• Title/Summary/Keyword: Indexing Technique

Search Result 203, Processing Time 0.019 seconds

Micrografting and Heat Treatment Combination for Eliminating Virus of CTV-infected Citrus (CTV 바이러스 보균 감귤나무로부터 열처리와 경정접목을 통한 바이러스 제거)

  • Chae, Chi Won;Yun, Su Hyun;Park, Jae Ho;Hyun, Jae Wook;Koh, Sang Wook;Lee, Dong Hoon
    • Journal of Life Science
    • /
    • v.23 no.2
    • /
    • pp.267-272
    • /
    • 2013
  • This study was conducted to eliminate viruses from citrus-infected plants using micrografting and thermotherapy. Six citrus cultivars including a 'Setoka' hybrid were used as plant sources. The TAS-ELISA technique demonstrated that several plants were CTV positive. However, no CTV symptoms were detected in plants obtained from shoots and treated at a high temperature of $40^{\circ}C$ during the day and night and micrografted for two weeks with old trifoliate orange rootstock in vitro. Indexing of CTV, SDV, and CTLV for RT-PCR analysis of the eleven citrus seedlings, including 'Setoka', 'Samdajosang', 'Pungkwang', 'Shiranuhi', and 'Ehimekashi dai28go' was virus free following the micrografting and thermal therapy.

An Iterative, Interactive and Unified Seismic Velocity Analysis (반복적 대화식 통합 탄성파 속도분석)

  • Suh Sayng-Yong;Chung Bu-Heung;Jang Seong-Hyung
    • Geophysics and Geophysical Exploration
    • /
    • v.2 no.1
    • /
    • pp.26-32
    • /
    • 1999
  • Among the various seismic data processing sequences, the velocity analysis is the most time consuming and man-hour intensive processing steps. For the production seismic data processing, a good velocity analysis tool as well as the high performance computer is required. The tool must give fast and accurate velocity analysis. There are two different approches in the velocity analysis, batch and interactive. In the batch processing, a velocity plot is made at every analysis point. Generally, the plot consisted of a semblance contour, super gather, and a stack pannel. The interpreter chooses the velocity function by analyzing the velocity plot. The technique is highly dependent on the interpreters skill and requires human efforts. As the high speed graphic workstations are becoming more popular, various interactive velocity analysis programs are developed. Although, the programs enabled faster picking of the velocity nodes using mouse, the main improvement of these programs is simply the replacement of the paper plot by the graphic screen. The velocity spectrum is highly sensitive to the presence of the noise, especially the coherent noise often found in the shallow region of the marine seismic data. For the accurate velocity analysis, these noise must be removed before the spectrum is computed. Also, the velocity analysis must be carried out by carefully choosing the location of the analysis point and accuarate computation of the spectrum. The analyzed velocity function must be verified by the mute and stack, and the sequence must be repeated most time. Therefore an iterative, interactive, and unified velocity analysis tool is highly required. An interactive velocity analysis program, xva(X-Window based Velocity Analysis) was invented. The program handles all processes required in the velocity analysis such as composing the super gather, computing the velocity spectrum, NMO correction, mute, and stack. Most of the parameter changes give the final stack via a few mouse clicks thereby enabling the iterative and interactive processing. A simple trace indexing scheme is introduced and a program to nike the index of the Geobit seismic disk file was invented. The index is used to reference the original input, i.e., CDP sort, directly A transformation techinique of the mute function between the T-X domain and NMOC domain is introduced and adopted to the program. The result of the transform is simliar to the remove-NMO technique in suppressing the shallow noise such as direct wave and refracted wave. However, it has two improvements, i.e., no interpolation error and very high speed computing time. By the introduction of the technique, the mute times can be easily designed from the NMOC domain and applied to the super gather in the T-X domain, thereby producing more accurate velocity spectrum interactively. The xva program consists of 28 files, 12,029 lines, 34,990 words and 304,073 characters. The program references Geobit utility libraries and can be installed under Geobit preinstalled environment. The program runs on X-Window/Motif environment. The program menu is designed according to the Motif style guide. A brief usage of the program has been discussed. The program allows fast and accurate seismic velocity analysis, which is necessary computing the AVO (Amplitude Versus Offset) based DHI (Direct Hydrocarn Indicator), and making the high quality seismic sections.

  • PDF

Index-based Searching on Timestamped Event Sequences (타임스탬프를 갖는 이벤트 시퀀스의 인덱스 기반 검색)

  • 박상현;원정임;윤지희;김상욱
    • Journal of KIISE:Databases
    • /
    • v.31 no.5
    • /
    • pp.468-478
    • /
    • 2004
  • It is essential in various application areas of data mining and bioinformatics to effectively retrieve the occurrences of interesting patterns from sequence databases. For example, let's consider a network event management system that records the types and timestamp values of events occurred in a specific network component(ex. router). The typical query to find out the temporal casual relationships among the network events is as fellows: 'Find all occurrences of CiscoDCDLinkUp that are fellowed by MLMStatusUP that are subsequently followed by TCPConnectionClose, under the constraint that the interval between the first two events is not larger than 20 seconds, and the interval between the first and third events is not larger than 40 secondsTCPConnectionClose. This paper proposes an indexing method that enables to efficiently answer such a query. Unlike the previous methods that rely on inefficient sequential scan methods or data structures not easily supported by DBMSs, the proposed method uses a multi-dimensional spatial index, which is proven to be efficient both in storage and search, to find the answers quickly without false dismissals. Given a sliding window W, the input to a multi-dimensional spatial index is a n-dimensional vector whose i-th element is the interval between the first event of W and the first occurrence of the event type Ei in W. Here, n is the number of event types that can be occurred in the system of interest. The problem of‘dimensionality curse’may happen when n is large. Therefore, we use the dimension selection or event type grouping to avoid this problem. The experimental results reveal that our proposed technique can be a few orders of magnitude faster than the sequential scan and ISO-Depth index methods.hods.