• Korean Journal of Construction Engineering and Management
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• v.22 no.4
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• pp.41-49
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• 2021

Domestic maintenance strategies are shifting from safety assessment to performance assessment, and related systems and laws are being restructured to meet those criteria. In order to introduce asset management based on performance evaluation, related evaluation methods such as performance measures and level of service should be made to evaluate performance according to the characteristics of the structure, but these are not well-prepared in Korea. In this study, we present a computerized model and system for implementing asset management that introduces techniques such as performance evaluation, life cycle cost analysis, performance measures, and level of service in conjunction with existing maintenance and safety diagnosis procedures. The features of this system consist of three modules to enable separate operations of existing maintenance, safety management and asset management. The system is designed to be used as a reference for public institutions to introduce asset management in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.97-106
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• 2019

Today, many smart sensor's measurement instruments are used to check the safety situation of various medium and large bridge structures that should be maintained in the construction facilities, but most of them use the method of measuring and confirming the displacement behavior of the bridge at regular intervals. In order to continuously check the safety situation, various measuring instruments are used, but most of them are not able to measure and measure the displacement and behavior of main construction structures at regular intervals. In this study, GNSS and environment smart sensors and drone's image data are transmitted to wireless network so that risk of many bridge's structures can be detected beforehand. As a result, by diagnosing the fine displacement of the bridge in real time and its condition, reinforcement, repair and disaster prevention measures for the structural parts of the bridges, which are expected to be dangerous, and various disasters and accidents can be prevented, and disaster can be prevented could suggest a new alternative.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.2
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• pp.351-359
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• 2019

In order to improve the problem of parking which is getting worse day by day, the municipality carries out a survey on the actual situation of the parking lot supply and demand periodically according to the related law. However, in the existing evaluation method, the parking demand that occurs under the condition that the demand is suppressed by the parking supply and regulation due to the limit of the survey method is investigated. In addition, the analysis is conducted only for the present year, and prediction and analysis of future parking problems are limited. Therefore, we propose a method to evaluate the status of parking supply and demand, which is differentiated to improve the problem of the existing evaluation method. As a result, comparing the existing method with the improved method, it can be seen that the improved evaluation method can be useful for establishing the long-term parking policy for the improvement of parking problems.

• The Journal of Bigdata
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• v.5 no.2
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• pp.1-15
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• 2020

The duty-free industry before COVID-19 has continuously grown since 2000, along with the increase of demand in tourism industry. To cope with the increased demand, the duty free companies have kept the strategies which focused on the sales volume. Therefore, they have developed the ways to increase the volume and capacity, not the efficient operations. In the most of previous research, however, authors have proposed the better strategies for marketing and supporting policies. It is very hard to find the previous research which dealt with the operations like logistics and inventory management. Therefore, in this study, it has been predicted the future demand of frequently purchased items in airport duty free shops based on the estimated number of departing passengers by the linear regression, which concluded with the appropriate inventory level. In addition, it has been analyzed the expected effects by introducing the inventory management policy considering the cost and efficiency of operations. Based on the results of this study, it may be possible to reduce total cost and improve productivity by predicting the excessive inventory problems at duty-free shops and improving cycles of supplying items.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.55-67
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• 2022

Sensor data can provide fault diagnosis for equipment. However, the cause analysis for fault results of equipment is not often provided. In this study, we propose an explainable convolutional neural network framework for the sensor-based time series classification model. We used sensor-based time series dataset, acquired from vehicles equipped with sensors, and the Wafer dataset, acquired from manufacturing process. Moreover, we used Cycle Signal dataset, acquired from real world mechanical equipment, and for Data augmentation methods, scaling and jittering were used to train our deep learning models. In addition, our proposed classification models are convolutional neural network based models, FCN, 1D-CNN, and ResNet, to compare evaluations for each model. Our experimental results show that the ResNet provides promising results in the context of time series classification with accuracy and F1 Score reaching 95%, improved by 3% compared to the previous study. Furthermore, we propose XAI methods, Class Activation Map and Layer Visualization, to interpret the experiment result. XAI methods can visualize the time series interval that shows important factors for sensor data classification.

• Journal of the Korea Institute of Building Construction
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• v.22 no.2
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• pp.171-182
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• 2022

The regular assessment of a building is important to understand structural safety and latent risk in the early stages of building life cycle. However, methods of traditional assessment are subjective, atypical, labor-intensive, and time-consuming and as such the reliability of these results has been questioned. This study proposed a method to bring accurate results using a 3D laser scanner and integrate them in Building Information Modeling (BIM) to visualize defective condition. The specific process for this study was as follows: (1) semi-automated data acquisition using 3D laser scanner and python script, (2) scan-to-BIM process, (3) integrating and visualizing defective conditions data using dynamo. The method proposed in this study improved efficiency and productivity in a building assessment through omitting the additional process of measurement and documentation. The visualized 3D model allows building facility managers to make more effective decisions. Ultimately, this is expected to improve the efficiency of building maintenance works.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.1005-1013
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• 2021

With the prolonged COVID-19, the existing academic gap is widening. The purpose of this study is to provide homeroom teachers with a visual confirmation of the academic achievement gap in grades and classrooms through academic achievement analysis, and to use this to help them design lessons and explore ways to improve the academic achievement gap. The data of students' Korean and math diagnostic evaluation scores at the beginning of the school year were visualized as clusters using the K-means algorithm, and as a result, it was confirmed that a meaningful clusters were formed. In addition, through the results of the teacher interview, it was confirmed that this system was meaningful in improving the academic achievement gap, such as checking the learning level and academic achievement of students, and designing classes such as individual supplementary instruction and level-specific learning. This means that this academic achievement data analysis system helps to improve the academic gap. This study provides practical help to homeroom teachers in exploring ways to improve the academic gap in grades and classes, and is expected to ultimately contribute to improving the academic gap.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.117-122
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• 2022

In this paper, we developed a vehicle control terminal using IoT and low-power long-distance communication (NB-IoT) technology. This system collects information on the location and status of a parked vehicle, and transmits the vehicle status to the vehicle owner's terminal in real time with low power to prevent vehicle theft, and in the case of a vehicle in motion, When primary information about the vehicle, such as an impact, is collected and transmitted to the server, the server analyzes the relevant data to generate secondary information on traffic congestion, road damage, and safety accidents. By sending it, you can know the exact arrival time of the vehicle at its destination. This terminal device is an IoT gateway for a vehicle and can be connected to various wired and wireless sensors inside the vehicle. In addition, the data collected from vehicle maintenance, efficient operation, and vehicles can be usefully used in the private or public sector.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.292-294
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• 2021

The digital twin-based smart pipe integrated management system is an integrated solution for efficient operation and monitoring that we propose. We buried a waterway pipe underground with self-diagnostic and condition monitoring sensor functions. This pipe sends sensing data and accumulates it. Our system analyzes data to make smart decisions. The main functions of this system are remote control and monitoring. Therefore, "how to configure monitoring in real time" is a big issue. For this purpose, we designed a special real-time-based agent function. In this paper, to solve this problem, a layered architecture was proposed based on transmission points where sensor data are exchanged. An agent was placed in each layer to look at the lower layer and periodically monitor whether there were any changes in the sensor in real time. Finally, the agent system was designed and the conceptual model level was implemented to verify excellence.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.621-635
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• 2023

The assessment of structural condition is a crucial process for evaluating its usability and determining the diagnostic cycle. The currently employed manpower-based methods suffer from issues related to safety, efficiency, and objectivity. To address these concerns, research based on deep learning using images is being conducted. However, acquiring structural damage data is challenging, making it difficult to construct a substantial amount of training data, thus limiting the effectiveness of deep learning-based condition assessment. In this study, we propose a foundation model-based 2-step structural damage analysis to overcome the lack of training data in image-based structural condition assessments. We subdivided the elements of structural condition assessment into instantiation and quantification. In the quantification step, we applied a foundation model for image segmentation. Our method demonstrated a 10%-point increase in mean intersection over union compared to conventional image segmentation techniques, with a notable 40%-point improvement in the case of rebar exposure. We anticipate that our proposed approach will enhance performance in domains where acquiring training data is challenging.