• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.859-868
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• 2016

This paper proposes a new global positioning system (GPS) receiver algorithm to improve the positioning accuracy of a transporter using fault detection and isolation techniques from satellite signals. To improve the positioning accuracy, several factors including a feasible number of satellite signals, SNR, NAV Measurement Quality Indicator (mesQI), and Doppler, among others, have been utilized in the proposed algorithm. To increase the number of feasible satellite signals, an erroneous satellite signal has been replaced by the previous one. In conventional approaches, received GPS signals are analyzed and directly determined to be contaminated or not. The only clean signals are utilized for identifying the current location. This fault detection and isolation (FDI) feasibility test is popular for commercial GPS receivers. In the urban environment, especially near a building, the feasible number of satellite signals becomes insufficient to position the transporter. To overcome this problem, satellite signals are efficiently selected and recovered. Additionally, using the proposed GPS receiver algorithm, a feasible number of satellite signals can be increased, thereby improving the positional accuracy. Real world experiments using a transporter that carries blocks in a shipyard have demonstrated the superiority of the proposed algorithm compared to conventional approaches.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.211-217
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• 2019

Location positioning systems are available in applications such as mobile, robotic tracking systems and Wireless location-based service (LBS) applications. The GPS system is the most well-known location tracking system, but it is not easy to use indoors. The method of radio frequency identification (RFID) location tracking was studied in terms of cost-effectiveness for indoor location tracking systems. Most RFID systems use active RFID tags using expendable batteries, but in this paper, an inexpensive indoor location tracking system using passive RFID tags has been developed. A pattern matching method and a system for tracing location by generating regression curves were studied to use precision tracking algorithms. The system was tested by verifying the level of error caused by noise. The three-dimensional curves are produced by the regression equation estimated the statistically meaningful coordinates by the differential equation. The proposed system could also be applied to mobile robot systems, AGVs and mobile phone LBSs.

• The Journal of the Acoustical Society of Korea
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• v.40 no.6
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• pp.578-586
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• 2021

We propose a semi-supervised learning method based on Variational AutoEncoder (VAE) and Unsupervised Data Augmentation (UDA) to improve the performance of an end-to-end speech recognizer. In the proposed method, first, the VAE-based augmentation model and the baseline end-to-end speech recognizer are trained using the original speech data. Then, the baseline end-to-end speech recognizer is trained again using data augmented from the learned augmentation model. Finally, the learned augmentation model and end-to-end speech recognizer are re-learned using the UDA-based semi-supervised learning method. As a result of the computer simulation, the augmentation model is shown to improve the Word Error Rate (WER) of the baseline end-to-end speech recognizer, and further improve its performance by combining it with the UDA-based learning method.

• Journal of Internet of Things and Convergence
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• v.10 no.4
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• pp.43-53
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• 2024

Tomatoes are rich in nutrients like lycopene, β-carotene, and vitamin C. However, they often suffer from biological and environmental stressors, resulting in significant yield losses. Traditional manual plant health assessments are error-prone and inefficient for large-scale production. To address this need, we collected a comprehensive dataset covering the entire life span of tomato plants, annotated across 5 health states from 1 to 5. Our study introduces an Attention-Enhanced DS-ResNet architecture with Channel-wise attention and Grouped convolution, refined with new training techniques. Our model achieved an overall accuracy of 80.2% using 5-fold cross-validation, showcasing its robustness in precisely classifying the health states of tomato plants.

• Journal of the Korea Society for Simulation
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• v.26 no.2
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• pp.41-49
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• 2017

In the acquisition program, the conceptual design is the most important step toward specifying the military objectives, establishing requirements and determining future developmental directions, of a target system. However, if both the requirements and directions are incorrectly set due to the lack of development experiences and literature backgrounds in the target systems, such as future ground combat vehicles, it may become a major risk in the future design phases and the entire acquisition program. In order to correct these errors in the future phases, time, effort and cost are required. Therefore, it is necessary to reduce the errors that occur in the initial stages to effectively acquire the future ground combat vehicles. This paper describes the initial design method for verifying the requirements and the developmental directions and estimating the system performance at the conceptual design through the system-level physical modeling and simulation (M&S) and the target system performance analysis. The system-level physical M&S use cutting-edge design tools, model-based designs and geometric-based designs. The system performance estimation is driven from the results of the system-level physical M&S and the specialized system analysis software.

• Journal of Internet Computing and Services
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• v.7 no.3
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• pp.31-39
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• 2006

Ubiquitous and pervasive environment presents opportunities for a rich set of location aware applications such as car navigation and intelligent robots, interactive virtual games, logistics service, asset tracking etc. Typical indoor location systems require better accuracy than what current outdoor location systems provide, Outdoor location technologies such as GPS have poor indoor performance because of the harsh nature of indoor environments, In this paper we present a novel reducing interference location system that is particularly well suited to support context aware computing. The system, called EEM (Enhance Envelop Method) alms to combine the advantages of real time tracking systems that implement distributed environment with the suitability of infrastructure sensor network.

• The KIPS Transactions:PartD
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• v.12D no.7 s.103
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• pp.931-936
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• 2005

There may be subtle errors in embedded software since its functionality is very complex. Thus formal verification for detecting them is very needed. Model checking is one of formal verification techniques, and SLAM is a well-known software model checking tool for verifying safety properties of embedded C program. In this paper, we develop a software model checker like SLAM for verifying embedded Java program Compared to SLAM, our tool allows to verify liveness properties as well as safety ones. As a result, we verify some desired properties in embedded Java program for controlling REGO robot.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.2913-2918
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• 2011

This paper proposed the friction model using Preisach algorithm with neural network based on experimental results. In order to apply the neural network algorithm, the back propagation update rule was used and the updated weighting factor of neural network was applied to distribute function of Preisach model. In order to implement the proposed algorithm, the LabView software was used to apply to the precision control of mechanical system. The evaluation of the proposed friction model was executed through experiments.

• Journal of Korea Game Society
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• v.10 no.6
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• pp.157-168
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• 2010

A terrain is an essential element for constructing a virtual world in which game characters and objects make various interactions with one another. Creating a terrain requires a great deal of time and repetitive editing processes. This paper presents a 3D terrain reconstruction system to create 3D terrain in virtual space based on real terrain data. In this system, it converts the coordinate system of the height maps which are generated from a stereo camera and a laser scanner from global GPS into 3D world using the x and z axis vectors of the global GPS coordinate system. It calculates the movement vectors and the rotation matrices frame by frame. Terrain meshes are dynamically generated and rendered in the virtual areas which are represented in an undirected graph. The rendering meshes are exactly created and updated by correcting terrain data errors. In our experiments, the FPS of the system was regularly checked until the terrain was reconstructed by our system, and the visualization quality of the terrain was reviewed. As a result, our system shows that it has 3 times higher FPS than other terrain management systems with Quadtree for small area, improves 40% than others for large area. The visualization of terrain data maintains the same shape as the contour of real terrain. This system could be used for the terrain system of realtime 3D games to generate terrain on real time, and for the terrain design work of CG Movies.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.115-123
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• 2018

Various types of robots running on power transmission lines have been developed for the purpose of line patrol monitoring. They usually have complex mechanism to run and avoid obstacles on the power line, but nevertheless did not show satisfactory performance for going over the obstacles. Moreover, they were so heavy that they could not be easily installed on the lines. To compensate these problems, flying robots have been developed and recently, multi-copter drones with flight stability have been used in the electric power industry. The drones could be remotely controlled by human operators to monitor power distribution lines. In the case of transmission line patrol, however, transmission towers are huge and their spans are very long, and thus, it is very difficult for the pilot to control the patrol drones with the naked eye from a long distance away. This means that the risk of a drone crash onto electric power facilities always resides. In addition, there exists another danger of electromagnetic interference with the drones on autopilot waypoint tracking under ultra-high voltage environments. This paper presents a patrol monitoring plan of autopilot drones for power transmission lines and its field tests. First, the magnetic field effect on an autopilot patrol drone is investigated. Then, how to build the flight path to avoid the magnetic interference is proposed and our autopilot drone system is introduced. Finally, the effectiveness of the proposed patrol plan is confirmed through its field test results in the 154 kV, 345 kV and 765 kV transmission lines in Chungcheongnam-do.