• Journal of Platform Technology
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• v.8 no.2
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• pp.22-31
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• 2020

The construction and operation of industrial automation has been actively taking place from manufacturing plan to production for improving operational efficiency of production line and flexibility of equipment. ISO/TC184 is standardizing on operating methods that can share information of programmable device controllers such as PLC and IoT that are geographically distributed in the production line. In this study, the design of the cell controller consists of PLC group and IoT group that perform signals such as temperature sensors, gas sensors, and pressure sensors for thermal processes and corresponding motors or valves. The operation and analysis of the cell controller were performed using SDN(Software Defined Network) and the three types of process services performed in thermal processes are real-time transmission service, loss-sensitive large-capacity transmission service, and normal transmission service. The simulation result showed that the average loss rate improved by about 17% when the traffic increased before and after the application of the SDN route technique, and the delay in the real-time service was as low as 1 ms.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.1
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• pp.1-6
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• 2021

Recently, unmanned facilities have been introduced and operated in a way that reduces the cost and development of IT technology. Although unmanned facilities have advantages in terms of efficiency and economy, they have disadvantages such as failure of unmanned facilities and malfunctions, causing damage to facilities caused by intruders, and information leakage. In addition, it is necessary to visit the person in charge at all times to inspect the unmanned facilities, resulting in management costs. In this paper, we designed a system that checks the status of unmanned surveillance facilities in real time to check and automatically recover problems such as malfunctions, and to notify managers of situations by text messages in real time. The system to be designed consists of an integrated network video server (NVR) that receives and determines information on the operation status of the main equipment such as video, sound, and lighting, and a real-time text message using an SMS server.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.309-314
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• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• Journal of Mechanical Science and Technology
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• v.15 no.4
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• pp.448-458
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• 2001

The primary goal of virtual prototyping is to eliminate the need for fabricating physical prototypes, and to reduce cost and time for developing new products. A virtual prototyping seeks to create a virtual environment where the development of a new model can be flexible as well as rapid, and experiments can be carried out effectively concerning kinematics, dynamics, and control aspects of the model. This paper addresses the virtual environment used for virtual prototyping of a passenger vehicle. It has been developed using the dVISE environment that provides such useful features as actions, events, sounds, and light features. A vehicle model including features, and behaviors is constructed by employing an object-oriented paradigm and contains detailed information about a real-size vehicle. The human model is also implemented not only for visual and reach evaluations of the developed vehicle model, but also for behavioral visualization during a crash test. For the real time driving simulation, a neural network model is incorporated into the virtual environment. The cases of passing bumps with a vehicle are discussed in order to demonstrate the applicability of a set of developed models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.473-494
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• 2020

To provide a guaranteed Quality of Service (QoS) to real-time traffic in High-Speed Downlink Packet Access (HSDPA) core network, we proposed an enhanced mechanism. For an enhanced QoS, a Class-Based Low Latency Fair Queueing (CBLLFQ) packet scheduling algorithm is introduced in this work. Packet classification, metering, queuing, and scheduling using differentiated services (DiffServ) environment was the points in focus. To classify different types of real-time voice and multimedia traffic, the QoS provisioning mechanisms use different DiffServ code points (DSCP).The proposed algorithm is based on traffic classes which efficiently require the guarantee of services and specified level of fairness. In CBLLFQ, a mapping criterion and an efficient queuing mechanism for voice, video and other traffic in separate queues are used. It is proved, that the algorithm enhances the throughput and fairness along with a reduction in the delay and packet loss factors for smooth and worst traffic conditions. The results calculated through simulation show that the proposed calculations meet the QoS prerequisites efficiently.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.387-392
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• 2002

This paper presents a new scheme of neural network controller to improve the robustuous of robot manipulator using digital signal processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. During past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Perforating of the proposed controller is illustrated. This paper describes a new approach to the design of adaptive controller and implementation of real-time control for assembling robotic manipulator using digital signal processor. Digital signal processors used in implementing real time adaptive control algorithm are TMS320C50 series made in TI'Co..

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.418-421
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• 2009

This paper presents a human-machine interaction based on a realtime upper limb motion prediction method using surface electromyography (sEMG). The motions were predicted using an artificial neural network algorithm and sEMG signals which are acquired from five muscles, and then a manipulator was controlled to follow after the predicted motions. Upper limb motions were restricted to 2D vertical plane with the contact condition between a user and an end-effector of manipulator. In order to demonstrate the feasibility of the proposed method, experiments using developed method and using a goniometer were performed. The results showed that the proposed real-time motion prediction method can be implemented a human-machine interaction system.

• KEPCO Journal on Electric Power and Energy
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• v.3 no.1
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• pp.17-21
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• 2017

Recently, the Korea Enhanced Power system Simulator (KEPS) was upgraded with new processor cards and various peripheral devices. The purpose of the upgrade is for the large-scale AC/DC simulation studies for different purposes such as FACTS, PMU applications, and SPS. The need for such study is now growing in KEPCO network. Frequently, traditional ways of performing the necessary study had been found to be less adequate for guiding the key decisions in the company. Therefore, the growing needs, as well as the revealed inadequacy of the traditional system studies, had been attributing to the momentum for the upgrade project. This paper explains the details of the upgrade project. As an example of presenting the effectiveness of the upgraded RTDS system in KEPRI-KEPCO, a large-scale AC/DC real time simulation case which includes the entire Korean network and a planned MMC-HVDC system is introduced.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2277-2287
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• 2015

In recent times, multilevel inverters are given high priority in many large industrial drive applications. However, the reliability of multilevel inverters are mainly affected by the failure of power electronic switches. In this paper, open-switch and short-switch failure of multilevel inverters and its identification using a high performance diagnostic system is discussed. Experimental and simulation studies were carried out on five level cascaded H-Bridge multilevel inverter and its output voltage waveforms were analyzed at different switch fault cases and at different modulation index values. Salient frequency domain features of the output voltage signal were extracted using the discrete wavelet transform multi resolution signal decomposition technique. Real time application of the proposed fault diagnostic system was implemented through the LabVIEW software. Artificial neural network was trained offline using the Matlab software and the resultant network parameters were transferred to LabVIEW real time system. In the proposed system, it is possible to precisely identify the individual faulty switch (may be due to open-switch (or) short-switch failure) of multilevel inverters.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.134-139
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• 2001

This paper presents a new scheme of neural network controller to improve the robustuous of robot manipulator using digital signal processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. During past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Perforating of the proposed controller is illustrated. This paper describes a new approach to the design of adaptive controller and implementation of real-time control for assembling robotic manipulator using digital signal processor. Digital signal processors used in implementing real time adaptive control algorithm are TMS320C50 series made in TI'Co..