• Journal of Sensor Science and Technology
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• v.32 no.4
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• pp.232-237
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• 2023

This paper presents a system for estimating the position of a magnet using a magnetic sensor. An algorithm is presented to analyze the waveform and output voltage values of the magnetic field generated at each position when the magnet moves and to estimate the position of the magnet based on the analyzed data. Here, the magnet is sufficiently small to be inserted into a blood vessel and has a micro-magnetic field of hundreds of nanoteslas owing to the small size and shape of the guide wire. In this study, a highly sensitive magneto-impedance (MI) sensor was used to detect these micro-magnetic fields. Nine MI sensors were arranged in a 3×3 configuration to detect a magnetic field that changes according to the position of the magnet through the MI sensor, and the voltage value output was polynomially regressed to specify a position value for each voltage value. The accuracy was confirmed by comparing the actual position value with the estimated position value by expanding it from a 1D straight line to a 3D space. Additionally, we could estimate the position of the magnet within a 3% error.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.20-29
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• 2013

The compression of video data is intended for real-time transmission of band-limited channels. Compressed video bit-streams are very sensitive to transmission error. If we lose packets or receive them with errors during transmission, not only the current frame will be corrupted, but also the error will propagate to succeeding frames due to the spatio-temporal predictive coding structure of sequences. Error detection and concealment is a good approach to reduce the bad influence on the reconstructed visual quality. To increase concealment efficiency, we need to get some more accurate error detection algorithm. In this paper, We hide specific data into the motion vector difference of each macro-block, which is obtained from the procedure of inter prediction mode in H.264/AVC. Then, the location of errors can be detected easily by checking transmitted specific data in decoder. We verified that the proposed algorithm generates good performances in PSNR and subjective visual quality through the computer simulation by H.324M mobile simulation tool.

• Journal of the Korea Institute of Building Construction
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• v.23 no.2
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• pp.209-220
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• 2023

Ensuring accuracy within tolerance is crucial for a marking robot; however, rebar displacement frequently occurs during the structural work process, necessitating corrections to layout lines or rebar locations. To guarantee precision and automation, the marking robot must be capable of measuring rebar error and determining appropriate adjustments for marking lines and rebar placement. Consequently, this study proposes a method for measuring rebar location error using a LiDAR sensor and implementing a layout assessment process based on the measurement results. The rebar recognition experiment using the LiDAR sensor yielded an average error of 5mm, demonstrating a reliable level of accuracy for wall rebars. Additionally, this research proposed a process that enables the robot to evaluate rebar and marking corrections based on the error range. The findings of this study can contribute to the automated operation of marking robots while accounting for construction errors, potentially leading to improvements in structural quality.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.2
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• pp.146-156
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• 2010

The objective of this study was to improve the accuracy of calculation and estimation of solar radiation and duration of sunshine, which are the most important variables of photovoltaic power generation in deciding the location of photovoltaic facilities efficiently. With increasing interest in new and renewable energies, research on solar energy is also being conducted actively, but there have not been many studies on the location of photovoltaic facilities. Thus, this study calculated solar duration and solar radiation based on geographical factors, which have the most significant effect on solar energy in GIS environment, and corrected the results of analysis using diffuse radiation. Moreover, we performed ordinary kriging, a spatial statistical analysis method, for estimating values for parts deviating from the spatial resolution of input data, and used variogram, which can determine the spatial interrelation and continuity of data, in order to estimate accurate values. In the course, we compared the values of variogram factors and estimates from applicable variogram models, and selected the model with the lowest error rate. This method is considered helpful to accurate decision making on the location of photovoltaic facilities.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.146-153
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• 2010

For the indoor location, wireless fingerprinting is most favorable because fingerprinting is most accurate among the technique for wireless network based indoor location which does not require any special equipments dedicated for positioning. As fingerprinting method,k-nearest neighbor(KNN) has been widely applied for indoor location in wireless location area networks(WLAN), but its performance is sensitive to number of neighborsk and positions of reference points(RPs). So possibilistic fuzzy c-means(PFCM) clustering algorithm is applied to improve KNN, which is the KNN/PFCM hybrid algorithm presented in this paper. In the proposed algorithm, through KNN,k RPs are firstly chosen as the data samples of PFCM based on signal to noise ratio(SNR). Then, thek RPs are classified into different clusters through PFCM based on SNR. Experimental results indicate that the proposed KNN/PFCM hybrid algorithm generally outperforms KNN and KNN/FCM algorithm when the locations error is less than 2m.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.3
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• pp.331-339
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• 2016

Real time location (RTL) system which can control the safety of laborers in the underground space is developed in this study. This innovative system can monitor the location and history of movement of multiple laborers in real time. To accommodate constrains of the underground space, the system is portable and composed with low-battery mode. Since conventional method to detect the location of laborer with radio signal strength indicator (RSSI) contains high errors, new measurement system using accelerometers and correction method are suggested in this study. Field test is performed to validate the developed system. The error for moving laborer was 0.4 m and for non-moving laborers was 0.2 m. Thus, it is found that the new RTL system can be used to monitor the location of laborers in the underground construction space.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.465-468
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• 2007

An intelligent home network system using low-power and low-cost sensor nodes was designed and implemented. In Intelligent Home Network System, active home appliances control is composed of RSSI (Received Signal Strength Indicator) based user indoor location tracking, dynamic multi-hop routing, and learning integration remote-control. Through the remote-control learning, home appliances can be controlled in wireless network environment. User location information for intelligent service is calculated using RSSI based Triangle measurement method, and then the received location information is passed to Smoothing Algorithm to reduce error rate. In order to service Intelligent Home Network, moreover, the sensor node is designed to be held by user. The gathered user data is transmitted through dynamic multi-hop routing to server, and real-time user location & environment information are displayed on monitoring program.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.106-121
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• 2008

In this paper, we proposed and designed the protocol for energy efficiency and the center of data aiming at the design of a Multi Location Awareness System that recognizes a shadow site in parking and tunnel, which stands on the basis of CSS(Chirp Spread Spectrum) method using ISM Band of IEEE 802.15.4a that aware close location with wireless RF only. As a result of the protocol measurement, it displays the observation errors of less than 15cm, the data error rate of less than 5%, and can implement the Multi Location Awareness System with maximum length of life for 13.5 days using battery of 3V(1500 mAh).

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.369-379
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• 2022

In weighted k-nearest neighbor (WkNN)-based Fingerprinting positioning step, a process of comparing the requested positioning signal with signal information for each reference point stored in the fingerprint DB is performed. At this time, the higher the number of matched base station identifiers, the higher the possibility that the terminal exists in the corresponding location, and in fact, an additional weight is added to the location in proportion to the number of matching base stations. On the other hand, if the matching number of base stations is small, the selected candidate reference point has high dependence on the similarity value of the signal. But one problem arises here. The positioning signal can be compared with the repeater signal in the signal information stored on the DB, and the corresponding reference point can be selected as a candidate location. The selected reference point is likely to be an outlier, and if a certain weight is applied to the corresponding location, the error of the estimated location information increases. In order to solve this problem, this paper proposes a WkNN technique including an outlier removal function. To this end, it is first determined whether the repeater signal is included in the DB information of the matched base station. If the reference point for the repeater signal is selected as the candidate position, the reference position corresponding to the outlier is removed based on the clustering technique. The performance of the proposed technique is verified through data acquired in Seocho 1 and 2 dongs in Seoul.

• Journal of Animal Environmental Science
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• v.17 no.2
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• pp.93-100
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• 2011

This study was conducted to verify the applicability of robot milking system through acquisition and analysis of model teat's position information using scanning range finder (SRF). Model teats, same size and shape as real teats, were designed to analyze the properties according to the material, distance error and angle error of the sensor. In addition, 2-dimensional distance information of each teats was obtained at same time with 4 teat models and the result were as follows. 1. In the case of the fingers on the experiment for selection of materials for teat model, the distance error was from 4.3 mm to 1.3 mm, average was 2.8 mm as a minimum record. In the case of rubber material, average distance error was 4.3 mm. So, this material was considered to be a most suitable model. 2. The distance error was maximum at 100 mm distance. The more distance increased, the less error increased up to 300 mm. Then the error increased after 300 mm and decreased again. 3. The maximum angle error of 10.1 mm was measured at $170^{\circ}$, in case of $70^{\circ}$ the error was 0.2 mm as a minimum value. There was no specific tendency to error of angle. 4. In the 2-dimensional location error for 4 teat models, distance error was 3.8 mm as minimum and 7.2 mm as maximum. The angle error was $1.2^{\circ}$ as maximum. All of errors were included within the accuracy of sensor, the robot milking system was considered to be applicable to measure the distance of teats due to the measuring velocity of SRF and the hole size of teat-cup.