• 한국ITS학회:학술대회논문집
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• 2008.11a
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• pp.158-160
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• 2008

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.280-286
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• 2022

In order to efficiently collect data, it is essential to locate the facilities and analyze the movement data. The current technology for location collection can collect data using a GPS sensor, but GPS has a strong straightness and low diffraction and reflectance, making it difficult for indoor positioning. In the case of indoor positioning, the location is determined by using wireless network technologies such as Wifi, but there is a problem with low accuracy as the error range reaches 20 to 30 m. In this paper, using BLE 4.2 built in Raspberry Pi, we implement Bluetooth Smart Ready. In detail, a beacon was produced for Advertise, and an experiment was conducted to support the serial port for data transmission/reception. In addition, advertise mode and connection mode were implemented at the same time, and a 3-count gradual algorithm and a quadrangular positioning algorithm were implemented for Bluetooth RSSI error correction. As a result of the experiment, the average error was improved compared to the first correction, and the error rate was also improved compared to before the correction, confirming that the error rate for position measurement was significantly improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.737-740
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• 2009

In this paper, in order to improve the location estimation error existing in RTLS(Real Time Location Service) system for the mobility individual, we proposed a method of speed-adaptive location estimation that the transmitting signaling period is adaptively changed according to the changing speed of a mobility individual for each location interval. To get the more accurate location estimation values, we analyzed both the location values measured by Hybrid(TDOA and RSSI) method by using AeroScout TM RTLS system and the estimated value obtained from the theoretical calculation by using the Least Squares Method. Finally, we compared the analyzed values with a real location of mobility individual. From the experimental results based on our proposed method, it can be seen that the location estimation error for the real location of a mobility individual can be improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2243-2250
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• 2014

In wireless sensor networks(WSNs), geographical routing algorithms can enhance the network capacity. However, in real WSNs, it is difficult for each node to know its physical location accurately. Especially, indoor environments contain various obstacles such as concrete wall, furniture which cause non-line-of-sight(NLOS) conditions. To solve the problem, we propose location error compensation algorithm by using two difference topology constructions. First topology is based on mobile node's location which is obtained from anchor nodes. Second topology is based on mutual distance from neighbor nodes. The proposed algorithm efficiently detects and corrects the location errors and significantly enhances the network performance of geographic routing in the presence of location errors.

• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1767-1774
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• 2016

In this paper, we propose the adaptation filtering for correcting the movement path of the recognized object by the depth information. When we recognize the object by the depth information, the path error should be occurred because of the noises in the depth information. The path error is corrected by appling the lowpass filtering, but the lowpass filtering is not efficient when the changes of the object's movement are rapid. In this paper, we apply the adaptation filtering that it gives weights adaptively as the difference between the predicted location and the measured location. To apply the adaptation filtering, we can see that the proposed method can correct accurately the path error of the radical change from simulation results.

• Proceedings of the IEEK Conference
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• 2000.11b
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• pp.281-284
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• 2000

This paper describes design of a (32, 28) Reed Solomon decoder for optical compact disk with double error detecting and correcting capability. A variety of error correction codes(ECCs) have been used in magnetic recordings, and optical recordings. Among the various types of ECCs, Reed Solomon(RS) codes has emerged as one the most important ones. The most complex circuit in the RS decoder is the part for finding the error location numbers by solving error location polynomial, and the circuit has great influence on overall decoder complexity. We use RAM based architecture with Euclid's algorithm, Chien search algorithm and Forney algorithm. We have developed VHDL model and peformed logic synthesis using the SYNOPSYS CAD tool. The total umber of gate is about 11,000 gates.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.629-638
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• 2005

We derive the approximate maximum likelihood estimators of the scale parameter and location parameter of the extreme value distribution based on multiply Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1926-1933
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• 2013

Many localization algorithms have been proposed for Wireless Sensor Networks (WSNs). The IEEE 802.15.4a-based location-aware-system can provide precise ranging distance between two mobile nodes. The mobile nodes can obtain their exact locations by using accurate ranging distances. However, the indoor environments contain various obstacles which cause non-line-of-sight (NLOS) conditions. In NLOS condition, the IEEE 802.15.4a-based location-aware system has a large scale location error. To solve the problem, we propose location error compensation in indoor environment by using MST-based topology control. Experimental and simulation results show that the proposed algorithm improves location accuracy in NLOS conditions.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.4
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• pp.1-7
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• 2012

This paper proposes a new indoor location recognition system using a ZigBee network and a global positioning system(GPS). The proposed location recognition system applies GPS values that are mainly used for outdoor location recognition, to indoor location recognition; hence the techniques conventionally separated for the indoor and outdoor location recognition are integrated into one location recognition technique. The proposed system recognizes a location using the distance between nodes. Although the distance between nodes can be calculated by measuring the strength of the received ZigBee signals, generally the measured distance is not accurate and has high error rates since the strength of the ZigBee signals is different depending on the distance. In order to reduce the error rate, we have subdivided the output power of the received ZigBee signals into five levels. When a moving node generates a signal, each fixed node transmits the received signal strength and its own GPS information to other nodes, so the moving node can find its own accurate location in terms of the received signals.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.99-105
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• 2011

Location-Based Service(LBS) is a service that provides a variety of convenience in life using location information that can be obtained by mobile communication network or satellite signal. In order to provide LBS precisely and efficiently, we have to need technologies such as location determination technology, platform technology and server technology first. In this study, we studied on how we can reduce the error on location determination of objects such people and things. Fingerprint location determination method was applied to this study because it can be used at current wireless communication infrastructure and less influenced by a variety of noisy environment than other location determination methods. We used the time of arrival(ToA) method in fingerprint location determination method. In order to confirm the performance of suggested method, we developed location determination test program with LAbVIEW 2010 and performed the test. According to indoor test results, the suggested method reduced the distance error by 24%, 34% and 19% respectively at indoor environment compared with deterministic kWNN and Rice Gaussian fingerprint methods.