• The Journal of the Acoustical Society of Korea
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• v.31 no.4
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• pp.260-265
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• 2012

A robust audio fingerprinting method is presented based on segmentation boundaries. In order to obtain robustness against linear speed changes, fingerprint extraction and matching are synchronized with the segmentation boundaries. Experimental results show that the proposed method is also robust against other common audio processing steps including low bit-rate compression, equalization, and time-scale modification.

• ETRI Journal
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• v.36 no.6
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• pp.999-1007
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• 2014

The robustness of an audio fingerprinting system in an actual noisy environment is a major challenge for audio-based content identification. This paper proposes a high-performance audio fingerprint extraction method for use in portable consumer devices. In the proposed method, a salient audio peak-pair fingerprint, based on a modulated complex lapped transform, improves the accuracy of the audio fingerprinting system in actual noisy environments with low computational complexity. Experimental results confirm that the proposed method is quite robust in different noise conditions and achieves promising preliminary accuracy results.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.373-378
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• 2016

Recently, IPS(Indoor Positioning System) Technology has been progressing study and research, It has been studied in the fingerprinting and trilateration continuously. however because Fingerprinting and Trilateration Technology use AP(Access Point) for Positioning Calculation, Fingerprinting and Trilateration are not never had a credit positioning accuracy by using unstable RSSI in large scale. in this paper, to improve the problem about precise positioning in wide area, we introduced a concept of Sector including Cell. Sectors are not involved in each other and only fingerprinting calculation is proceed in a sector. we suggest this fingerprinting system considering efficiency and accuracy and compared to conventional fingerprinting, we demonstrated our system efficiency by mathematical techniques.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.1-9
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• 2006

For the indoor positioning, wireless fingerprinting is most favorable because fingerprinting is most accurate among the techniques for wireless network based indoor positioning which does not require any special equipments dedicated for positioning. The deployment of a fingerprinting method consists of off-line phase and on-line phase. Off-line phase is not a time critical procedure, but on-line phase is indeed a time-critical procedure. If it is too slow then the user's location can be changed while it is calculating and the positioning method would never be accurate. Even so there is no research of improving efficiency of on-line phase of wireless fingerprinting. This paper proposes a decision-tree method for wireless fingerprinting and performs comparative analysis of the fingerprinting techniques including K-NN, Bayesian and our decision-tree.

• Journal of Information Technology Applications and Management
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• v.15 no.2
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• pp.51-65
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• 2008

The purpose of this paper is introducing WiFi based EKF(Extended Kalman Filter) method for indoor positioning. The advantages of our EKF method include: 1) Any special equipment dedicated for positioning is not required. 2) implementation of EKF does not require off-line phase of fingerprinting methods. 3) The EKF effectively minimizes squared deviation of the trilateration method. In order to experimentally prove the advantages of our method, we implemented indoor positioning systems making use of the K-NN(K Nearest Neighbors), Bayesian, decision tree, trilateration, and our EKF methods. Our experimental results show that the average-errors of K-NN, Bayesian and decision tree methods are all close to 2.4 meters whereas the average errors of trilateration and EKF are 4.07 meters and 3.528 meters, respectively. That is, the accuracy of our EKF is a bit inferior to those of fingerprinting methods. Even so, our EKF is accurate enough to be used for practical indoor LBS systems. Moreover, our EKF is easier to implement than fingerprinting methods because it does not require off-line phase.

• 한국해양학회지
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• v.21 no.2
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• pp.118-123
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• 1986

A gas chromatographic oil fingerprinting method is a technique used for comparative source identification of spilled oil. The hydrocarbon and sulfur compound analysis by gas chromatography are generally used for analyzing oils. However, due to the complexity of oils, another technique is also needed for comparative identification. In this study, polycyclic aromatic hydrocarbons contained in crude oil and heavy fuel oil are analyzed by gas chromatography. They are relatively unaffected by weathering condition because they are stable. The oil fingerprinting of polycyclic aromatic hydrocarbons by GC seems to be a reliable technique for analyzing oils in identification of sources and kinds of oils.

• Genomics & Informatics
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• v.4 no.2
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• pp.87-93
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• 2006

With the rapid development of MS technologiesy, the demands for a more sophisticated MS interpretation algorithm haves grown as well. We have developed a new protein fingerprinting method using a binomial distribution, (fBIND). With the fBIND, we improved the performance accuracy of protein fingerprinting up to the maximum 49% (more than MOWSE) and 2% than(at a previous binomial distribution approach studied by of Wool et al.) as compared to the established algorithms. Moreover, we also suggest a the statistical approach to define the significance of transcription factors and motifs in the identified proteins based on the Gene Ontology (GO). Abbreviations: fBIND, fingerprinting using binomial distribution; GO, Gene Ontology; MS, Mass Spectrometry; PMF, peptide mass fingerprinting; nr, nonredundant; SGD, Saccharomyces Genome Database

• The Journal of the Acoustical Society of Korea
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• v.34 no.2
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• pp.157-162
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• 2015

In this paper, we propose an audio fingerprinting using robust hash based on the MCLT (Modulated Complex Lapped Transform) peak-pair. In existing methods, the robust audio fingerprinting is not generated if various distortions occurred; time-scaling, pith-shifting and equalization. To solve this problem, we used the spectrum of the MCLT, an adaptive thresholding method for detection of prominent peaks and the novel hash function in the audio fingerprinting. Experimental results show that the proposed method is highly robust in various distorted environments and achieves better identification rates compared to other methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.64-73
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• 2012

In this paper, we propose a method to search for identical videos. The proposed method is spatio-temporal group feature fingerprinting. Frame of video is extracted from fixed rate method and is partitioned into vertical group and horizontal group. Descriptor is made of each group feature that is extracted from binary fingerprinting. Next, use descriptor of original video to build a two type of fingerprinting database and matching with query video. To efficient and effective video copy detection, method have high robustness, independence, matching speed. In proposed method, group feature have high robustness and independence in variable modification of video. Building a original fingerprinting database is able to fast matching with query video. The proposed method shows performance improvement in variable modifications in comparison to the existing methods. Especially, very singular performance in speed improvement is great advantage of this paper.

• Journal of Digital Contents Society
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• v.15 no.1
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• pp.129-136
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• 2014

Wi-Fi fingerprinting system is a very popular positioning method used in indoor spaces. The system depends on Wi-Fi Received Signal Strength (RSS) from Access Points (APs). However, the Wi-Fi RSS is changeable by multipath fading effect and interference due to walls, obstacles and people. Therefore, the Wi-Fi fingerprinting system produces low position accuracy. Also, Wi-Fi signals pass through walls. For this reason, the existing system cannot distinguish users' floor. To solve these problems, this paper proposes a LED fingerprinting system for accurate indoor positioning. The proposed system uses a received optical power from LEDs and LED-Identification (LED-ID) instead of the Wi-Fi RSS. In training phase, we record LED fingerprints in database at each place. In serving phase, we adopt a K-Nearest Neighbor (K-NN) algorithm for comparing existing data and new received data of users. We show that our technique performs in terms of CDF by computer simulation results. From simulation results, the proposed system shows that a positioning accuracy is improved by 8.6 % on average.