• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.6
• /
• pp.133-141
• /
• 2008

As interactive multimedia have come into wide use, user interfaces such as remote controllers or classical computer mice have several limitations that cause inconvenience. We propose a vision-based pointing device to resolve this problem. We analyzed the moving image from the camera which is embedded in the pointing device and estimate the movement of the device. The pose of the cursor can be determined from this result. To process in the real time, we used the low resolution of $288{\times}208$ pixel camera and comer points of the screen were tracked using local optical flow method. The distance from screen and device was calculated from the size of screen in the image. The proposed device has simple configurations, low cost, easy use, and intuitive handhold operation like traditional mice. Moreover it shows reliable performance even in the dark condition.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.12A
• /
• pp.966-974
• /
• 2011

In this paper, we propose an asset tracking system for applying a container port environment. If we attempt to apply this common locating system to a port environment for logistics automation, the system performance is degraded because there are many steel obstacles that cause interference in the RF communication and measurement. We divided readers into two types - fixed and mobile readers; hence, the location method operates in two steps for efficient wireless communication and precise measurement. In addition, the system estimates the location with trajectory information of assets when the small number of measurement is gathered. We implemented all the system components and installed these at a real port for evaluation. The success rate of communication and estimation is much better than that of the existing general locating system, and the location precision is substantially increased.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.1
• /
• pp.141-144
• /
• 2006

The deviations in the injection orbital parameters, resulting from launcher dispersions, need to be estimated and used for autonomous satellite operations. For the proposed small satellite mission of the university there will be two GPS receivers onboard the satellite to provide the instantaneous orbital state to the onboard data handling system. In order to meet the power requirements, the satellite will be sun-tracking whenever there is no imaging operation. For imaging activities, the satellite will be maneuvered to nadir-pointing mode. Due to such different modes of orientation the geometry for the GPS receivers will not be favorable at all times and there will be instances of poor geometry resulting in no output from the GPS receivers. Onboard the satellite, the orbital information should be continuously available for autonomous switching on/off of various subsystems. The paper presents the strategies to make use of small arcs of data from GPS receivers to compute the mean orbital parameters and use the updated orbital parameters to calculate the position and velocity whenever the same is not available from GPS receiver. Thus the navigation message from the GPS receiver, namely the position vector in Earth-Centered-Earth-Fixed (ECEF) frame, is used as measurements. As for estimation, two techniques - (1) batch least squares method, and (2) Kalman Filter method are used for orbit estimation (in real time). The performance of the onboard orbit estimation has been assessed based on hardware based multi-channel GPS Signal simulator. The results indicate good converge even with short arcs of data as the GPS navigation data are generally very accurate and the data rate is also fast (typically 1Hz).

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.2
• /
• pp.359-364
• /
• 2006

Interference can seriously degrade the performance of GPS receiver because GPS signal has extremely low power at earth surface. This paper presents a Narrowband Interference Excision Filter (NIEF) in frequency domain that removes narrowband interferences with small signal loss. A NIEF transforms the received GPS signals with interferences into the frequency domain with FFT and then compute statistics such as mean and standard deviation to determine an excision threshold. All spectrums exceeding the threshold are removed and the remaining spectrums are restored by IFFT. A NIEF effectively can remove various and strong interferences with a simple structure. However, the signal power loss is unavoidable during FFT and IFFT. Besides the hamming window and overlap technique, a threshold-whitening technique and an adaptive detection threshold are adopted to effectively reduce the signal power loss. The performance of implemented NIEF is evaluated using real signals obtained by 12 bit GPS signal acquisition board. The output of NIEF is fed into the Software Defined Receiver to evaluate the acquisition and tracking performance. Experimental results shows that many types of interference such as single-tone CWI, AM, FM, swept CWI and multi-tones CWI are effectively mitigated with small signal power loss.

• Journal of KIISE
• /
• v.42 no.7
• /
• pp.910-918
• /
• 2015

This paper presents a parameter visualization technique to overcome the limitation of the naked eye in contrast-enhanced ultrasonography. A method is also proposed to compensate for the distortion and noise in ultrasound image sequences. Meaningful parameters for diagnosing liver disease can be extracted from the dynamic patterns of the contrast enhancement in ultrasound images. The visualization technique can provide more accurate information by generating a parametric image from the dynamic data. Respiratory motions and noise from micro-bubble in ultrasound data may cause a degradation of the reliability of the diagnostic parameters. A multi-stage algorithm for respiratory motion tracking and an image enhancement technique based on the Markov Random Field are proposed. The usefulness of the proposed methods is empirically discussed through experiments by using a set of clinical data.

• Smart Structures and Systems
• /
• v.24 no.5
• /
• pp.567-585
• /
• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.35-35
• /
• 2019

본 연구에서는 분포형 수문 모형 Drying Stream Assessment Tool and Water Flow Tracking (DrySAT-WTF)을 활용해 우리나라의 1976년부터 2015년까지의 유출량을 산정하고, 이를 다층퍼셉트론(Multi Layer Perceptron) 인경신경망 모형(Artificial Neural Network Model)에 적용해 미래 유출을 예측하였다. DrySAT-WFT은 전국 표준 유역을 대상으로 하천 건천화 원인 추적 및 평가를 위해 개발된 모형으로 유출모의를 위한 기상자료 외에 건천화 영향 요소를 고려하기 위한 산림 높이, 도로망, 지하수 이용량, 토지이용, 토심 변화에 대한 DB를 적용 가능한 것이 특징이다. DrySAT-WFT를 위한 기상자료로 모의 기간에 대한 일별 강우량, 상대습도, 평균풍속, 평균 및 최고, 최저 기온, 일조시간을 구축하였으며, 연대별 건천화 영향 요소 DB를 구축하여 적용하였다. 전국 다목적 댐 보 12지점의 유량을 활용해 모형의 보정(2005-2010) 및 검증(2011-2015)을 실시한 결과, 평균 결정계수(Coefficient of determination, $R^2$)는 0.76, 모형효율성계수(Nash-Sutcliffe efficiency, NSE)는 0.62, 평균제곱근오차(average root mean square error, RMSE)는 3.09로 신뢰성 있는 유출 모의 결과를 나타내었다. 미래 유출량 예측을 위한 MLP-ANN은 1976년부터 2015년까지의 유출 모의 결과를 Training Set으로 훈련하여 $R^2$가 0.5 이상이 되어 신뢰성을 확보하였고, 2016년부터 2018년까지의 기간을 1개월 단위로 실제 유출량과 예측 유출량을 비교하며 적용성을 검증 및 향상시켰다.

• Journal of the Optical Society of Korea
• /
• v.5 no.2
• /
• pp.55-59
• /
• 2001

Results of an experimental study of possible ways to extend the capabilities of a big size transmission type holographic screen are presented. Different approaches to the problem of making a big size screen have been considered and tested experimentally. Up to 60$\times$80 $\textrm{cm}^2$ screens have been recorded on a single photographic plate VRP-M. By attaching a mirror behind the screen, the reflection mode of operation has been obtained. In this arrangement some additional peculiarities appear in the screen, which can be used to extend the screen capabilities. The first possibility is to increase the screen size by mosaicking the subscreens in the reflection mode of operation. Screens of 120$\times$80 $\textrm{cm}^2$ and 180$\times$40 $\textrm{cm}^2$ have been obtained by proper alignment of 60$\times$40 $\textrm{cm}^2$ subscreens. The second possibility is to move the viewing Bone by rotation of the screen together with the mirror and thereby realize by the eye-tracking capability. Methods of increasing vertical size of the viewing zone have been considered. Along with the multi-exposure method, which was considered in previous papers, addition of the vertical diffuser with the optimized scattering angle has been tested experimentally. The vertical size of the viewing zone has been increased by up to 10-15 cm. Another method consists of usage of a diffraction grating with vertical dispersion to solve the same problem.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.5
• /
• pp.203-208
• /
• 2021

At the manufacturing site, workers have been operating by inputting materials into the manufacturing process and leaving input records according to the work instructions, but product LOT tracking has been not possible due to many omissions. Recently, it is being carried out as a system to automatically input materials using RFID-Tag. In particular, the initial automatic recognition rate was good at 97 percent by automatically generating input information through RACK (TAG) ID and RACK input time analysis, but the automatic recognition rate continues to decrease due to multi-material RACK, TAG loss, and new product input issues. It is expected that it will contribute to increasing speed and yield (normal product ratio) in the overall production process by improving automatic recognition rate and real-time monitoring through the establishment of artificial intelligent smart factory datasets.

• The Journal of Korean Institute of Information Technology
• /
• v.16 no.12
• /
• pp.49-56
• /
• 2018

As the era of the 4th industrial revolution comes, there is a growing interest in the use of UAVs. While various technologies are being developed using drones, controlling flight of drones is the most basic. Hovering control is essential in order to enable autonomous flight, especially during flight control of drones. In this paper, we design drones based on ATmega2560, Sonar, Optical Flow, and acceleration / gyro 6 axis sensor for drones hovering control, and developed horizontal control, altitude control, position tracking and fixed algorithm based on PID control. In this research, in order to measure the objective result of the drone, keeping the altitude immediately after the drone takes off according to the time, measure the movement value until the position is fixed and stable hovering is maintained and compared analyzed. Experimental results show that the drones can stably hover within 4cm horizontal and 2cm vertical from 50cm above the reference coordinates.