divided into 4 domains were then provided with a target. We finally analyzed and compared the performance of the developed camera system including the synchronization and time of data transfer and image data loss, etc.