• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.137-138
• /
• 2006

NEMO(Network MObility) is a complex model of mobile network which refers to a forming of Nested Mobile Network by a moving transportation like vessel, bus, or a train which then moves a Mobile Node, or by a movement of a PAN(Personal Area Network). In a Nested NEMO, pinball routing is the primary obstacle as exemplified by the IPv6 environment. This paper will focus on improving such models as RRH, RBU+ and MANET Approach, that attempted to solve pinball routing by route optimization.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.03a
• /
• pp.107-111
• /
• 1998

This paper presents a now approach to the design of intelligent contorl system for track vehicle system using fuzzy logic based on neural network. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. Moreover, We develop a Windows 95 version dynamic simulator which can simulate a track vehicle model in 3D graphics space. It is proposed a learning controller consisting of two neural network-fuzzy based of independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The dynamic simulator for track vehicle is developed by Microsoft Visual C++. Graphic libraries, OpenGL, by Silicon Graphics, Inc. were utilized for 3D Graphics. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

• Proceedings of the KIEE Conference
• /
• 2007.10a
• /
• pp.101-102
• /
• 2007

Heart diseases are critical and should be detected as soon as possible. A stethoscope is a simple device to find cardiac disorder but requires keen experiences in heart sounds. We evaluate a cardiac disorder classifier by using heart sounds recorded by a digital wireless stethoscope developed in this work. The classifier uses hidden Markov models with circular state transition to model the heart sounds. We train the classifier using two kinds of data: One recorded by using our stethoscope and the other sampled from a clean heart sound database. In classification experiments using 165 sound clips, the classifier shows the classification accuracy of 82% in classifying 6 cardiac disorder categories.

• Proceedings of the Safety Management and Science Conference
• /
• 2004.11a
• /
• pp.213-220
• /
• 2004

A purpose of this research is building a Parameter Evaluation Simulation(PES) program which is present proper parameter value to calculate line capacity. This research performs a detailed simulation and a analysis of it using PES and it is developed on the basis of Line Capacity Simulation model. Chosen simulation sectors are that happened a big change of a line capacity because of joining a high speed train(KTX). Moreover this research performs a sensitivity analysis when basic data are changed.

• Proceedings of the KSR Conference
• /
• 2003.05a
• /
• pp.734-739
• /
• 2003

When a train moves on rails, wheel and rail vibrate to produce contact noise and contact force. The former results in airborne noise and the latter transmits through bogie and excites carbody to generate structure borne noise. In this paper, wheel vibration is studied by theoretical and experimental approaches. Theoretical analysis is performed by finite element method and experimental analysis is performed by impact test. Using modal analysis and model tunning, we could have good agreement between the two approaches.

• Proceedings of the KSR Conference
• /
• 2002.05a
• /
• pp.437-445
• /
• 2002

The development of railway vehicle and bogie involves the proper selection of design parameters not only to achieve high speed of the train but also to reduce the vibration. In this study, an analytical model of a high speed freight car is developed to find the critical speed. The high speed freight car can generate the snake motion of the lateral, rolling and yawing motion of the car body and the bogie. The numerical analysis for the equation motions with 17 degrees of freedom showed the running stability and the critical speed due to the snake motion. Also the vibration modes of the high speed freight car was calculated using ADAMS RAIL software, which showed that the critical speed have the yawing modes of the car body and the bogie.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.13 no.12
• /
• pp.1288-1296
• /
• 2001

A scheme for on-line fault detection and diagnosis of an air-handling unit is presented. The fault detection scheme uses residuals which are generated by comparing each measurement with analytical redundancies computed from the reference models. In this paper, artificial neural networks (ANNs) are used to estimate analytical redundancy and to classify faults. The Lebenburg-Marquardt algorithm is used to train feed forward ANNs that provide estimates of continuous states and diagnosis results. The simulation result demonstrated that the ANNs can effectively detect and diagnose faults in the highly non-linear and complex HVAC systems.

• Proceedings of the Safety Management and Science Conference
• /
• 2003.05a
• /
• pp.53-61
• /
• 2003

The process of railway traffic planning is composed of several steps such as long - term, mid - term, short - term, and real - time plan. The planning of vehicle and manpower resources is a main research topic in tactical short - term planning step Railway vehicle is usually consisted of a power car, passenger/freight cars and human resource is composed of engine driver, cabin crew, ground personnel. So far , power car was main research target in railway vehicle scheduling problem. Recently according as the light electric railway or high - speed railway is introduced, the operational planning of train set vehicles become important . In this paper , we introduce the conceptional model for trainset restoring problem and developed heuristic algorithm.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.34C no.1
• /
• pp.42-50
• /
• 1997

Vector quantization has shown to be useful for compressing data related with a wide rnage of applications such as image processing, speech processing, and weather satellite. Neural networks of images this paper propses a efficient neural network learning algorithm, called learning count control algorithm based on the frquency sensitive learning algorithm. This algorithm can train a results more codewords can be assigned to the sensitive region of the human visual system and the quality of the reconstructed imate can be improved. We use a human visual systrem model that is a cascade of a nonlinear intensity mapping function and a modulation transfer function with a bandpass characteristic.

• Speech Sciences
• /
• v.13 no.3
• /
• pp.7-18
• /
• 2006

Diagnosis of pathological voice is one of the important issues in biomedical applications of speech technology. This study focuses on the discrimination of voice disorder using HMM (Hidden Markov Model) for automatic detection between normal voice and vocal fold disorder voice. This is a non-intrusive, non-expensive and fully automated method using only a speech sample of the subject. Speech data from normal people and patients were collected. Mel-frequency filter cepstral coefficients (MFCCs) were modeled by HMM classifier. Different states (3 states, 5 states and 7 states), 3 mixtures and left to right HMMs were formed. This method gives an accuracy of 93.8% for train data and 91.7% for test data in the discrimination of normal and vocal fold disorder voice for sustained /a/.