• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.115-125
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• 2019

In this paper, the image is received from the camera and the lane is sensed. There are various ways to detect lanes. Generally, the method of detecting edges uses a lot of the Sobel edge detection and the Canny edge detection. The minimum use of multiplication and division is used when designing for the hardware configuration. The images are tested using a black box image mounted on the vehicle. Because the top of the image of the used the black box is mostly background, the calculation process is excluded. Also, to speed up, YCbCr is calculated from the image and only the data for the desired color, white and yellow lane, is obtained to detect the lane. The median filter is used to remove noise from images. Intermediate filters excel at noise rejection, but they generally take a long time to compare all values. In this paper, by using addition, the time can be shortened by obtaining and using the result value of the median filter. In case of the Sobel edge detection, the speed is faster and noise sensitive compared to the Canny edge detection. These shortcomings are constructed using complementary algorithms. It also organizes and processes data into parallel processing pipelines. To reduce the size of memory, the system does not use memory to store all data at each step, but stores it using four line buffers. Three line buffers perform mask operations, and one line buffer stores new data at the same time as the operation. Through this work, memory can use six times faster the processing speed and about 33% greater quantity than other methods presented in this paper. The target operating frequency is designed so that the system operates at 50MHz. It is possible to use 2157fps for the images of 640by360 size based on the target operating frequency, 540fps for the HD images and 240fps for the Full HD images, which can be used for most images with 30fps as well as 60fps for the images with 60fps. The maximum operating frequency can be used for larger amounts of the frame processing.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.89-96
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• 2015

IT is widely used for biomechanics and AHRS sensor also be highlighted with small sized characteristics and price competitiveness in the field of motion measurement and analysis of sports. In this paper, we attach the AHRS to the figure skate shoes to measure the motion data like spin, forward/backward, jump, in/out edge and toe movement. In order to reduce the measurement error, we have adopted the sensors equipped with Madgwick complementary filtering and also use Euler angle to quaternion conversion to reduce the Gimbal-lock effect. We test and experiment the accuracy and execution time of the pattern recognition algorithms like PCA, ICA, LDA, SVM to show the recognition possibility of it on the basic motions of figure skating from the 9-axis trajectory information which is gathered from AHRS sensor. From the result, PCA, ICA have low accuracy, but LDA, SVM have good accuracy to use for recognition of basic motions of figure skating.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.10
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• pp.1796-1803
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• 2006

This Paper describes a systematic method for designing the $H_{\infty}$ controller for the inverted pendulum which is a nonlinear and single-input double-outputs system. In particular, the open-loop system is conbined with a pre-filter to shape the open-loop transfer function for the sensitivity function ind the complementary sensitivity function to be kept the desirable frequency characteristics. Consequently, the loop shaping technique of the open-loop transfer function reduces the impacts of the model uncertainties, measurement noises and exogenous disterbances on the dynamic characteristics of the inverted pendulum. The results of simulation and experiment show the efficiency of the proposed control method comparing with conventional PID control method.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.569-575
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• 2013

This paper proposes a method for PDR (Pedestrian Dead-Reckoning) using a low cost IMU. Generally, GPS has been widely used for localization of pedestrians. However, GPS is disabled in the indoor environment such as in buildings. To solve this problem, this research suggests the PDR scheme with an IMU attached to the pedestrian's waist. However, despite the fact many methods have been proposed to estimate the pedestrian's position, but their results are not sufficient. One of the most important factors to improve performance is, a new calibration method that has been proposed to obtain the reliable sensor data. In addition to this calibration, the PDR method is also proposed to detect steps, where estimation schemes of step length, attitude, and heading angles are developed. Peak and zero crossings are detected to count the steps from 3-axis acceleration values. For the estimation of step length, a nonlinear step model is adopted to take advantage of using one parameter. Complementary filter and zero angular velocity are utilized to estimate the attitude of the IMU module and to minimize the heading angle drift. To verify the effectiveness of this scheme, a real-time system is implemented and demonstrated. Experimental results show an accuracy of below 1% and below 3% in distance and position errors, respectively, which can be achievable using a high cost IMU.

• Journal of the Korean Society for Railway
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• v.15 no.5
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• pp.454-458
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• 2012

The CBTC(Communication based Train Control) and WPAN(Wireless Personal Area Network) systems employed on 2.4GHz ISM band wireless networks provide complementary service within the same environment. Coexistence between the networks will be impaired if the mutual packets are uncertainty associated the timing or gaussian distance. This paper analyzes the impact of the mutual interference and proposed method to minimize the effect of the WPAN system signals on CBTC system. The performance analysis is illustrated by examining the symbol error rate versus signal to noise interference ratio in terms of carrier frequency offset. The method contributes to reduce the symbol error rate drastically. However it can't be a fundamental solution for the impact on the interference problem. It may be needed for railway only frequency after checking the problems of the current railway frequency.

• Korean Institute of Interior Design Journal
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• v.15 no.1 s.54
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• pp.147-157
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• 2006

The purpose of this study is to fond out the characteristics of color perception and preferred color scheme of the aged who becomes color weak due to yellowed eye sight. For this, this study was composed of two steps. First, an experimental simulation on aged vision using Spectrophotometer(CM-2600d, Minolta) attached Y-2 filter as a quasi lenses of the aged eye. The color data of 120 color chips of the aged vision was measured and analyzed to grasp the characteristics of color perception of the age. Then, a questionnaire survey was carried out with color chips and 8 interior color schemes. They participated in a questionnaire survey of the level of identification among the color chips of 11 tones of R, G, PB, as well as a survey of the preference color schemes. The result of this study are as follow; 1) The range of color perception on hue narrowed into YR, Y, GY, G. Especially, the aged have failed perception of B${\cdot}$PB${\cdot}$P${\cdot}$RP(short wave length of light) by yellowed eye sight. 2) The level of identification among the color chips of 11 tones of R,G,PB are different by each color. But Very Pale, Pale, Strong, Vivid are fractionated similarly in almost color. 3) In the preference of interior color scheme of the aged, preference color harmony scheme Is the complementary color scheme that is easy for identification, rather than analogous color scheme. The preferred dominant color is warm color rather than cool color.

• Transactions on Electrical and Electronic Materials
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• v.12 no.6
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• pp.262-266
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• 2011

A simulation study of a current-mode direct current (DC)-DC boost converter is presented in this paper. This converter, with a fully-integrated power module, is implemented by using bipolar complementary metal-oxide semiconductor (BiCMOS) technology. The current-sensing circuit has an op-amp to achieve high accuracy. With the sense metal-oxide semiconductor field-effect transistor (MOSFET) in the current sensor, the sensed inductor current with the internal ramp signal can be used for feedback control. In addition, BiCMOS technology is applied to the converter, for accurate current sensing and low power consumption. The DC-DC converter is designed with a standard 0.35 ${\mu}m$ BiCMOS process. The off-chip inductor-capacitor (LC) filter is operated with an inductance of 1 mH and a capacitance of 12.5 nF. Simulation results show the high performance of the current-sensing circuit and the validity of the BiCMOS converter. The output voltage is found to be 4.1 V with a ripple ratio of 1.5% at the duty ratio of 0.3. The sensing current is measured to be within 1 mA and follows to fit the order of the aspect ratio, between sensing and power FET.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1773-1793
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• 2023

Automated machine learning, often referred to as "AutoML," is the process of automating the time-consuming and iterative procedures that are associated with the building of machine learning models. There have been significant contributions in this area across a number of different stages of accomplishing a data-mining task, including model selection, hyper-parameter optimization, and preprocessing method selection. Among them, preprocessing method selection is a relatively new and fast growing research area. The current work is focused on the recommendation of preprocessing methods, i.e., feature subset selection (FSS) algorithms. One limitation in the existing studies regarding FSS algorithm recommendation is the use of a single learner for meta-modeling, which restricts its capabilities in the metamodeling. Moreover, the meta-modeling in the existing studies is typically based on a single group of data characterization measures (DCMs). Nonetheless, there are a number of complementary DCM groups, and their combination will allow them to leverage their diversity, resulting in improved meta-modeling. This study aims to address these limitations by proposing an architecture for preprocess method selection that uses ensemble learning for meta-modeling, namely AutoFE-Sel. To evaluate the proposed method, we performed an extensive experimental evaluation involving 8 FSS algorithms, 3 groups of DCMs, and 125 datasets. Results show that the proposed method achieves better performance compared to three baseline methods. The proposed architecture can also be easily extended to other preprocessing method selections, e.g., noise-filter selection and imbalance handling method selection.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.247-258
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• 2003

In this paper, we present a pen-shaped input device equipped with accelerometers and gyroscopes that measure inertial movements when a user writes on 2 or 3 dimensional space with the pen. The measurements from gyroscope are integrated once to find the attitude of the system and are used to compensate gravitational effect in the accelerations. Further, the compensated accelerations are integrated twice to yield the position of the system, whose basic concept stems from the field of inertial navigation. However, the accuracy of the position measurement significantly deteriorates with time due to the integrations involved in recovering the handwriting trajectory This problem is common in the inertial navigation system and is usually solved by the periodic or aperiodic calibration of the system with external reference sources or other information in the filed of inertial navigation. In the presented paper, the calibration of the position or velocity is performed on-line and off-line. In the on-line calibration stage, the complementary filter technique is used, where a Kalman filter plays an important role. In the off-line calibration stage, the constant component of the resultant navigational error of the system is removed using the velocity information and motion detection algorithm. The effectiveness and feasibility of the presented system is shown through the experimental results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.395-401
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• 2018

Recently, most of mobile devices are equipped with GNSS (Global Navigation Satellite System). When the GNSS signal is available, it is easy to obtain position information. However, GNSS is not suitable solution for indoor localization, since the signals are normally not reachable inside buildings. A wide varieties of technology have been developed as a solution for indoor localization such as Wi-Fi, beacons, and inertial sensor. With the increased sensor combinations in mobile devices, mobile devices also became feasible to provide a solution, which based on PDR (Pedestrian Dead Reckoning) method. In this study, we utilized the combination of three sensors equipped in mobile devices including accelerometer, digital compass, and gyroscope and applied three representative PDR methods. The proposed methods are done in three stages; step detection, step length estimation, and heading determination and the final indoor localization result was evaluated with terrestrial LiDAR (Light Detection And Ranging) data obtained in the same test site. By using terrestrial LiDAR data as reference ground truth for PDR in two differently designed experiments, the inaccuracy of PDR methods that could not be found by existing evaluation method could be revealed. The firstexperiment included extreme direction change and combined with similar pace size. Second experiment included smooth direction change and irregular step length. In using existing evaluation method which only checks traveled distance, The results of two experiments showed the mean percentage error of traveled distance estimation resulted from three different algorithms ranging from 0.028 % to 2.825% in the first experiment and 0.035% to 2.282% in second experiment, which makes it to be seen accurately estimated. However, by using the evaluation method utilizing terrestrial LiDAR data, the performance of PDR methods emerged to be inaccurate. In the firstexperiment, the RMSEs (Root Mean Square Errors) of x direction and y direction were 0.48 m and 0.41 m with combination of the best available algorithm. However, the RMSEs of x direction and y direction were 1.29 m and 3.13 m in the second experiment. The new evaluation result reveals that the PDR methods were not effective enough to find out exact pedestrian position information opposed to the result from existing evaluation method.