• Special Issue of the Society of Naval Architects of Korea
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• 2008.09a
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• pp.33-37
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• 2008

The evidence of the Cargo tank volume is very important between Buyer and Seller for agreement each other for LNG Ship. CTS(Custody Transfer System) Radar type level gauging sensor to be measured for cargo volume. The data of Trim & List sensor to be compensated for measuring data which is original data of the CTS sensor. The latest days, the Buyer would have posed a problem both the location and the accuracy of trim/list sensor specially neared final stage of the ship's delivery. So, we would like to report the introducing to the trim/list sensor and the confirmation of actual location for the trim/list sensor.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1327-1335
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• 2010

In this paper, we want to develop objective priors for the common location parameter in two half-t distributions with unequal scale parameters. The half-t distribution is a non-regular class of distribution. One can not develop the reference prior by using the algorithm of Berger of Bernardo (1989). Specially, we derive the reference priors and prove the propriety of joint posterior distribution under the developed priors. Through the simulation study, we show that the proposed reference prior matches the target coverage probabilities in a frequentist sense.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.4
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• pp.144-150
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• 2006

IEC 61850 is the worldwide protocol for the substation automation system. IEC 61850 transports the information which consists of different formats such as GOOSE(Generic Object Oriented Substation Event), MMS(Manufacturing Message Specification), SV(Sampled Values) and so on. For real time data transmission, GOOSE can be used. The remote-bus current data which were collected in a local-bus current differential IED can be transmitted to a distance IED at the same location by using GOOSE messages. The distance IED can eliminate the reactance effect by using the transmitted remote-bus current data. This method can improve the performance of the fault location.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.266-268
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• 2003

This paper proposes the Fault Location Estimation Algorithm in the parallel transmission lines. These algorithm uses a variable data window method based on least square error method to estimate fault impedance quickly. And it selects the optimal equation according to the operation situation and usable fault data for minimizing the fault estimation error effected by the zero sequence mutual coupling. After simulation result, we can see that these algorithm estimates fault location more rapidly and exactly.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.51-57
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• 2017

The purpose of this study is to design a system that can be used for military simulation and virtual training using the location information of individual soldier's weapons. After acquiring the location information using Arduino's GPS shield, it is designed to transmit data to the Smartphone using Bluetooth Shield, and transmit the data to the server using 3G/4G of Smartphone in real time. The server builds the system to measure, analyze and manage the current position and the tracking information of soldier. Using this proposed system makes it easier to analyze the training situation for individual soldiers and expect better training results.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.39-46
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• 2019

Human mobility estimation plays a key factor in a lot of promising applications including location-based recommendation systems, urban planning, and disease outbreak control. We study the human mobility estimation problem in the case where recent locations of a person-of-interest are unknown. Since matrix decomposition is used to perform latent semantic analysis of multi-dimensional data, we propose a human location estimation algorithm based on matrix factorization to reconstruct the human movement patterns through the use of information of persons with correlated movements. Specifically, the optimization problem which minimizes the difference between the reconstructed and actual movement data is first formulated. Then, the gradient descent algorithm is applied to adjust parameters which contribute to reconstructed mobility data. The experiment results show that the proposed framework can be used for the prediction of human location and achieves higher predictive accuracy than a baseline model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2961-2975
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• 2022

The Location-Based Service (LBS) is one of the most well-known services on the Internet. Positioning is the primary association with LBS services. This study proposes an intelligent LoRa-based positioning system, called AI@LBS, to provide accurate location data. The fingerprint mechanism with the clustering algorithm in unsupervised learning filters out signal noise and improves computing stability and accuracy. In this study, data noise is filtered using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, increasing the positioning accuracy from 95.37% to 97.38%. The problem of data imbalance is addressed using the SMOTE (Synthetic Minority Over-sampling Technique) technique, increasing the positioning accuracy from 97.38% to 99.17%. A field test in the NTUST campus (www.ntust.edu.tw) revealed that AI@LBS system can reduce average distance error to 0.48m.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.47-53
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• 2011

To enable the efficient operation of ITS, it is necessary to collect location data for vehicles on the road. In the case of futuristic transportation systems like ubiquitous transportation and smart highway, a method of data collection that is advanced enough to incorporate road lane recognition is required. To meet this requirement, technology based on radio frequency identification (RFID) has been researched. However, RFID may fail to yield accurate location information during high-speed driving because of the time required for communication between the tag and the reader. Moreover, installing tags across all roads necessarily incurs an enormous cost. One cost-saving alternative currently being researched is to utilize GNSS (global navigation satellite system) carrierbased location information where available. For lane recognition using GNSS, a precise digital map for determining vehicle position by lane is needed in addition to the carrier-based GNSS location data. A "precise digital map" is a map containing the location information of each road lane to enable lane recognition. At present, precise digital maps are being created for lane recognition experiments by measuring the lanes in the test area. However, such work is being carried out through comparison with vehicle driving information, without definitions being established for detailed performance specifications. Therefore, this study analyzes the performance requirements of a precise digital map capable of lane recognition based on the accuracy of GNSS location information and the accuracy of the precise digital map. To analyze the performance of the precise digital map, simulations are carried out. The results show that to have high performance of this system, we need under 0.5m accuracy of the precise digital map.

• Journal of KIISE:Information Networking
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• v.32 no.1
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• pp.80-88
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• 2005

In ubiquitous spaces, a user wants to be provided with a VOD service while moving one space to another freely. Since the traditional VOD system is dependent on user location, the VOD server transmits video data to a single client during a session. If the user moves to another space, he/she should close the old session and make a new request for the same video. However, the location-aware VOD system supports user mobility by closing and opening the session automatically. That is, the VOD system automatically perceives the movement of a user and allows the server to change the data flow so that a client near the user can receive the video data. This paper proposes a location-aware VOD service architecture and a session handoff scheme to provide a mobile user with continuous video delivery and implements a location-aware VOD prototype system based on Jini and Java. In experiment, we show that the proposed handoff scheme has a smaller handoff delay than the other handoff scheme.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.456-457
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• 2021

Recently, in order to more accurately provide indoor location-based services, technologies using Wi-Fi fingerprints and deep learning are being studied. Among the deep learning models, an RNN model that can store information from the past can store continuous movements in indoor positioning, thereby reducing positioning errors. When using an RNN model for indoor positioning, the collected training data must be continuous sequential data. However, the Wi-Fi fingerprint data collected to determine specific location information cannot be used as training data for an RNN model because only RSSI for a specific location is recorded. This paper proposes a region clustering technique for sequential input data generation of RNN models based on Wi-Fi fingerprint data.