• Korean Journal of Construction Engineering and Management
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• v.21 no.5
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• pp.11-19
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• 2020

A daily progress monitoring and further schedule management of a construction project have a significant impact on the construction manager's decision making in schedule change and controlling field operation. However, a current site monitoring method highly relies on the manually recorded daily-log book by the person in charge of the work. For this reason, it is difficult to take a detached view and sometimes human error such as omission of contents may occur. In order to resolve these problems, previous researches have developed automated site monitoring method with the object recognition-based visualization or BIM data creation. Despite of the research results along with the related technology development, there are limitations in application targeting the practical construction projects due to the constraints in the experimental methods that assume the fixed equipment at a specific location. To overcome these limitations, some smart devices carried by the field workers can be employed as a medium for data creation. Specifically, the extracted information from the site picture by object recognition technology of CNN model, and positional information by GIPS are applied to update 4D BIM data. A standard CNN model is developed and BIM data modification experiments are conducted with the collected data to validate the research suggestion. Based on the experimental results, it is confirmed that the methods and performance are applicable to the construction site management and further it is expected to contribute speedy and precise data creation with the application of automated progress monitoring methods.

• Journal of the Korean Society for Computer Game
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• v.31 no.4
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• pp.197-203
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• 2018

As people's interest in Virtual Reality has recently increased, peripherals have also made many progress. There is a lot of research being done from VR environment to VR configuration through scanning at room level with various interface devices that can interact with objects in the environment. According to current VR research Home VR uses multiple haptic interfaces to interact with objects configured in the VR environment, the method uses room scanning to some extent is beyond the spatial constraints and may use tracking equipment to interact with real objects. And advances in 3D printers have enabled the distribution of commercial 3D printers and home 3D printers, and made it easy for 3D printers to create models of their choice at home or at home. Considering the above two factors, We think it is necessary to study the difference between a model's object that people feel when interacting directly with an easy-to-create model in a VR environment. Therefore, in this paper, we are going to implement objects produced by 3D printers in VR space and study the differences between using real objects and other general interaction equipment through user testing with those that are actually implemented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.77-83
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• 2020

The heat treatment facility is in a situation where the scope of application of the remote IOT system is expanding due to the harsh environment caused by high heat and long working hours among the root industries. In this heat treatment process environment, the IOT middleware is required to play a pivotal role in interpreting, managing and controlling data information of IoT devices (sensors, etc.). Until now, the system controlled by the heat treatment remotely was operated with the command of the operator's batch system without overall monitoring of the site situation. However, for the safety and precise control of the heat treatment facility, it is necessary to control various sensors and recognize the surrounding work environment. As a solution to this, the heat treatment safety support system presented in this paper proposes a support system that can detect the access of the work manpower to the heat treatment furnace through thermal image detection and operate safely when ordering work from a remote location. In addition, an OPEN CV-based deterioration analysis system using DNN deep learning network was constructed for faster and more accurate recognition than general fixed hot spot monitoring-based thermal image analysis. Through this, we would like to propose a system that can be used universally in the heat treatment environment and support the safety management specialized in the heat treatment industry.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.19-28
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• 2021

Corrosion is the degradation of metals by reaction with the environment. It is difficult to completely remove. Corrosion proceeds rapidly after the protective barrier is destroyed, and several reactions occur that alter the composition and properties of the metal surface and local environments, such as diffusion of metal cations into the matrix, the formation of oxides, and local pH changes. The study of corrosion of steel and iron is of theoretical and practical interest and is receiving considerable attention. Acid solutions, which are widely used in industrial pickling, acid descaling, cleaning and acidification of oil wells, require the use of corrosion inhibitors to suppress corrosion attacks on metallic materials. Physical removal of rust requires expensive special equipment, and chemical removal of it can cause corrosion or shorten the life of the metal. In this study, an eco-friendly rust cleaner was developed using cosmetics and food materials by applying the concept of perm reducing agent and chelate, and applied to remove rust from industrial and hot water pipes and various industrial devices. As a result, it was found that rust cleaners remove rust more effectively and safely compared to conventional treatment methods. At the same time, the rust removal efficiency was 1.75 to 2.5 times better for industrial piping and 1.56 to 2.2 times better for boiler hot water than conventional methods.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.479-489
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• 2022

In order to understand how to increase the use of virtual training content at K University's online lifelong education institute, this study examined the use experience, content recognition, field practice replacement, and requirements, focusing on the examples of operating institutions. To this end, 12 institutions that operated virtual training contents distributed by the K University Online Lifelong Education Center in 2020 were selected for in-depth interviews and qualitative analysis was conducted on the interviews of 11 institutions. As a result of the analysis, first, the experience of using the contents of the virtual training operating institution was aimed at changing the educational environment, supplementing theoretical learning, and improving the sense of practice. Second, according to a survey on the recognition of virtual training content, if the importance and utilization of the content are high, it can be replaced by on-site practice in non-face-to-face classes, such as experiences of facilities and equipment, attracting interest and attention. Third, in many cases, the perception of replacement for field practice is not unreasonable to use as a pre-training material for field practice, but it is difficult to replace field practice. Fourth, content quality improvements can be summarized as content quality improvement, content access and manipulation improvement, dedicated device development, training for instructors, and curriculum systematization. Fifth, institutional requirements include improving the quality of virtual training content itself, equipment support, curriculum systemization and characterization, systematic curriculum and detailed content sharing, detailed guidance on using virtual training content, introducing how to use content, and recruiting instructors. This study is meaningful in that it sought ways to improve the utilization of virtual training content based on the perception of virtual training content operating institutions.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.889-898
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• 2013

Due to the popularization of high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy to make high-quality counterfeit money. However, the probability of detecting counterfeit money to the general public is extremely low and the detection device is expensive. In this paper, a counterfeit money detection algorithm using a general purpose scanner and computer system is proposed. First, the printing features of color printers are calculated using morphological operations and gray-level co-occurrence matrix. Then, these features are used to train a support vector machine classifier. This trained classifier is applied for identifying either original or counterfeit money. In the experiment, we measured the detection rate between the original and counterfeit money. Also, the printing source was identified. The proposed algorithm was compared with the algorithm using wiener filter to identify color printing source. The accuracy for identifying counterfeit money was 91.92%. The accuracy for identifying the printing source was over 94.5%. The results support that the proposed algorithm performs better than previous researches.

• Journal of dental hygiene science
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• v.15 no.5
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• pp.603-611
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• 2015

This research is aimed at cutting off hearing loss and other harmful factors due to noise and providing basic material for noise reduction plan. As the research method, this research assessed noise by measuring acoustic pressure level and frequency in various situation of non-treatment and treatment. As the measurement result, average noise degree of high speed handpiece of non-treatment, ultrasonic waves scaler, and low speed handpiece showed 58~66 dB(A). Average noise degree of scaling of treatment, tooth elimination, and denture adjust showed 73~81 dB(A). The result is inferior to recognized standards of noise induced hearing loss. But the result of assessing this with (noise rating) NR curve was NR-73~78, which exceeded general workplace noise standard. This level can cause hearing loss when exposed to a long time. Therefore, treatment office noise during dental treatment can cause psychological and physical damage in dental clinic employees, and it is urgently required to establish systematic and active noise reduction plan.

• Journal of the Korean Society for Marine Environment & Energy
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• v.7 no.3
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• pp.122-130
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• 2004

Crude oil is complex mixture of thousands of different organic compound formed from a variety of organic materials that are chemically converted under differing geological conditions over long periods of time. Also oil composition varies according to crude source, refining, processing, handling and storage. The oil fingerprint method is application of specific knowledge of petrochemicals and use of sophisticated analytical equipment and techniques to identify the source(s) of oil pollution. KNMPA currently utilizes three primary analytical techniques: Gas Chromatography (GC), Fluorescence Spectroscopy(FL) and Infrared Spectroscopy(IR). Of all these techniques, GC technique are most widely used. Gas Chromatography is used as a primary analytical method because high reliableness, high separating efficiency and repeatability, but it is timeconsumable. The study results of identification of waterborne spilled oil by Fast Gas Chromatograph method showed that analytical time is cut down to 30minutes in comparison with packed column method and chromatograms represent high resolution and high repeatability.

• Journal of radiological science and technology
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• v.32 no.2
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• pp.195-203
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• 2009

Image registration is a fundamental task in image processing used to match two or more images. It gives new information to the radiologists by matching images from different modalities. The objective of this study is to develop 2D image registration algorithm for PET/CT and CT images acquired by different systems at different times. We matched two CT images first (one from standalone CT and the other from PET/CT) that contain affluent anatomical information. Then, we geometrically transformed PET image according to the results of transformation parameters calculated by the previous step. We have used Affine transform to match the target and reference images. For the similarity measure, mutual information was explored. Use of particle swarm algorithm optimized the performance by finding the best matched parameter set within a reasonable amount of time. The results show good agreements of the images between PET/CT and CT. We expect the proposed algorithm can be used not only for PET/CT and CT image registration but also for different multi-modality imaging systems such as SPECT/CT, MRI/PET and so on.

• Journal of Environmental Impact Assessment
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• v.27 no.4
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• pp.378-393
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• 2018

As atmospheric fine dust problems in Korea become more serious, there are growing needs to find the concentration of fine particles in indoor and outdoor areas and there are increasing demands for sensor-based portable monitoring devices capable of measuring fine dust concentrations instantly. The low-cost portable monitoring devices have been widely manufactured and used without the prescribed certification standards which would cause unnecessary confusion to the concerned public. To evaluate the reliability those devices and to improve their usability, following studies were conducted in this work; 1) The comparisons between sensor-based devices and comparison with more accurate devices were performed. 2) Several experiments were conducted to understand usefulness of the portable monitoring devices. As results, the absolute concentration levels need to be adjusted due to insensitivity of the tiny light scattering sensors in the portable devices, but their linearity and reproducibility seem to be acceptable. By using those monitoring devices, users are expected to have benefits of recognizing the changes of concentration more quickly and could help preventing themselves from the adverse health impacts.