• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1271-1278
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• 2018

The NDT using ultrasonic is largely divided into A-Scan and C-Scan methods. Since A-Scan method is subject to subjective judgement by trained personnel, C-Scan method has been introduced, which presents the weld area in two dimensions by placing the transducers two dimensionally used in the A-Scan method. Therefore, it is necessary to develop equipment that can provide weld quality without the help of a welding expert and the presentation of effective C-Scan images. Thus, in this paper, the algorithms that express a low resolution 2-dimensional gray image formed by C-Scan method as a high-resolution color C-Scan image and automatically determine the weld quality from the generated C-Scan color image. The high resolution color C-Scan images proposed in this paper allow the exact shape of the weld point to be expressed, and an objective algorithm to use this image to automatically determine weld quality.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.386-394
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• 2019

This research will describe algorithm for class diagram extraction from problem statements. Class diagram notation consist of class name, attributes, and operations. Class diagram can be extracted from the problem statement automatically by using Natural Language Processing (NLP). The extraction results heavily depends on the algorithm and preprocessing stage. The algorithm obtained from various sources with additional rules that are obtained in the implementation phase. The evaluation features using five problem statement with different domains. The application will capture the problem statement and draw the class diagram automatically by using Windows Presentation Foundation(WPF). The classification accuracy of 100% was achieved. The final algorithm achieved 92 % of average precision score.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.47-54
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• 2019

This study is concerned with the mechanism and structure of an optical microscope and an automatic multi-focus algorithm for automatically selecting sharp images from multiple foci of a cell. To obtain precise cell images quickly, a z-axis actuator with a resolution of $0.1{\mu}m$ was designed to control an optical microscope Moreover, a lighting control system was constructed to select the color and brightness of light that best suit the object being viewed. Cell images are captured by the instrument and the sharpness of each image is determined using Gaussian and Laplacian filters. Next, cubic spline interpolation and peak detection algorithms are applied to automatically find the most vivid points among multiple images of a single object. A cancer cell imaging experiment using propidium iodide staining confirmed that a sharp multipoint image can be obtained using this microscope. The proposed system is expected to save time and effort required to extract suitable cell images and increase the convenience of cell analysis.

• Computers and Concrete
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• v.24 no.5
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• pp.437-444
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• 2019

PLC and its expansion module, electric ball valve and cooling pipe, electric heating steel plate and various components of the system, which is used to control test and process data. By automatically adjusting the opening of the valve, the system makes the top temperature and cooling speed develop along the ideal temperature diachronic curve. Moreover, the system enables the temperature difference between inside and surface of test block limited in a given range by automatically controlling the surface board heating. The method of physical simulation test by sandbox with built-in cooling water pipe and heating rod is adopted. On the premise of a given standard value, the operation of the system is checked under different working conditions. Further, an extension of this system is proposed, which enables its application to obtain some thermal parameters when cooperating with numerical simulation.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.1
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• pp.1-7
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• 2021

In this paper, we presented the experimental basis for the theoretical background and robustness of the Convolutional Neural Network for object recognition based on artificial intelligence. An experimental result was performed to visualize the weighting filters and feature maps for each layer to determine what characteristics CNN is automatically generating. experimental results were presented on the trend of learning error and identification error rate by checking the relevance of the weight filter and feature map for learning error and identification error. The weighting filter and characteristic map are presented as experimental results. The automatically generated characteristic quantities presented the results of error rates for moving and rotating robustness to geometric changes.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.203-208
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• 2020

In this paper, we propose the design and implementation of a desktop LED stand and smart app that automatically adjusts color temperature and illuminance for optimal brightness and eye health by improving the structural problem of the LED stand. It is a tabletop LED stand that supports optimal brightness through color temperature control and heat transfer through infrared LED to relieve eye strain through blood circulation and muscle movement. The LED stand works with the smartphone to automatically adjust the optimal brightness and color temperature for the user's environment. In addition, the brightness of the infrared LED is adjusted to a living frequency of 4Hz to relax the eye muscles and reduce eye strain. This study implemented an effective measured data-based system of previous studies through the color temperature and illumination of LED lighting, and near-infrared rays, and presented meaningful results by conducting an experiment to prove the effect through subjects.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.33-45
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• 2023

This paper proposes an algorithm that automatically converts images into Pipo, painting images using OpenCV-based image processing technology. The existing "purity," "palm," "puzzling," and "painting," or Pipo, painting image production method relies on manual work, so customized production has the disadvantage of coming with a high price and a long production period. To resolve this problem, using the OpenCV library, we developed a technique that automatically converts an image into a Pipo painting image by designing a module that changes an image, like a picture; draws a line based on a sector boundary; and writes sector numbers inside the line. Through this, it is expected that the production cost of customized Pipo painting images will be lowered and that the production period will be shortened.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.847-854
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• 2022

The aim of this study is to develop a Named Entity Recognition (NER) model to automatically identify construction-related organizations from news articles. This study collected news articles using web crawling technique and construction-related organizations were labeled within a total of 1,000 news articles. The Bidirectional Encoder Representations from Transformers (BERT) model was used to recognize clients, constructors, consultants, engineers, and others. As a pilot experiment of this study, the best average F1 score of NER was 0.692. The result of this study is expected to contribute to the establishment of international business strategies by collecting timely information and analyzing it automatically.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.686-688
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• 2021

The performance assessment in real sea is very important to increase the reliability of the fishing gear automatically identification monitoring system. The concept of real sea experiment for fishing gear automatically identification monitoring system is introduced and results of communication performance of RoLa and LTE Cat.M1 modules are reported through this research.

• Journal of Drive and Control
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• v.19 no.1
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• pp.1-7
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• 2022

Recently, a re-painting robot was developed to semi-automatically conduct blasting work in bridge spaces to improve work productivity and worker safety. In this study, a vision sensor-based monitoring module was developed to automatically move the re-painting robot along the path. The monitoring module provides direction information to the robot by analyzing the boundary between the painting surface and the metal surface. To stably measure images in unstable environments, various techniques for improving image visibility were applied in this study. Then, the driving performance was verified in a similar environment.