Incremental-search fast vector quantiser using triangular inequalities for multiple anchors

1998 ◽  
Vol 34 (12) ◽  
pp. 1192 ◽  
Author(s):  
Sun Young Choi ◽  
Soo-Ik Chae
Keyword(s):  
Author(s):  
Shyue-Liang Wang ◽  
Ju-Wen Shen ◽  
Tuzng-Pei Hong

Mining functional dependencies (FDs) from databases has been identified as an important database analysis technique. It has received considerable research interest in recent years. However, most current data mining techniques for determining functional dependencies deal only with crisp databases. Although various forms of fuzzy functional dependencies (FFDs) have been proposed for fuzzy databases, they emphasized conceptual viewpoints and only a few mining algorithms are given. In this research, we propose methods to validate and incrementally search for FFDs from similarity-based fuzzy relational databases. For a given pair of attributes, the validation of FFDs is based on fuzzy projection and fuzzy selection operations. In addition, the property that FFDs are monotonic in the sense that r1 ? r2 implies FDa(r1) ? FDa(r2) is shown. An incremental search algorithm for FFDs based on this property is then presented. Experimental results showing the behavior of the search algorithm are discussed.


2016 ◽  
Vol 234 ◽  
pp. 49-77 ◽  
Author(s):  
Sandip Aine ◽  
Maxim Likhachev
Keyword(s):  

2001 ◽  
Vol 8 (45) ◽  
Author(s):  
Ivan B. Damgård ◽  
Gudmund Skovbjerg Frandsen

We present an Extended Quadratic Frobenius Primality Test (EQFT), which is related to the Miller-Rabin test and the Quadratic Frobenius test (QFT) by Grantham. EQFT is well-suited for generating large, random prime numbers since on a random input number, it takes time about equivalent to 2 Miller-Rabin tests, but has much smaller error probability. EQFT extends QFT by verifying additional algebraic properties related to the existence of elements of order 3 and 4. We obtain a simple closed expression that upper bounds the probability of acceptance for any input number. This in turn allows us to give strong bounds on the average-case behaviour of the test: consider the algorithm that repeatedly chooses random odd k bit numbers, subjects them to t iterations of our test and outputs the first one found that passes all tests. We obtain numeric upper bounds for the error probability of this algorithm as well as a general closed expression bounding the error. For instance, it is at most 2^{-143} for k=500, t=2 . Compared to earlier similar results for the Miller-Rabin test, the results indicates that our test in the average case has the effect of 9 Miller-Rabin tests, while only taking time equivalent to about 2 such tests. We also give bounds for the error in case a prime is sought by incremental search from a random starting point. While EQFT is slower than the average case on a small set of inputs, we present a variant that is always fast, i.e. takes time about 2 Miller-Rabin tests. The variant has slightly larger worst case error probability than EQFT, but still improves on previous proposed tests.


Author(s):  
Ana I. Torre-Bastida ◽  
Jesús Bermúdez ◽  
Arantza Illarramendi ◽  
Eduardo Mena ◽  
Marta González

Author(s):  
Veronica Maidel ◽  
Dmitry Epstein

Web search has become an integral part of everyday online activity. Existing research on search behavior offers an extensive and detailed account of what searchers do when they encounter the search results pages. Yet, there is limited inquiry into what drives the particular search decisions that are being made and what contextual factors drive this behavior. This study provides a user-centric inquiry focused on in-depth detailed investigation of search-related decision-making processes. It builds on data collected through analysis of structured observations of young adults performing searches on their personal laptops. It focuses explicitly on the decisions the users make after completing a query and facing a list of search results. The study reveals a pattern of sophisticated use of a variety of explicit cues, tacit and contextual knowledge, as well as employment of an incremental search strategy.


2012 ◽  
Vol 548 ◽  
pp. 363-366
Author(s):  
Mao Hu Wang ◽  
Zhen Liang Xu

This article simulates an open pit slope stability using the ANSYS software, which is based on the finite element strength reduction theory, three kinds of slope instability criterion of the strength reduction method are applied to judge whether the slope is on the limit equilibrium state, the incremental search method is used to search the safety factor of the slope stability, and the results show that, the slope body damages when the plastic zone developed from the top to the bottom, in the numerical simulation the finite element iteration calculation didn’t just converge, the corresponding former level of reduction factor is the safety factor, This article can have a guiding significance on the safety production of the open-pit mine.


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