• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.299-300
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• 2008

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.34-46
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• 2016

Networked Control System (NCS) has evolved in the past decade through the advances in communication technology. The problems involved in NCS are broadly classified into two categories namely network issues due to network and control performance due to system network. The network problems are related to bandwidth allocation, scheduling and network security, and the control problems deal with stability analysis and delay compensation. Various delays with variable length occur due to sharing a common network medium. Though most delays are very less and mostly neglected, the network induced delay is significant. It occurs when sensors, actuators, and controllers exchange data packet across the communication network. Networked induced delay arises from sensor to controller and controller to actuator. This paper presents an adaptive delay compensation process for efficient control. Though Smith predictor has been commonly used as dead time compensators, it is not adaptive to match with the stochastic behavior of network characteristics. Time delay adaptive compensation gives an effective control to solve dead time, and creates a virtual environment using the plant model and computed delay which is used to compensate the effect of delay. This approach is simulated using TrueTime simulator that is a Matlab Simulink based simulator facilitates co-simulation of controller task execution in real-time kernels, network transmissions and continuous plant dynamics for NCS. The simulation result is analyzed, and it is confirmed that this control provides good performance.

• Journal of Korea Multimedia Society
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• v.22 no.1
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• pp.1-9
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• 2019

Single image rain removal is a typical inverse problem which decomposes the image into a background scene and a rain streak. Recent works have witnessed a substantial progress on the task due to the development of convolutional neural network (CNN). However, existing CNN-based approaches train the network with synthetically generated training examples. These data tend to make the network bias to the synthetic scenes. In this paper, we present an unsupervised framework for removing rain streaks from real-world rainy images. We focus on the natural phenomena that static rainy scenes capture a common background but different rain streak. From this observation, we train siamese network with the real rain image pairs, which outputs identical backgrounds from the pairs. To train our network, a real rainy dataset is constructed via web-crawling. We show that our unsupervised framework outperforms the recent CNN-based approaches, which are trained by supervised manner. Experimental results demonstrate that the effectiveness of our framework on both synthetic and real-world datasets, showing improved performance over previous approaches.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.289-294
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• 2012

In this paper, we take advantage of the characteristics of mobile smartphones can be serviced without the constraints of time and space, and Study was developed by a variety of mobile services were done in a traditional offline can be implemented in real-time Case Management Community. To this end, in addition to general PC/laptop, smart mobile until the configuration interface provide the same environment for HTML5 Web Switching and Optimal Network on the same device-specific browser Size to the implementation of the next generation of Web standards, HTML5-based integrated case management Web and Mobile Web. Hybrid App Development OS supports various kinds of smart devices based on SenchaTouch Mobile Framework between the server real-time synchronization and message through the implementation of the Push Notification function, administrators and guardians real-time two-way communication between the subjects is a real-time implementation of the system was implemented Case Management Community.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.6
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• pp.1128-1140
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• 2009

In this paper, we present a patient real-time vital sign information transmission system to effectively support developing real-time communication service by using a real-time object model named TMO (Time-Triggered Message-Triggered Object). Also, we describe the application environment as the ICU(Intensive Care Unit) to guarantee real-time service message with TMO structure in distributed network systems. We have to design to obtain useful vital sign information, which is generated at parsing data receiver modulor of HIS with TMO structure, that is offered by the central monitor. Vital sign informations of central monitor is composed of the raw data of several bedsite patient monitors. We are willing to maintain vital sign information of real time and continuity that is generated from the bedsite patient monitor. It is able to apply to remote medical examination and treatment. we proposed integration method between a vital sign database systems and hospital information systems. In the real time simulation techniques based on TMO object modeling, We have observed several advantages to the TMO structuring scheme. TMO object modeling has a strong traceability between requirement specification and design.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.57.2-57
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• 2001

Timed token protocols inadequately provide periodic communication service, although this is crucial for hard real time systems. We propose an approach to guaranteeing periodic communication service on a timed token protocol network. In this approach, we allocate bandwidth to each node so that the summation of bandwidth allocations is Target Token Rotation Time (TTRT). If a node cannot consume the allocated time, the residual time can be used by other nodes for non-periodic service using a timer which contains the unused time value and is appended to the token. This approach can always guarantee transmission of real-time messages before their deadlines when the network utilization is less than 50%.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.1
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• pp.63-68
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• 2009

As the complexity of the power system becomes higher, tests of the new devices, such as exciter and PCS(Power Conversion System) of the distributed generation sources, in the real operating condition are more important. However tests of the unverified devices in the real power system may cause hazardous malfunction of the system. In order to avoid this problem, power devices may be tested with the real-time simulators instead of the real power system. This paper presents an real-time multi machine power system simulator using PCs(Personal Computer) and Fast Ethernet. Developed real-time simulator performs the electro-mechanical dynamic simulation of multi-machine power system by the network distributed computing technique. Because the simulator consists of usual PCs and Fast Ethernet, it is possible to make up a simulation system very cheaper than the conventional real-time simulator which consists of dedicated expensive hardware devices. The performance of the developed simulator is tested and verified with the scaled model excitation system. The test which adjust the control parameters of the exciter is performed with the well-known New England 10 generator 39 bus sample power system.

• Journal of Broadcast Engineering
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• v.9 no.2
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• pp.119-130
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• 2004

We have developed a prototype super-high-definition (SHD) digital cinema distribution system that can store, transmit, and display eight-million-pixel motion pictures that have the image quality of a 35-mm film movie. The system contains a movie server, a real-time decoder, and an SHB projector. Using a Gigabit Ethernet link and TCP/IP, the server transmits JPEG2000 compressed motion picture data streams to the decoder at transmission speeds as high as 300 Mbps. The received data streams are decompressed by the decoder, and then projected onto a screen via the projector. By using an enlarged TCP window, multiple TCP streams, and a shaping function to control the data transmission quantity, we achieved real-time streaming of SHD movie data at about 300 Mbps between Chicago and Los Angeles, a distance of more than 3000 km. We also improved the decoder performance to show movies with Image qualities of 450 Mbps or higher. Since UDP is more suitable than TCP for fast long-distance streaming, we have developed an SHD digital cinema UDP relay system, in which UDP is used for transmission over a fast long-distance network. By using four pairs of server-side-proxy and decoder-side-proxy, 450-Mbps movie data streams could be transmitted.

• KNOM Review
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• v.22 no.3
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• pp.13-19
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• 2019

Network anomaly detection is a technology that collects information about flows on a network and detects malicious attacks occurring in a network in real time. In-band Network Telemetry (INT) technology provides more detailed information in real time, that is not provided by existing networks, such as hop latency and queue occupancy. In this paper, we propose the method to implement an anomaly detection system with higher performance by using INT as an input feature of machine learning and verify it through experiments.

• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.1-12
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• 1996

We propose a new approach to classifying a time series data into one of the autoregressive moving-average (ARMA) models. It is bases on two pattern recognition concepts for solving time series identification. The one is an extended sample autocorrelation function (ESACF). The other is a neural network-driven decision tree classifier(NNDTC) in which two pattern recognition techniques are tightly coupled : neural network and decision tree classfier. NNDTc consists of a set of nodes at which neural network-driven decision making is made whether the connecting subtrees should be pruned or not. Therefore, time series identification problem can be stated as solving a set of local decisions at nodes. The decision values of the nodes are provided by neural network functions attached to the corresponding nodes. Experimental results with a set of test data and real time series data show that the proposed approach can efficiently identify the time seires patterns with high precision compared to the previous approaches.