• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.7
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• pp.918-925
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• 2017

Multiple reflections on exterior equipment with complex shape on naval ships cause unexpectedly high Radar Cross Section (RCS) distributions, and the directions of reradiated electromagnetic waves are hard to predict. Therefore, the optimum arrangement of exterior equipments should be considered according to the Radar Absorbing Structure (RAS) method. In this paper, the optimum arrangement for exterior equipments was determined to reduce multiple reflections and RCS even with complex shapes. The sequential descending arrangement method was used to establish an optimum arrangement algorithm. An LCS-2 type model was selected for optimum exterior equipment arrangements. In order to reduce computational cost, RCS distributions and multiple reflection path analysis of exterior equipments was carried out to select exterior equipments for optimum arrangement, and an optimum arrangement was determined to find positions with minimum RCS values. Also, the RCS reduction effect was analyzed using detectable radar range.

• 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.85-96
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• 2023

This study developed and evaluated a safe route guidance service for electric personal assistive mobility device used mainly by the mobility impaired people to improve their mobility. Thirteen underlying factors affecting the mobility of electric personal assistive mobility device have been derived through a survey with the mobility impaired people and employees in related organizations in Busan Metropolitan City. After assigning safety scores to individual factors and identifying the relevant factors along routes of interest with an object detection AI model, the safe route for electric personal assistive mobility device was provided through an optimal path-finding algorithm. As a result of comparing the general route of T-map and the recommended route of this study for the identical routes, the latter had relatively fewer obstacles and the gentler slope than the former, implicating that the recommended route is safer than the general one. As future works, it is necessary to enhance the function of a route guidance service based on the real-time location of users and to conduct spot investigations to evaluate and verify its social acceptability.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.487-496
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• 2020

For the purpose of next generation technology for robot perfomances, a RAoRA (Robot Actor on Robot Arm) structure was proposed using a robot arm joined with a humanoid robot actor. Mechanical analysis, machine design and fabrication were performed for motions combined with the robot arm and the humanoid robot actor. Kinematical analysis for 3D model, spline interpolation of positions, motion control algorithm and control devices were developed for movements of the robot actor. Preliminary visualization, simulation tools and integrated operation of consoles were constructed for the non-professionals to produce intuitive and safe contents. Air walk was applied to test the developed platform. The air walk is a natural walk close to a floor or slow ascension to the air. The RAoRA also executed a performance with 5 minute-running time. Finally, the proposed platform of robot performance presented intensive and live motions which was impossible in conventional robot performances.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.10-21
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• 2022

In order to improve formal presentation attitudes such as presentation of job interviews and presentation of project results at the company, there are few automated methods other than observation by colleagues or professors. In previous studies, it was reported that the speaker's stable speech and gaze processing affect the delivery power in the presentation. Also, there are studies that show that proper feedback on one's presentation has the effect of increasing the presenter's ability to present. In this paper, considering the positive aspects of correction, we developed a program that intelligently corrects the wrong presentation habits and attitudes of college students through facial analysis of videos and analyzed the proposed program's performance. The proposed program was developed through web-based verification of the use of redundant words and facial recognition and textualization of the presentation contents. To this end, an artificial intelligence model for classification was developed, and after extracting the video object, facial feature points were recognized based on the coordinates. Then, using 4000 facial data, the performance of the algorithm in this paper was compared and analyzed with the case of facial recognition using a Teachable Machine. Use the program to help presenters by correcting their presentation attitude.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.57-64
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• 2023

The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.593-598
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• 2018

Computational fluid dynamics was used to develop a heat-recovery ventilator for preventing freezing in cold weather. An optimal internal return damper was applied, and a prototype was made for frost and freezing experiments. A total of 16 models were used to design the optimal internal return damper with the maximum exhaust recirculation ratio. The exhaust recirculation ratio of the exhaust air to the outdoor air was 59.9-62.3%. The tests showed that frost and freezing did not occur at outdoor air temperatures of $-15^{\circ}C$ or higher in both exhaust recirculation operation and normal operation. However, at an outdoor air temperature of $-20^{\circ}C$, no freezing occurred in the outdoor air area when the internal return damper was opened by 45 degrees. Heat recovery ventilators for preventing cold weather frost and freezing should be operated in two operation modes: normal and exhaust recirculation mode. An operating algorithm was developed for the heat-recovery ventilator operating in normal mode when the outdoor temperature is higher than $-15^{\circ}C$ and recirculation mode when the temperature is lower.

• Journal of the Korea Concrete Institute
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• v.26 no.3
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• pp.401-409
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• 2014

This research develops tools and strategies for optimizing RC column sections applied in tall buildings. Optimization parameters are concrete strength and section shape, the objective function for which is subject to several predefined constraints drawn from the original structural design. For this purpose, we developed new components for StrAuto, a parametric modeling and optimization tool for building structure. The components receive from external analysis solvers member strengths calculated from the original design model, and output optimized column sections satisfying the minimum cost. Using these components, optimized sections are firstly obtained for each predefined concrete strength applied to the whole floors in the project building. The obtained results for each concrete strength are comparatively examined to determine the fittest sections which will also result in the fittest vertical zoning for concrete strength. The main optimization scenario for this is to search for the vertical levels where the identical optimized sections coincide for the two different concrete strengths in concern, and select those levels for the boundaries where a concrete strength will be changed to another. The optimization process provided in this research is a product of an intensive development designed for a specific member in a specific project. Thus, the algorithm suggested takes on a microscopic and mathematical approach. However, the technique has a lot of potential that it can further be extensively developed and applied for future projects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.794-805
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• 2017

This paper proposes a Hardware-In-Loop(HIL) Simulator for a Wind Turbine and an operational control algorithm to evaluate the performance of a wind turbine control system. It provides not only for the validation of the control logics, safety functions and H/W failure, but also for the high reliability of the wind turbines (by reducing/and the reduction of the operating expense(OPEX) through performance evaluation tests with complex scenarios. On the other hand, the proposed simulator uses MATLAB, CODER, and the PLC library to operate in synchronization with the hardware, and a real-time processing-based wind turbine module including a dynamic model and control system, wind module, grid module and host PC to manage the HIL-simulator. Several experiments were carried out under the above concept to verify the effectiveness of the proposed WT HIL-simulator.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.93-106
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• 2021

Many recent studies on deep learning-based road crack detection have shown significantly more improved performances than previous works using algorithm-based conventional approaches. However, many deep learning-based studies are still focused on classifying the types of cracks. The classification of crack types is highly anticipated in that it can improve the crack detection process, which is currently relying on manual intervention. However, it is essential to calculate the severity of the cracks as well as identifying the type of cracks in actual pavement maintenance planning, but studies related to road crack detection have not progressed enough to automated calculation of the severity of cracks. In order to calculate the severity of the crack, the type of crack and the area of the crack in the image must be identified together. This study deals with a method of using Mobilenet-SSD that is deep learning-based object detection techniques to effectively automate the simultaneous detection of crack types and crack areas. To improve the accuracy of object-detection for road cracks, several experiments were conducted to combine the U-Net for automatic segmentation of input image and object-detection model, and the results were summarized. As a result, image masking with U-Net is able to maximize object-detection performance with 0.9315 mAP value. While referring the results of this study, it is expected that the automation of the crack detection functionality on pave management system can be further enhanced.