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About 10,000 papers for “Algorithm”

Algorithm.

Junyi Xu (2601184), Li Yao (113027), Le Li (356426) · Figshare · 2015

Cited by 0Open access

ALGORITHM

A Phase-based, Iris Recognition · 2014

Abstract-The increase demand in security system concern to issues such as person identity and theft detection the need of a new reliable security system. A biometric system provides automatic identification of an individual, based on a unique feature or characteristic possessed by the individual. Iris recognition is regarded as the most reliable and accurate biometric identification system. Iris recognition is perhaps the most accurate means of personal identification due to uniqueness of the patterns contained in each iris. The iris recognition system consists of an automatic segmentation system that is based on edge detection and Hough transform, and is able to detect the circular iris and pupil region and occluding eyelids and eyelashes. The extracted iris region is then normalized into a rectangular block with constant dimensions to account for imaging in consistencies. Finally, the image matching algorithm which specifically focuses on the characteristics of the phase components obtained from two-dimensional Fourier Transformation of an image. The Phase Only Correlation (POC) and Band Limited Phase Only Correlation (BLPOC) are the most fundamental transformations, the features of which include superior discrimination capability over the ordinary recognition system.

Cited by 0

Algorithm

Ramon Mata‐Toledo · Van Nostrand's Scientific Encyclopedia · 2005

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Algorithm

Shashi Shekhar, Hui Xiong, Xun Zhou · Encyclopedia of GIS · 2017

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algorithm

2024

Citation: 'algorithm' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.11405 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms. Requests for commercial usage of the compendium should be directed to IUPAC.

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Algorithm

Advances in educational technologies and instructional design book series · 2023

Algorithm is a description of a process that is broken down into steps to accomplish something. It is a concept used in the field of information processing. Since it is strictly described so that it can withstand any conditions, it becomes an abstract and formal notation. As the amount of data to be processed increases, it is difficult to see from these notations what kind of transformation process the initial state will undergo to reach the final state. The dynamic visualization of an algorithm explicitly conveys its contained essence to the learner through the manifestation of the changing whole. This is difficult to obtain by thinking from formal descriptions. This chapter clarifies the significance of visualization through four topics: Sorting algorithm, search algorithm, tower of Hanoi, and sweep method.

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Algorithm

Sonja Brentjes · MPG.PuRe (Max Planck Society) · 2017

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Algorithm.

Peng Huang (105814), Wenjun Ye (9243929), Yawu Wang (9243932) · Figshare · 2020

Cited by 0Open access

Algorithm ∗

W. W. Hager, G. Bencteux, E. Cancès et al. · 2009

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algorithm

Baharak Rastegari, Anne Condon · 2006

Cited by 0

Algorithm

Álvaro Gutiérrez, Re Campo, Félix Monasterio-huelin et al. · 2009

The information provided is the sole responsibility of the authors and does not necessarily reflect the opinion of the members of IRIDIA. The authors take full responsability for any copyright breaches that may result from publication of this paper in the IRIDIA – Technical Report Series. IRIDIA is not responsible for any use that might be made of

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Algorithm

Jadhav Arvind Uttamrao · 2014

algorithm decreases the number of data base scans during frequent item set mining to improve association rule mining process. In this paper, we present parallel version of TBAR algorithm. Parallel version of TBAR algorithm decreases the time required for association rule mining process by making candidate item set generation, frequent item set generation and association rule generation process parallel.

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Algorithm

2008

[R,p]=sqr(A) computes the upper triangular n-by-n matrix R in the QR factorization of the sparse m-by-n; m * n; matrix A(r; p), QT A(r; p) = ` R0 ' : Here, p is a postordered column ordering and r the row ordering used. Since R is invariant under row orderings of A, r is not made available for the user. [R,p,c]=sqr(A,b) does also compute the n first components of QT b(r). This vector/matrix is often used in the solution of sparse linear least squares problems.

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Algorithm .

Yanrong Lu (739990), Lixiang Li (154535), Xing Yang (262520) et al. · Figshare · 2015

Cited by 0Open access

Algorithm.

Xuemei Zhang (89768), Gengui Zhou (16813939), Jian Cao (16485) et al. · Figshare · 2023

<div><p>Remanufacturing is a sustainable product reutilization strategy to realize responsible consumption and production. However, remanufacturing practice can be subject to deficient consumer perception, production capacity constraint, uncertain demand and government intervention. This paper considers outsourced remanufacturing mode to establish and investigate a remanufacturing supply chain (RSC) network consisting of multiple manufacturers, retailers and remanufacturers. Optimality conditions with RSC network members are derived utilizing variation inequality. Numerical examples based on data accumulated from a remanufacturing enterprise and questionnaire survey on consumer perception for remanufactured products, are presented to put the proposed model into practice. Influences of product heterogeneity (new and remanufactured products), consumer preference, production capacity constraint, product price competitiveness, market demand fluctuation, and government financial measures on RSC network production and pricing strategies are investigated through numerical analyses. Analytical results indicate that pricing for the remanufactured product would be equivalent to that of the new product when consumers value the remanufactured product at a relatively high level, however an excessive penchant for the remanufactured product is less profitable especially from the perspective of the remanufacturer. In general, an upper-middle level of consumer preference for the remanufactured product is the most favourable scenario. When remanufacturing industry is just emerging, a high tax will be imposed on the manufacturer to accumulate remanufacturing subsidy for the government to achieve its balanced budget. As the remanufacturing industry develops and consumer environmental awareness enhances, it is especially essential for the government to establish a levy-subsidy mechanism to maintain sustainable progress of the industry. Combining main conclusions with the background of Chinese remanufacturing industry, managerial implications are provided from respective perspectives of enterprises’ remanufacturing operation, government financial regulation, and consumer awareness enhancement. The analyses and results are especially relevant as a reference for remanufacturing decision-makings as well as government financial regulations, thus enhancing production sustainability as well as environmental benefits.</p></div>

Cited by 0Open access

A fusion algorithm based on HITS algorithm and MASEL algorithm

Han Yuan-jie · 2006

In order to search better resources,a new mining algorithm is introduced in this paper,which integrates HITS algorithm with MASEL algorithm.This method makes HITS and MASEL algorithms complement each other.It can also solve the problem of topic drift in HITS algorithm as well as the problem that MASEL algorithm can't efficiently find hubs and authorities WebPages.The results of simulation studies show that the fusion method performs better than the HITS and MASEL algorithms in terms of returning large number of relevant pages to a given query.

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1KEY WORDS: Aco Algorithm, Current Algorithm,(C-Ant miner) Proposed Algorithm(New Pheromone Update Algorithm)

2015

Mining information and knowledge from large database has been recognized by many researchers as a key research topic in database system and machine learning and by many industrial companies as an important area with an opportunity of major revenues. One of the data mining tasks gaining significant attention is the classification rules extraction from databases. The goal of this task is

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