• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.215-217
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• 2005

There are two types of packet loss probabilities used in both the network layer and the physical layer within the wireless transmitter such as a queueing discard probability and transmission loss probability. We analyze these loss performances in order to guarantee Quality of Service (QoS) which is the basic of the future network. The queuing loss probability is caused by a maximum allowable delay time and the transmission loss probability is caused by a wireless channel error. These two types of packet loss probabilities are not easily analyzed due to recursive feedback which, originates as a result at a queueing delay and a number of retransmission attempts. We consider a wireless transmitter to a M/D/1 queueing model. We configurate the model to have a finite-size FIFO buffer in order to analyze the real-time traffic streams. Then we present the approaches used for evaluating the loss probabilities of this M/D/1/K queueing model. To analyze the two types of probabilities which have mutual feedbacks with each other, we drive the solutions recursively. The validity and accuracy of the analysis are confirmed by the computer simulation. From the following solutions, we suggest a minimum of 'a Maximum Allowable Delay Time' for real-time traffic in order to initially guarantee the QoS. Finally, we analyze the required service rate for each type utilizing real-time traffic and we apply our valuable analysis to a N-user's wireless network in order to get the fundamental information (types of supportable real-type traffics, types of supportable QoS, supportable maximum number of users) for network design.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.713-718
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• 2014

This paper proposed a real-time monitoring system that can realize effective operation of snowplows each of the local autonomous entities secures to cope with disasters in Korea like a wintertime heavy snowfall and also can promptly cope with the spot facing a heavy snowfall disaster by doing real-time monitoring on the information of the snow-removal site and the mobility of the vehicles. Also, the study has designed a relay terminal analysis tool so that the proposed system can analyze all kinds of controlling information and diagnose the relay terminal effectively. The proposed system can realize effective and emergent coping with the situations of a heavy snowfall disaster through real-time routing trace as well as effective work progress within a short time by doing real-time monitoring on the information about the status of snow-removal work and vehicle controlling for snow-removal work as well as the location information of snow-removal vehicles in the situations of a heavy snowfall.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.5
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• pp.11-24
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• 2011

A real-time hybrid test of a 3 story-3 bay reinforced concrete frame which is divided into numerical and physical substructure models under uniaxial earthquake excitation was run using a fixed iteration implicit HHT time integration method. The first story inner non-ductile column was selected as the physical substructure model, and uniaxial earthquake excitation was applied to the numerical model until the specimen failed due to severe damage. A finite-element analysis program, Mercury, was newly developed and optimized for a real-time hybrid test. The drift ratio based on the top horizontal displacement of the physical substructure model was compared with the result of a numerical simulation by OpenSees and the result of a shaking table test. The experiment in this paper is one of the most complex real-time hybrid tests, and the description of the hardware, algorithm and models is presented in detail. If there is an improvement in the numerical model, the evaluation of the tangent stiffness matrix of the physical substructure model in the finite element analysis program and better software to reduce the computational time of the element state determination for the force-based beam-column element, then the comparison with the results of the real-time hybrid test and the shaking table test deserves to make a recommendation. In addition, for the goal of a "Numerical simulation of the complex structures under dynamic loading", the real time hybrid test has enough merit as an alternative to dynamic experiments of large and complex structures.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.121-128
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• 2021

In order to design a real time big data collection and analysis system of manufacturing data in a smart factory, it is important to establish an appropriate wired/wireless communication system and protocol. This paper introduces the latest communication protocol, OPC-UA (Open Platform Communication Unified Architecture) based client/server function, applied user interface technology to configure a network for real-time data collection through IoT Integration. Then, Database is designed in MES (Manufacturing Execution System) based on the analysis table that reflects the user's requirements among the data extracted from the new cutting process automation process, bush inner diameter indentation measurement system and tool monitoring/inspection system. In summary, big data analysis system introduced in this paper performs SPC (statistical Process Control) analysis and visualization analysis with interface of OPC-UA-based wired/wireless communication. Through AI learning modeling with XGBoost (eXtream Gradient Boosting) and LR (Linear Regression) algorithm, quality and visualization analysis is carried out the storage and connection to the cloud.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.31-37
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• 2015

Data generated from sensors are exploding with recent development of IoT. This paradigm shift requires various industry fields that demand instant actions to analyze the arising data on a real-time basis, along with the real-time visualization analysis. As the existing visualization systems, however, perform visualization after storing data, the response time of the server cannot guarantee the ms-level processing that is close to real-time. They also have a problem of destroying data that can be major resources as they do not possess the process resources. Therefore, a smart gardening system that applies a real-time visualization algorithm using IoT sensing data under a gardening environment was designed and implement in this study. The response time of the server was measured to evaluate the performance of the suggested system. As a result, the response speed of the suggested real-time visualization algorithm was guaranteeing the ms-level processing close to real-time.

• Research in Plant Disease
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• v.14 no.3
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• pp.219-222
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• 2008

Real time PCR was used to discriminate Colletotrichum acutatum and C. gloeosporioides for analysis of population density. Two primers, caInt2 and cgint, used for conventional PCR to discriminate two species were modified with fluorescent dye to make probe for real time PCR. Fluorescence signals were successfully detected by fCaInt2 and vCgint probe coupled with primer pair Unicon and Unicor1 resulting in discrimination of C. acutatum and C. gloeosporioides by comparison of delta Rn value.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.507-519
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• 2000

n this paper, we implement the real-time scheduler which performs extended schedulability testing, to reconfigure Mach kernel in which Real-Time scheduling is possible. for this purpose, first, we propose the configuration factors according to requirements of Real-Time operation systems and we analyze a Real-time scheduling algorithm. Second, for the reconfiguration of Mach kernel, we propose the modified data structure through the analysis of Mach kernel environments and scheduling. Third, we suggest the extended scheduling method by analyzing conventional Real-Time scheduling policies. Fourth, we implement the scheduler which executes tasks according to the Earliest-Deadline-First scheduling and the Rate Monotonic scheduling.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.3
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• pp.209-219
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• 1996

Fieldbus provides a real-time data communication among field devices in the process control and manufacturing automation systems. In this paper, a Petri Net model of the 1993 draft of IEC/ISA fieldbus which is proposed as an international standard of fieldbus network is developed. Based on the Petri Net model, discrete-event simulation model of IEC/ISA fieldbus network is developed. This paper evaluates the network induced delay in the data link layer of IEC/ISA fieldbus using the simulation model. In addition, an integrated discrete-event/continuous-time simulation model of fieldbus system and distributed control system is developed. This paper investigates the real-time data processing capability of IEC/ISA fieldbus and the effect of network-induced delay to the performance of control system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.6
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• pp.228-234
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• 2002

This paper proposes a real-time application of rationalized Haar transform which is based on the local rationalized Haar transform, local operational matrix and local delay operational matrix. This approach let a general sampling time be used by introducing a scaling factor. In the existing method of orthogonal functions, a major disadvantage is that process signals need to be recorded prior to obtaining their expansions. This paper proposes a novel method of rationalized Haar transform to overcome this shortcoming. And the proposed method is suitable for the analysis of linear systems. The proposed method is expected to the applicable to the adaptive control which demanded to the real-time applications.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.3 s.96
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• pp.215-221
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• 1999

The object of the thermal error compensation system in machine tools is improving the accuracy of a machine tool through real time error compensation. The accuracy of the machine tool totally depends on the accuracy of thermal error model. A thermal error model can be obtained by appropriate combination of temperature variables. The proposed method for optimal variable selection in the thermal error model is based on correlation grouping and successive regression analysis. Collinearity matter is improved with the correlation grouping and the judgment function which minimizes residual mean square is used. The linear model is more robust against measurement noises than an engineering judgement model that includes the higher order terms of variables. The proposed method is more effective for the applications in real time error compensation because of the reduction in computational time, sufficient model accuracy, and the robustness.