• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.167-170
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• 2005

We performed field test and analyzed results of field test in variable HFC(Hybrid Fiber Coaxial) network environments. And we investigated whether the test results is satisfied in DOCSIS(Data-over-Cable Service Interface Specification) 2.0 and OpenCable standard. Also, we propose HFC improvement problem for HFC Network quality as BcN(Broadband convergence Network) access network. We tested three sample areas. The sample areas represent various type of SO(System Operator) in korea. The field test was to measure signal level about digital channels. In results of multiple digital channels, in case of "Equalizer ON", we could be obtained very good test results. The results of field test were shown in satisfying recommended values in DOCSIS 2.0 and OpenCable. So, we could have confidence through field test that BcN will be possible to be adapted to environment of korea HFC network.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.1927-1933
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• 2006

This paper proposes the implementation plan of information network for an E-Navigation. Firstly, It configures to the network system based on E-Navigation information network using information and communication technology. And then, it builds on the total port network and tuning up the maritime traffic support system. It will expect to the efficiency through information network between ship to ship related pen operator. Building of information network for the E-Navigation, it is to build on the wireless internet infrastructure for the port logistics and traffic safety.

• Journal of Korea Port Economic Association
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• v.20 no.1
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• pp.79-93
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• 2004

Recently, the change of shipping and port environment has required the new strategy from the liners, terminal operators, ports. The ports of call in the North American and European line also has changed as the Chinese ports made rapid advance. This seems to result from the fact that the trend of the container transportation by sea has developed the traditional concept, called port-to-port system that directly links between a port and another port into the network with complicated hierarchical structure reflecting costs, efficiency, and strategy of the Mega Carrier. This paper suggests the factors for Busan port to become the hub port of northeast Asia by analyzing the change of the liners' strategy along the change of the shipping and port environment, the global management of the operator of container port, and the amount of containers flowing in the northeast Asia.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.147-154
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• 1998

As technical systems in building are being developed, the processes and systems get more difficult for the average operator to understand. When operating a complex facility, it is beneficial in equipment management to provide the operator with tools which can help in dicision making for recovery from a failure of the system. The main object of the study is to develop real-time automatic fault detection and diagnosis system for optimal operation of IBS building.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.1
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• pp.54-59
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• 2006

The smart space is composed of the wire and/or wireless network, multi-sensor-based environment, and many various controllers. For the smart space, this paper presents a new design method of multirate digital decentralized controller using the intelligent digital redesign technique. In specific, the proposed method is based on the delta-operator and the multirate sampling and takes the form of the LMIs. To shows the feasibility of the suggested method, the computer simulations for Heating, ventilating, and ai. conditioning (HVAC) system are provided.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.133-142
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• 2011

Overhead facility design problem(OFDP) is one of the shortest rectilinear flow network problem(SRFNP)[4]. Genetic algorithm(GA), artificial immune system(AIS), population management genetic algorithm (PM) and greedy randomized adaptive search procedures (GRASP) were introduced to solve OFDP. A path matrix formed individual was designed to represent rectilinear path between each facility. An exchange crossover operator and an exchange mutation operator were introduced for OFDP. Computer programs for each algorithm were constructed to evaluate the performance of algorithms. Computation experiments were performed on the quality of solution and calculations time by using randomly generated test problems. The average object value of PM was the best of among four algorithms. The quality of solutions of AIS for the big sized problem were better than those of GA and GRASP. The solution quality of GRASP was the worst among four algorithms. Experimental results showed that the calculations time of GRASP was faster than any other algorithm. GA and PM had shown similar performance on calculation time and the calculation time of AIS was the worst.

• Journal of Institute of Convergence Technology
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• v.6 no.1
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• pp.43-47
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• 2016

In this paper, we report a work-in-progress about development of multi-drone system for smart agriculture. The multi-drone system is controlled via a haptic teleoperation by a human operator. The purpose of the multi-drone system is that let the human operator to easily handle the multiple drones which are maintaining a fixed formation using ZigBee communication network.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.363-372
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• 2017

This paper presents a novel face recognition algorithm based on the deep convolution neural network and key point detection jointed local binary pattern methodology to enhance the accuracy of face recognition. We firstly propose the modified face key feature point location detection method to enhance the traditional localization algorithm to better pre-process the original face images. We put forward the grey information and the color information with combination of a composite model of local information. Then, we optimize the multi-layer network structure deep learning algorithm using the Fisher criterion as reference to adjust the network structure more accurately. Furthermore, we modify the local binary pattern texture description operator and combine it with the neural network to overcome drawbacks that deep neural network could not learn to face image and the local characteristics. Simulation results demonstrate that the proposed algorithm obtains stronger robustness and feasibility compared with the other state-of-the-art algorithms. The proposed algorithm also provides the novel paradigm for the application of deep learning in the field of face recognition which sets the milestone for further research.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.94-98
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• 2009

A video caption recognition system has been developed for broadcasting sport events such as major league baseball. The purpose of the system is to translate the information expressed in English units such as miles per hour (MPH) to the international system of units (SI) such as km/h. The system detects the ball speed displayed in the video and recognizes the numerals. The ball speed is then converted to km/h and displayed by the following character generator (CG) system. Although neural-network based methods are widely used for character and numeral recognition, we use template matching to avoid the training process required before the broadcasting. With the proposed template matching method, the operator can cope with the situation when the caption’s appearance changed without any notification. Templates are configured by the operator with a captured screenshot of the first pitch with ball speed. Templates are updated with following correct recognition results. The accuracy of the recognition module is over 97%, which is still not enough for live broadcasting. When the recognition confidence is low, the system asks the operator for the correct recognition result. The operator chooses the right one using hot keys.