• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.10
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• pp.930-936
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• 2014

Smart Multiple-Tap to be introduced in this paper, is an electronic device that controls the Multibple-Tap through the Smartphone. It runs on network and has an inbuilt Zigbee communication module. Thus, users can control home devices from remote through home server. Mentioned home server is operated as a gateway and is connected with smart devices on the Internet. To sum up, Users using this Smart Multiple-Tap can check the state information of the multi-tap ON/OFF and can control immediately by smartphone. also, Smart Multiple-Tap perfectly shut down the standby power. when users turn off each of the Smart Multiple-Tap's circle, It drives automatically lowest electricity-consuming mode and shut down the standby power by its own built-in SSR module. therefore, it will bring the energy saving effect on environment using Smart Multiple-Tap.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.15-19
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• 2004

Domestic use, or embody program that transmit NMEA protocol using multi port as software and is using because there is no fee and product that develop NMEA protocol Multiplexer, import mounting for foreign climax present. These method is paid or there is problem that must make out special processing part in each application program. Also, each mountings that display NMEA protocol can cause double resources waste and damage etc. because manufacturing firm and platform are different. Can act separatively as single hardware module of reliable processing method and high efficiency to supplement this in this treatise, and because using design of optimized cue, heighten memory efficiency of module, and proposed NMEA protocol Multiplexer that can keep high trustability of Come on, deviation compass, echo sound, mountings of GPS and so on and real time communication that is main input sensor equipment about embodiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.11
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• pp.2238-2248
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• 1994

In this paper, we analyze a Microwave Amplifier Ultra-Wideband charateristic to apply Multi-Giga b/s optical receiver preamplifier in high speed optical communication system. To obtain frequency expanding effect. we analyze the frequency gain degradation effects of capacitances in the GaAs MESFET small-signal equivalent circuit and design Feedback amplifier Module(FAM) which has inductor peaking elements to compensate its effects and to expand frequency band. We derive optimum inductor peaking values in order to get flat gain in frequency band. The input and the output impedances of FAM are matched by Real Frequency Method and we design one and two stage ultra wideband microwave amplifier. With simulation results, it show $6.36\sim6.86dB$ and $9.1\sim10.3dB$ gains and execllent gain flatness in $0.5\sim12GHz$ respectively.

• The Journal of the Acoustical Society of Korea
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• v.30 no.4
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• pp.190-196
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• 2011

Bandwidth extension is a technique to improve speech quality and intelligibility, extending from 300-3400 Hz narrowband speech to 50-7000 Hz wideband speech. This paper designs an artificial bandwidth extension (ABE) module embedded in the AMR (adaptive multi-rate) decoder, reducing LPC/LSP analysis and algorithm delay of the ABE module. We also introduce a fast search codebook mapping method for ABE, and design a low power BWE technique based on the AMR decoder. The proposed ABE method reduces the computational complexity and the algorithm delay, respectively, by 28 % and 20 msec, compared to the traditional DTE (decode then extend) method. We also introduce a weighted classified codebook mapping method for constructing the spectral envelope of the wideband speech signal.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.3
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• pp.67-76
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• 2012

In this paper, collision analysis of the full rake for the Next Generation High-speed EMU is conducted using a 3D/1D hybrid model, which combines 3-dimensional (3D) front-end structure of finite element model and 1-dimensional (1D) multi-body dynamics model in order to analyze train collision with a standard 3D deformable obstacle. The crush forces, passengers' accelerations and energy absorptions of a full rake train can be easily obtained through a simulation of a 1D dynamics model composed of nonlinear springs, dampers and masses. Also the obtained simulation results are very similar to those of a 3D model if an overriding behavior does not occur during collision. The standard obstacle in TSI regulation has been changed from a rigid body to a deformable body, and therefore 3D collision simulations should be conducted because their simulation results depends on the front-end structure of a train. According to the obstacle collision analysis of this study, the obstacle collides with the driver's upper structure after overriding over the front-end module. The 3D/1D hybrid model is effective to evaluate a main energy-absorbing module that is frequently changed during design process and reduce the need time of the modeling and analysis when compared to a 3D full car body.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.493-496
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• 2005

The PMU (Payload Management Unit) in MSC (Multi-Spectral Camera) is the main subsystem for the management, control and power supply of the MSC payload operation. The PMU shall handle the communication with the BUS (Spacecraft) OBC (On Board Computer) for the command, the telemetry and the communications with the various MSC units. The PMU will perform that distributes power to the various MSC units, collects the telemetry reports from MSC units, performs thermal control of the EOS (Electro-Optical Subsystem), performs the NUC (Non-Uniformity Correction) function of the raw imagery data, and rearranges the pixel data and output it to the DCSU (Data Compression and Storage Unit). The BUS provides high voltage to the MSC. The PMU is connected to primary and redundant BUS power and distributes the high unregulated primary voltages for all MSC sub-units. The PSM (Power Supply Module) is an assembly in the PMU implements the interface between several channels on the input. The bus switches are used to prevent a single point system failure. Such a failure could need the PSS (Power Supply System) requirement to combine the two PSM boards' bus outputs in a wired-OR configuration. In such a configuration if one of the boards' output gets shorted to ground then the entire bus could fail thereby causing the entire MSC to fail. To prevent such a short from pulling down the system, the switch could be opened and disconnect the short from the bus. This switch operation is controlled by the BUS.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.59-64
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• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to chose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless it can learn the optimal policy if the agent can visit every state- action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem. we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL)as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. This paper introduces the concept of AMMQL and presents details of its application into dynamic positioning of robot soccer agents.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.9
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• pp.1240-1248
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• 2013

This paper describes a switching-level operation analysis of BTB(Back-To-Back) converter for HVDC(high voltage DC) application based on MMC(modular multi-level converter). A switching-level operation analysis for BTB converter is very important to understand the converter operation in detail and check the voltage and current transients in each components. However, the development of switching-level simulation model for the actual size BTB Converter is very difficult because the MMC normally has more than 150 sub-modules for each arm. So, a switching level simulation model for the 11-level MMC-based BTB converter was developed with PSCAD/EMTDC software, which has 12 sub-modules for the positive arm and another 12 sub-modules for the negative arm. The DC-voltage balance algorithm, the circulating-current reduction algorithm, the harmonic reduction algorithm, and the redundancy operation algorithm were included in this simulation model. The developed simulation model can be utilized to analyze the MMC-based BTB converter for HVDC application in switching level and to develop the protection scheme for the MMC-based BTB converter for HVDC application.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.321-324
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• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement Beaming is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement loaming is different from supervised teaming in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement loaming algorithms like Q-learning do not require defining or loaming any models of the surrounding environment. Nevertheless it can learn the optimal policy if the agent can visit every state-action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem, we suggest Adaptive Mediation-based Modular Q-Learning(AMMQL) as an improvement of the existing Modular Q-Learning(MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state space effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. This paper introduces the concept of AMMQL and presents details of its application into dynamic positioning of robot soccer agents.

• Smart Structures and Systems
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• v.15 no.6
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• pp.1583-1600
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• 2015

When natural disasters occur, including earthquakes, tsunamis, and debris flows, they are often accompanied by various types of damages such as the collapse of buildings, broken bridges and roads, and the destruction of natural scenery. Natural disaster detection and warning is an important issue which could help to reduce the incidence of serious damage to life and property as well as provide information for search and rescue afterwards. In this study, we propose a novel computer vision technique for debris flow detection which is feature-based that can be used to construct a debris flow event warning system. The landscape is composed of various elements, including trees, rocks, and buildings which are characterized by their features, shapes, positions, and colors. Unlike the traditional methods, our analysis relies on changes in the natural scenery which influence changes to the features. The "background module" and "monitoring module" procedures are designed and used to detect debris flows and construct an event warning system. The multi-criteria decision-making method used to construct an event warring system includes gradient information and the percentage of variation of the features. To prove the feasibility of the proposed method for detecting debris flows, some real cases of debris flows are analyzed. The natural environment is simulated and an event warning system is constructed to warn of debris flows. Debris flows are successfully detected using these two procedures, by analyzing the variation in the detected features and the matched feature. The feasibility of the event warning system is proven using the simulation method. Therefore, the feature based method is found to be useful for detecting debris flows and the event warning system is triggered when debris flows occur.