The real-time kinematic (RTK) is one of precise positioning methods using Global Positioning System (GPS) data. In the long baseline GPS RTK, the ionospheric and tropospheric delays are critical factors for the positioning accuracy. In this paper we present RTK algorithms for long baselines more than 100 km with estimating tropospheric delays. The state vector is estimated by the extended Kalman filter. We show the experimental results of GPS RTK for various baselines (162.10, 393.37, 582.29, and 1283.57 km) by using the Korea Astronomy and Space Science Institute GPS data and one International GNSS Service (IGS) reference station located in Japan. As a result, we present that long baseline GPS RTK can provide the accurate positioning for users less than few centimeters.
Kim, Hong Gyun;Park, Sung Wook;Yeo, Kang Dong;Lee, Moon Se;Park, Hyuck Jin;Lee, Jung Hyun;Hong, Sung Jin
The Journal of Engineering Geology
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v.26
no.2
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pp.197-205
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2016
Rainfall-induced landslide disaster case histories are typically required to establish critical lines based on the decrease coefficient for judging the likelihood of slope collapse or failure; however, reliably setting critical lines is difficult because the number of nationwide disaster case histories is insufficient and not well distributed across the region. In this study, we propose a method for setting the critical area to judge the risk of slope collapse without disaster case history information. Past 10 years rainfall data based on decrease coefficient are plotted as points, and a reference line is established by connecting the outermost points. When realtime working rainfall cross the reference line, warning system is operating and this system can be utilized nationwide through setting of reference line for each AWS (Automatic Weather Station). Warnings were effectively predicted at 10 of the sites, and warnings could have been issued 30 min prior to the landslide movement at eight of the sites. These results indicate a reliability of about 67%. To more fully utilize this model, it is necessary to establish nationwide rainfall databases and conduct further studies to develop regional critical areas for landslide disaster prevention.
MPEG-4 is a standard for multimedia applications and provides a set of technologies to satisfy the needs of authors, service providers and end users alike. In this paper, we suggest a Real-time Multiple Circular Buffer (M4RM Buffer) model, which is suitable for streaming these MPEG-4 contents efficiently. M4RM buffer generates each structure of the buffer, which matches well with each object composing an MPEG-4 content, according to the transferred information, and manipulates multiple read/write operations only by its reference. It divides the decoder buffer and the composition buffer, which are described in the standard, by the unit of frame allocated to minimize the range of access. This buffer unit of a frame is allocated according to the object description. Also, it processes the objects synchronization within the buffer and provides APIs for an efficient buffer management to process the real-time user events. Based on the performance evaluation, we show that M4RM buffer model decreases the waiting time in a buffer frame, and so allows the real-time streaming of an MPEG-4 content using the smaller size of the memory block than IM1-2D and Window Media Player.
Park, Jin Sol;Han, Joong-Hee;Kwon, Jay Hyoun;Shin, Han Sup
Spatial Information Research
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v.22
no.3
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pp.23-24
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2014
NGII (National Geographic Information Institute) has been providing VRS (Virtual Reference Station) service so that could determine precise positioning in real time since 2007. However, since the VRS service has to maintain the connected status with VRS server, the number of users who can use VRS service are limited by capacity of VRS server. To solve this problem, NGII has been providing FKP (Virtual Reference Station) service using one way telecommunication from November 1, 2012. Therefore, it is predicted that the usage of FKP service will increase in public surveying and cadastral resurveying in the future. However, the studies with respect to analysis of FKP precision for applying to public surveying and cadastral resurveying is not conducted enough. In this study, to analyse the application possibility of FKP on the public surveying and cadastral resurveying, the two kind analysis were performed. First is the analysis of accuracy according to the configuration of reference station of FKP and VRS. One is consisted of same reference stations, another is consisted of different reference stations. Second is the accuracy anlalysis of horizontal and vertical positioning acquiring VRS and FKP data in various measurement environment based on VRS regulation. Result of first study, Positioning accuracy according to the configuration of the reference stations satisfies related regulation. However, accuracy of FKP in case of different reference stations is worse than in case of same reference stations.. The result of second test shows that the horizontal precision of FKP and VRS in good measurement environment satisfy the allowed precision. However, in some case, horizontal precision of FKP and VRS in poor measurement environment exceed the allowed precision. In addition, the number of exceeding the allowed precision in the FKP is more than the VRS. The vertical precision of the VRS satisfy related work provision. In conclusion, the result of this study shows that the FKP only in open area should be used for public survey and cadastral resurvey. Therefore the additional studies with respect to the improvement of FKP precision should be conducted.
One-way Network-RTK(Real Time Kinematics) is considered as a method which can satisfy moving vehicle's recently-required high accuracy and mobility. When we use one-way Network RTK for vehicle navigation, multiple cells-based system is required to provide the service continuously in wide area. The rover which moves through various cells inevitably experiences a correction discontinuity, which is not eliminated by the DD(Double Difference) method and to cause 13cm(horizontal) and 48cm(vertical) position error. We suggest three solutions to reduce this discontinuity, which are identification of master RS with neighbor networks, duplication of communication module to receive corrections from other cells, and ambiguity adjustment between neighbor cells. All of our suggestions reduce the error to 1/4 wavelength in measurement and 3cm in position-domain, and we suggest the ambiguity adjustment is the best when we consider the extendibility of service area and the cost of rover device.
Fair packet scheduling algorithms supporting quality-of-services of real-time multimedia applications can be classified into the following two design schemes in terms of the reference time used in calculating the timestamp of arriving packet: Finish-time Design (FD) and Start-time Design (SD) schemes. Since the former can adjust the latency of a flow with raising the flow's reserved rate, it has been applied to a router for the guaranteed service of the IETF (Internet Engineering Task Force) IntServ model. However, the FD scheme may incur severe bandwidth loss for traffic flows requiring low-rate but strong delay bound such as internet phone. In order to verify the usefulness of the SD scheme based router for the IETF guaranteed service, this paper analyzes and compares two design schemes in terms of bandwidth and payload utilizations. It is analytically proved that the SD scheme is better bandwidth utilization than the FD one, and the simulation result shows that the SD scheme gives better payload utilization by up to 20%.
Journal of Korean Library and Information Science Society
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v.52
no.1
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pp.155-178
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2021
In the era of the 4th industrial revolution, public libraries need a strategy for promoting intelligent library services in order to actively respond to changes in the external environment such as artificial intelligence. Therefore, in this study, based on the concept of artificial intelligence and analysis of domestic and foreign artificial intelligence related trends, policies, and cases, we proposed the future direction of introduction and development of artificial intelligence services in the library. Currently, the library operates a reference information service that automatically provides answers through the introduction of artificial intelligence technologies such as deep learning and natural language processing, and develops a big data-based AI book recommendation and automatic book inspection system to increase business utilization and provide customized services for users. Has been provided. In the field of companies and industries, regardless of domestic and overseas, we are developing and servicing technologies based on autonomous driving using artificial intelligence, personal customization, etc., and providing optimal results by self-learning information using deep learning. It is developed in the form of an equation. Accordingly, in the future, libraries will utilize artificial intelligence to recommend personalized books based on the user's usage records, recommend reading and culture programs, and introduce real-time delivery services through transport methods such as autonomous drones and cars in the case of book delivery service. Service development should be promoted.
A stereoscopic 3D video service is able to provide a 3D video service while keeping backward compatibility with the existing 2D video service. In the terrestrial digital television (DTV) system, a stereoscopic video codec is required to have high coding efficiency in order to provide a 3D video service in the same channel capacity. A hybrid codec consisting of MPEG-2 for base video and H.264/AVC or HEVC for 3D auxiliary video is considered. Furthermore, Non-Real-Time (NRT) delivery of stereoscopic video is also considered as a service scenario for 3DTV services to overcome the limited bandwidth. In this paper, we propose a stereoscopic video coding scheme using adaptive loop filter (ALF) which had been considered in HEVC as a pre-/post-filter for enhancing coding efficiency in NRT-based 3DTV services. In order to apply ALF as a post-filter to the reconstructed additional view coded by H.264/AVC, we devise a method in which ALF is adaptively applied based on a structure determined by using macroblock (MB) coding information such as MB mode type and reference index instead of coding unit (CU) structure on which ALF is applied in the HEVC. Experimental results shows that the proposed stereoscopic video coding scheme applying ALF obtains up to 24.9% gain of bit saving.
Park, Han-Earl;Roh, Kyoung Min;Yoo, Sung-Moon;Choi, Byung-Kyu;Chung, Jong-Kyun;Cho, Jungho
Journal of Positioning, Navigation, and Timing
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v.3
no.4
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pp.131-141
/
2014
Over the last decade, the Global Navigation Satellite System (GNSS) has been increasingly utilized as a meteorological research tool. The Korea Astronomy and Space Science Institute (KASI) has also been developing a near real-time GNSS precipitable water vapor (PWV) information management system that can produce a precise PWV for the Korean Peninsula region using GNSS data processing and meteorological measurements. The goal of this paper is to evaluate whether the precise point positioning (PPP) strategy will be used as the new data processing strategy of the GNSS-PWV information management system. For this purpose, quality assessment has been performed by means of a comparative analysis of the troposphere zenith total delay (ZTD) estimates from KASI PPP solutions (KPS), KASI network solutions (KNS), and International GNSS Service (IGS) final troposphere products (IFTP) for ten permanent GNSS stations in the Korean Peninsula. The assessment consists largely of two steps: First, the troposphere ZTD of the KNS are compared to those of the IFTP for only DAEJ and SUWN, in which the IFTP are used as the reference. Second, the KPS are compared to the KNS for all ten GNSS stations. In this step, the KNS are used as a new reference rather than the IFTP, because it was proved in the previous step that the KNS can be a suitable reference. As a result, it was found that the ZTD values from both the KPS and the KNS followed the same overall pattern, with an RMS of 5.36 mm. When the average RMS was converted into an error of GNSS-PWV by considering the typical ratio of zenith wet delay and PWV, the GNSS-PWV error met the requirement for PWV accuracy in this application. Therefore, the PPP strategy can be used as a new data processing strategy in the near real-time GNSS-PWV information management system.
In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.
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