• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.866-870
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• 1995

To make a mobile robot to get to a goal point, path which connects the mobile robot and the goal point is needed and a path planning is necessary. There are various kinds of a path planning. Well known methods are skeleton method, cell decomposition method and potential field method. But each method has both fortes and defects. In this paper, we propose a new method of path planning to find a path for mobile robot. It is obtained by modifying a Voronoi diagram. An original Voronoi diagram can make a safe path but its result is not satisfied. First defect of path, finded by the original Voronoi diagram, is sulplus of safty which make a path longer. Second defect is that the original Voronoi diagram method has a problem of connecting the Voronoi daigram with start/goal point of mobile robot. These defects are removed in proposed algorithm in this paper. We define a function to show the quality of paths. And by computer simulation, paths are compared and its result are shown.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.1005-1011
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• 2004

Squeeze film dampers (SFDs) have been commonly used to effectively enhance the dynamic behavior of the rotating shaft supported by rolling element bearings. However, due to the recent trends of high operating speed, high load capacity and light weight in rotating machinery, it is becoming increasingly important to change the dynamic characteristics of rotating machines in operation so that the excessive vibrations, which may occur particularly when passing through critical speeds or unstable regions, can be avoided. Semi-active type SFDs using magneto-rheological fluid (MR fluid), which responds to an applied magnetic field with a change in rheoloaical behavior, are introduced in order to find its applications to rotating machinery as an effective device attenuating unbalance responses. In this paper, a semi-active SFD using MR fluid is designed, tested and identified by means of linear analysis to investigate the capability of changing its dynamic properties such as damping and stiffness. Furthermore, the proposed device is applied to a rotor system to investigate its potential capability for vibration attenuation: an efficient method for selecting the optimal location of the proposed damper is introduced and control algorithm that could improve the unbalance response properties of a flexible rotor is also proposed.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1138-1145
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• 2022

While pursuing digitalization and paperless projects, the construction industry needs to settle on how to make the most of digitized data and information. On-site workers, who currently rely on paper documents to check and review design and construction plans, will need alternative ways to efficiently access the information without using any paper. Augmented Reality is a potential solution where the information customized to a user is aligned with the physical world. This paper proposes the Augmented Reality framework to deliver the information on on-site resources (e.g., workers and equipment) using head-mounted devices. The proposed framework was developed by interoperating Augmented Reality-supported devices and a digital twin platform in which all information related to ongoing tasks is accumulated in real-time. On-site resources appearing in the user's field of view are automatically detected by an object detection algorithm and then assigned to the corresponding information by matching the data in the digital twin platform. Preliminary experiments show the feasibility of the proposed framework. Worker detection results can be visualized on HoloLens 2 in near real-time, and the matching process obtained the accuracy greater than 88%.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.107-114
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• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.

• Journal of Animal Environmental Science
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• v.20 no.3
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• pp.117-124
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• 2014

The objectives were to assess the use of near-infrared reflectance spectroscopy (NIRS) as a tool for estimating nutrient compositions of corn kernel, and to apply an NIRS-based indium gallium arsenide array detector to the system for collecting spectra and analyzing calibration equations using equipments designed for field application. Partial Least Squares Regression (PLSR) was employed to develop calibration equations based on representative data sets. The kennard-stone algorithm was applied to induce a calibration set and a validation set. As a result, the method for structuring a calibration set significantly affected prediction accuracy. The prediction of chemical composition of corn kernel resulted in the following (kennard-stone algorithm: relative) moisture ($R^2=0.82$, RMSEP=0.183), crude protein ($R^2=0.80$, RMSEP=0.142), crude fat ($R^2=0.84$, RMSEP=0.098), crude fiber ($R^2=0.74$, RMSEP=0.098), and crude ash ($R^2=0.81$, RMSEP=0.048). Result of this experiment showed the potential of NIRS to predict the chemical composition of corn kernel.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.351-357
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• 2022

Purpose: Convolutional neural networks (CNNs) have rapidly emerged as one of the most promising artificial intelligence methods in the field of medical and dental research. CNNs can provide an effective diagnostic methodology allowing for the detection of early-staged diseases. Therefore, this study aimed to evaluate the performance of a deep CNN algorithm for apical lesion segmentation from panoramic radiographs. Materials and Methods: A total of 1000 panoramic images showing apical lesions were separated into training (n=800, 80%), validation (n=100, 10%), and test (n=100, 10%) datasets. The performance of identifying apical lesions was evaluated by calculating the precision, recall, and F1-score. Results: In the test group of 180 apical lesions, 147 lesions were segmented from panoramic radiographs with an intersection over union (IoU) threshold of 0.3. The F1-score values, as a measure of performance, were 0.828, 0.815, and 0.742, respectively, with IoU thresholds of 0.3, 0.4, and 0.5. Conclusion: This study showed the potential utility of a deep learning-guided approach for the segmentation of apical lesions. The deep CNN algorithm using U-Net demonstrated considerably high performance in detecting apical lesions.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.233-237
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• 2006

3D travel time tomography was conducted to characterize the subsuface structure in the valley area. In this study, an area($200m{\times}200m$), where borehole informations were available to aid in the interpretation, was covered with wide source/receiver coverage. In data acquisition, both hole to hole and reverse VSP array was employed. For the inversion, 3D seismic traveltime tomography algorithm based on Fresnel volume was implemented. When compared 3D velocity cube with the geological survey and drilling logs, both results were matched well. From this, we concluded that 3D seismic travel time tomography has enough potential to the field application.

• Journal of the Society of Naval Architects of Korea
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• v.30 no.2
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• pp.43-53
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• 1993

There exist two difficulties in the nonlinear wave-body problems. First is the abrupt behavior near the intersection point between the body and the free surface, and second is the far field treatment. In this paper, the far field treatment is considered. The main idea is the Taylor series expansion of free-surface geometry and the application of F.F.T. algorithm. The numerical step is as follows. The velocity potential is expressed by the Green's theorem. and the solution is obtained by iteration method. In the iteration stage, the expressions by the Green's theorem are transformed to the convolution forts with the expansion of free surface by the wave slope. Here F.F.T. is applied, so the computing time can be of O(Nlog N) where N is the number of unknowns. The numerical analysis is carried out and the results are compared with other results in linear floating body problem and nonlinear moving pressure patch problem, and good agreements are obtained. Finally nonlinear floating body radiation problem is carried out with computing time of O(Nlog N).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.2
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• pp.159-167
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• 1992

This paper describes a feature extraction process by using a multi-layer neural network and is applied to the Korean stroke pattern for on line hand written character recognition, In the first layer the features are detected during the writing process and in the second layer the stroke specific features are extracted. A modified Masking field algorithm for direction co9nstancy has been used in this neural network and the resulting action potential of stroke specific features represents statistical distribution of the features in the on-line input stroke pattern and these results can be used in the recognition of on-line hand written Korean characters successfully.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.6
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• pp.812-819
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• 2012

Interference and jamming are becoming increasing concern to a radar system nowdays. AESA(Active Electronically Steered Array) antennas and adaptive beamforming(ABF), in which antenna beam patterns can be modified to reject the interference, offer a potential solution to overcome the problems encountered. In this paper, we've developed a planar active phased array radar system, in which ABF, target detection and tracking algorithm operate in real-time. For the high output power and the low noise figure of the antenna, we've designed the S-band TRMs based on GaN HEMT. For real-time processing, we've used wavelenth division multiplexing technique on fiber optic communication which enables rapid data communication between the antenna and the signal processor. Also, we've implemented the HW and SW architecture of Real-time Signal Processor(RSP) for adaptive beamforming that uses SMI(Sample Matrix Inversion) technique based on MVDR(Minimum Variance Distortionless Response). The performance of this radar system has been verified by near-field and far-field tests.