• Title/Summary/Keyword: Physical Machine

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A Study on the Fault Diagnosis in Web-based Virtual Machine (웹기반 가상시계에서의 고장진단에 관한 연구)

  • 서정완;강무진
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2001.04a
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    • pp.430-434
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    • 2001
  • Virtual manufacturing system is integrated computer model that represents the precise and whole structure of manufacturing system and simulates its physical and logical behavior in operation.[1] A virtual machine is computer model that represents a CNC machine tool and one of core elements of virtual manufacturing system. In this paper, it is emphasized that a virtual machine must be web-based system for serving information to all attendants in a real machine tool without the restriction of time or location, and then in the fault diagnosis, one of important modules of a virtual machine, the methods of both using the controller signal and web-based expert system are proposed.

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Motion Recognition for Kinect Sensor Data Using Machine Learning Algorithm with PNF Patterns of Upper Extremities

  • Kim, Sangbin;Kim, Giwon;Kim, Junesun
    • The Journal of Korean Physical Therapy
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    • v.27 no.4
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    • pp.214-220
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    • 2015
  • Purpose: The purpose of this study was to investigate the availability of software for rehabilitation with the Kinect sensor by presenting an efficient algorithm based on machine learning when classifying the motion data of the PNF pattern if the subjects were wearing a patient gown. Methods: The motion data of the PNF pattern for upper extremities were collected by Kinect sensor. The data were obtained from 8 normal university students without the limitation of upper extremities. The subjects, wearing a T-shirt, performed the PNF patterns, D1 and D2 flexion, extensions, 30 times; the same protocol was repeated while wearing a patient gown to compare the classification performance of algorithms. For comparison of performance, we chose four algorithms, Naive Bayes Classifier, C4.5, Multilayer Perceptron, and Hidden Markov Model. The motion data for wearing a T-shirt were used for the training set, and 10 fold cross-validation test was performed. The motion data for wearing a gown were used for the test set. Results: The results showed that all of the algorithms performed well with 10 fold cross-validation test. However, when classifying the data with a hospital gown, Hidden Markov model (HMM) was the best algorithm for classifying the motion of PNF. Conclusion: We showed that HMM is the most efficient algorithm that could handle the sequence data related to time. Thus, we suggested that the algorithm which considered the sequence of motion, such as HMM, would be selected when developing software for rehabilitation which required determining the correctness of the motion.

A Study on the Virtual Switch Implementation and Comparison for Smart Node Platform (가상 스위치 구현 및 비교에 관한 연구)

  • Jeong, Gab Joong;Choi, Kang-Il
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.12
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    • pp.2911-2918
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    • 2014
  • Nowadays, most Internet servers run on virtual a network which connects each virtual machine, to process large amounts of data on single physical computer. The virtual machines for their own purposes are interconnected to other virtual server systems with various types of operating systems. Each virtual server may share one physical computer resources and operates at a service seamlessly to each other. Sometimes even the virtual machines are implemented using a method that lease the physical IT resources without purchasing physical server. Therefore, a virtual switch is needed to improve the performance when a large number of virtual machines operate on physical server. In this study, the implementation and investigation was performed for the virtual switches, OpenvSwitch and DPDKvSwitch, in order to provide the necessary high-performance cloud services to creative business.

Effect of False Twist Processing Conditions on the Physical Properties of PET DTY (PET 가연공정특성이 DTY의 물성에 미치는 영향)

  • 이민수;김승진;박경순
    • Textile Coloration and Finishing
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    • v.15 no.6
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    • pp.33-38
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    • 2003
  • This study surveys the effects of POY physical properties and processing conditions of belt texturing machine to the textured yarns. The various textured yarns are made with the variations of 1st heater temperature, draw ratio, velocity ratio, and the physical properties of these specimens such as yam linear density, tenacity, breaking strain, and wet and dry thermal shrinkages are measured and analysed with the various processing conditions of texturing machine. Especially, the thermal characteristics of the textured yarns, which are affected at the fabric hands and the determination of the processing conditions in the dyeing and finishing processes, are investigated through the thermal stress analyser and DSC experiments.

Physical-Layer Technology Trend and Prospect for AI-based Mobile Communication (AI 기반 이동통신 물리계층 기술 동향과 전망)

  • Chang, K.;Ko, Y.J.;Kim, I.G.
    • Electronics and Telecommunications Trends
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    • v.35 no.5
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    • pp.14-29
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    • 2020
  • The 6G mobile communication system will become a backbone infrastructure around 2030 for the future digital world by providing distinctive services such as five-sense holograms, ultra-high reliability/low-latency, ultra-high-precision positioning, ultra-massive connectivity, and gigabit-per-second data rate for aerial and maritime terminals. The recent remarkable advances in machine learning (ML) technology have recognized its efficiency in wireless networking fields such as resource management and cell-configuration optimization. Further innovation in ML is expected to play an important role in solving new problems arising from 6G network management and service delivery. In contrast, an approach to apply ML to a physical-layer (PHY) target tackles the basic problems in radio links, such as overcoming signal distortion and interference. This paper reviews the methodologies of ML-based PHY, relevant industrial trends, and candiate technologies, including future research directions and standardization impacts.

A Study on the On-the-Machine Measuring using a laser displacement sensor (레이저 변위 센서를 이용한 기상측정에 관한 연구)

  • 권세진;이정근;박정환;고태조;김선호
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.10a
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    • pp.371-374
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    • 2002
  • From reverse-engineering's point of view, the main step is the digitizing or gathering three-dimensional points on the target physical model. As well known, the touch or scanning probe gives higher accuracy, while the non-contact digitizing apparatus by use of laser or structured light can rapidly obtain digitized points of great bulk without contacting onto the part surface of the physical model. We propose a digitizing methodology by use of the LK-031 laser displacement sensor, which was tested with a physical model.

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Production Equipment Monitoring System Based on Cloud Computing for Machine Manufacturing Tools

  • Kim, Sungun;Yu, Heung-Sik
    • Journal of Korea Multimedia Society
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    • v.25 no.2
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    • pp.197-205
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    • 2022
  • The Cyber Physical System(CPS) is an important concept in achieving SMSs(Smart Manufacturing Systems). Generally, CPS consists of physical and virtual elements. The former involves manufacturing devices in the field space, whereas the latter includes the technologies such as network, data collection and analysis, security, and monitoring and control technologies in the cyber space. Currently, all these elements are being integrated for achieving SMSs in which we can control and analyze various kinds of producing and diagnostic issues in the cyber space without the need for human intervention. In this study, we focus on implementing a production equipment monitoring system related to building a SMS. First, we describe the development of a fog-based gateway system that links physical manufacturing devices with virtual elements. This system also interacts with the cloud server in a multimedia network environment. Second, we explain the proposed network infrastructure to implement a monitoring system operating on a cloud server. Then, we discuss our monitoring applications, and explain the experience of how to apply the ML(Machine Learning) method for predictive diagnostics.

Transient Characteristics and Physical Constraints of Grid-Tied Virtual Synchronous Machines

  • Yuan, Chang;Liu, Chang;Yang, Dan;Zhou, Ruibing;Tang, Niang
    • Journal of Power Electronics
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    • v.18 no.4
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    • pp.1111-1126
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    • 2018
  • In modern power systems, distributed generators (DGs) result in high stress on system frequency stability. Apart from the intermittent nature of DGs, most DGs do not contribute inertia or damping to systems. As a result, a new control method referred to as a virtual synchronous machine (VSM) has been proposed, which brought new characteristics to inverters such as synchronous machines (SM). DGs employing an energy storage system (ESS) provide inertia and damping through VSM control. Meanwhile, energy storage presents some physical constraints in the VSM implementation level. In this paper, a VSM mathematical model is built and analyzed. The dynamic responses of the output active power are presented when a step change in the frequency occurs. The influences of the inertia constant, damping factor and operating point on the ESS volume margins are investigated. In addition, physical constraints are proposed based on these analyses. The proposed physical constraints are simulated using PSCAD/EMTDC software and tested through RTDS experiment. Both simulation and RTDS test results verify the analysis.

On the Application of Channel Characteristic-Based Physical Layer Authentication in Industrial Wireless Networks

  • Wang, Qiuhua;Kang, Mingyang;Yuan, Lifeng;Wang, Yunlu;Miao, Gongxun;Choo, Kim-Kwang Raymond
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.6
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    • pp.2255-2281
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    • 2021
  • Channel characteristic-based physical layer authentication is one potential identity authentication scheme in wireless communication, such as used in a fog computing environment. While existing channel characteristic-based physical layer authentication schemes may be efficient when deployed in the conventional wireless network environment, they may be less efficient and practical for the industrial wireless communication environment due to the varying requirements. We observe that this is a topic that is understudied, and therefore in this paper, we review the constructions and performance of several commonly used test statistics and analyze their performance in typical industrial wireless networks using simulation experiments. The findings from the simulations show a number of limitations in existing channel characteristic-based physical layer authentication schemes. Therefore, we believe that it is a good idea to combine machine learning and multiple test statistics for identity authentication in future industrial wireless network deployment. Four machine learning methods prove that the scheme significantly improves the authentication accuracy and solves the challenge of choosing a threshold.

A Study on the Generation of B-Spline Surface by 3D Measurement Data (3차원 측정 데이터의 B-스플라인 곡면식 적영에 대한 연구)

  • 구영희
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1998.03a
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    • pp.76-81
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    • 1998
  • The purpose of this study is the generation of B-spline surface by the 3D measurement data. The hardware of the system comprises PC and digitizing machine, machining center. There are three steps, (1) physical model measuring on the 3D laser digitizing machine, (2) B-spline surface modeling and Fairing, (3) CNC machining by the NC code. It is developed a software package, with which can conduct a micro CAM system in the PC without economical burden.

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