• Journal of Korea Game Society
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• v.14 no.2
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• pp.77-84
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• 2014

Presence of soft shadow effects from an area light makes virtual scenes look more realistic. However, since computation of soft shadow effects takes a long time, acceleration methods are required to apply it to real-time 3D applications. Many researches assumed that area lights are white rectangles. We suggest a new method which renders soft shadows under the area light source having arbitrary shape and color. In order to approximate visibility test, we use a shadow mapping result near a pixel. Complexity of shadow near a pixel is used to determine degree of precision of our visibility estimation. Finally, our method can present more realistic soft shadows for the area light that have more general shape and color in real-time.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.410-413
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• 2007

Water vapor in the atmosphere is an influential factor of the hydrosphere cycle, which exchanges heat through phase change and is essential to precipitation. Because of its significance in altering weather, the estimation of water vapor amount and distribution is crucial to determine the precision of the weather forecasting and the understanding of regional/local climate. It is shown that it is reliable to measure precipitable water (PW) using long baseline (500-2000km) GPS observations. However, it becomes infeasible to derive absolute PW from GPS observations in Taiwan due to geometric limitation of relatively short-baseline network. In this study, a method of deriving Near-Real-Time PW from short baseline GPS observations is proposed. This method uses a reference station to derive a regression model for wet delay, and to interpolate the difference of wet delay among stations. Then, the precipitable water is obtained by using a conversion factor derived from radiosondes. The method has been tested by using the reference station located on Mt. Ho-Hwan with eleven stations around Taiwan. The result indicates that short baseline GPS observations can be used to precisely estimate the precipitable water in near-real-time.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.1
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• pp.25-30
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• 2017

Currently, most of the grain sorter uses CCD optic camera to find defective products. The aim of this paper is to use the CCD camera, and aim for improving the sorting power of the grain separator by using NIR(Near Infrared Radiation) sensor based on moisture content measurement algorithm. We intend to develop a system to develop an NFC imaging system in real time by developing an NIR imaging system and developing the grain sorter system that is considered to be defective in real time by checking the internal moisture content of the raw material in the real time.

• Earthquakes and Structures
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• v.5 no.2
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• pp.129-142
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• 2013

Linear and nonlinear time history analyses have been becoming more common in seismic analysis and design of structures with advances in computer technology and earthquake engineering. One of the most important issues for such analyses is the selection of appropriate acceleration time histories and matching these histories to a code design acceleration spectrum. In literature, there are three sources of acceleration time histories: artificial records, synthetic records obtained from seismological models and accelerograms recorded in real earthquakes. Because of the increase of the number of strong ground motion database, using and scaling real earthquake records for seismic analysis has been becoming one of the most popular research issues in earthquake engineering. In general, two methods are used for scaling actual earthquake records: scaling in time domain and frequency domain. The objective of this study is twofold: the first is to discuss and summarize basic methodologies and criteria for selecting and scaling ground motion time histories. The second is to analyze scaling results of time domain method according to ASCE 7-05 and Eurocode 8 (1998-1:2004) criteria. Differences between time domain method and frequency domain method are mentioned briefly. The time domain scaling procedure is utilized to scale the available real records obtained from near fault motions and far fault motions to match the proposed elastic design acceleration spectrum given in the Eurocode 8. Why the time domain method is preferred in this study is stated. The best fitted ground motion time histories are selected and these histories are analyzed according to Eurocode 8 (1998-1:2004) and ASCE 7-05 criteria. Also, characteristics of both near fault ground motions and far fault ground motions are presented by the help of figures. Hence, we can compare the effects of near fault ground motions on structures with far fault ground motions' effects.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.236-251
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• 2020

As remote sensing technologies are evolving, and more satellites are orbited, the demand for using satellite data for disaster monitoring is rapidly increasing. Although natural and social disasters have been monitored using satellite data, constraints on establishing an integrated satellite-based near real-time disaster monitoring system have not been identified yet, and thus a novel framework for establishing such system remains to be presented. This research identifies constraints on establishing satellite data-based near real-time disaster monitoring systems by devising and testing a new conceptual framework of disaster monitoring, and then presents a feasible disaster monitoring system that relies mainly on acquirable satellite data. Implementing near real-time disaster monitoring by satellite remote sensing is constrained by technological and economic factors, and more significantly, it is also limited by interactions between organisations and policy that hamper timely acquiring appropriate satellite data for the purpose, and institutional factors that are related to satellite data analyses. Such constraints could be eased by employing an integrated computing platform, such as Amazon Web Services(AWS), which enables obtaining, storing and analysing satellite data, and by developing a toolkit by which appropriate satellites'sensors that are required for monitoring specific types of disaster, and their orbits, can be analysed. It is anticipated that the findings of this research could be used as meaningful reference when trying to establishing a satellite-based near real-time disaster monitoring system in any country.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.325-334
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• 2022

Digital twin has the advantages of quality improvement and cost reduction, so it is widely applied to various industries. In this paper, a method to implement the major technologies of digital twin easily and quickly is presented. These include data management and relay servers, real-time monitoring applications including remote control interfaces, and direct connection protocols for video streaming. In addition, an algorithm for controlling a two-wheeled vehicle with a 2D interface is also proposed. The implemented system performs near real-time synchronization between the real environment and the virtual space. The delay time that occurs in remote control of the vehicle in the real environment was compared with the results of applying the proposed delay time reduction method. In addition, in the case of 2D interface-based control, an algorithm that can guarantee the user experience was implemented and applied to the actual environment and verified through experiments.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.471-484
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• 2017

GNSS PWV (Precipitable Water Vapor) is recognized as an important factor for weather forecasts of typhoons and heavy rainfall. Domestic and foreign research have been published that improve weather forecasts using GNSS PWV as initial input data to NWP (Numerical Weather Prediction) model. For rainfall-related weather forecasts, PWV should be provided in real time or NRT (Near-Real Time) and the accuracy and integrity should be maintained. In this paper, the development process of NRT GNSS PWV system using PPP (Precise Point Positioning). To this end, we optimized the variables related to tropospheric delay estimation of PPP. For the analysis of the PPP NRT PWV system, we compared the PWV precision of RP (Relative Positioning) and PPP. As a result, the accuracy of PPP was lower than that of RP, but good results were obtained in the PWV data integrity. Future research is needed to improve the precision of PWV in the PPP method.

• Journal of Astronomy and Space Sciences
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• v.21 no.2
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• pp.129-140
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• 2004

KAO(Korea Astronomy Observatory) GPS group has developed an iRTK system as a near-real time positioning system using GPS carrier phase data. We focused on improving the accuracy of positioning through the updated capability of data processing of KAO's iRTK system using low-cost L1 carrier phase receiver. The accuracy of a positioning was demonstrated by Extended Kalman filter. Experiments were accomplished using from 30m to 20km baselines. Within 10km, the positioning accuracy was improved by approximately 50-70% to the previous study using one minute observable data. However, it took two minutes to obtain 1m level positioning accuracy at 20km point. We expect that the developed iRTK system can be applied to the various fields of GPS in near-real time positioning.

• Journal of Aerospace System Engineering
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• v.14 no.2
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• pp.1-11
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• 2020

Detecting obstacles and generating a suitable path to avoid obstacles in real time is a prime mission requirement for UAVs. In areas, close to buildings and people, detecting obstacles in the path and estimating its own position (egomotion) in GPS degraded/denied environments are usually addressed with vision-based Simultaneous Localization and Mapping (SLAM) techniques. This presents possibilities and challenges for the feasible path generation with constraints of vehicle dynamics in the configuration space. In this paper, a near real-time feasible path is shown to be generated in the ORB-SLAM framework using a chain-based path planning approach in a force field with dynamic constraints on path length and minimum turn radius. The chain-based path plan approach generates a set of nodes which moves in a force field that permits modifications of path rapidly in real time as the reward function changes. This is different from the usual approach of generating potentials in the entire search space around UAV, instead a set of connected waypoints in a simulated chain. The popular ORB-SLAM, suited for real time approach is used for building the map of the environment and UAV position and the UAV path is then generated continuously in the shortest time to navigate to the goal position. The principal contribution are (a) Chain-based path planning approach with built in obstacle avoidance in conjunction with ORB-SLAM for the first time, (b) Generation of path with minimum overheads and (c) Implementation in near real time.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.455-462
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• 2020

Noise which is unwanted sound is a serious pollutant that can affect human health, as well as the working and living environment if exposed to humans. However, current noise management on the construction project is generally conducted after the noise exceeds the regulation standard, which increases the conflicts with inhabitants near the construction site and threats to the safety and productivity of construction workers. To overcome the limitations of the current noise management methods, the activities of construction equipment which is the main source of construction noise need to be managed throughout the construction period in real-time. Therefore, this paper proposed a framework for automatically detecting noise sources in construction sites in real-time based on convolutional neural networks (CNNs) according to the following four steps: (i) Step 1: Definition of the noise sources; (ii) Step 2: Data preparation; (iii) Step 3: Noise source classification using the audio CNN; and (iv) Step 4: Noise source detection using the visual CNN. The short-time Fourier transform (STFT) and temporal image processing are used to contain temporal features of the audio and visual data. In addition, the AlexNet and You Only Look Once v3 (YOLOv3) algorithms have been adopted to classify and detect the noise sources in real-time. As a result, the proposed framework is expected to immediately find construction activities as current noise sources on the video of the construction site. The proposed framework could be helpful for environmental construction managers to efficiently identify and control the noise by automatically detecting the noise sources among many activities carried out by various types of construction equipment. Thereby, not only conflicts between inhabitants and construction companies caused by construction noise can be prevented, but also the noise-related health risks and productivity degradation for construction workers and inhabitants near the construction site can be minimized.