• Title/Summary/Keyword: fingerprinting method

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Investigating chemical features of Panax notoginseng based on integrating HPLC fingerprinting and determination of multiconstituents by single reference standard

  • Yang, Zhenzhong;Zhu, Jieqiang;Zhang, Han;Fan, Xiaohui
    • Journal of Ginseng Research
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    • v.42 no.3
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    • pp.334-342
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    • 2018
  • Background: Panax notoginseng is a highly valued medicine and functional food, whose quality is considered to be influenced by the size, botanical parts, and growth environments. Methods: In this study, a HPLC method integrating fingerprinting and determination of multiconstituents by single reference standard was established and adopted to investigate the chemical profiles and active constituent contents of 215 notoginseng samples with different sizes, from different botanical parts and geographical regions. Results: Chemical differences among main root, branch root, and rotten root were not distinct, while rhizome and fibrous root could be discriminated from other parts. The notoginseng samples from Wenshan Autonomous Prefecture and cities nearby were similar, whereas samples from cities far away were not. The contents of major active constituents in main root did not correlate with the market price. Conclusion: This study provided comprehensive chemical evidence for the rational usage of different parts, sizes, and growth regions of notoginseng in practice.

Development of Indoor Lighting Control System based on Fingerprinting (Fingerprinting 기반의 실내조명 제어 시스템 개발)

  • Cho, Kyoung-woo;Han, Byung-hun;Oh, Chang-heon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.661-663
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    • 2014
  • Lighting that installed in large buildings detects a movement of passer using human-detecting sensor or occupancy sensor. It can turn on lighting automatically using sensor when there is any movement and turn off when there is no movement to reduce unnecessary power consumption. However, there is a problem of malfunction due to improper location of the sensor. Also the case of passage, even after passing through the passage, lighting is turned on for a long time. It does not reduce the power consumption efficiently. In this paper, we propose a method to control lighting by estimating the position of the passer. According to the result simulated in one passage, it is confirmed that the time of turning on the lighting is reduced about 7 minute compared to existing methods.

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Classification of Service Types using Website Fingerprinting in Anonymous Encrypted Communication Networks (익명 암호통신 네트워크에서의 웹사이트 핑거프린팅을 활용한 서비스 유형 분류)

  • Koo, Dongyoung
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.4
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    • pp.127-132
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    • 2022
  • An anonymous encrypted communication networks that make it difficult to identify the trace of a user's access by passing through several virtual computers and/or networks, such as Tor, provides user and data privacy in the process of Internet communications. However, when it comes to abuse for inappropriate purposes, such as sharing of illegal contents, arms trade, etc. through such anonymous encrypted communication networks, it is difficult to detect and take appropriate countermeasures. In this paper, by extending the website fingerprinting technique that can identify access to a specific site even in anonymous encrypted communication, a method for specifying and classifying service types of websites for not only well-known sites but also unknown sites is proposed. This approach can be used to identify hidden sites that can be used for malicious purposes.

Indoor Path Recognition Based on Wi-Fi Fingerprints

  • Donggyu Lee;Jaehyun Yoo
    • Journal of Positioning, Navigation, and Timing
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    • v.12 no.2
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    • pp.91-100
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    • 2023
  • The existing indoor localization method using Wi-Fi fingerprinting has a high collection cost and relatively low accuracy, thus requiring integrated correction of convergence with other technologies. This paper proposes a new method that significantly reduces collection costs compared to existing methods using Wi-Fi fingerprinting. Furthermore, it does not require labeling of data at collection and can estimate pedestrian travel paths even in large indoor spaces. The proposed pedestrian movement path estimation process is as follows. Data collection is accomplished by setting up a feature area near an indoor space intersection, moving through the set feature areas, and then collecting data without labels. The collected data are processed using Kernel Linear Discriminant Analysis (KLDA) and the valley point of the Euclidean distance value between two data is obtained within the feature space of the data. We build learning data by labeling data corresponding to valley points and some nearby data by feature area numbers, and labeling data between valley points and other valley points as path data between each corresponding feature area. Finally, for testing, data are collected randomly through indoor space, KLDA is applied as previous data to build test data, the K-Nearest Neighbor (K-NN) algorithm is applied, and the path of movement of test data is estimated by applying a correction algorithm to estimate only routes that can be reached from the most recently estimated location. The estimation results verified the accuracy by comparing the true paths in indoor space with those estimated by the proposed method and achieved approximately 90.8% and 81.4% accuracy in two experimental spaces, respectively.

A Moving Path Control of an Automatic Guided Vehicle Using Relative Distance Fingerprinting (상대거리 지문 정보를 이용한 무인이송차량의 주행 경로 제어)

  • Hong, Youn Sik;Kim, Da Jung;Hong, Sang Hyun
    • KIPS Transactions on Computer and Communication Systems
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    • v.2 no.10
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    • pp.427-436
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    • 2013
  • In this paper, a method of moving path control of an automatic guided vehicle in an indoor environment through recognition of marker images using vision sensors is presented. The existing AGV moving control system using infrared-ray sensors and landmarks have faced at two critical problems. Since there are many windows in a crematorium, they are going to let in too much sunlight in the main hall which is the moving area of AGVs. Sunlight affects the correct recognition of landmarks due to refraction and/or reflection of sunlight. The second one is that a crematorium has a narrow indoor environment compared to typical industrial fields. Particularly when an AVG changes its direction to enter the designated furnace the information provided by guided sensors cannot be utilized to estimate its location because the rotating space is too narrow to get them. To resolve the occurrences of such circumstances that cannot access sensing data in a WSN environment, a relative distance from marker to an AGV will be used as fingerprinting used for location estimation. Compared to the existing fingerprinting method which uses RSS, our proposed method may result in a higher reliable estimation of location. Our experimental results show that the proposed method proves the correctness and applicability. In addition, our proposed approach will be applied to the AGV system in the crematorium so that it can transport a dead body safely from the loading place to its rightful destination.

FFT Based Information Concealing Method for Video Copyright Protection (동영상 저작권보호를 위한 FFT 기반 정보 은닉 기법)

  • Choi, Il-Mok;Hwang, Seon-Cheol
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.62 no.4
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    • pp.204-209
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    • 2013
  • FFT based fingerprinting to conceal more information has developed for video copyright protection. More complex information of video is necessary to prove an ownership and legal distributions in invisible form. This paper describes a method to insert more information and to detect them. $3{\times}3$ points structure is used to present information. The possible ways to show are 8bit, $2^8$ = 256 where one point of 9 is always turn on. The points are marked in frequency domain that both real and imaginary party numbers are modified. The five successive frames of same scenes are used to mark because the same scene has very similar shape in FFT result. However, the detail values of coefficients are totally different each other to recognize the marked points. This paper also describes a method to detect the marked points by averaging and correlation algorithm. The PSNRs of marked images by our method had 51.138[dB] to 51.143[dB]. And we could get the correlation values from 0.79 to 0.87.

Accelerating Magnetic Resonance Fingerprinting Using Hybrid Deep Learning and Iterative Reconstruction

  • Cao, Peng;Cui, Di;Ming, Yanzhen;Vardhanabhuti, Varut;Lee, Elaine;Hui, Edward
    • Investigative Magnetic Resonance Imaging
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    • v.25 no.4
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    • pp.293-299
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    • 2021
  • Purpose: To accelerate magnetic resonance fingerprinting (MRF) by developing a flexible deep learning reconstruction method. Materials and Methods: Synthetic data were used to train a deep learning model. The trained model was then applied to MRF for different organs and diseases. Iterative reconstruction was performed outside the deep learning model, allowing a changeable encoding matrix, i.e., with flexibility of choice for image resolution, radiofrequency coil, k-space trajectory, and undersampling mask. In vivo experiments were performed on normal brain and prostate cancer volunteers to demonstrate the model performance and generalizability. Results: In 400-dynamics brain MRF, direct nonuniform Fourier transform caused a slight increase of random fluctuations on the T2 map. These fluctuations were reduced with the proposed method. In prostate MRF, the proposed method suppressed fluctuations on both T1 and T2 maps. Conclusion: The deep learning and iterative MRF reconstruction method described in this study was flexible with different acquisition settings such as radiofrequency coils. It is generalizable for different in vivo applications.

A Study on Online Fraud and Abusing Detection Technology Using Web-Based Device Fingerprinting (웹 기반 디바이스 핑거프린팅을 이용한 온라인사기 및 어뷰징 탐지기술에 관한 연구)

  • Jang, Seok-eun;Park, Soon-tai;Lee, Sang-joon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.5
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    • pp.1179-1195
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    • 2018
  • Recently, a variety of attacks on web services have been occurring through a multiple access environment such as PC, tablet, and smartphone. These attacks are causing various subsequent damages such as online fraud transactions, takeovers and theft of accounts, fraudulent logins, and information leakage through web service vulnerabilities. Creating a new fake account for Fraud attacks, hijacking accounts, and bypassing IP while using other usernames or email addresses is a relatively easy attack method, but it is not easy to detect and block these attacks. In this paper, we have studied a method to detect online fraud transaction and obsession by identifying and managing devices accessing web service using web-based device fingerprinting. In particular, it has been proposed to identify devices and to manage them by scoring process. In order to secure the validity of the proposed scheme, we analyzed the application cases and proved that they can effectively defend against various attacks because they actively cope with online fraud and obtain visibility of user accounts.

Error Estimation Method for Matrix Correlation-Based Wi-Fi Indoor Localization

  • Sun, Yong-Liang;Xu, Yu-Bin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.11
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    • pp.2657-2675
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    • 2013
  • A novel neighbor selection-based fingerprinting algorithm using matrix correlation (MC) for Wi-Fi localization is presented in this paper. Compared with classic fingerprinting algorithms that usually employ a single received signal strength (RSS) sample, the presented algorithm uses multiple on-line RSS samples in the form of a matrix and measures correlations between the on-line RSS matrix and RSS matrices in the radio-map. The algorithm makes efficient use of on-line RSS information and considers RSS variations of reference points (RPs) for localization, so it offers more accurate localization results than classic neighbor selection-based algorithms. Based on the MC algorithm, an error estimation method using artificial neural network is also presented to fuse available information that includes RSS samples and localization results computed by the MC algorithm and model the nonlinear relationship between the available information and localization errors. In the on-line phase, localization errors are estimated and then used to correct the localization results to reduce negative influences caused by a static radio-map and RP distribution. Experimental results demonstrate that the MC algorithm outperforms the other neighbor selection-based algorithms and the error estimation method can reduce the mean of localization errors by nearly half.

Efficient Indoor Location Estimation using Multidimensional Indexes in Wireless Networks

  • Jun, Bong-Gi
    • International Journal of Contents
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    • v.5 no.2
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    • pp.59-63
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    • 2009
  • Since it is hard to use GPS for tracking mobile user in indoor environments, much research has focused on techniques using existing wireless local area network infrastructure. Signal strength received at a fixed location is not constant, so fingerprinting approach which use pattern matching is popular. But this approach has to pay additional costs to determine user location. This paper proposes a new approach to find user's location efficiently using an index scheme. After analyzing characteristics of RF signals, the paper suggests the data processing method how the signal strength values for each of the access points are recorded in a radio map. To reduce computational cost during the location determination phase, multidimensional indexes for radio map with the important information which is the order of the strongest access points are used.