• 제어로봇시스템학회논문지
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• 제10권4호
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• pp.377-384
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• 2004

Nowadays, control systems consist of smart sensors, smart actuators, and controllers connected via fieldbus. Some devices such as motors in plant environments generate high degrees of EMI or noise. This noise may cause communication errors and make the successful transmission of data longer. Therefore, the noise condition has to be considered at the design of a reliable control system based on a network. This paper presents a scheduling method of task and message to guarantee the given end-to-end constraints under noise environments. A noise model with multi-sources of noise is used, and the analysis method of message's response time is presented when the noise model is applied to CAN (Controller Area Network). Two kinds of noise models are applied to an example system, and the effect to each control loop s end-to-end response time is analyzed. We believe that the proposed method help system designers design the control system guaranteeing its requirements under noise environment.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.292-302
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• 2022

The radar tomographic imaging is based on the Radar Cross-Section "RCS" of the materials of a shape under examination and investigation. The RCS varies as the conductivity and permittivity of a target, where the target has a different material profile than other background objects in a scene. In this research paper, we use Hierarchical Performance Modeling "HPM" and a framework developed earlier to determine/spot bottleneck(s) for pattern recognition of materials using a combination of the Single Layer Perceptron (SLP) technique and tomographic images in radar systems. HPM provides mathematical equations which create Objective Functions "OFs" to find an average performance metric such as throughput or response time. Herein, response time is used as the performance metric and during the estimation of it, bottlenecks are found with the help of OFs. The obtained results indicate that processing images consumes around 90% of the execution time.

• 융합보안논문지
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• 제5권4호
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• pp.27-32
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• 2005

최근 초고속 인터넷의 확산과 댁내 가전기기들의 지능화에 따라, 홈 네트워크(Home Network)에 대한 사회적인 관심이 높아지고 있다. 언제 어디서나 컴퓨팅이 가능한 유비쿼터스 컴퓨팅 사회에서는 개인의 컴퓨터환경 의존도가 증가함에 따라 사이버공격으로 인한 개인생활의 위협도 증가할 수 밖에 없다. 홈네트워크는 유비쿼터스 컴퓨팅 환경으로 가는 시작점이라고 할 수 있으므로 인터넷을 통한 사이버공격의 증가는 눈앞에 현실로 다가오고 있는 홈네트워크의 활성화를 방해하는 장해물로 대두될 것이 틀림없으므로 이에 대한 대응책 마련이 시급하다고 할 수 있다. 이와 같은 다양한 환경에서는 현재보다도 복잡한 위협이 존재할 것이다. 따라서 본 논문에서는 현재의 홈네트워크 시스템 환경을 분석하고 이에 따른 보안 위협과 향후 다가올 유비쿼터스 환경의 침해 유형에 대해서 살펴보고자 한다.

• Journal of Information Processing Systems
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• 제11권1호
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• pp.39-56
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• 2015

Continuous multi-interval prediction (CMIP) is used to continuously predict the trend of a data stream based on various intervals simultaneously. The continuous integrated hierarchical temporal memory (CIHTM) network performs well in CMIP. However, it is not suitable for CMIP in real-time mode, especially when the number of prediction intervals is increased. In this paper, we propose a real-time integrated hierarchical temporal memory (RIHTM) network by introducing a new type of node, which is called a Zeta1FirstSpecializedQueueNode (ZFSQNode), for the real-time continuous multi-interval prediction (RCMIP) of data streams. The ZFSQNode is constructed by using a specialized circular queue (sQUEUE) together with the modules of original hierarchical temporal memory (HTM) nodes. By using a simple structure and the easy operation characteristics of the sQUEUE, entire prediction operations are integrated in the ZFSQNode. In particular, we employed only one ZFSQNode in each level of the RIHTM network during the prediction stage to generate different intervals of prediction results. The RIHTM network efficiently reduces the response time. Our performance evaluation showed that the RIHTM was satisfied to continuously predict the trend of data streams with multi-intervals in the real-time mode.

• 제어로봇시스템학회논문지
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• 제5권6호
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• pp.734-743
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• 1999

In this paper, a real-time communication method using a PICNET-NP(Plant instrumentation and Control Network for Nuclear Power plant) is proposed with an analysis of the control network requirements of DCS(Distributed Control System) in nuclear power plants. The method satisfies deadline in case of worst data traffics by considering aperiodic and periodic real-time data and others. In addition, the method was used to analyze the data characteristics of the DCS in existing nuclear power plant. The result shows that use of this method meets the response time requirement(100ms).

• International Journal of Safety
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• 제5권2호
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• pp.6-11
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• 2006

The time delay in servo control on LonWorks/IP Virtual Device Network (VDN) is highly stochastic in nature. LonWorks/IP VDN induced time delay deteriorates the performance and stability of the real-time distributed control system and hinders an effective preventive and predictive maintenance. Especially in real-time distributed servo applications on the factory floor, timely response is essential for predictive and preventive maintenance. In order to guarantee the stability and performance of the system for effective preventive and predictive maintenance, LonWorks/IP VDN induced time delay needs to be predicted and compensated for. In this paper position control simulation of DC servo motor using Zero Phase Error Tracking Controller (ZPETC) as a feedforward controller, and Internal Model Controllers (IMC) based on Smith predictor with disturbance observer as a feedback controller is performed. The validity of the proposed control scheme is demonstrated by comparing the IMC based on Smith predictor with disturbance observer.

• 한국안전학회지
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• 제21권4호
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• pp.25-32
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• 2006

LonWorks over IP(LonWorks-IP) virtual device network(VDN) is an integrated form of LonWorks device network and IP data network. In especially real-time distributed servo applications on the factory floor, timely response is essential for predictive and preventive maintenance. The time delay in servo control on LonWorks-IP based VDN has highly stochastic nature. LonWorks-IP based VDN induced transmission delay deteriorates the performance and stability of the real-time distributed control system and can't give an effective preventive and predictive maintenance. In order to guarantee the stability and performance of the system, and give an effective preventive and predictive maintenance, LonWorks-IP based VDN induced time-varying uncertain time delay needs to be predicted and compensated. In this paper new Pill control scheme based on Smith predictor, disturbance observer and band pass filter is proposed and tested through computer simulation about position control of DC servo motor. It is shown that how can the proposed control scheme be designed to minimize the effects of uncertain varying time delay and model uncertainties. The validity of the proposed control scheme is compared and demonstrated with the comparison of internal model controllers(IMC) based on Smith predictor with and without disturbance observer.

• 전기학회논문지
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• 제59권11호
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• pp.1964-1970
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• 2010

A new intelligent power network (Smart Grid) that grafts some new technologies, such as the extension of the new and reproducible energy, electric motors, and electric storages, onto the regulation of green house gases according to the recent convention on climate changes has been actively promoted. As establishing such an intelligent power network, it is possible to implement a real-time rate system according to the change from the conventional single directional information transmission to the bidirectional information transmission. Such a real-time rate system can provide power during the chip rate hour by avoiding the high rate hour although customers use the same level of power through providing such real-time rate information including power generation costs. In this study, the establishment of an operating system that makes an effective use of the real-time rate system and its operation method are to be proposed.

• 한국해양공학회지
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• 제36권5호
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• pp.295-302
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• 2022

The initial response to a marine accident can play a key role to minimize the accident. Therefore, various decision support systems have been developed using sensors, simulations, and active response equipment. In this study, we developed an algorithm to predict damage locations using ship motion data with bidirectional long short-term memory (BiLSTM), a type of recurrent neural network. To reflect the low frequency ship motion characteristics, 200 time-series data collected for 100 s were considered as input values. Heave, roll, and pitch were used as features for the prediction model. The F1-score of the BiLSTM model was 0.92; this was an improvement over the F1-score of 0.90 of a prior model. Furthermore, 53 of 75 locations of damage had an F1-score above 0.90. The model predicted the damage location with high accuracy, allowing for a quick initial response even if the ship did not have flood sensors. The model can be used as input data with high accuracy for a real-time progressive flooding simulator on board.

• International Journal of Computer Science & Network Security
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• 제24권1호
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• pp.61-70
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• 2024

Cloud Computing is internet-based computing, where the users are provided with whatever service they need from the resources, software, and information. Recently, the security of cloud computing is considered as one of the major issues for both cloud service providers CSP and end-users. Privacy and highly confidential data make many users refuse to store their data within cloud computing, since data on cloud computing is not dully secured. The cryptographic algorithm is a technique which is used to maintain the security and privacy of the data on the cloud. In this research, we applied eight different cryptographic algorithms on Xen and KVM as hypervisors on cloud computing, to be able to measure and compare the performance of the two hypervisors. Response time and CPU utilization while encryption and decryption have been our aspects to measure the performance. In terms of response time and CPU utilization, results show that KVM is more efficient than Xen on average at 11.5% and 11% respectively. While TripleDES cryptographic algorithm shows a more efficient time response at Xen hypervisor than KVM.