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About 10,000 papers for “Combinatorial analysis”

Combinatorial Analysis

Richard Bellman, Marshall Hall · Proceedings of symposia in applied mathematics · 1960

Cited by 66

Combinatorial Analysis

Postnikov, Alexander · DSpace@MIT (Massachusetts Institute of Technology) · 2005

This course analyzes combinatorial problems and methods for their solution. Prior experience with abstraction and proofs is helpful. Topics include: Enumeration, generating functions, recurrence relations, construction of bijections, introduction to graph theory, network algorithms and, extremal combinatorics.

Cited by 0Open access

Combinatorial Image Analysis

Reneta P. Barneva, Valentin E. Brimkov, Giorgio Nordo · Lecture notes in computer science · 2023

Cited by 1Open access

Combinatorial Fusion Analysis

D. Frank Hsu, Yun‐Sheng Chung, Bruce S. Kristal · IGI Global eBooks · 2011

Combination methods have been investigated as a possible means to improve performance in multi-variable (multi-criterion or multi-objective) classification, prediction, learning, and optimization problems. In addition, information collected from multi-sensor or multi-source environment also often needs to be combined to produce more accurate information, to derive better estimation, or to make more knowledgeable decisions. In this chapter, we present a method, called Combinatorial Fusion Analysis (CFA), for analyzing combination and fusion of multiple scoring. CFA characterizes each Scoring system as having included a Score function, a Rank function, and a Rank/score function. Both rank combination and score combination are explored as to their combinatorial complexity and computational efficiency. Information derived from the scoring characteristics of each scoring system is used to perform system selection and to decide method combination. In particular, the rank/score graph defined by Hsu, Shapiro and Taksa (Hsu et al., 2002; Hsu & Taksa, 2005) is used to measure the diversity between scoring systems. We illustrate various applications of the framework using examples in information retrieval and biomedical informatics.Request access from your librarian to read this chapter's full text.

Cited by 4

Combinatorial Image Analysis

IWCIA 2018 Porto, Reneta P. Barneva, Valentin E. Brimkov et al. · Lecture notes in computer science · 2018

Cited by 0Open access

Combinatorial Analysis 1

Goldwasser, John L. · The Research Repository @ WVU (West Virginia University) · 2022

Cited by 0

Combinatorial Dipstick Analysis.

Nol Salcedo (9023363), Ankita Reddy (4597858), Adam R. Gomez (12329687) et al. · Figshare · 2022

<p>(A) SARS-CoV-2 S1 mAbs and (B) SARS-CoV-2 N mAbs were tested in a matrix for interaction with SARS-CoV-2 S1 or N and without added antigen as a control (—). mAbs were either conjugated to the nanoparticle or placed onto the nitrocellulose paper. SARS-CoV-2 S1 or SARS-CoV-2 N, at final concentrations of 125 ng/ml, were allowed to react with the rapid antigen tests. The pairwise immunochromatography signal intensities are scored as low binding (1, >201 normalized grey scale pixel intensity), medium binding (2, 141–200 normalized grey scale pixel intensity), or high binding (3, <140 normalized grey scale pixel intensity), with a majority of the combinations presenting with no signal (white). Grey boxes represent combinations not tested.</p> <p>(TIF)</p>

Cited by 0Open access