• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1026-1031
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• 2021

With the development of global automotive technology and the expansion of market size, demand for vehicles is increasing, which is leading to a decrease in the number of passengers on the road and an increase in the number of vehicles on the road. This causes traffic jams, and in order to solve these problems, the number of illegal vehicles continues to increase. Various technologies are being studied to crack down on these illegal activities. Previously developed systems use trigger equipment to recognize vehicles and photograph vehicles using infrared cameras to detect the number of passengers on board. In this paper, we propose a vehicle occupant detection system with deep learning model techniques without exploiting existing system-applied trigger equipment. The proposed technique proposes a system to detect vehicles by establishing triggers within images and to apply deep learning object recognition models to detect real-time boarding personnel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1053-1059
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• 2021

In order to realize a smart home, a new type of service that converges the two technologies is required as a method to overcome the respective limitations of augmented reality and IoT technologies. Augmented reality recognizes objects and projects augmented content with the recognized objects on the screen. This technology mainly uses image processing methods such as markers as a method for recognizing objects. In this paper, an augmented reality-based IoT control platform using markers was developed. By defining a marker unique to the object, a unique identifier displayed on the camera was distinguished. A smart home system was implemented by calling a controller to control things. The proposed system receives state information of objects through symptom reality and transmits control commands. The proposed platform was verified by manipulating household lights.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.308-312
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• 2022

3D printing technology, which creates a physical object by various material deposition, has been widely used in recent years in the manufacturing field because of its advantages. Among the various printing technologies, droplet-based 3D printing technology (e.g., Polyjet^®) enables a high-resolution printing using photocurable materials such as hydrogels. Depending on the degree of light exposure, ejected photocurable droplets may have different properties (e.g., viscosity) until they collide with the substrate and it leads to the different spreading behaviors of the droplets (i.e., impact, spreading, and recoiling) during deposition on the substrate. In this study, experimental observation and analysis of the changes in hydrogel droplet viscosity and spreading behavior according to the light exposure were carried out based on high-speed image processing.

• Journal of Information Technology Services
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• v.21 no.2
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• pp.97-107
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• 2022

Recently, interest in smart factories is increasing. Investments to improve intelligence/automation are also being made continuously in manufacturing plants. Facility automation based on sensor data collection is now essential. In addition, we are operating our factories based on data generated in all areas of production, including production management, facility operation, and quality management, and an integrated standard information system. When producing LCD polarizer products, it is most important to link trace information between data generated by individual production processes. All systems involved in production must ensure that there is no data loss and data integrity is ensured. The large-capacity data collected from individual systems is composed of key values linked to each other. A real-time quality analysis processing system based on connected integrated system data is required. In this study, large-capacity data collection, storage, integration and loss prevention methods were presented for optimization of LCD polarizer production. The identification Risk model of inspection products can be added, and the applicable product model is designed to be continuously expanded. A quality inspection and analysis system that maximizes the yield rate was designed by using the final inspection image of the product using big data technology. In the case of products that are predefined as analysable products, it is designed to be verified with the big data knn analysis model, and individual analysis results are continuously applied to the actual production site to operate in a virtuous cycle structure. Production Optimization was performed by applying it to the currently produced LCD polarizer production line.

• Journal of The Korean Astronomical Society
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• v.55 no.4
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• pp.111-121
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• 2022

Based on the light an exoplanet blocks from its host star as it passes in front of it during a transit, the mid-transit time can be determined. Periodic variations in mid-transit times can indicate another planet's gravitational influence. We investigate 83 transits of TrES-1 b as observed from 6-inch telescopes in the MicroObservatory robotic telescope network. The EXOTIC data reduction pipeline is used to process these transits, fit transit models to light curves, and calculate transit midpoints. This paper details the methodology for analyzing transit timing variations (TTVs) and using transit measurements to maintain ephemerides. The application of Lomb-Scargle period analysis for studying the plausibility of TTVs is explained. The analysis of the resultant TTVs from 46 transits from MicroObservatory and 47 transits from archival data in the Exoplanet Transit Database indicated the possible existence of other planets affecting the orbit of TrES-1 and improved the precision of the ephemeris by one order of magnitude. We now estimate the ephemeris to be (2 455 489.66026 BJD_TDB ± 0.00044 d) + (3.0300689 ± 0.0000007) d × epoch. This analysis also demonstrates the role of small telescopes in making precise midtransit time measurements, which can be used to help maintain ephemerides and perform TTV analysis. The maintenance of ephemerides allows for an increased ability to optimize telescope time on large ground-based telescopes and space telescope missions.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.113-118
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• 2022

Motivated by people highlighting important phrases while reading or taking notes we propose a neural network training method by highlighting defective pixel areas to classify effectively defect types of images with complex background textures. To verify our proposed method we apply it to the problem of classifying the defect types of tire band fabric images that are too difficult to classify. In addition we propose a backlight highlighting technique which is tailored to the tire band fabric images. Backlight highlighting images can be generated by using both the GradCAM and simple image processing. In our experiment we demonstrated that the proposed highlighting method outperforms the traditional method in the view points of both classification accuracy and training speed. It achieved up to 13.4% accuracy improvement compared to the conventional method. We also showed that the backlight highlighting technique tailored for highlighting tire band fabric images is superior to a contour highlighting technique in terms of accuracy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.67-77
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• 2022

An automatic freeway bus-only lane enforcement system was developed and assessed in a real-world environment. Observation of a bus-only lane on the Youngdong freeway, South Korea, revealed that approximately 99% of the vehicles violated the high-occupancy vehicle (HOV) lane regulation. However, the current enforcement by the police not only exhibits a low enforcement rate, but also induces unnecessary safety and delay concerns. Since vehicles with six passengers or higher are permitted to enter freeway bus-only lanes, identifying the number of passengers in a vehicle is a core technology required for a freeway bus-only lane enforcement system. To that end, infrared cameras and the You Only Look Once (YOLOv5) deep learning algorithm were utilized. For assessment of the performance of the developed system, two environments, including a controlled test-bed and a real-world freeway, were used. As a result, the performances under the test-bed and the real-world environments exhibited 7% and 8% errors, respectively, indicating satisfactory outcomes. The developed system would contribute to an efficient freeway bus-only lane operations as well as eliminate safety and delay concerns caused by the current manual enforcement procedures.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3268-3276
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• 2023

The practice of identifying the potential zones for mineral exploration in a speedy and low-cost method includes the use of satellite imagery analysis as a part of remote sensing techniques. It is challenging to explore the iron mineralization of a region through conventional methods which are a time-consuming process. The current study utilizes the Hyperion satellite imagery for mapping the iron mineralization and associated geological features in the Irikkur region, Kannur, Kerala. Along with the remote sensing results, the field study and laboratory-based analysis were conducted to retrieve the ground truth point and geochemical proportion to verify the iron ore mineralization. The MC simulation showed for shielding properties indicate an increase in the linear attenuation coefficient with raising the Fe₂O₃+SiO₂ concentrations in the investigated rocks where it is varied at 0.662 MeV in the range 0.190 cm^-1 - 0.222 cm^-1 with rising the Fe₂O₃+SiO₂ content from 57.86 wt% to 71.15 wt%. The analysis also revealed that when the γ-ray energy increased from 0.221 MeV to 2.506 MeV, sample 1 had the largest linear attenuation coefficient, ranging from 9.33 cm1 to 0.12 cm^-1. Charnockite rocks were found to have exceptional shielding qualities, making them an excellent natural choice for radiation shielding applications.

• Journal of the Korean Geotechnical Society
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• v.23 no.12
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• pp.109-116
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• 2007

This study has reviewed the applicability of displacement measurement by using a digital vision technique based on typical photogrammetric methods. In this study, a series of experimental measurements have been performed in order to improve the accuracy of digital vision measurement by establishing criteria of factors of various vision measurements. It is found that the digital vision measurement tends to show higher accuracy as the image size(resolution) and the focal length become larger and the distance to an object becomes closer. It is also observed that measurement error decreases with processing as many images as possible in various angles. Applicability on high-resolution displacement measurement is proved by applying the digital vision measurement developed in this study to a large scale loading test of concrete lining.

• Journal of Korean Society of Spine Surgery
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• v.26 no.1
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• pp.26-32
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• 2019

Study Design: Review article. Objectives: To present the latest knowledge on spine surgery using augmented reality (AR). Summary of Literature Review: AR is a new technology that simulates interactions with real-world surroundings using computer graphics, and it is a field that has recently been highlighted as part of the fourth industrial revolution. Materials and Methods: Review of related literature and introduction of latest research. Results: Spine surgery using AR is currently in its early stages. If industry, academia, and research institutes cooperate and develop, spine surgery using AR is highly likely to develop to the next level. Conclusions: Spine surgeons should strive to develop relevant technology.