• 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.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.576-578
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• 2006

The wide use of digital media during the past few years, has led to an increase of digital piracy and tampering. To deal with these problems, the concept of digital fingerprinting has been introduced. Digital fingerprinting is an effective method to identify users who might try to redistribute multimedia content. In this paper, we propose new digital image fingerprinting techniques using watermark shifting scheme and concept of domain.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.1-9
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• 2012

The popularity of digital music and smart phones led to develope noise-robust real-time audio fingerprinting system in various ways. In particular, The Multiple Hashing(MLH) of fingerprint algorithms is robust to noise and has an elaborate structure. In this paper, we propose a filter engine based on MLH to achieve better performance. In this approach, we compose a energy-intensive filter to improve the accuracy of Q/R from music database and a statistic filter to remove continuity and redundancy. The energy-intensive filter uses the Discrite Cosine Transform(DCT)'s feature gathering energy to low-order bits and the statistic filters use the correlation between searched fingerprint's information. Experimental results show that the superiority of proposed algorithm consists of the energy and statistical filtering in noise environment. It is found that the proposed filter engine achieves more robust to noise than Philips Robust Hash(PRH), and a more compact way than MLH.

• Genomics & Informatics
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• v.11 no.3
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• pp.102-113
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• 2013

Metagenomics has become one of the indispensable tools in microbial ecology for the last few decades, and a new revolution in metagenomic studies is now about to begin, with the help of recent advances of sequencing techniques. The massive data production and substantial cost reduction in next-generation sequencing have led to the rapid growth of metagenomic research both quantitatively and qualitatively. It is evident that metagenomics will be a standard tool for studying the diversity and function of microbes in the near future, as fingerprinting methods did previously. As the speed of data accumulation is accelerating, bioinformatic tools and associated databases for handling those datasets have become more urgent and necessary. To facilitate the bioinformatics analysis of metagenomic data, we review some recent tools and databases that are used widely in this field and give insights into the current challenges and future of metagenomics from a bioinformatics perspective.

• Journal of Microbiology and Biotechnology
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• v.22 no.6
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• pp.780-787
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• 2012

The maize pathogen Gibberella moniliformis produces fumonisins, a group of mycotoxins associated with several disorders in animals and humans, including cancer. The current focus of our research is to understand the regulatory mechanisms involved in fumonisin biosynthesis. In this study, we employed a proteomics approach to identify novel genes involved in the fumonisin biosynthesis under nitrogen stress. The combination of genome sequence, mutant strains, EST database, microarrays, and proteomics offers an opportunity to advance our understanding of this process. We investigated the response of the G. moniliformis proteome in limited nitrogen (N0, fumonisin-inducing) and excess nitrogen (N+, fumonisin-repressing) conditions by one- and two-dimensional electrophoresis. We selected 11 differentially expressed proteins, six from limited nitrogen conditions and five from excess nitrogen conditions, and determined the sequences by peptide mass fingerprinting and MS/MS spectrophotometry. Subsequently, we identified the EST sequences corresponding to the proteins and studied their expression profiles in different culture conditions. Through the comparative analysis of gene and protein expression data, we identified three candidate genes for functional analysis and our results provided valuable clues regarding the regulatory mechanisms of fumonisin biosynthesis.

• Korean Journal of Veterinary Research
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• v.44 no.1
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• pp.57-64
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• 2004

The common pathogen Salmonella enteirtidis (S. enteritidis) is the major cause of foodborne disease. Protein identification by peptide mass fingerprinting using the matrix-assisted laser desorption ionization time of fight (MALDI-TOF) mass spectrometry (MS) can analysis unambiguously identity the spots from 2-dimensional electrophoresis (2-DE) gel. In this report, we examined protein components from patterns of S. enteritidis proteins. In addition, antigens that are recognized by sera can be identified by immunoblotting. This study that 2-DE analysis of S. enteritidis yields useful information concerning S. enteritidis proteome, the results that have been obtained led to a more detailed understanding of Salmonella pathology and open further interesting fields for future work.