• Journal of the Korea Society for Simulation
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• v.25 no.4
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• pp.127-135
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• 2016

Even thought modernized marine navigation devices help navigators, marine accidents has been often occurred and ship collision is one of the main types of the accidents. Various studies on the assessment method of collision risk have been reported, and studies using fuzzy theory are remarkable for the reason that reflect linguistic and ambiguous criteria for real situations. In these studies, collision risks were assessed on the assumption that the current state of navigation ship would be maintained. However, navigators ignore or turn off frequent alarms caused by the devices predicting collision risk, because they think that they can avoid the collisions in the most of situations. This paper proposes a model of predicting ship collision risk considering the general patterns of collision avoidance, and the approach is based on fuzzy inference and discrete event system specification (DEVS) formalism.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.780-789
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• 2018

Nowadays, gun crimes occur very frequently not only in public places but in alleyways around the world. In particular, it is essential to detect a person armed by a pistol to prevent those crimes since small guns, such as pistols, are often used for those crimes. Because conventional works for armed person detection have treated an armed person as a single object in an input image, their accuracy is very low. The reason for the low accuracy comes from the fact that the gunman is treated as a single object although the pistol is a relatively much smaller object than the person. To solve this problem, we propose a novel algorithm called APDA(Armed Person Detection Algorithm). APDA detects the armed person using in a post-processing the positions of both wrists and the pistol achieved by the CNN-based human body feature detection model and the pistol detection model, respectively. We show that APDA can provide both 46.3% better recall and 14.04% better precision than SSD-MobileNet.

• Journal of the Korea Institute of Building Construction
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• v.23 no.3
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• pp.273-284
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• 2023

This study is centered on the combined use of LiDAR(Light Detection and Ranging) and AR(Augmented Reality) technologies during vertical and horizontal frame measurements in construction projects. The intention is to enhance the quality control procedure, elevate accuracy, and curtail manual labor along with time expenditure. Present methods for accuracy inspection in frame construction often grapple with reliability concerns due to subjective interpretation and the scope for human error. This research recommends the application of LiDAR and AR technologies to counter these issues and augment the efficiency of the inspection process, along with facilitating the dissemination of results. The suggested technique involves the collection of 3D point cloud data of the frame utilizing LiDAR and leveraging this data for checks on construction accuracy. Furthermore, the inspection outcomes are fed into a BIM (Building Information Modeling) model, and the results are visualized via AR. Upon juxtaposing this methodology with the current approach, it is evident that it offers benefits in terms of objective inspection, speed, precise result sharing, and potential enhancements to the overall quality and productivity of construction projects.

• Journal of the Korean Society of Radiology
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• v.11 no.7
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• pp.555-564
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• 2017

The current radiation risk assessment for occupational exposure is based on the measured exposure dose and health checkups of workers. This people-centered risk assessment may occur errors because absence of using personal dosimeter or unrelated health symptoms of individuals lead to difficulties in obtaining accurate data from workers. In addition, although the established legal upper dose limit was used as a reference for the assessment, it does not imply that this limit is the optimal dose of radiation workers should get; ALARA principle should always be appreciated. Therefore, a new risk assessment model that can take account of all the important factors and implement optimization of radiation protection is required at the national level. In this paper, based on the KOSHA Risk Assessment, we studied on the workplace-centered risk assessment model for radiation field rather than the people-centered. The result of the study derived a right model for radiation field through the analysis of the risk assessment methods in various fields and also found data acquisition methods and procedures for applying to the model. Multidimensional model centering on the workplace will enables more accurate radiation risk assessment by using a risk index and radar plot, and consequently contribute to the efficient worker management, preemptive worker protection and implementation of optimization of radiation protection.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.23-31
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• 2023

Software development involves a series of stages, including requirements analysis, design, implementation, unit testing, and integration testing, similar to those used in the system engineering process. This study utilized MathWorks' model-based design platform to develop multi-function radar software and evaluated its feasibility and efficiency. Because the development of conventional radar software is performed by a unit algorithm rather than in an integrated form, it requires additional efforts to manage the integrated software, such as requirement analysis and integrated testing. The mode-based platform applied in this paper provides an integrated development environment for requirements analysis and allocation, algorithm development through simulation, automatic code generation for deployment, and integrated requirements testing, and result management. With the platform, we developed multi-level models of the multi-function radar software, verified them using test harnesses, managed requirements, and transformed them into hardware deployable language using the auto code generation tool. We expect this Model-based integrated development to reduce errors from miscommunication or other human factors and save on the development schedule and cost.

• 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 Digital Convergence
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• v.15 no.8
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• pp.391-400
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• 2017

The purpose of this paper is to present the effect of image stimulation on body stability as a conceptual model and to investigate the effect of image stimulus(2D, VR) on body stability(hand stability) through experiments Recently, stereoscopic images such as virtual and augmented reality are combined with smart phones and exercise equipments, and the diffusion is becoming active. The possibility of a safety accident or human error is also increasing as it temporarily affects the balance of the body and hand stability after the image stimulus is removed. The conceptual model is presented based on the results of previous studies. Based on the experimental results, the conceptual model has been explained in combination with the human information processing process and cognitive resource models that take place in the brain. Twenty subjects were exposed to 2D and VR stimuli, and display fatigue was measured by cybersickness questionnaire and hand stability by hand steadiness tester. Experimental results show that VR images induce higher display fatigue and lower hand stability than 2D. In this study, it is meaningful that hand stability according to image type and display fatigue level which have not been tried yet is revealed through conceptual model and experiment.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.4
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• pp.265-272
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• 2023

This paper presents a conceptual strategy and technologies for the digital transformation of design and construction of reinforced concrete (RC) structures. The development of an automated detail design strategy for RC structures is described. Integrated digital platform based on 5D BIM concept is proposed for the replacement of the current technology environment-based 2D CAD. Generally, the detail design development is labor-intensive and iterative. Effective automation of relevant aspects can dramatically improve productivity and accuracy. The proposed solutions for the automated BIM modeling based on the rebar and formwork detail design automation achieves the productivity and accuracy sufficient for site application. The platform integrates and manages the information flow between each solution or application and provides it to all participants of the project. Finally, it is expected that the proposed strategy and technologies can be further enhanced to achieve the productivity and accuracy needed for widespread site application and digital transformation.

• Journal of the Korea Society of Computer and Information
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• v.25 no.10
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• pp.35-42
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• 2020

In this study, we propose a crack detection method using limited data with a U-Net based image inpainting technique that is a modified unsupervised anomaly detection method. Concrete cracking occurs due to a variety of causes and is a factor that can cause serious damage to the structure in the long term. In general, crack investigation uses an inspector's visual inspection on the concrete surfaces, which is less objective in judgment and has a high possibility of human error. Therefore, a method with objective and accurate image analysis processing is required. In recent years, the methods using deep learning have been studied to detect cracks quickly and accurately. However, when the amount of crack data on the building or infrastructure to be inspected is small, existing crack detection models using it often show a limited performance. Therefore, in this study, an unsupervised anomaly detection method was used to augment the data on the object to be inspected, and as a result of learning using the data, we confirmed the performance of 98.78% of accuracy and 82.67% of harmonic average (F1_Score).

• Spatial Information Research
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• v.22 no.3
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• pp.79-87
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• 2014

In order to foster rapid disaster response and public life protection, National Emergency Management Agency has been trying to spread 'Emergency Rescue Standard System' on a national scale since 2006. The agency has also intensified management of firefighter's safety on disaster site by implementing danger predication training, specialized training and education and safety procedure check as a part of safety management officer duties. Nevertheless, there are limitations for effective fire fighting steps, such as damage spreading and life damage due to unawareness of illegal converted structure, structure transformation by high temperature and nearby hazardous material storage as well as extemporary situation handling endangered firefighter's life. In order to eliminate these limitations there is a need for an effort and technology application to minimize human errors such as inaccurate situational awareness, wrong decision built on experience and judgment of field commander and firefighters. The purpose of this study is to propose a new disaster response model which is applied with geospatial information. we executed spatial contextual awareness map analysis using fire-fighting vulnerable zone model to propose the new disaster response model and also examined a case study for Dalseo-gu in Daegu Metropolitan City. Finally, we also suggested operational concept of new proposed model on a national scale.