• 대한산업공학회지
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• 제35권1호
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• pp.119-128
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• 2009

In this paper, we analyze the effect of the data aggregation level on the MAC performance when RFID (Radio Frequency Identification) logistics data, which can be aggregated at RFID readers to reduce the transmission overhead, are transmitted in IEEE 802.11 wireless LANs. For various data aggregation levels, the throughputs and latencies of the DCF (Distributed Coordination Function) and PCF (Point Coordination Function) MAC protocols are analyzed by computer simulation. From the simulation analysis, we propose the appropriate input traffic load for real-time RFID logistics data transmitted in IEEE 802.11 wireless LANs.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.405-408
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• 1998

Generally, the principle function of simulator control loading system is to provide the pilot or student with the "feel" of the actual aircraft flight control systems during flight, taxing, and in malfunction. Flight control "feel" is the resistance felt by the pilot when moving a control stick or pedal, coupled with the amount of control surface deflection, and hence aircraft response, resulting from the input. Therefore, the control loading servo must be capable of performing to some general list of requirements derived from real aircraft control forces. In this paper, we deal with a $\mu-controller$ design for a control loading system of the flight simulator. For this, we derive a frequency response of the hydraulic system from the identification data and then design a controller using a $\mu-synthesis$ method. Under the same condition of simulation, $\mu-controller$ provides the superior performance than PID controller.than PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.150-154
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• 1993

A new method is proposed for obtaining Volterra kernals of a nonlinear system by use of a nonlinear systems by use of pseudorandom M-sequences and correlation technique. M-sequence is applied to a nonlinear technique. M-sequence is applied to a nonlinear system and the crosscorrelation function between the input and the output displays not only the linear impulse response of the linear part of the system, but also crosssections of the Volterra kernals of nonlinear system. Simulations are carried out for up to 3rd order Volterra kernal, and the results show a good agreement with the theoretical considerations.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1815-1821
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• 2015

Rapid increase in population growth has made the mankind to delve in appropriate identification of individuals through biometrics. Foot Print Recognition System is a new challenging area involved in the Personal recognition that is easy to capture and distinctive. Foot Print has its own dimensions, different in many ways and can be distinguished from one another. The main objective is to provide a novel efficient automated system Segmentation using Foot Print based on structural relations among the features in order to overcome the existing manual method. This system comprises of various statistical computations of various foot print parameters for identifying the factors like Instep-Foot Index, Ball-Foot Index, Heel- Index, Toe- Index etc. The input is naked footprint and the output result to an efficient segmentation system thereby leading to time complexity.

• 대한산업공학회지
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• 제27권3호
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• pp.305-314
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• 2001

In this paper, we construct an automatic evaluation system of psychological feeling for corporate identity (CI) symbol mark based on a fuzzy neural network technique. The system is modelled by trainable fuzzy inference rules with several input variables (qualitative and quantitative design components of CI symbol mark) and a single output variable (consumer's feeling). The back propagation learning algorithm, which is a conventional learning method of multilayer feedforward neural networks, is used for parameter identification of the fuzzy inference system. The learning ability to train data and the generalization ability to test data are evaluated for the proposed evaluation system by computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2198-2202
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• 2005

In this paper we have presented a condition monitoring method of check valve using neural network. The acoustic emission sensor was used to acquire the condition signals of check valve in direct vessel injection (DVI) test loop. The acquired sensor signal pass through a signal conditioning which are consisted of steps; rejection of background noise, amplification, analogue to digital conversion, extract of feature points. The extracted feature points which represent the condition of check valve was utilized input values of fault diagnosis algorithms using pre-learned neural network. The fault diagnosis algorithm proceeds fault detection, fault isolation and fault identification within limited ranges. The developed algorithm enables timely diagnosis of failure of check valve’s degradation and service aging so that maintenance and replacement could be preformed prior to loss of the safety function. The overall process has been experimented and the results are given to show its effectiveness.

• 전기학회논문지
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• 제65권4호
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• pp.642-651
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• 2016

For the acceleration and brake systems of an autonomous vehicle, the dynamic models from acceleration (brake) pedal input to driving(braking) torque at the vehicle wheel are represented by a set of linear transfer functions in this paper. We present an experimental method that can identify these models using a single rectangular pulse response data. Various magnitude of inputs with different running speeds are applied to experimental tests. All the identified models are demonstrated by the measured data. Both acceleration and brake models have been also validated by comparing the velocity of a full vehicle model associated with the proposed models with the measured vehicle velocity.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문초록집
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• pp.386.1-386
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• 2002

It is necessary to determine the vibration source and its transmission paths in order to develop a low-noise compressor Through the use of multiple-input/single-output(MISO) model, the transmission paths of vibration within a reciprocating compressor have been investigated. In order to identify the transmission path, we measure the accelerations of the block and transverse vibrations of the line discharge tube. (omitted)

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.619-623
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• 1992

In pattern recognition, the conventional neural networks contain a large number of weights and require considerable training times and preprocessor to classify a transformed patterns. In this paper, we propose a constrained pattern recognition method which is insensitive to rotation of input pattern by various degrees and does not need any preprocessing. Because these neural networks can not be trained by the conventional training algorithm such as error back propagation, a novel training algorithm is suggested. As such a system is useful in problem related to calssify overse side and reverse side of 500 won coin. As an illustrative example, identification problem of overse and reverse side of 500 won coin is shown.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2017년도 제55차 동계학술대회논문집 25권1호
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• pp.213-216
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• 2017

본 논문에서는 사용자 입력패턴 분석을 통한 행위 기반 인증 방법을 제안한다. 이 알고리즘은 기기를 통해 들어온 사용자의 다양한 입력정보를 받아오고, 받아온 정보를 분석하여 사용자만의 고유한 정보를 추출한다. 이렇게 추출된 정보를 데이터베이스에 저장 후, 사용자에 대한 인증요청이 들어오면 입력 정보들과 저장된 입력정보의 일치여부에 따라 인증을 허용할지 결정한다. 이를 이용하면 사용자의 고유한 행위에 대한 정보를 가지고 인증을 진행하기 때문에, 사용자의 기억에 의존하지 않고 간단하게 인증 절차를 진행할 수 있다. 본 논문에서는 실험을 통해 모인 데이터를 분석하여 제안하는 인증 방법이 실질적으로 사용자 인증에 적용 될 수 있음을 보인다.