• Title/Summary/Keyword: RF fingerprinting

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Ginsenoside Content of North American Ginseng (Panax quinquefolius L. Araliaceae) in Relation to Plant Development and Growing Locations

  • Jackson, Chung Ja C.;Dini, Jean-Paul;Lavandier, Clara;Faulkner, Harold;Rupasinghe, H.P. vasantha;Proctor, John T.A.
    • Journal of Ginseng Research
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    • v.27 no.3
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    • pp.135-140
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    • 2003
  • North American ginseng (Panax quinquefolius L.) was analysed for total ginsenosides and ten major ginsenosides (R$_{0}$ , Rb$_1$, Rb$_2$, Rc, Rd, Re, Rf, Rg$_1$, pseudoginsenoside F$_{11}$ and gypenoside XVII), and variations in ginsenoside content with age of plant (over a four-year-period) and geographic location (Ontario versus British Columbia) were investigated. In the roots the total ginsenoside content increased with age up to 58-100 mgㆍg$^{-1}$ dry weights in the fourth year, but in leaves it remained constant over time. Roots and leaves, moreover, had different proportions of individual ginsenosides. The most abundant ginsenosides were Rb$_1$ (56mgㆍg$^{-1}$ for Ontario; 37mgㆍg$^{-1}$ for British Columbia) and Re (21mgㆍg$^{-1}$ for Ontario; 15 mgㆍg$^{-1}$ for British Columbia) in roots, and Rd (28-38 mgㆍg$^{-1}$ ), Re (20-25 mgㆍg$^{-1}$ ), and Rb$_2$ (13-19 mgㆍg$^{-1}$ ) in leaves. Measurable quantities of Rf were found in leaves (0.4-1.8 mgㆍg$^{-1}$ ) but not in roots or stems. Our results show that ginsenoside profiles in general, and Rf in particular, could be used for chemical fingerprinting to distinguish the different parts of the ginseng plant, and that ginseng leaves could be valuable sources of the ginsenosides Rd, Re, and Rb$_2$.

Analysis of Localization Technology Performance Based on Accumulated RSSI Signal Using Simulation (시뮬레이션을 이용한 누적 RSSI 신호 기반의 항법 기술 성능 분석)

  • Beomju Shin;Taikjin Lee
    • Journal of Positioning, Navigation, and Timing
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    • v.13 no.3
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    • pp.331-339
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    • 2024
  • Reliable and precise indoor localization is crucial for personal navigation, emergency rescue, and monitoring workers indoors. To use this technology in different applications, it is important to make it less dependent on infrastructure and to keep the error as small as possible. Fingerprinting stands out as a popular choice for indoor positioning because it leverages existing infrastructure and works with just a smartphone. However, its accuracy heavily relies on the quality of that infrastructure. For instance, having too few access points or beacons can greatly reduce its effectiveness. To reduce dependence on RF infrastructure, we have developed surface correlation (SC) using accumulated Received Signal Strength Indicator (RSSI) signals This approach constructs a user mask for radio map comparisons using an accumulated RSSI vector and the trajectory of the user, which is estimated through PDR. The location with the highest correlation is considered as the user's position after comparison. Through a simulation, the performance of short RSSI vector-based technology and SC is analyzed, and future directions for the development of SC are discussed.

Performance Analysis of Indoor Localization Algorithm Using Virtual Access Points in Wi-Fi Environment (Wi-Fi 환경에서 가상 Access Point를 이용한 실내 위치추정 알고리즘의 성능분석)

  • Labinghisa, Boney;Lee, Dong Myung
    • KIPS Transactions on Computer and Communication Systems
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    • v.6 no.3
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    • pp.113-120
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    • 2017
  • In recent years, indoor localization has been researched for the improvement of its localization accuracy capability in Wi-Fi environment. The fingerprint and RF propagation models has been the main approach in determining indoor positioning. With the use of fingerprint, a low-cost, versatile localization system can be achieved without the use of external hardware. However, only a few research have been made on virtual access points (VAPs) among indoor localization models. In this paper, the idea of indoor localization system using fingerprint with the addition of VAP in Wi-Fi environment is discussed. The idea is to virtually add APs in the existing indoor Wi-Fi system, this would mean additional virtually APs in the network. The experiments of the proposed algorithm shows the positive results when 2VAPs are used compared with only APs. A combination of 3APs and 2VAPs in the 3rd case had the lowest average error of 3.99 among its 4 scenarios.