• Journal of the Institute of Convergence Signal Processing
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• v.23 no.1
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• pp.28-36
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• 2022

Currently, the automation and intelligence of the shipbuilding industry have improved its work production capacity and cost competitiveness, but the reduction rate of safety accidents among industrial site workers is still low and the damage caused by safety accidents is very serious, so there is a need for improvement according to the workplace. This research aims to demonstrate the connectivity between smart safety helmets in the demonstration area to verify the effectiveness along with the development of smart helmets for worker protection and environmental safety in shipyards. For efficient communication between workers, impact noise of over 95dB was confirmed in the workplace, and noise reduction was required. To solve this problem, the filtering performance was compared and analyzed using the Butterworth, Chebyshev, and elliptic algorithms. The connectivity test and noise reduction method between smart helmets proposed in this study will increase the usability and safety of the field through the development of advanced smart helmets tailored to the shipbuilding workplace in the future.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.10-18
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• 2022

Purpose: For smooth performance of flood analysis due to heavy rain disasters at energy storage facilities in the Incheon area, field surveys, observational surveys, and pre-established reports and drawings were analyzed. Through the field survey, the characteristics of pipelines and rivers that have not been identified so far were investigated, and based on this, the input data of the SWMM model selected for inundation analysis was constructed. Method: In order to determine the critical duration through the probability flood analysis according to the calculation of the probability rainfall intensity by recurrence period and duration, it is necessary to calculate the probability rainfall intensity for an arbitrary duration by frequency, so the research results of the Ministry of Land, Transport and Maritime Affairs were utilized. Result: Based on this, the probability of rainfall by frequency and duration was extracted, the critical duration was determined through flood analysis, and the rainfall amount suggested in the disaster prevention performance target was applied to enable site safety review. Conclusion: The critical duration of the base was found to be a relatively short duration of 30 minutes due to the very gentle slope of the watershed. In general, if the critical duration is less than 30 minutes, even if flooding occurs, the scale of inundation is not large.

• Korean Journal of Construction Engineering and Management
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• v.23 no.4
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• pp.3-14
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• 2022

Autonomous equipment requires a large amount of data from various environments. However, it takes a lot of time and cost for an experiment in a real construction sites, which are difficulties in data collection and processing. Therefore, this study aims to develop a virtual environment for autonomous tower cranes technology development and validation. The authors defined automation functions and operation conditions of tower cranes with three performance criteria: operational design domain, object and event detection and response, and minimum functional conditions. Afterward, this study developed a virtual environment for learning and validation for autonomous functions such as recognition, decision making, and control using the Unity game engine. Validation was conducted by construction industry experts with a fidelity which is the representative matrix for virtual environment assessment. Through the virtual environment platform developed in this study, it will be possible to reduce the cost and time for data collection and technology development. Also, it is also expected to contribute to autonomous driving for not only tower cranes but also other construction equipment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.239-247
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• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.323-332
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• 2022

As various services using AI technology are being developed, much attention is being paid to AI service production. Recently, AI technology is acknowledged as one of ICT services, a lot of research is being conducted for general-purpose AI service production. In this paper, I describe the research results in terms of systems for AI service production, focusing on the distribution and production of machine learning models, which are the final steps of general machine learning development procedures. Three different Ubuntu systems were built, and experiments were conducted on the system, using data from 2017 validation COCO dataset in combination of different AI models (RFCN, SSD-Mobilenet) and different communication methods (gRPC, REST) to request and perform AI services through Tensorflow serving. Through various experiments, it was found that the type of AI model has a greater influence on AI service inference time than AI machine communication method, and in the case of object detection AI service, the number and complexity of objects in the image are more affected than the file size of the image to be detected. In addition, it was confirmed that if the AI service is performed remotely rather than locally, even if it is a machine with good performance, it takes more time to infer the AI service than if it is performed locally. Through the results of this study, it is expected that system design suitable for service goals, AI model development, and efficient AI service production will be possible.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.211-218
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• 2021

This paper addressed the problems of controlling the coupled pitch-roll motions in a marine vessel exposed to the regular waves in the longitudinal and transversal directions. Stabilization of the pitch and roll motions can be regarded as the essential task to ensure the safety of a ship's navigation. One of the important features in the pitch-roll motions is the resonance phenomena, which result in unexpected large responses in terms of pitch and roll modes in some specific conditions. Besides, owing to its inherent characteristics of coupled combination and nonlinearity of restoring terms, the vessel shows various dynamical behaviors according to the system parameters, especially in the pitch responses. Above all, it can be seen that suppression of pitch rate remains the most significant challenge to overcome for ship maneuvering safety studies. To secure the stable upright condition, a quasi-sliding mode control scheme is employed to reduce the undesirable pitch and roll responses as well as chattering elimination. The Lyapunov theory is adopted to guarantee the closed stability of the pitch-roll system. Numerical simulations demonstrate the effectiveness of the control scheme. Finally, the control goals of state convergences and chattering reduction are effectively realized through the proposed control synthesis.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.848-859
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• 2022

This paper presents a novel 360-degree video streaming system for large-scale immersive displays and its ongoing implementation. Recent VR systems aim to provide a service for a single viewer on HMD. However, the proposed 360-degree video streaming system enables multiple viewers to explore immersive contents on a large-scale immersive display. The proposed 360-degree video streaming system is being developed in 3 research phases, with the final goal of providing 6DoF. Currently, the phase 1: implementation of the 3DoF 360-degree video streaming system prototype is finished. The implemented prototype employs subpicture-based viewport-dependent streaming technique, and it achieved bit-rate saving of about 80% and decoding speed up of 543% compared to the conventional viewport-independent streaming technique. Additionally, this paper demonstrated the implemented prototype on UCSB AlloSphere, the large-scale instrument for immersive media art exhibition.

• Resources Recycling
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• v.31 no.3
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• pp.40-52
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• 2022

This study analyzed the amount of carbon dioxide reduction and economic benefits of detailed processes of CO₂ 6,000 tons plant facilities with mineral carbonation technology using carbon dioxide and coal materials emitted from domestic circulating fluidized bed combustion power plants. Coal ash reacted with carbon dioxide through carbon mineralization facilities is produced as a complex carbonate and used as a construction material, accompanied by a greenhouse gas reduction. In addition, it is possible to generate profits from the sales of complex carbonates and carbon credits produced in the process. The actual carbon dioxide reduction per ton of complex carbonate production was calculated as 45.8 kgCO₂eq, and the annual carbon dioxide reduction was calculated as 805.3 tonCO₂, and the benefit-cost ratio (B/C Ratio) is 1.04, the internal rate return (IRR) is 10.65 % and the net present value (NPV) is KRW 24,713,465 won, which is considered economical. Carbon mineralization technology is one of the best solutions to reduce carbon dioxide considering future carbon dioxide reduction and economic potential.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.152-163
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• 2022

In this paper, we present a method to enable an unmanned aerial vehicle to drop the sonobuoy, an essential element of anti-submarine warfare, in an optimal deployment. To this end, an environment simulating the distribution of sound detection performance was configured through the Unity game engine, and the environment directly configured using Unity ML-Agents and the reinforcement learning algorithm written in Python from the outside communicated with each other and learned. In particular, reinforcement learning is introduced to prevent the accumulation of wrong actions and affect learning, and to secure the maximum detection area for the sonobuoy while the vehicle flies to the target point in the shortest time. The optimal placement of the sonobuoy was achieved by applying the Deep Deterministic Policy Gradient (DDPG) algorithm. As a result of the learning, the agent flew through the sea area and passed only the points to achieve the optimal placement among the 70 target candidates. This means that an autonomous aerial vehicle that deploys a sonobuoy in the shortest time and maximum detection area, which is the requirement for optimal placement, has been implemented.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.12
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• pp.889-898
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• 2022

In this paper, parallel computing method on the three-dimensional electromagnetic field is proposed. The present electromagnetic scattering analysis is conducted based on the time-harmonic vector wave equation and the finite element method. The edge-based element and 2^nd -order absorbing boundary condition are used. Parallelization of the elemental numerical integration and the matrix assemblage is accomplished by allocating the partitioned finite element subdomain for each processor. The graph partitioning library, METIS, is employed for the subdomain generation. The large sparse matrix computation is conducted by MUMPS, which is the parallel computing library based on the multi-frontal method. The accuracy of the present program is validated by the comparison against the Mie-series analytical solution and the results by ANSYS HFSS. In addition, the scalability is verified by measuring the speed-up in terms of the number of processors used. The present electromagnetic scattering analysis is performed for a perfect electric conductor sphere, isotropic/anisotropic dielectric sphere, and the missile configuration. The algorithm of the present program will be applied to the finite element and tearing method, aiming for the further extended parallel computing performance.