• Bulletin of the Korean Chemical Society
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• v.34 no.7
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• pp.2143-2147
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• 2013

Matrix assisted laser desorption/ionization (MALDI) mass spectrometry (MS) is a very effective method for lipid mass fingerprinting. However, MALDI MS suffered from spectral complexities, differential ionization efficiencies, and poor reproducibility when analyzing complex lipid mixtures without prior separation steps. Here, we aimed to find optimal MALDI sample preparation methods which enable selective or class-wide mass fingerprinting of two totally different lipid classes. In order to achieve this, various matrices with additives were tested against the mixture of phosphatidylcholine (PC) and cerebrosides (Cers) which are abundant in animal brain tissues and also of great interests in disease biology. Our results showed that, from complex lipid mixtures, 2,4,6-trihydroxyacetophenone (THAP) with $NaNO_3$ was a useful MALDI matrix for the class-wide fingerprinting of PC and Cers. In contrast, THAP efficiently generated PC-focused profiles and graphene oxide (GO) with $NaNO_3$ provided Cer-only profiles with reduced spectral complexity.

• ETRI Journal
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• v.28 no.4
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• pp.509-512
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• 2006

In a real environment, sound recordings are commonly distorted by channel and background noise, and the performance of audio identification is mainly degraded by them. Recently, Philips introduced a robust and efficient audio fingerprinting scheme applying a differential (high-pass filtering) to the frequency-time sequence of the perceptual filter-bank energies. In practice, however, the robustness of the audio fingerprinting scheme is still important in a real environment. In this letter, we introduce alternatives to the frequency-temporal filtering combination for an extension method of Philips' audio fingerprinting scheme to achieve robustness to channel and background noise under the conditions of a real situation. Our experimental results show that the proposed filtering combination improves noise robustness in audio identification.

• 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.

• The Journal of Society for e-Business Studies
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• v.16 no.3
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• pp.159-168
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• 2011

To identify fraud clicks in the Internet advertisement, existing studies have considered keyword, visit time, and client IP as an independent variable for the standard. These methods have limitations in identifying the fraud clicks that utilize automation tools, for they are methods based on client IP and human activities on the Internet. This paper proposes that fingerprinting values of the variable combination should be used to identify fraud clicks. The proposed model is composed of 3 stages and the fingerprinting values are compared with the other input data at each stage; IP fingerprinting in the first stage, IP and session data fingerprinting in the second stage, and session data and keyword fingerprinting in the third stage. We showed that the proposed model of the fraud click identification is more correct than existing methods through experiments according to the proposed scheme.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.353-359
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• 2004

The illegal copying and redistribution of digitally-stored information is a crucial problem to distributors who electronically sell digital data. Fingerprinting scheme is a techniques which supports copyright protection to track redistributors of electronic information using cryptographic techniques. Anonymous fingerprinting schemes, differ from symmetric fingerprinting, prevent the merchant from framing a buyer by making the fingerprinted version known to the buyer only. And the scheme, differ from asymmetric fingerprinting, allows the buyer to purchase goods without revealing her identity to the merchant. In this paper, a new anonymous fingerprinting scheme based on secret sharing is introduced. The merchant finds a sold version that has been distributed, and then he is able to retrieve a buyer's identity and take her to court. And Schnorr's digital signature prevents the buyer from denying the fact he redistributed. The buyer's anonymity relies on the security of discrete logarithm and secure two-party computations.

• Journal of Korea Multimedia Society
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• v.7 no.9
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• pp.1263-1272
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• 2004

In this paper, we present a novel video fingerprinting implementation method to identify the source of illegal copies. The video fingerprinting is achieved by the insertion of uniform distributed random number is made by seller and buyer's identification key-in the video wavelet coefficients by their temporal wavelet transform. The proposed fingerprinting is able to detect unique fingerprint of video contents even if they have been distorted by collusion attacks and MPEG2 compression. Especially, we use characteristics of the temporal wavelet transform to assign user's embedding area. Experimental results show the traceability of unauthorized distribution of video contents and its robustness to various collusion attacks and MPEG2 compression.

• Journal of Microbiology
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• v.38 no.1
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• pp.8-10
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• 2000

In order to rapidly identify and differentiate Salmonella typhimurium from the intestinal gram-negative bacteria, randomly amplified polymorphic DNA (RAPD) fingerprinting of Salmonella typhimurium was carried out using random primers designated OPA-13 (5'-CAGCACCCAC-3'), OPB-10 (5'-CGTCTGGGAC-3'), OPB-18 (5'-CCACAGCAGT-3'), and OPJ-10 (5'-AAGCCCGAGG-3'), and its patterns compared with 6 representive intestinal, gram-negative bacterial strains, Vibrio parahaemolyticus, V. vulnificus, Enterobacter cloacae, Escherichia coli O157:H7, Pseudomonas aeruginosa, and Proteus sp., which are often found in foods. S. typhimurium had unique and distinct fingerprinting patterns. RAPD fingerprinting is thus concluded to be a rapid and sensitive method for the identification of S. typhimurium compared to conventional culturing procedures or immunoassays.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.390-395
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• 2009

The robustness of audio fingerprinting system in a noisy environment is a principal challenge in the area of content-based audio retrieval. The selected feature for the audio fingerprints must be robust in a noisy environment and the computational complexity of the searching algorithm must be low enough to be executed in real-time. The audio fingerprint proposed by Philips uses expanded hash table lookup to compensate errors introduced by noise. The expanded hash table lookup increases the searching complexity by a factor of 33 times the degree of expansion defined by the hamming distance. We propose a new method to improve noise robustness of audio fingerprinting in noise environment using predominant pitch which reduces the bit error of created hash values. The sub-fingerprint of our approach method is computed in each time frames of audio. The time frame is transformed into the frequency domain using FFT. The obtained audio spectrum is divided into 33 critical bands. Finally, the 32-bit hash value is computed by difference of each bands of energy. And only store bits near predominant pitch. Predominant pitches are extracted in each time frames of audio. The extraction process consists of harmonic enhancement, harmonic summation and selecting a band among critical bands.

• Journal of information and communication convergence engineering
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• v.14 no.4
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• pp.207-214
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• 2016

In this paper, we propose a radial reference map-based location fingerprinting technique with constant spacing from an access point (AP) to all reference points by considering the minimum dynamic range of the received signal strength indicator (RSSI) obtained through an experiment conducted in an indoor environment. Because the minimum dynamic range, 12 dBm, of the RSSI appeared every 20 cm during the training stage, a cell spacing of 80 cm was applied. Furthermore, by considering the minimum dynamic range of an RSSI in the location estimation stage, when an RSSI exceeding the cumulative average by ${\pm}6dBm$ was received, a previously estimated location was provided. We also compared the location estimation accuracy of the proposed method with that of a conventional fingerprinting technique that uses a grid reference map, and found that the average location estimation accuracy of the conventional method was 21.8%, whereas that of the proposed technique was 90.9%.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.375-382
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• 2009

This paper proposes a new audio fingerprinting method based on compressed-domain features. By basing on the compressed domain, the computational efficiency of the proposed method can be greatly enhanced. Especially we deal with MDCT domain, which is widely employed in audio compression, and extract three kinds of subband features; energy, centroid, and flatness. By taking signs after differentially filtering each feature, binary audio fingerprints are obtained. The identification performance of the three kinds of fingerprints are experimentally compared. Among the considered compressed-domain subband features, the subband energy showed the best performance for fingerprinting.