• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.4
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• pp.415-423
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• 2001

This paper deals with the data processing method relative to reference frames through the calculation of absolute coordinates of permanent GPS site which was established at Sungkyunkwan University. In this paper. we computed the ITRF97 coordinates with high precision (0.0001 ppm) from GPS data analysis. Also, we derived the accurate coordinates referred to WGS84 and Korean Geodetic Datum (KGD) using transformation parameters provided. ITRF97 coordinates were computed by using the GIPSY-OASIS II (GOA II) software and the algorithms for determining the position developed Jet Propulsion Laboratory (JPL). The coordinates referred to WGS84 and KGD were derived from the transformation parameters provided by International Earth Rotation Service (IERS) and National Geography Institute (NGI). The parameters determined by NGI were calculated from the 2000 project of the establishment of geocentric coordinate system. We tested its availability through the comparison of the coordinates obtained from local GPS data analysis.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.6
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• pp.718-731
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• 2003

SAN(Storage Area Network) was developed in response to the requirements of high availability of data, scalable growth, and system performance. In order to use the SAN more efficiently, most of the SAN operating software supports storage virtualization concepts that allow users to view physical storage devices of the SAN as a large volume. A logical volume manager plays a key role in storage virtualization. It realizes the storage virtualization by mapping logical addresses to physical addresses. In this paper, we design and implement an efficient and flexible mapping method for the logical volume manager. Additionally we also design and implement a free space management method for flexible mapping. Our mapping method supports a snapshot that preserves a volume image at certain time and on-line reorganization to allow users to add or remove storage devices to and from the SAN even while the system is running. To justify our mapping method, we compare it with the mapping method of the GFS (Global File System) through various experiments.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.3
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• pp.260-267
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• 2007

GPS adapter kit (GAK) is a GPS/INS guided range extension system to improve the accuracy and availability of existing dumb bombs. In this paper, a van test result of GPS/INS navigation module (NM) for guided bomb with GAK has been presented. The NM consists of a commercial MEMS IMU, embedded GPS receiver and navigation computer unit (NCU). The GPS receiver of NM was designed to use multiple antennas for satellite visibility and GPS attitude determination. The real-time navigation software was designed by modularized structure to guarantee the maintainability and extensibility. In order to evaluate the performance of the NM, a van test was preformed by using a high performance INS - Honeywell H-726 MAPS(Modular Azimuth Position System).The van test results show that the GAK NM with GPS attitude measurement gives better navigation performance than a conventional GPS/INS integration and good coasting capabilities under jamming environment.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.93-99
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• 2010

Since the facility management for various facilities in urban area are conducted by general managers who have poor knowledge for surveying technology, it is not easy to trace the exact location of the facility in a short time with the GIS map only by themselves in the field. In order to improve it, VRS-RTK or SBAS DGPS system integrated with UMPC and PDA which is uploaded GIS field software are being used recently however lot of difficulties are still existed with the GPS positioning in urban area due to the lack of visible satellites, no reception of correction data and multipath error by the interruption of the high buildings and houses etc. Therefore, in this study, we applied with Network DGPS system which allows better reception of satellite signal and correction data even in dense housing areas with the use of GNSS receiver and CDMA mobile phone. Based on the analysis of field data, it was confirmed that standard deviations of the Network DGPS positioning are 0.3 to 0.84m with a very high positioning rate even in dense housing areas. Therefore, it was concluded that the Network DGPS system could be used widely to fast and accurate positioning for various facilities management works in dense housing areas in the future.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.253-259
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• 2017

Recent development in science and technology has modernized the weapon system of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need accurate demand forecasts for spare parts. We attempted to find consumption pattern using data mining techniques. First we gathered a large amount of component consumption data through the DELIIS (Defense Logistics Intergrated Information System). Through data collection, we obtained 42 variables such as annual consumption quantity, ASL selection quantity, order-relase ratio. The objective variable is the quantity of spare parts purchased in f-year and MSE (Mean squared error) is used as the predictive power measure. To construct an optimal demand forecasting model, regression tree model, randomforest model, neural network model, and linear regression model were used as data mining techniques. The open software R was used for model construction. The results show that randomforest model is the best value of MSE. The important variables utilized in all models are consumption quantity, ASL selection quantity and order-release rate. The data related to the demand forecast of spare parts in the DELIIS was collected and the demand for the spare parts was estimated by using the data mining technique. Our approach shows improved performance in demand forecasting with higher accuracy then previous work. Also data mining can be used to identify variables that are related to demand forecasting.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.313-320
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• 2019

Nowadays, as the availability of tiny, low-cost microcomputer increases at a high level, mobile robots are experiencing remarkable enhancements in hardware design, software performance, and connectivity advancements. In order to control Turtlebot 2, several algorithms have been developed using the Robot Operating System(ROS). However, ROS requires to be run on a high-cost computer which increases the hardware cost and the power consumption to the robot. Therefore, design an algorithm based on low-cost hardware is the most innovative way to reduce the unnecessary costs of the hardware, to increase the performance, and to decrease the power consumed by the computer on the robot. In this paper, we present a path-finding algorithm for TurtleBot 2 based on low-cost hardware. We implemented the algorithm using Raspberry pi, Windows 10 IoT core, and RPLIDAR A2. Firstly, we used Raspberry pi as the alternative to the computer employed to handle ROS and to control the robot. Raspberry pi has the advantages of reducing the hardware cost and the energy consumed by the computer on the robot. Secondly, using RPLIDAR A2 and Windows 10 IoT core which is running on Raspberry pi, we implemented the path-finding algorithm which allows TurtleBot 2 to navigate from the starting point to the destination using the map of the area. In addition, we used C# and Universal Windows Platform to implement the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.11
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• pp.502-510
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• 2006

In this paper, we describe implementation of a computer access device for the severly motor-disability. Many people with severe motor disabilities need an augmentative communication technology. Those who are totally paralyzed, or 'locked-in' cannot use conventional augmentative technologies, all of which require some measure of muscle control. The forehead is often the last site to suffer degradation in cases of severe disability and degenerative disease. For example, In ALS(Amyotrophic Lateral Sclerosis) and MD(Muscular dystrophy) the ocular motorneurons and ocular muscles are usually spared permitting at least gross eye movements, but not precise eye pointing. We use brain and body forehead bio-potentials in a novel way to generate multiple signals for computer control inputs. A bio-amplifier within this device separates the forehead signal into three frequency channels. The lowest channel is responsive to bio-potentials resulting from an eye motion, and second channel is the band pass derived between 0.5 and 45Hz, falling within the accepted Electroencephalographic(EEG) range. A digital processing station subdivides this region into eleven components frequency bands using FFT algorithm. The third channel is defined as an Electromyographic(EMG) signal. It responds to contractions of facial muscles and is well suited to discrete on/off switch closures, keyboard commands. These signals are transmitted to a PC that analyzes in a time series and a frequency region and discriminates user's intentions. That software graphically displays user's bio-potential signals in the real time, therefore user can see their own bio-potentials and control their physiological signals little by little after some training sessions. As a result, we confirmed the performance and availability of the developed system with experimental user's bio-potentials.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.171-174
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• 2006

A large number of service providers in countries all over the world have established GNSS reference station networks in the last years and are using network software today to provide a correction stream to the user as a routine service. In current GNSS network processing, all the geometric related information such as ionospheric free carrier phase ambiguities from all stations and satellites, tropospheric effects, orbit errors, receiver and satellite clock errors are estimated in one centralized Kalman filter. Although this approach provides an optimal solution to the estimation problem, however, the processing time increases cubically with the number of reference stations in the network. Until now one single Personal Computer with Pentium 3.06 GHz CPU can only process data from a network consisting of no more than 50 stations in real time. In order to process data for larger networks in real time and to lower the computational load, a federated filter approach can be considered. The main benefit of this approach is that each local filter runs with reduced number of states and the computation time for the whole system increases only linearly with the number of local sensors, thus significantly reduces the computational load compared to the centralized filter approach. This paper presents the technical aspect and performance analysis of the federated filter approach. Test results show that for a network of 100 reference stations, with the centralized approach, the network processing including ionospheric modeling and network ambiguity fixing needs approximately 60 hours to process 24 hours network data in a 3.06 GHz computer, which means it is impossible to run this network in real time. With the federated filter approach, only less than 1 hour is needed, 66 times faster than the centralized filter approach. The availability and reliability of network processing remain at the same high level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.587-594
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• 2018

The purpose of this study is to propose a power demand volatility evaluation system based on LSTM and not to verify the accuracy of the demand module which is a core module, but to recognize the sudden change of power pattern by using deeplearning in the actual power demand monitoring system. Then we confirm the availability of the module. Also, we tried to provide a visualized report so that the manager can determine the fluctuation of the power usage patten by applying it as a module to the web based system. It is confirmed that the power consumption data shows a certain pattern in the case of government offices and hospitals as a result of implementation of the volatility evaluation system. On the other hand, in areas with relatively low power consumption, such as residential facilities, it was not appropriate to evaluate the volatility.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.309-315
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• 2017

Recently it has drawn much attention on the technologies about Internet of Things (IoT) which connects objects with constrained resource and heterogenous communication module in order to communicate information via internet. We propose a real-time sensor monitoring system based on IPv6 over Bluetooth Low Energy (BLE), which is included in Bluetooth 4.2 Specification. Since this system uses a publish-subsribe based IoT protocol, so called Message Queueing Telemetry Transport (MQTT), neither transforming network data nor any proxy server is needed in order to transmit data. Through the web client connected to this system, you can monitor sensor data sent by BLE device in real-time, intermediated via MQTT broker and then delivered to the client via HTTP and websocket protocol. In this paper we evaluated network capacity and availability of the implemented test platform. Thus by using this system it is possible to make development cost low and to construct IoT network with heterogenous devices easily.