• Biomedical Science Letters
• /
• v.8 no.1
• /
• pp.39-46
• /
• 2002

Amplified fragment length polymorphism (AFLP) is a recently developed PCR-based high resolution fingerprinting method that is able to generate complex banding patterns which can be used to delineate intraspecific genetic relationships among bacteria. In this study, we have modified and evaluated a PCR-based technique, amplified fragment length polymorphism (AFLP) analysis, for use in fingerprinting strains of Staphylococcus aureus. Single-enzyme amplified fragment length polymorphism (SE-AFLP) analysis was used to perform strain identification of Staphylococus aureus. By careful selection of AFLP primers, it was possible to obtain reproducible and sensitive identification to strain level. AFLP fingerprinting of 5 reference strains of Staphylococcus aureus and 65 strains of Staphylococcus aureus that were isolated from food sources of different area and diverse genomic types of Staphylococcus aureus were recognized. As a result of this study, we found that the AFLP patterns of Staphylococcus aureus isolated from Seoul, Taejeon and Gwang-Ju indicated the close relation with genetic similarity. The main purpose of this study was to find an alternative and reliable fingerprinting method to study the overall genetic diversity, using Staphylococcus aureus species as an example, and observed if the method can be successfully applied to all staphylococcal species.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.05a
• /
• pp.861-863
• /
• 2014

Fingerprinting technique exists at the position assumption system for the service of indoor location-based. However, there is a problem it takes a long time to build fingerprinting map. We need to verify that received signal of WAP(wireless access point) is similar at all times in a similar space in order to solve these problems. This paper proposes a plan that is able to build fingerprinting map by using the received signal data of WAP. To do this, change the positon of WAP in the same space, It is confirmed the process of change of the RSSI corresponding to the distance. We also confirmed that the RSSI collected from elsewhere in the space a similar change in the same manner.

• The Journal of Korean Institute of Information Technology
• /
• v.17 no.2
• /
• pp.71-77
• /
• 2019

With 5G standards proceeding in earnest and increasing demand for services of indoor localization, research on indoor location recognition is being studied in various industrial fields, and research based on fingerprint recognition technology using Wireless Local Area Network (WLAN) is representative. In this paper, we propose an indoor positioning system based on fingerprinting technique that uses Cloud Radio Access Network (C-RAN) architecture and Channel State Information (CSI). In order to improve the performance in indoor positioning, we combined existing fingerprinting method and K nearest neighbor (KNN) technology which is one of the machine running technique. The performance improvements of the proposed indoor positioning system was verified by comparative experiments with the existing localization technique in a indoor localizztion testbed.

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

• Journal of Positioning, Navigation, and Timing
• /
• v.12 no.3
• /
• pp.271-280
• /
• 2023

Pedestrian Dead Reckoning (PDR) methods using initial sensors are being studied to provide the location information of smart device users in indoor environments where satellite signals are not available. PDR can continuously estimate the location of a pedestrian regardless of the walking environment, but has the disadvantage of accumulating errors over time. Unlike this, WiFi signal-based wireless positioning technology does not accumulate errors over time, but can provide positioning information only where infrastructure is installed. It also shows different positioning performance depending on the environment. In this paper, an integrated positioning technology integrating two positioning techniques with different error characteristics is proposed. A technique for correcting the error of PDR was designed by using the location information obtained through WiFi Measurement-based fingerprinting as the measurement of Extended Kalman Filte (EKF). Here, a technique is used to variably calculate the error covariance of the filter measurements using the WiFi Fingerprinting DB and apply it to the filter. The performance of the proposed positioning technology is verified through an experiment. The error characteristics of the PDR and WiFi Fingerprinting techniques are analyzed through the experimental results. In addition, it is confirmed that the PDR error is effectively compensated by adaptively utilizing the WiFi signal to the environment through the EKF to which the adaptive error covariance proposed in this paper is applied.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.7
• /
• pp.81-88
• /
• 2009

Fingerprinting scheme is a technique which supports the copyright protection to track redistributors of digital content using cryptographic techniques. These schemes enable the original merchant to identify the original buyer of the digital data by embedding fingerprints into digital contents. Asymmetric property of fingerprinting schemes is important to keep the buyer's privacy. In this paper, we propose a symmetric encryption based fingerprinting protocol without trusted third party. Our scheme enables the reduction of computational costs for the encryption using symmetric key encryption scheme. Since a trusted third party doesn't take part in making the fingerprint of each buyer, the protocol doesn't need to control the trusted third party and it is more secure against collusion attack.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.6
• /
• pp.146-153
• /
• 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 Society on Water Environment
• /
• v.24 no.2
• /
• pp.195-200
• /
• 2008

To analyze the riverine microbial community structure, genetic fingerprints and ecological indexes such as species abundances, diversity, evenness, dominance of targeted rivers in Gyeonggi Province were acquired and evaluated using terminal restriction fragment length polymorphism (T-RFLP) technique. Genetic fingerprinting technique such as T-RFLP, which is able to show the microbial community clearly unlike traditional culture-dependent techniques, was thought to be useful to analyse the riverine microbial ecosystem under various factors. Riverine ecosystem evaluation using visible organisms would give biased results with time, targeted organism and researcher. But, T-RFLP, which can exclude the subjected biases such as culture condition and identification, would be an option to understand natural ecosystem by including the microorganisms that defy culture but perform important functions.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.5
• /
• pp.1881-1903
• /
• 2015

With the fast-developing of mobile terminals, positioning techniques based on fingerprinting method draws attention from many researchers even world famous companies. To conquer some shortcomings of the existing fingerprinting systems and further improve its performance, we propose a radio map building and updating technique, which is able to customize the spatial and temporal dependency of radio maps. The method includes indoor propagation and penetration modeling and the analysis of human traffic. Based on the combination of Ray-Tracing Algorithm, Finite-Different Time-Domain and Rough Set Theory, the approach of indoor propagation modeling accurately represents the spatial dependency of the radio map. In terms of temporal dependency, we specifically study the factor of moving people in the interest area. With measurement and statistics, the factor of human traffic is introduced as the temporal updating component. We improve our existing indoor positioning system with the proposed building and updating method, and compare the localization accuracy. The results show that the enhanced system can conquer the influence caused by moving people, and maintain the confidence probability stable during week, which enhance the actual availability and robustness of fingerprinting-based indoor positioning system.