• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.141-148
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• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.541-548
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• 2021

Recently, multispectral cameras are being actively utilized in various application fields such as agriculture, forest management, coastal environment monitoring, and so on, particularly onboard UAV's. Resultant multispectral images are typically georeferenced primarily based on the onboard GPS (Global Positioning System) and IMU (Inertial Measurement Unit)or accurate positional information of the pixels, or could be integrated with ground control points that are directly measured on the ground. However, due to the high cost of establishing GCP's prior to the georeferencing or for inaccessible areas, it is often required to derive the positions without such reference information. This study aims to provide a means to improve the georeferencing performance of a multispectral camera images without involving such ground reference points, but instead with the simultaneously onboard high resolution RGB camera. The exterior orientation parameters of the drone camera are first estimated through the bundle adjustment, and compared with the reference values derived with the GCP's. The results showed that the incorporation of the images from a high resolution RGB camera greatly improved both the exterior orientation estimation and the georeferencing of the multispectral camera. Additionally, an evaluation performed on the direction estimation from a ground point to the sensor showed that inclusion of RGB images can reduce the angle errors more by one order.

• Journal of Environmental Health Sciences
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• v.47 no.6
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• pp.521-529
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• 2021

Background: The coronavirus disease (COVID-19) has caused changes in human activity, and these changes may possibly increase or decrease exposure to fine dust (PM_2.5). Therefore, it is necessary to evaluate the exposure to PM_2.5 in relation to the outbreak of COVID-19. Objectives: The purpose of this study was to compare and evaluate the exposure to PM_2.5 concentrations by the variation of dynamic populations before and after the outbreak of COVID-19. Methods: This study evaluated exposure to PM_2.5 concentrations by changes in the dynamic population distribution in Guro-gu, Seoul, before and after the outbreak of COVID-19 between Jan and Feb, 2020. Gurogu was divided into 2,204 scale standard grids of 100 m×100 m. Hourly PM_2.5 concentrations were modeled by the inverse distance weight method using 24 sensor-based air monitoring instruments. Hourly dynamic population distribution was evaluated according to gender and age using mobile phone network data and time-activity patterns. Results: Compared to before, the population exposure to PM_2.5 decreased after the outbreak of COVID-19. The concentration of PM_2.5 after the outbreak of COVID-19 decreased by about 41% on average. The variation of dynamic population before and after the outbreak of COVID-19 decreased by about 18% on average. Conclusions: Comparing before and after the outbreak of COVID-19, the population exposures to PM_2.5 decreased by about 40%. This can be explained to suggest that changes in people's activity patterns due to the outbreak of COVID-19 resulted in a decrease in exposure to PM_2.5.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1385-1394
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• 2022

This study was to analyze the change in albedo by level-2 land cover map for 20 years(2002-2021) using MODerate resolution Imaging Spectroradiometer (MODIS) data. Also, the difference from the MODIS data was analyzed using the 10-year (2012-2021) data of Visible Infrared Imaging Radiometer Suite (VIIRS). For the albedo data of MODIS and VIIRS, daily albedo data, MCD43A3 and VNP43IA, of 500 m spatial resolution of sinusoidal tile grid produced by Bidirectional Reflectance Distribution Function (BRDF) model were prepared for the South Korea range. Reprojection was performed using the code written based on Python 3.9, and the nearest neighbor was applied as the resampling method. White sky albedo and black sky albedo of shortwave were used for analysis. As a result of 20-year albedo analysis using MODIS data, the albedo tends to rise in all land use. Compared to the 2000s (2002-2011), the average albedo of the 2010s (2012-2021) showed the most significant increase of 0.0027 in the forest area, followed by the grass increase of 0.0024. As a result of comparing the albedo of VIIRS and MODIS, it was found that the albedo of VIIRS was larger from 0.001 to 0.1, which was considered to be due to differences in the surface reflectivity according to the time of image capture and sensor characteristics.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.278-286
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• 2022

In this study, a 33-mode Free-Flooded Ring (FFR) transducer was designed to apply piezoelectric single crystal PIN-PMN-PT, which has high piezoelectric constants and electromechanical coupling coefficient. To ensure low-frequency high transmitting sensitivity characteristics with a small size of FFR transducer, the commercial FFR transducer based on piezoelectric ceramics was compared. To develop the FFR transducer with broadband characteristics, a piezoelectric segmented ring structure inserted with inactive elements was applied. The oil-filled structure was applied to minimize the change of acoustic characteristics of the ring transducer. It was verified that the transmitting voltage response, underwater impedance, and beam pattern matched the finite element numerical simulation results well through an acoustic test. The difference in the transmitting voltage response between the measured and the simulated results is about 1.3 dB in cavity mode and about 0.3 dB in radial mode. The fabricated FFR transducer had a higher transmitting voltage response compared to the commercial transducer, but the diameter was reduced by about 17 %. From this study, it was confirmed that the feasibility of a single crystal-applied FFR transducer with compact size and high-power characteristics. The effectiveness of the performance prediction by simulation was also confirmed.

• Applied Chemistry for Engineering
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• v.33 no.2
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• pp.126-132
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• 2022

Alkaline fuel cells using liquid fuels such as hydrazine and ammonia are gaining great attention as a clean and renewable energy solution possibly owing to advantages such as excellent energy density, simple structure, compact size in fuel container, and ease of storage and transportation. However, common shortcomings including cathode flooding, fuel crossover, side yield reactions, and fuel security and toxicity are still challenging issues. Real time monitoring of fuel concentrations integrated into a fuel cell device can help improving fuel cell performance via predicting any loss of fuels used at a cathode for efficient energy production. There have been extensive research efforts made on developing real-time sensing platforms for hydrazine and ammonia. Among these, recent advancements in electrochemical sensors offering high sensitivity and selectivity, easy fabrication, and fast monitoring capability for analysis of hydrazine and ammonia concentrations will be introduced. In particular, research trend on the integration of metallic and metal oxide nanoparticles and also their hybrids with carbon-based nanomaterials into electrochemical sensing platforms for improvement in sensitivity and selectivity will be highlighted.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.314-323
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• 2022

Vessel Traffic Services (VTS) operators perform traffic management tasks using VTS systems and sensor equipment designated as VTS facilities to promote the safety and efficiency of vessel traffic. The necessary VTS information for effective operations could be obtained through the additional access of various information channels other than the designated VTS facility. To unify these various information access windows, the development of the VTS cloud system is in progress. In this study, the operational information analysis for VTS was performed through VTS tasks-facility linkage analysis to identify the user required information according to the introduction of the VTS cloud system. The VTS task analysis was performed through research of the international and domestic literature, and expert interviews. The necessary information were identified and linked according to the VTS facilities. As a result of the analysis, 37 categories of necessary information were identified for internal and external information windows, and 8 information windows were selected other than the present VTS equipment. The identified user requirements would be applied to the structure design of the VTS cloud system. In the future, it is necessary to update user requirements through scenario-based user operation analysis and to conduct additional research on the system interface design.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.18-29
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• 2022

Recently, cooperative intelligent transport systems (C-ITS) testbeds have been deployed in great numbers, and advanced autonomous driving research using V2X communication technology has been conducted actively worldwide. In particular, the broadcasting services in their beginning days, giving warning messages, basic safety messages, traffic information, etc., gradually developed into advanced network services, such as platooning, remote driving, and sensor sharing, that need to perform real-time. In addition, technologies improving these advanced network services' throughput and latency are being developed on many fronts to support these services. Notably, this research analyzed the network latency requirements of the advanced network services to develop a remote driving service for the droid type low-speed robot based on the 3GPP C-V2X communication technology. Subsequently, this remote driving service's performance was evaluated using system modeling (that included the operator behavior) and simulation. This evaluation showed that a respective core and access network latency of less than 30 ms was required to meet more than 90 % of the remote driving service's performance requirements under the given test conditions.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.1-10
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• 2022

As the volume of marine hazardous and noxious substances (HNSs) transported in domestic and overseas seas increases, the risk of HNS spill accidents is gradually increasing. HNS leaked into the sea causes destruction of marine ecosystems, pollution of the marine environment, and human casualties. Secondary accidents accompanied by fire and explosion are possible. Therefore, various types of HNSs must be rapidly detected, and a control strategy suitable for the characteristics of each substance must be established. In this study, the ground HNS spill experiment process and application result of detection algorithms were presented based on hyperspectral remote sensing. For this, styrene was spilled in an outdoor pool in Brest, France, and simultaneous observation was performed through a hyperspectral sensor. Pure styrene and seawater spectra were extracted by applying principal component analysis (PCA) and the N-Findr method. In addition, pixels in hyperspectral image were classified with styrene and seawater by applying spectral matching techniques such as spectral distance similarity (SDS), spectral correlation similarity (SCS), spectral similarity value (SSV), and spectral angle mapper (SAM). As a result, the SDS and SSV techniques showed good styrene detection results, and the total extent of styrene was estimated to be approximately 1.03 m². The study is expected to play a major role in marine HNS monitoring.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.691-695
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• 2023

Currently, the utilization of measurement results of the automated measurement system is very low and is at the level of providing only fragmentary measurement results. In this study, we are going to study a structure behavior analysis 3D display system with high precision and reliability for automated measurement data obtained by constructing big data by transmitting massive data values measured in real time to the cloud and using a Python-based algorithm. As a result of the study, as a system that can evaluate the behavior of a structure to a manager in real time, it provides analysis data in real time without significant restrictions regardless of the type of measurement data and sensor, and derived it as a 3D display. In addition, it was analyzed that the manager could grasp the behavior graph of the structure in real time and more easily judge the derivation of the weak part of the structure through data analysis. In the future, by analyzing the behavior of structures in three dimensions using past and present data, it is expected that more effective measurement results can be obtained in terms of repair, reinforcement, and maintenance of realistic structures.