• Journal of the Korea Convergence Society
• /
• v.10 no.4
• /
• pp.33-38
• /
• 2019

Recently, to support location-based services, there have been many researches which consider the spatial network. For this, there are many experimental data for data processing on the road network. However, the data to process the trajectory of moving objects are not suitable. Therefore, we propose index structure to process the trajectory data on the road network and the trajectory data generation algorithm. In addition, to prove efficiency of our index structure and algorithm, we show that edge-based trajectory data are generated through the proposed algorithm using the map data of San Francisco Bay.

• Electronics and Telecommunications Trends
• /
• v.36 no.4
• /
• pp.48-60
• /
• 2021

Following the global air-traffic market growth outlook, urgency of technical development is needed in responding to changes in the international air-traffic management paradigm and to prepare technology securing and spreading strategies, which are consistent with systematic aviation weather service policies and evolution direction. Although air traffic has decreased significantly due to COVID-19, normalcy is expected from 2024, as announced by IATA. According to the future air transportation market outlook and development trends of related technologies, Korea has established and implementing the next-generation air transportation system construction plan(NARAE) to secure international competitiveness and leadership in the future. Therefore, this paper describes the technical, economic background and requirements of numerical model-based aviation weather R&D projects for successful implementation of domestic NARAE plans and providing aviation safety and air traffic service efficiency. Furthermore, we proposed numerical-model-based technology development content, strategies and detailed load-map.

• Journal of Multimedia Information System
• /
• v.8 no.2
• /
• pp.101-110
• /
• 2021

In computer vision, single-image super resolution has been an area of research for a significant period. Traditional techniques involve interpolation-based methods such as Nearest-neighbor, Bilinear, and Bicubic for image restoration. Although implementations of convolutional neural networks have provided outstanding results in recent years, efficiency and single model multi-scalability have been its challenges. Furthermore, previous works haven't placed enough emphasis on real-number scalability. Interpolation-based techniques, however, have no limit in terms of scalability as they are able to upscale images to any desired size. In this paper, we propose a convolutional neural network possessing the advantages of the interpolation-based techniques, which is also efficient, deeming it suitable in practical implementations. It consists of convolutional layers applied on the low-resolution space, post-up-sampling along the end hidden layers, and additional layers on high-resolution space. Up-sampling is applied on a multiple channeled feature map via bicubic interpolation using a single model. Experiments on architectural structure, layer reduction, and real-number scale training are executed with results proving efficient amongst multi-scale learning (including scale multi-path-learning) based models.

• Journal of KIBIM
• /
• v.10 no.3
• /
• pp.33-42
• /
• 2020

Recently, in the smart construction field, it is possible to construct spatial information of 3D data base quickly and accurately using drones, LiDARs and ARs,. Most public ordering institutions are pushing for the efficiency of construction work through establishing and announcing road maps and guidelines for utilizing BIM for the entire life cycle of construction. However, in most policies, the impact of 3D data on the entire life cycle is limited by only partially constructing and utilizing 3D data or by being mentioned. In addition, many public institutions, construction companies and planning companies did not actively utilize survey information during the actual construction phase, despite the possibility of using 3D survey information. In order to confirm the utilization of survey information, a total of eight private construction companies were selected and interviewed by experts. The analysis shows that most of companies lack the performance of drone measurements or have a lack of awareness of advantages, and among them, construction companies are relatively active. Based on these opinions, this study examined the usability of surveying information and examined measures to expand the utilization of survey information in legal and institutional aspects, technology development aspects and industrial development.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.2
• /
• pp.103-111
• /
• 2021

MMS (Mobile Mapping System) is being used for HD (High Definition) map construction because it enables fast and accurate data construction, and it is receiving a lot of attention. However, research on the use of MMS in the construction field is insufficient. In this study, road surveying and inspection of construction structures were performed using MMS. Through data acquisition and processing using MMS, point cloud data for the study site was created, and the accuracy was evaluated by comparing with traditional surveying methods. The accuracy analysis results showed a maximum of 0.096m, 0.091m, and 0.093m in the X, Y, and H directions, respectively. Each RMSE was 0.012m, 0.015m, and 0.006m. These result satisfy the accuracy of topographic surveying in the general survey work regulation, indicating that construction surveying using MMS is possible. In addition, a 3D model was created using the design data for the underpass road, and the inspection was performed by comparing it with the MMS data. Through inspection results, deviations in construction can be visually confirmed for the entire underground roadway. The traditional method takes 6 hours for the 4.5km section of the target area, but MMS can significantly shorten the data acquisition time to 0.5 hours. Accurate 3D data is essential data as basic data for future smart construction. With MMS, you can increase the efficiency of construction sites with fast data collection and accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.10
• /
• pp.3373-3389
• /
• 2022

Exploration of mobile robot without prior data about environments is a fundamental problem during the SLAM processes. In this work, we propose improved version of previous Rmap algorithm by modifying its Exploration submodule. Despite the previous Rmap's performance which significantly reduces the overhead of the grid map, its exploration module costs a lot because of its rectangle following algorithm. To prevent that, we propose a new Rmap+ algorithm for autonomous path planning of mobile robot to explore an unknown environment. The algorithm bases on paired frontiers. To navigate and extend an exploration area of mobile robot, the Rmap+ utilizes the inner and outer frontiers. In each exploration round, the mobile robot using the sensor range determines the frontiers. Then robot periodically changes the range of sensor and generates inner pairs of frontiers. After calculating the length of each frontiers' and its corresponding pairs, the Rmap+ selects the goal point to navigate the robot. The experimental results represent efficiency and applicability on exploration time and distance, i.e., to complete the whole exploration, the path distance decreased from 15% to 69%, as well as the robot decreased the time consumption from 12% to 86% than previous algorithms.

• Computers and Concrete
• /
• v.29 no.1
• /
• pp.1-14
• /
• 2022

Several aspects influence corrosive processes in reinforced concrete (RC) structures such as environmental conditions, structural geometry and mechanical properties. Since these aspects present large randomnesses, probabilistic models allow a more accurate description of the corrosive phenomena. Besides, the definition of limit states in the reliability assessment requires a proper mechanical model. In this context, this study proposes a straightforward methodology for the mechanical-probabilistic modelling of RC structures subjected to reinforcements' corrosion. An improved damage approach is proposed to define the limit states for the probabilistic modelling, considering three main degradation phenomena: concrete cracking, rebar yielding and rebar corrosion caused either by chloride or carbonation mechanisms. The stochastic analysis is evaluated by the Monte Carlo simulation method due to the computational efficiency of the Lumped Damage Model for Corrosion (LDMC). The proposed mechanical-probabilistic methodology is implemented in a computational framework and applied to the analysis of a simply supported RC beam and a 2D RC frame. Curves illustrate the probability of failure evolution over a service life of 50 years. Moreover, the proposed model allows drawing the probability of failure map and then identifying the critical failure path for progressive collapse analysis. Collapse path changes caused by the corrosion phenomena are observed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.91-93
• /
• 2021

This paper proposes an architecture to develop a mobile package tour application using geofence technology to increase tourism management effectiveness and efficiency. The proposed application allows the tour guide to set a virtual fence on a map with a certain radius dynamically as the virtual boundary to keep tourists inside both when visiting a place or when the tour is moving. The virtual fences are set up for allowing the tour guide to monitoring the tourist's movement by sending a warning to the tourist to get back inside the fence and a notification for the tour guide. If this geofence technology is applied to the package tour application, the tour guide will able to manage the package tour easily and conveniently.

• Nuclear Engineering and Technology
• /
• v.55 no.5
• /
• pp.1838-1854
• /
• 2023

This paper presents a hybrid algorithm to solve the multi-objective path planning (MOPP) problem for mobile robots in a static nuclear accident environment. The proposed algorithm mimics a real nuclear accident site by modeling the environment with a two-layer cost grid map based on geometric modeling and Monte Carlo calculations. The proposed algorithm consists of two steps. The first step optimizes a path by the hybridization of improved ant colony optimization algorithm-modified A^* (IACO-A^*) that minimizes path length, cumulative radiation dose and energy consumption. The second module is the high radiation dose rate avoidance strategy integrated with the IACO-A^* algorithm, which will work when the mobile robots sense the lethal radiation dose rate, avoiding radioactive sources with high dose levels. Simulations have been performed under environments of different complexity to evaluate the efficiency of the proposed algorithm, and the results show that IACO-A^* has better path quality than ACO and IACO. In addition, a study comparing the proposed IACO-A^* algorithm and recent path planning (PP) methods in three scenarios has been performed. The simulation results show that the proposed IACO-A^* IACO-A^* algorithm is obviously superior in terms of stability and minimization the total cost of MOPP.

• Advances in Computational Design
• /
• v.7 no.4
• /
• pp.345-369
• /
• 2022

Infectious disease emergency hospitals are usually temporarily built during the pneumonia epidemic with higher requirements regarding diagnosis and treatment efficiency, hygiene and safety, and infection control.This study aims to identify how the Building Information Modeling (BIM) + Industrialized Building System (IBS) approach could rapidly deliver an infectious disease hospital and develop site epidemic spreading algorithms. Coronavirus-19 pneumonia construction site spreading algorithm model mind map and block diagram of the construction site epidemic spreading algorithm model were developed. BIM+IBS approach could maximize the repetition of reinforced components and reduce the number of particular components. Huoshenshan Hospital adopted IBS and BIM in the construction, which reduced the workload of on-site operations and avoided later rectification. BIM+IBS integrated information on building materials, building planning, building participants, and construction machinery, and realized construction visualization control and parametric design. The delivery of Huoshenshan Hospital was during the most critical period of the Coronavirus-19 pneumonia epidemic. The development of a construction site epidemic spreading algorithm provided theoretical and numerical support for prevention. The agent-based analysis on hospital evacuation observed "arched" congestion formed at the evacuation exit, indicating behavioral blindness caused by fear in emergencies.