• Structural Engineering and Mechanics
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• v.5 no.4
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• pp.471-490
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• 1997

In this paper, the classical Irons' patch tests which have been generally accepted for the convergence proof of a finite element are performed for Mindlin plate bending elements with a special emphasis on the nonconforming elements. The elements considered are 4-node and 8-node quadrilateral isoparametric elements which have been dominantly used for the analyses of plate bending problems. It was recognized from the patch tests that some nonconforming Mindlin plate elements pass all the cases of patch tests even though nonconforming elements do not preserve conformity. Then, the clues for the Mindlin plate element to pass the Irons' patch tests are investigated. Also, the convergent characteristics of some nonconforming Mindlin plate elements that do not pass the Irons' patch tests are examined by weak patch tests. The convergence tests are performed on the benchmark numerical problems for both nonconforming elements which pass the patch tests and which do not. Some conclusions on the relationship between the patch test and convergence of nonconforming Mindlin plate elements are drawn.

• ETRI Journal
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• v.37 no.2
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• pp.251-261
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• 2015

We present a novel method for real-time automatic license plate detection in high-resolution videos. Although there have been extensive studies of license plate detection since the 1970s, the suggested approaches resulting from such studies have difficulties in processing high-resolution imagery in real-time. Herein, we propose a novel cascade structure, the fastest classifier available, by rejecting false positives most efficiently. Furthermore, we train the classifier using the core patterns of various types of license plates, improving both the computation load and the accuracy of license plate detection. To show its superiority, our approach is compared with other state-of-the-art approaches. In addition, we collected 20,000 images including license plates from real traffic scenes for comprehensive experiments. The results show that our proposed approach significantly reduces the computational load in comparison to the other state-of-the-art approaches, with comparable performance accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2509-2528
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• 2019

There are various styles of license plates for different countries and use cases that require style-specific methods. In this paper, we propose and illustrate a multi-style license plate recognition system. The proposed system performs a series of processes for license plate candidates detection, structure classification, character segmentation and character recognition, respectively. Specifically, we introduce a license plate structure classification process to identify its style that precedes character segmentation and recognition processes. We use a K-Nearest Neighbors algorithm with pre-training steps to recognize numbers and characters on multi-style license plates. To show feasibility of our multi-style license plate recognition system, we evaluate our system for multi-style license plates covering single line, double line, different backgrounds and character colors on Korean and the U.S. license plates. For the evaluation of Korean license plate recognition, we used a 50 minutes long input video that contains 138 vehicles of 6 different license plate styles, where each frame of the video is processed through a series of license plate recognition processes. From two experiments results, we show that various LP styles can be recognized under 50 ms processing time and with over 99% accuracy, and can be extended through additional learning and training steps.

• Journal of Advanced Technology Convergence
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• v.2 no.4
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• pp.7-11
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• 2023

In this study, we presented a method to recognize vehicle license plates using CNN techniques. A vehicle plate is normally used for the official identification purposes by the authorities. Most regular Optical Character Recognition (OCR) techniques perform well in recognizing printed characters on documents but cannot make out the registration number on the number plates. Besides, the existing approaches to plate number detection require that the vehicle is stationary and not in motion. To address these challenges to number plate detection we make the following contributions. We create a database of captured vehicle number plate's images and recognize the number plate character using Convolutional Neural Networks. The results of this study can be usefully used in parking management systems and enforcement cameras.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.4
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• pp.175-181
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• 2018

Stamping process and rubber pad forming process were performed to manufacture the bipolar plate for fuel cells. For that, a vacuum die casting process and a semi-solid forming process wherein liquid-state materials were used were adopted. After preparing the blank with the stainless steel thin plate having a thickness of 0.1 mm, the bipolar plate channel was formed with the stamping process and rubber pad forming process. The depth of the bipolar plate channel prepared by the stamping method was 0.45 mm and the depth of the bipolar plate channel prepared by the rubber pad forming process was 0.41 mm. Meanwhile, with the vacuum die casting and semi solid forming, the bipolar plate having a channel depth of 0.3 mm, same as the size of the die, could be formed.

• Structural Engineering and Mechanics
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• v.5 no.1
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• pp.69-83
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• 1997

A new efficient hybrid/mixed thin~moderately thick plate bending element with 6-node (HM6-14) is formulated based on the Reissner-Mindlin plate bending theory. The convergence of this element is proved by error estimate theories and verified by patch test respectively. Numerical studies on such an element as HM6-14 demonstrate that it has remarkable convergence, invariability to geometric distorted mesh situations, to axial rotations, and to node positions, and no "locking" phenomenon in thin plate limit. The present element is suitable to many kinds of shape and thin~moderately thick plate bending problems. Further, in comparison with original hybrid/mixed plate bending element HP4, the present element yields an improvement of solutions. Therefore, it is an efficient element and suitable for the development of adaptive multi-field finite element method (FEM).

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.12
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• pp.1153-1160
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• 2010

A circular plate is the main part of a circular saw blade, which is widely used in industrial cutting tools. In experiments using a circular saw containing slots, we observed that a number of natural frequencies are simultaneously emerged in specific frequency regions. The interesting phenomenon is called the frequency convergence. Effects of design parameters such as the number, the length and the width of slots, on the frequency-convergence phenomenon are analyzed by FEM simulations using ALGOR. The frequency-convergence phenomenon will be intensified when the number, length and width of slots increase.

• Korean Journal of Optics and Photonics
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• v.32 no.5
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• pp.220-229
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• 2021

The optical characteristics of high-power direct-lit white light-emitting diode (LED) lighting were investigated, where a quantum dot (QD) film was adopted to enhance the color-rendering index (CRI). The transmittance of the diffuser plate and the concentration of the QD film were varied in this study. The color coordinates and the correlated color temperature (CCT) did not show any appreciable change, while the CRI values increased slightly as the transmittance of the diffuser plate decreased. The investigated optical properties were nearly independent of the viewing angle, and the luminance distribution was close to Lambertian. The CCT decreased from approximately 6000 K to approximately 4000 K as the concentration of the QD film increased from 0 to 7.5 wt%, which was due to the enhanced red component in the emission spectrum. The CRI increased to approximately 95 for some optical configurations of the lighting. These results demonstrate that glare-free, color-changeable, high-rendering LED lighting can be realized by using a combination of a diffuser plate of appropriate transmittance and a red QD film.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.699-706
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• 2021

Existing license plate recognition system is used as an optical character recognition method, but a method of using deep learning has been proposed in recent studies because it has problems with image quality and Korean misrecognition. This requires a lot of data collection, but the collection of license plates is not easy to collect due to the problem of the Personal Information Protection Act, and labeling work to designate the location of individual license plates is required, but it also requires a lot of time. Therefore, in this paper, to solve this problem, five types of license plates were created using a virtual Korean license plate generation program according to the notice of the Ministry of Land, Infrastructure and Transport. And the generated license plate is synthesized in the license plate part of collectable vehicle images to construct 10,147 learning data to be used in deep learning. The learning data classifies license plates, Korean, and numbers into individual classes and learn using YOLOv5. Since the proposed method recognizes letters and numbers individually, if the font does not change, it can be recognized even if the license plate standard changes or the number of characters increases. As a result of the experiment, an accuracy of 96.82% was obtained, and it can be applied not only to the learned license plate but also to new types of license plates such as new license plates and eco-friendly license plates.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.661-680
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• 2016

The vehicle license plate recognition (VLPR) system analyzes and monitors the speed of vehicles, theft of vehicles, the violation of traffic rules, illegal parking, etc., on the motorway. The VLPR consists of three major parts: license plate detection (LPD), license plate character segmentation (LPCS), and license plate character recognition (LPCR). This paper presents an efficient method for the LPCS and LPCR of Korean vehicle license plates (LPs). LP tilt adjustment is a very important process in LPCS. Radon transformation is used to correct the tilt adjustment of LP. The global threshold segmentation method is used for segmented LP characters from two different types of Korean LPs, which are a single row LP (SRLP) and double row LP (DRLP). The cross-correlation matching method is used for LPCR. Our experimental results show that the proposed methods for LPCS and LPCR can be easily implemented, and they achieved 99.35% and 99.85% segmentation and recognition accuracy rates, respectively for Korean LPs.