• Wind and Structures
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• v.13 no.3
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• pp.293-307
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• 2010

This paper describes a new method for the estimation of six complex aerodynamic admittance functions. The aerodynamic admittance functions relate buffeting forces to the incoming wind turbulent components, of which the estimation accuracy affects the prediction accuracy of the buffeting response of long-span bridges. There should be two aerodynamic admittance functions corresponding to the longitudinal and vertical turbulent components, respectively, for each gust buffeting force. Therefore, there are six aerodynamic admittance functions in all for the three buffeting forces. Sears function is a complex theoretical expression for the aerodynamic admittance function for a thin airfoil. Similarly, the aerodynamic admittance functions for a bridge deck should also be complex functions. This paper presents a separated frequency-by-frequency method for estimating the six complex aerodynamic admittance functions. A new experimental methodology using an active turbulence generator is developed to measure simultaneously all the six complex aerodynamic admittance functions. Wind tunnel tests of a thin plate model and a streamlined bridge section model are conducted in turbulent flow. The six complex aerodynamic admittance functions, determined by the developed methodology are compared with the Sears functions and Davenport's formula.

• International Journal of Automotive Technology
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• v.8 no.2
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• pp.249-258
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• 2007

This paper proposes a method that can be used for the resistance estimation of a PWM (Pulse Width Modulation)-driven solenoid. By using estimated solenoid resistance, the PWM duty ratio was compensated to be proportional to the solenoid current. The proposed method was developed for use with EHB (Electro-Hydraulic Braking) systems, which are essential features of the regenerative braking system of many electric vehicles. Because the HU (Hydraulic Unit) of most EHB systems performs not only ABS/TCS/ESP (Electronic Stability Program) functions but also service braking function, the possible duration of continuous solenoid driving is so long that the generated heat can drastically change the level of solenoid resistance. The current model of the PWM-driven solenoid is further developed in this paper; from this a new resistance equation is derived. This resistance equation is solved by using an iterative method known as the FPT (fixed point theorem). Furthermore, by taking the average of the resistance estimates, it was possible to successfully eliminate the effect of measurement noise factors. Simulation results showed that the proposed method contained a sufficient pass-band in the frequency response. Experimental results also showed that adaptive solenoid driving which incorporates resistance estimations is able to maintain a linear relationship between the PWM duty ratio and the solenoid current in spite of a wide variety of ambient temperatures and continuous driving.

• Bulletin of the Korean Chemical Society
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• v.26 no.11
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• pp.1673-1674
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• 2005

• Proceedings of the KTCVS Conference
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• 1993.06a
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• pp.128-128
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• 1993

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1098-1101
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• 2004

The ordinary stereo image of an object consists of data of left and right views. Therefore, the left and right image pairs have to be transmitted simultaneously in order to display 3-dimentional video at the remote site. However, due to the twice data in comparing with a monoscopic image of the same object, it needs to be compressed for fast transmission and resource saving. Hence, it needs an effective coding algorithm for compressing stereo image. It was found previously that compressing left and right frames independently will achieve the compression ratio lower than compressing by utilizing the spatial redundancy between both frames. Therefore, in this paper, we study the stereo image compression technique based on the multiresolution wavelet transform using varied disparity-block size for estimation and compensation. The size of disparity-block in the stereo pair subbands are scaling on a coarse-to-fine wavelet coefficients strategy. Finally, the reference left image and residual right image after disparity estimation and compensation are coded by using SPIHT coding. The considered method demonstrates good performance in both PSNR measures and visual quality for stereo image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2657-2675
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• 2013

A novel neighbor selection-based fingerprinting algorithm using matrix correlation (MC) for Wi-Fi localization is presented in this paper. Compared with classic fingerprinting algorithms that usually employ a single received signal strength (RSS) sample, the presented algorithm uses multiple on-line RSS samples in the form of a matrix and measures correlations between the on-line RSS matrix and RSS matrices in the radio-map. The algorithm makes efficient use of on-line RSS information and considers RSS variations of reference points (RPs) for localization, so it offers more accurate localization results than classic neighbor selection-based algorithms. Based on the MC algorithm, an error estimation method using artificial neural network is also presented to fuse available information that includes RSS samples and localization results computed by the MC algorithm and model the nonlinear relationship between the available information and localization errors. In the on-line phase, localization errors are estimated and then used to correct the localization results to reduce negative influences caused by a static radio-map and RP distribution. Experimental results demonstrate that the MC algorithm outperforms the other neighbor selection-based algorithms and the error estimation method can reduce the mean of localization errors by nearly half.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.104-114
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• 1996

For the improvement of productivity, the reduction of cost and time for manufacturing is mandatory, especially in the field of electromic industry. The study is concerned with a practical means of systematic assistance to formability estimation and selection of reliable design specification for electronic sheet metal parts. The objective of this research work is to develop a simulation system which hops to analyze the target processes with the finite element method and to acquire available design data quickly and exactly. The simulation system developed in the study consists of design verification, selection of optimal combination of parameters, knowledge acquisition and graphical user interface(GUI). Design verification is automatically carried out by using the finite element method. A data base management system and nomograms are utilized for knowledge acquisition. The developed system has been applied to some major sheet metal forming operations such as flanging, embossing, bending and blanking. According to the simulated results, the validation of the target processes has been confirmend. Analysis data, estimation rules of formability and graphical representation of the analysis have been employed for the designer's understanding and evaluation, thus providing a practical means of robust design and evaluation of forma- bility for producing electronic sheet metal parts.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.352-361
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• 2013

Combining multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) with a massive number of transmit antennas (massive MIMO-OFDM) is an attractive way of increasing the spectrum efficiency or reducing the transmission energy per bit. The effectiveness of Massive MIMO-OFDM is strongly affected by the channel state information (CSI) estimation method used. The overheads of training frame transmission and CSI feedback decrease multiple access channel (MAC) efficiency and increase the CSI estimation cost at a user station (STA). This paper proposes a CSI estimation scheme that reduces the training frame length by using a novel pilot design and a novel unitary matrix feedback method. The proposed pilot design and unitary matrix feedback enable the access point (AP) to estimate the CSI of the signal space of all transmit antennas using a small number of training frames. Simulations in an IEEE 802.11n channel verify the attractive transmission performance of the proposed methods.

• The Journal of Korea Robotics Society
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• v.14 no.4
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• pp.357-362
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• 2019

This paper proposes a model and train method that can real-time detect objects and distances estimation based on a monocular camera by applying deep learning. It used YOLOv2 model which is applied to autonomous or robot due to the fast image processing speed. We have changed and learned the loss function so that the YOLOv2 model can detect objects and distances at the same time. The YOLOv2 loss function added a term for learning bounding box values x, y, w, h, and distance values z as 클래스ification losses. In addition, the learning was carried out by multiplying the distance term with parameters for the balance of learning. we trained the model location, recognition by camera and distance data measured by lidar so that we enable the model to estimate distance and objects from a monocular camera, even when the vehicle is going up or down hill. To evaluate the performance of object detection and distance estimation, MAP (Mean Average Precision) and Adjust R square were used and performance was compared with previous research papers. In addition, we compared the original YOLOv2 model FPS (Frame Per Second) for speed measurement with FPS of our model.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.182-188
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• 2023

Due to the acceleration of an aging society, the need for lower limb exoskeletons to assist gait is increasing. And for use in daily life, it is essential to have technology that can accurately estimate gait phase even in the walking environment and walking speed of the wearer that changes frequently. In this paper, we implement an LSTM-based gait phase estimation learning model by collecting gait data according to changes in gait speed in outdoor level ground and stair environments. In addition, the results of the gait phase estimation error for each walking environment were compared after learning for both max hip extension (MHE) and max hip flexion (MHF), which are ground truth criteria in gait phase divided in previous studies. As a result, the average error rate of all walking environments using MHF reference data and MHE reference data was 2.97% and 4.36%, respectively, and the result of using MHF reference data was 1.39% lower than the result of using MHE reference data.