• Journal of the Ergonomics Society of Korea
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• v.30 no.4
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• pp.563-569
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• 2011

Objective: This study focuses on the effects of pre-cues informing the location of upcoming visual stimulus on finger movement response in the context of control-on-display interfaces. Background: Previous research on pre-cues focus on attention allocation and motion studies were limited to indirect control conditions. The design of this study aimed to collect data on the exact landing point for finger-tap responses to a given visual stimulus. Method: Controlled visual stimuli and tasks were presented on a UI evaluation system built using mobile web standards; response accuracy and response time were measured and collected as appropriate. Among the 16 recruited participants, 11 completed the experiment. Results: Providing pre-cue on the location of stimulus affected response time and response accuracy. The response bias, which is a distance from the center of stimulus to the finger-tap location, was larger when the pre-cue was given during a one-handed operation. Conclusion: Given a pre-cue, response time decreases, but with accuracy penalized. Application: In designing touch-screen UI's - more strictly, visual components also acting as controllers - designers would do well to balance human perceptual and cognitive characteristics strategically.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1337-1362
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• 2020

Advances in localization-based technologies and the increase in ubiquitous computing have led to a growing interest in location-based applications and services. High accuracy of the position of a wireless device is still a crucial requirement to be satisfied. Firstly, the rapid development of wireless communication technologies has affected the location accuracy of radio monitoring systems employed locally and globally. Secondly, the location is determined using standard complex computing methods and needs a relatively long execution time. In this paper, two geolocalization techniques, based on trigonometric and CORDIC computing processes, are proposed and implemented for Bluetooth-based indoor monitoring applications. Theoretical analysis and simulation results are investigated in terms of accuracy, scalability, and responsiveness. They show that the proposed techniques can locate a target wireless device accurately and are well suited for timing estimation.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1360-1362
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• 1999

This paper describes the fault location technique using wavelets in transmisson line. Estimation of fault location is performed using synchronized data sampled at two ends of line and travelling wave. The similar current wave modeled in PSCAD/EMTDC and MATLAB was applied to evaluate the accuracy of theory proposed in this paper. The results of fault location shown in this paper will be evaluated as an effective suggestion for fault location in real transmisson line

• Journal of Internet Computing and Services
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• v.2 no.5
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• pp.49-58
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• 2001

Mobile positioning measurement is the most important technology for Location Based Services in the cellular networks. Generally, we are expecting to use GPS to guarantee high accuracy of the mobile position, A CDMA network-based technique for the Mobile Station position calculation needs to be implemented in the cdma2000 network whether the handsets have GPS or not, The most reliable methods of the network-based location technologies are based on the estimation of time of signal traveling between MS and B18 in a network whose coordinates are identified, Other signal parameters such as the power of the received signal and the signal arrival direction cannot be used as main data for a location system because adoption of only the signal parameters will not meet the FCC requirements, In practice, the estimates of the time of signal propagation between MS and BTS always have errors resulting from low-resolution power of measurements and multi path signal propagation, This paper describes the combined network-based location technology in the cdma2000 1× necessary to meet US FCC requirements. The issues of a calibration table and statistic processing based on the pilot strength as well as combined network-based location technologies(TOA/ TDOA) will help to achieve higher location accuracy than specified in the US FCC Rule.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.308-311
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• 2008

One of the key technical elements of wireless sensor network (WSN) is location management of sensor nodes. Typical node location management methods use GPS, ultrasonic sensors or RSSI. In this paper we propose a new location management method which adopts regression analysis of RSSI measurement to improve the accuracy of sensor node position estimation. We also evaluated the performance of proposed method by comparing the experimental results with existing scheme. According to the results, our proposed method showed better accuracy than existing location management scheme using RSSI and Firis' equation.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.29-35
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• 2021

In this paper, we propose a method that combines KNN(K-Nearest Neighbor), Local Map Classification and Bayes Filter as a way to increase the accuracy of location positioning. First, in this technique, Local Map Classification divides the actual map into several clusters, and then classifies the clusters by KNN. And posterior probability is calculated through the probability of each cluster acquired by Bayes Filter. With this posterior probability, the cluster where the robot is located is searched. For performance evaluation, the results of location positioning obtained by applying KNN, Local Map Classification, and Bayes Filter were analyzed. As a result of the analysis, it was confirmed that even if the RSSI signal changes, the location information is fixed to one cluster, and the accuracy of location positioning increases.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.286-288
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• 2003

In this paper, we present our implementation of the direct camera model (image to ground) for SPOT5 and use it to assess the geometric accuracy of SPOT5 imagery. Our assessment confirms the location accuracy of SPOT5 imagery (without use of GCPs) is less than 50m. We further introduce a few attitude parameters to refine the camera model with GCPs. The model is applied to two SPOT5 supermode images, one near vertical, incidence angle of 3 degrees, and one far oblique, incidence angle of 27 degrees. The results show that accuracy (rms of check points) of about one pixel (2.5m) can be achieved with about 4 GCPs by using only 3 parameters to correct the yaw, pitch and roll of the satellite.

• 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 Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.217-227
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• 2022

In order to provide a location-based services regardless of indoor or outdoor space, it is important to provide position information of the terminal regardless of location. Among the wireless/mobile communication resources used for this purpose, Long Term Evolution (LTE) signal is a representative infrastructure that can overcome spatial limitations, but the positioning method based on the location of the base station has a disadvantage in that the accuracy is low. Therefore, a fingerprinting technique, which is a pattern recognition technology, has been widely used. The simplest yet widely applied algorithm among Fingerprint positioning technologies is k-Nearest Neighbors (kNN). However, in the kNN algorithm, it is difficult to find the optimal K value with the lowest positioning error for each location to be estimated, so it is generally fixed to an appropriate K value and used. Since the optimal K value cannot be applied to each estimated location, therefore, there is a problem in that the accuracy of the overall estimated location information is lowered. Considering this problem, this paper proposes a technique for adaptively varying the K value by using a Convolutional Neural Network (CNN) model among Artificial Neural Network (ANN) techniques. First, by using the signal information of the measured values obtained in the service area, an image is created according to the Physical Cell Identity (PCI) and Band combination, and an answer label for supervised learning is created. Then, the structure of the CNN is modeled to classify K values through the image information of the measurements. The performance of the proposed technique is verified based on actual data measured in the testbed. As a result, it can be seen that the proposed technique improves the positioning performance compared to using a fixed K value.

• Journal of the Korea Safety Management & Science
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• v.14 no.1
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• pp.217-224
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• 2012

Location-Based Services(LBS) is a service that provide location information by using communication network or satellite signal. In order to provide LBS precisely and efficiently, we studied how we can reduce the error on location determination of objects such people and things. We focus on using the least square method and triangulation positioning method to improves the accuracy of the existing location determination method. Above two methods is useful if the distance between the AP and the tags can be find. Though there are a variety of ways to find the distance between the AP and tags, least squares and triangulation positioning method are wildely used. In this thesis, positioning method is composed of preprocessing and calculation of location coordinate and detail of methodology in each stage is explained. The distance between tag and AP is adjusted in the preprocessing stage then we utilize least square method and triangulation positioning method to calculate tag coordinate. In order to confirm the performance of suggested method, we developed the test program for location determination with Labview2010. According to test result, triangulation positioning method showed up loss error than least square method by 38% and also error reduction was obtained through adjustment process and filtering process. It is necessary to study how to reduce error by using additional filtering method and sensor addition in the future and also how to improve the accuracy of location determination at the boundary location between indoor and outdoor and mobile tag.