• 전기의세계
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• v.26 no.1
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• pp.87-90
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• 1977

Various simulation techniques were developed in the modeling of biological system during the last decades. Mostly analog and hybrid simulation techniques have been used. The authors chose the Digital Analog Simulation (DAS) technique by using the MIMIC language to simulate the saccadic eye movement system performances on the digital computer. There have been various models presented by many investigators after Young & Stark's sampled-data model. The eye movement model chosen by the authors is Robinson's model III which shows the parallel information processing characteristics clearly to the double-step input stimuli. In the process of simulation, the parameter and constants used were based on the neurophysiological data of the human and animals. The analog model blocks were converted to the corresponding MIMIC block diagrams and programmed into the MIMIC statements. The program was run on the CDC Cyber 72-14 computer. The essential input stimulus was double-step of 5 and 10 degrees, and target durations chosen were 50,100 and 150 msec. The results obtained by the DAS technqiue were in good agreement with analog simulation carried out by other investigators as well as with the experimental human saccadic eye movement responses to double-step target movements.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.447-449
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• 1993

Digital filter is a signal processor which converts the sequence input sampled from analog signal into another sequence output. It includes software routines which filter digital signal, a computer system for executing the routines, and a data acquisition system which implements A/D, D/A signal conversion. In this paper, a data acquisition system is designed and implemented for one-board computer of MC68000. Also, the theory regarding signal conversion and and its problems occured in implementation are considered. And then, with the hardware implemented like this, design of a digital low-pass filter with the cutoff frequency of 200Hz is implemented, and related characteristics are considered.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.8
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• pp.2555-2560
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• 1996

Inspecting the dimensional accuracy of a car-body in assembly line is a very important process to assure high productivity. Now there exist two common inspecting methods in practice. One is to measure a sampled car-body with three dimensional measuring machine, and the other is to measure car-body with three dimensional measuring machine, and the other is to measure car-body in assembly line using many sensors fixed to a large jig frame. The formal method takes too long to inspect a sampled car-body of a same sort, and cannot therefore give an useful error trend for the whole production. On the other hand, the latter lacks flexibility and is very cost-intensive. By using industrial robots and sensors, an in-line Car-Body Measuring(CBM) system which ensured high flexiblity and sufficient accuracy was developed. This CBM cell operates in real production line and measures the check points by the non-contact type using camera and laser displacement sensor(LDS). This system can handle about 15 Measuring points within a cycle time of 40 seconds. A process computer controls whole process such as data acquisition file handling and data analysis. Robot arms changes in length due to ambient temperature fluctuation affecting the measuring accuracy. To compensate this error, a robot arm calibration process was developed.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.327-332
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• 2003

A new discretization method for nonlinear system with time-delay is proposed. It is based on the well-known Taylor series expansion and the zero-order hold (ZOH) assumption. We know that a discretization of linear system can be obtained with the ZOH assumption and within the sampling interval. A similar line of thinking is available in nonlinear case. The mathematical structure of the new discretization method is explored and under the structure, the sampled-data representation of nonlinear system including time-delay is computed. Provided that the discrete form of the single input nonlinear system with time-delay is derived, this result is easily extended to nonlinear system with multi-input time-delay. For simplicity two inputs are considered in this study. It is enough to generalize that of multiple inputs. Finally, the time-discretization of non-affine nonlinear system with time-delay is investigated for apply all nonlinear system

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.275-280
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• 2011

Due to high-speed of trains, the track deformation increases rapidly and may lead to track irregularities causing the track stability problem. To secure the track stability, the continual inspection on track irregularities is required. The paper presents a methodology for identifying track irregularity using the NARX neural network considering non-linearity in the train structural system. A simulation study has been carried out to examine the proposed method. Acceleration time history data measured at a bogie were re-sampled to every 0.25m track irregularity. In the simulation study, two sets of measured data were simulated. The second data set was obtained by a train with 10% more mass than the one for the first data set. The first set of simulated data was used to train the series-parallel mode of NARX neural network. Then, the track irregularities at the second time period are identified by using the measured acceleration data. The closeness of the identified track irregularity to the actual one is evaluated by PSD and RMSE.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.841-854
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• 2020

The paper explains the method to process, analyze and predict traffic patterns in Los Angeles county using Big Data and Machine Learning. The dataset is used from a popular navigating platform in the USA, which tracks information on the road using connected users' devices and also collects reports shared by the users through the app. The dataset mainly consists of information about traffic jams and traffic incidents reported by users, such as road closure, hazards, accidents. The major contribution of this paper is to give a clear view of how the large-scale road traffic data can be stored and processed using the Big Data system - Hadoop and its ecosystem (Hive). In addition, analysis is explained with the help of visuals using Business Intelligence and prediction with classification machine learning model on the sampled traffic data is presented using Azure ML. The process of modeling, as well as results, are interpreted using metrics: accuracy, precision and recall.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.4
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• pp.127-137
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• 2009

This paper is proposed that in-output Digital module is acquired a vibration signal of a rotating machinery by Data Acquisition System. The module is designed to get ride of nose through low pass filter on the vibration signal from sensors and set the gain value for being able to sampling AC to DC, and also the sampled data by sampler and the conversed data by DIP/FPGA is supplied to the analyzer for analysis at a software tool. The DIP(Digital Signal Processor) of the Digital input/output Board makes Average voltage, Peak to Peak voltage, RMS(Root Mean Square) and Gap voltage, also FFT(Fast Fourier Transform) for rotating vibration diagnosis.

• Journal of Astronomy and Space Sciences
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• v.15 no.1
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• pp.229-234
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• 1998

We study on a terrain contour matching algorithm using Radial Basis Functions(RBFs) for aided inertial navigation system for position fixing aircraft, cruise missiles or re-entry vehicles. The parameter optimization technique is used for updating the parameters describing the characteristics of an area with modified Gaussian least square differential correction algorithm and the step size limitation filter according to the amount of updates. We have applied the algorithm for matching a sampled area with a target area supposed that the area data are available from Radar Terrain Sensor(RTS) and Reference Altitude Sensor(RAS)

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.488-492
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• 1986

This paper presents a design method for PID controller using optimal control theory. The procedures of the applied method consist of (1) sampling the system response to the test signal, (2) processing the sampled data using RPE method to identify the parameters of the plant, (3) calculating the optimal value of the PID controller parameters using LQ theory. This controller is implemented on the digital computer and applied to real servomechanism, yielding satisfactory result.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.194-197
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• 1988

The unequal bit-error-probability of rate r=b/n binary convolutional code is analyzed. The error protection affored each digit of the b-tuple information word can be different from that afforded other digit. The property of the unequal protection can be applied to transmitting sampled data in PCM system.