• Title/Summary/Keyword: edge memory

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A Study on the Implementation of Edge-Following Insertion and grinding Tasks Using Robot Force Control (로보트의 힘제어를 이용한 윤곽 추적, 삽입 및 그라인딩 작업의 구현에 관한 연구)

  • 정재욱;이범희;고명삼
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.40 no.2
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    • pp.207-216
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    • 1991
  • In the case that the robot manipulator should respond to the variance and uncertainty of the environment in performing preforming precision tasks, it is indispensable that the robot utilizes the various sensors for intrlligence. In this paper, the robot force control method is implemented with a force/torque sensor, two personal computers, and a PUMA 560 manipulator for performing the various application tadks. The hybrid position/force control method is used to control the force and position axis separately. An interface board is designed to read the force/torque sensor output into the computer. Since the two computers should exchange the information quickly, a common memory board is designed. Before the algorithms of application tasks are developed, the basic force commands must be supplied. Thus, the MOVE-UNTIL command is used at the discrete time instant and, the MOVE-COMPLY is used at the continuous time instant for receiving the force feedback information. Using the two basic force commands, three application algorithms are developed and implemented for edge-following, insertion, and grinding tasks.

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Unstructured Pressure Based Method for All Speed Flows (전 속도영역 유동을 위한 비정렬격자 압력기반해법)

  • Choi, Hyung-Il;Lee, Do-Hyung;Maeng, Joo-Sung
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.26 no.11
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    • pp.1521-1530
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    • 2002
  • This article proposes a pressure based method for predicting flows at all speeds. The compressible SIMPLE algorithm is extended to unstructured grid framework. Convection terms are discretized using second-order scheme with deferred correction approach. Diffusion term discretization is based on structured grid analogy that can be easily adopted to hybrid unstructured grid solver. This method also uses node centered scheme with edge based data structure for memory and computing time efficiency of arbitrary grid types. Both incompressible and compressible benchmark problems are solved using the above methodology. The demonstration of this method is extended to slip flow problem that has low Reynolds number but compressibility effect. It is shown that the proposed method can improve efficiency in memory usage and computing time without losing any accuracy.

A Study of Micro Electrolytic-deburring for Nitinol (Nitinol 소재의 미세 전해디버링에 관한 연구)

  • Kim W.M.;Sin M.J.;Lee E.S.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2006.05a
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    • pp.229-230
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    • 2006
  • Shape memory alloy, Nitinol is used for medical stent, artificial human joint, antenna of artificial satellite, fire door, temperature sensor...etc. It is important for some nitinol product high precision and clean surface. In this study, we experiment about deburring of edge and surface of nitinol work piece with micro electrolytic-deburring. We made an observation in case electric currents are $1A{\sim}4A$, above 5A and each machining times.

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The Sequential GHT for the Efficient Pattern Recognition (효율적 패턴 인식을 위한 순차적 GHT)

  • 김수환;임승민;이규태;이태원
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.28B no.5
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    • pp.327-334
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    • 1991
  • This paper proposes an efficient method of implementing the generalized Hough transform (GHT), which has been hindered by an excessive computing load and a large memory requirement. The conventional algorithm requires a parameter space of 4 dimensions in detection a rotated, scaled, and translated object in an input image. Prior to the application of GHT to the input image, the proposed method determines the angle of rotation and the scaling factor of the test image using the proportion of the edge components between the reference image and test image. With the rotation angle and the scaling factor already determined, the parameter spaceis to be reduced to a simple array of 2 dimensions by applying the unit GHT only one time. The experiments with the image of airplanes reveal that both of the computing time and the requires memory size are reduced by 95 percent, without any degradatationof accuracy, compared with the conventional GHT algorithm.

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Development of a Detect-and-Acquisition System for Broadband Lightning Signals (광대역 낙뢰신호 탐지 및 획득 시스템 개발)

  • Song, Seung-Hun;Kim, Dong-Hyouc;Lee, Sung-Ho;Woo, Jung-Wook;Sung, Tae-Kyung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.8
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    • pp.1503-1510
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    • 2007
  • To implement a high-precision lightning tracking system utilizing TDOA measurements, high-speed data acquisition and precise timing synchronization between ground sensors should be achieved. At the same time, considering the size of digitizer's memory, the data memory needs to be managed so that only the sampled data around the occurrence of stepped leader pulse is stored. This paper presents a detection-and-acquisition system for lightning signals that is the main equipment of ground sensor in lightning tracking system. GPS clock module is used to get precise timing synchronization and the 500MHz high speed digitizer is employed. In order to detect the leading edge of the lightning pulse and save the sampled data and its timing, lightning detection module is implemented and multi-record method is employed in the proposed system. Field experiment results show that the proposed system can detect and save the lightning signal efficiently.

Optimal Moving Pattern Extraction of the Moving Object for Efficient Resource Allocation (효율적 자원 배치를 위한 이동객체의 최적 이동패턴 추출)

  • Cho, Ho-Seong;Nam, Kwang-Woo;Jang, Min-Seok;Lee, Yon-Sik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.689-692
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    • 2021
  • This paper is a prior study to improve the efficiency of offloading based on mobile agents to optimize allocation of computing resources and reduce latency that support user proximity of application services in a Fog/Edge Computing (FEC) environment. We propose an algorithm that effectively reduces the execution time and the amount of memory required when extracting optimal moving patterns from the vast set of spatio-temporal movement history data of moving objects. The proposed algorithm can be useful for the distribution and deployment of computing resources for computation offloading in future FEC environments through frequency-based optimal path extraction.

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Microstructural Observation of Phase Change Optical Disk by TEM (투과전자현미경을 이용한 상전이형 광디스크의 미세조직 관찰)

  • Kim, Soo-Chul;Kim, Gyeung-Ho
    • Applied Microscopy
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    • v.29 no.4
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    • pp.493-498
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    • 1999
  • With increasing demand for fast and reliable, yet economical data storage devices, the role of optical disk technology is becoming more important. In recent years, advanced laser technology combined with new materials has given the competitive edge over the traditional magnetic memory devices both in memory capacity and reliability of data retrieval. Continuing effort is being put into developing smaller and more complex structures for optical disks to increase their memory density. Characterization of such multilayered structure requires not only high spatial resolution for observation but also laborious specimen preparation. In this paper, the method of preparing optical disk specimens for TEM characterization is described in detail. The microstructural features in optical disks observed by TEM are also discussed.

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Companies Entering the Metabus Industry - Major Big Data Protection with Remote-based Hard Disk Memory Analysis Audit (AUDIT) System

  • Kang, Yoo seok;Kim, Soo dong;Seok, Hyeonseon;Lee, Jae cheol;Kwon, Tae young;Bae, Sang hyun;Yoon, Seong do;Jeong, Hyung won
    • Journal of Integrative Natural Science
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    • v.14 no.4
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    • pp.189-196
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    • 2021
  • Recently, as a countermeasure for cyber breach attacks and confidential leak incidents on PC hard disk memory storage data of the metaverse industry, it is required when reviewing and developing a remote-based regular/real-time monitoring and analysis security system. The reason for this is that more than 90% of information security leaks occur on edge-end PCs, and tangible and intangible damage, such as an average of 1.20 billion won per metaverse industrial security secret leak (the most important facts and numerical statistics related to 2018 security, 10.2018. the same time as responding to the root of the occurrence of IT WORLD on the 16th, as it becomes the target of malicious code attacks that occur in areas such as the network system web due to interworking integration when building IT infrastructure, Deep-Access-based regular/real-time remote. The concept of memory analysis and audit system is key.

Evaluation of Storage Engine on Edge-Based Lightweight Platform using Sensor·OPC-UA Simulator (센서·OPC-UA 시뮬레이션을 통한 엣지 기반 경량화 플랫폼 스토리지 엔진 평가)

  • Woojin Cho;Chea-eun Yeo;Jae-Hoi Gu;Chae-Young Lim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.803-809
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    • 2023
  • This paper analyzes and evaluates to optimally build a data collection system essential for factory energy management systems on an edge-based lightweight platform. A "Sensor/OPC-UA simulator" was developed based on sensors in an actual food factory and used to evaluate the storage engine of edge devices. The performance of storage engines in edge devices was evaluated to suggest the optimal storage engine. The experimental results show that when using the RocksDB storage engine, it has less than half the memory and database size compared to using InnoDB, and has a 3.01 times faster processing time. This study enables the selection of advantageous storage engines for managing time-series data on devices with limited resources and contributes to further research in this field through the sensor/OPC simulator.

Analysis on Lightweight Methods of On-Device AI Vision Model for Intelligent Edge Computing Devices (지능형 엣지 컴퓨팅 기기를 위한 온디바이스 AI 비전 모델의 경량화 방식 분석)

  • Hye-Hyeon Ju;Namhi Kang
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.24 no.1
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    • pp.1-8
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    • 2024
  • On-device AI technology, which can operate AI models at the edge devices to support real-time processing and privacy enhancement, is attracting attention. As intelligent IoT is applied to various industries, services utilizing the on-device AI technology are increasing significantly. However, general deep learning models require a lot of computational resources for inference and learning. Therefore, various lightweighting methods such as quantization and pruning have been suggested to operate deep learning models in embedded edge devices. Among the lightweighting methods, we analyze how to lightweight and apply deep learning models to edge computing devices, focusing on pruning technology in this paper. In particular, we utilize dynamic and static pruning techniques to evaluate the inference speed, accuracy, and memory usage of a lightweight AI vision model. The content analyzed in this paper can be used for intelligent video control systems or video security systems in autonomous vehicles, where real-time processing are highly required. In addition, it is expected that the content can be used more effectively in various IoT services and industries.