• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.3
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• pp.72-81
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• 2022

Positions of five drifting buoys deployed on August 2020 near southwestern area of Jeju Island and numerically predicted velocities were used to develop five Artificial Intelligence-based models (AI models) for the prediction of particle tracks. Five AI models consisted of three machine learning models (Extra Trees, LightGBM, and Support Vector Machine) and two deep learning models (DNN and RBFN). To evaluate the prediction accuracy for six models, the predicted positions from five AI models and one numerical model were compared with the observed positions from five drifting buoys. Three skills (MAE, RMSE, and NCLS) for the five buoys and their averaged values were calculated. DNN model showed the best prediction accuracy in MAE, RMSE, and NCLS.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.251-259
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• 2023

In the path traveling of differential-drive robots, the steering controller plays an important role in determining the path-following performance. When a robot with a pure-pursuit algorithm is used to continuously drive a right-angled driving path in an unstructured environment without turning in place, the robot cannot accurately follow the right-angled path and stops driving due to the ground and motor load caused by turning. In the case of pure-pursuit, only the current robot position and the steering angle to the current target path point are generated, and the steering component does not reflect the speed plan, which requires improvement for precise path following. In this study, we propose a driving algorithm for differentially driven robots that enables precise path following by planning the driving speed using the radius of curvature and fusing the planned speed with the steering angle of the existing pure-pursuit controller, similar to the Model Predict Control control that reflects speed planning. When speed planning is applied, the robot slows down before entering a right-angle path and returns to the input speed when leaving the right-angle path. The pure-pursuit controller then fuses the steering angle calculated at each path point with the accelerated and decelerated velocity to achieve more precise following of the orthogonal path.

• Smart Media Journal
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• v.11 no.9
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• pp.64-74
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• 2022

A number of studies related to underwater robots are being conducted to utilize marine resources. However, unlike ordinary drones, underwater robots have a problem that it is not easy to locate because the medium is water, not air. The monitoring and positioning program of underwater robots, an existing study for identifying underwater locations, has difficulty in locating and monitoring in small spaces because it aims to be utilized in large spaces. Therefore, in this paper, we propose a three-dimensional positioning program for continuous monitoring and command delivery in small spaces. The proposed program consists of a multi-dimensional positioning monitoring function and a ability to control the path of travel through a three-dimensional screen so that the depth of the underwater robot can be identified. Through the performance evaluation, a robot underwater could be monitored and verified from various angles with a 3D screen, and an error within the assumed range was verified as the difference between the set path and the actual position is within 6.44 m on average.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.150-159
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• 2022

This paper presents an implementation of detecting whether a helmet is worn and there is a fall accident through individual image analysis in real-time from extracting the image objects of several workers active in the industrial field. In order to detect image objects of workers, YOLO, a deep learning-based computer vision model, was used, and for whether a helmet is worn or not, the extracted images with 5,000 different helmet learning data images were applied. For whether a fall accident occurred, the position of the head was checked using the Pose real-time body tracking algorithm of Mediapipe, and the movement speed was calculated to determine whether the person fell. In addition, to give reliability to the result of a falling accident, a method to infer the posture of an object by obtaining the size of YOLO's bounding box was proposed and implemented. Finally, Telegram API Bot and Firebase DB server were implemented for notification service to administrators.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.185-193
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• 2022

This paper proposes an adaptive sliding mode control with radial basis function neural network(RBFNN) scheme to enhance the performance of position and attitude tracking control of quadrotor UAV. The RBFNN is utilized on the approximation of nonlinear function in the UAV dynmic model and the weights of the RBFNN are adjusted online according to adaptive law from the Lyapunov stability analysis to ensure the state hitting the sliding surface and sliding along it. In order to compensate the network approximation error and eliminate the existing chattering problems, the sliding mode control term is adjusted by adaptive laws, which can enhance the robust performance of the system. The simulation results of the proposed control method confirm the effectiveness of the proposed controller which applied for a nonlinear quadrotor UAV is presented. Form the results, it's shown that the developed control system is achieved satisfactory control performance and robustness.

• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.247-257
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• 2023

Precise counting of cell number stands in important position within clinical and research laboratories. Conventional methods such as hemocytometer, migration/invasion assay, or automated cell counters have limited in analytical time, cost, and accuracy., which needs an alternative way with time-efficient in-situ approach to broaden the application avenue. Here, we present simple coding-based cell counting method using image analysis tool, freely available image software (ImageJ). Firstly, we encapsulated RFP-expressing bacteria in a droplet using microfluidic device and automatically performed fluorescence image-based analysis for the quantification of cell numbers. Also, time-lapse images were captured for tracking the change of cell numbers in a droplet containing different concentrations of antibiotics. This study confirms that our approach is approximately 15 times faster and provides more accurate number of cells in a droplet than the external analysis program method. We envision that it can be used to the development of high-throughput image-based cell counting analysis.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.179-186
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• 2009

In this paper, we propose a head detection method based on vertical and horizontal pixel histogram analysis in order to overcome drawbacks of the previous head detection approach using Haar-like feature-based face detection. In the proposed method, we create the vertical and horizontal foreground pixel histogram images from the background subtraction image, which represent the number of foreground pixels in the same vertical or horizontal position. Then we extract feature points of a head region by applying Harris corner detection method to the foreground pixel histogram images and by analyzing corner points. The proposal method shows robust head detection results even in the face image covering forelock by hairs or the back view image in which the previous approaches cannot detect the head regions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.579-586
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• 2008

In this study, it was evaluated that the 3D tracking accuracy of basketball zone track line by real time GNSS satellite positioning methods which are VRS (Virtual Reference System), DGPS (Marine Differential GPS) and PP (Point Positioning) methods. The results of comparison between three methods over horizontal track of basketball zone, VRS, DGPS and PP methods showed ${\pm}$ several cm, ${\pm}$ m, and ${\pm}$ 2m horizontal position accuracy compared with real size respectively. And also, the grade and height deviation of the checking points on basketball zone by VRS method is very similar to the real grade and height, but results by DGPS and PP methods showed big variation and deviation in each case. We expected that VRS method using GNSS reference network will be a very useful tool compared with single based RTK method in real time accurate positioning such as precision construction fields, especially.

• Geophysics and Geophysical Exploration
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• v.8 no.4
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• pp.270-279
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• 2005

Under the research project supported by Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), we have conducted the development of GPR systems for landmine detection. Until 2005, we have finished development of two prototype GPR systems, namely ALIS (Advanced Landmine Imaging System) and SAR-GPR (Synthetic Aperture Radar-Ground Penetrating Radar). ALIS is a novel landmine detection sensor system combined with a metal detector and GPR. This is a hand-held equipment, which has a sensor position tracking system, and can visualize the sensor output in real time. In order to achieve the sensor tracking system, ALIS needs only one CCD camera attached on the sensor handle. The CCD image is superimposed with the GPR and metal detector signal, and the detection and identification of buried targets is quite easy and reliable. Field evaluation test of ALIS was conducted in December 2004 in Afghanistan, and we demonstrated that it can detect buried antipersonnel landmines, and can also discriminate metal fragments from landmines. SAR-GPR (Synthetic Aperture Radar-Ground Penetrating Radar) is a machine mounted sensor system composed of B GPR and a metal detector. The GPR employs an array antenna for advanced signal processing for better subsurface imaging. SAR-GPR combined with synthetic aperture radar algorithm, can suppress clutter and can image buried objects in strongly inhomogeneous material. SAR-GPR is a stepped frequency radar system, whose RF component is a newly developed compact vector network analyzers. The size of the system is 30cm x 30cm x 30 cm, composed from six Vivaldi antennas and three vector network analyzers. The weight of the system is 17 kg, and it can be mounted on a robotic arm on a small unmanned vehicle. The field test of this system was carried out in March 2005 in Japan.

• Korean Security Journal
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• no.21
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• pp.155-175
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• 2009

RFID that provide automatic identification by reading a tag attached to material through radio frequency without direct touch has some specification, such as rapid identification, long distance identification and penetration, so it is being used for distribution, transportation and safety by using the frequency of 125KHz, 134KHz, 13.56MHz, 433.92MHz, 900MHz, and 2.45GHz. Also it is one of main part of Ubiquitous that means connecting to net-work any time and any place they want. RFID is expected to be new growth industry worldwide, so Korean government think it as prospective field and promote research project and exhibition business program to linked with industry effectively. RFID could be used for access control of person and vehicle according to section and for personal certify with password. RFID can provide more confident security than magnetic card, so it could be used to prevent forgery of register card, passport and the others. Active RFID could be used for protecting operation service using it's long distance date transmission by application with positioning system. And RFID's identification and tracking function can provide effective visitor management through visitor's register, personal identification, position check and can control visitor's movement in the secure area without their approval. Also RFID can make possible of the efficient management and prevention of loss of carrying equipments and others. RFID could be applied to copying machine to manager and control it's user, copying quantity and It could provide some function such as observation of copy content, access control of user. RFID tag adhered to small storage device prevent carrying out of item using the position tracking function and control carrying-in and carrying-out of material efficiently. magnetic card and smart card have been doing good job in identification and control of person, but RFID can do above functions. RFID is very useful device but we should consider the prevention of privacy during its application.