Filters








9,289 Hits in 30.1 sec

Optimal Deterministic Group Testing Algorithms to Estimate the Number of Defectives [article]

Nader H. Bshouty, Catherine A. Haddad-Zaknoon
2020 arXiv   pre-print
We study the problem of estimating the number of defective items d within a pile of n elements up to a multiplicative factor of Δ>1, using deterministic group testing algorithms.  ...  For the adaptive deterministic settings, our results show that, any algorithm for estimating the defectives number up to a multiplicative factor of Δ must make at least Ω((D/Δ^2)log (n/D) ) tests.  ...  For the adaptive deterministic settings, our results show that, any algorithm for estimating the defectives number up to a multiplicative factor of ∆ must make at least Ω (D/∆ 2 ) log(n/D) tests.  ... 
arXiv:2009.02520v1 fatcat:qxuypzqru5e5vbburh5ayhr34m

Optimal Randomized Group Testing Algorithm to Determine the Number of Defectives

Nader H. Bshouty, Catherine A. Haddad-Zaknoon, Raghd Boulos, Foad Moalem, Jalal Nada, Elias Noufi, Yara Zaknoon, Susanne Albers
2020 Scandinavian Workshop on Algorithm Theory  
We study the problem of determining the exact number of defective items in an adaptive group testing by using a minimum number of tests.  ...  We improve the existing algorithm and prove a lower bound that shows that the number of tests in our algorithm is optimal up to small additive terms.  ...  In this paper, we study the problem of determining exactly the number of defective items with adaptive group testing algorithms.  ... 
doi:10.4230/lipics.swat.2020.18 dblp:conf/swat/BshoutyHBMNNZ20 fatcat:uowext3ubvbyjo73wwujnrxpxi

Optimal Randomized Group Testing Algorithm to Determine the Number of Defectives [article]

Nader H. Bshouty and Catherine A. Haddad-Zaknoon and Raghd Boulos and Foad Moalem and Jalal Nada and Elias Noufi and Yara Zaknoon
2020 arXiv   pre-print
We study the problem of determining exactly the number of defective items in an adaptive Group testing by using a minimum number of tests.  ...  We improve the existing algorithm and prove a lower bound that shows that the number of tests in our algorithm is optimal up to small additive terms.  ...  In this paper, we study the problem of determining exactly the number of defective items with adaptive Group testing algorithms.  ... 
arXiv:2001.00441v1 fatcat:d63ivz7p45cn3gb6whw7ejrwem

Group Testing for Efficiently Sampling Hypergraphs When Tests Have Variable Costs [article]

Laurence A. Clarfeld, Margaret J. Eppstein
2020 arXiv   pre-print
In the group-testing literature, efficient algorithms have been developed to minimize the number of tests required to identify all minimal "defective" sub-groups embedded within a larger group, using deterministic  ...  For both algorithms, we show that the optimal initial group size is a function of both the prevalence of defective sets and the positive:negative test cost ratio.  ...  Acknowledgment The authors thank Jeffrey S. Buzas and Damin Zhu for helpful discussions regarding group testing algorithms, which ultimately inspired this work. We also thank Paul D.H.  ... 
arXiv:2010.09205v1 fatcat:fs47tx5atbcdnmyfqvw2zksxzm

Adaptive Group Testing Algorithms to Estimate the Number of Defectives [article]

Nader H. Bshouty and Vivian E. Bshouty-Hurani and George Haddad and Thomas Hashem and Fadi Khoury and Omar Sharafy
2017 arXiv   pre-print
We study the problem of estimating the number of defective items in adaptive Group testing by using a minimum number of queries.  ...  We improve the existing algorithm and prove a lower bound that show that, for constant estimation, the number of tests in our algorithm is optimal.  ...  In this paper we study the problem of estimating the number of defective items |I| up to a multiplicative factor of 1 ± ǫ with an adaptive Group testing algorithms.  ... 
arXiv:1712.00615v1 fatcat:in46r7twmjdvvewa5xmp6wej54

Quantitative estimating size of deep defects in multi-layered structures from eddy current NDT signals using improved ant colony algorithm

Bo Ye, Ming Li, Gefei Qiu, Jun Dong, Fang Zeng
2014 Frattura ed Integrità Strutturale  
A novel approach to accurately quantify the two-dimensional axisymmetric deep defect size from eddy current nondestructive testing (NDT) signals is presented here.  ...  Detection and quantitative estimation of deep defects in multi-layered structures is an essential task in a range of technological applications, such as maintaining the integrity of structures, enhancing  ...  This paper presents an improved ant colony algorithm (IACA) and proposes the use of IACA to quantitative estimate defect size from EC inspection signals.  ... 
doi:10.3221/igf-esis.28.04 fatcat:2nppwe2hc5fzro56kumuzbuojm

Simple Codes and Sparse Recovery with Fast Decoding [article]

Mahdi Cheraghchi, João Ribeiro
2019 arXiv   pre-print
up to K defectives in a population of size N.  ...  This decoder can be applied to exact for-all sparse recovery over any field, improving upon previous results with the same number of measurements.  ...  Acknowledgments The authors thank Shashanka Ubaru and Thach V. Bui for discussions on the role of the bitmasking technique in sparse recovery.  ... 
arXiv:1901.02852v2 fatcat:v3fniwgi4nhdvjz4hktm5onawq

Competitive Group Testing and Learning Hidden Vertex Covers with Minimum Adaptivity [chapter]

Peter Damaschke, Azam Sheikh Muhammad
2009 Lecture Notes in Computer Science  
Here we explore group testing strategies that use a nearly optimal number of pools and a few stages although d is not known beforehand.  ...  The 2-stage strategies still require the knowledge of an upper bound d on the number of defectives, and they guarantee an almost optimal query complexity only relative to this d which can be much larger  ...  Acknowledgments This article was inspired by the first author's participation in the wonderful Dagstuhl Seminars 08301 "Group Testing in the Life Sciences" (2008) and 09281 "Search Methodologies" (2009  ... 
doi:10.1007/978-3-642-03409-1_9 fatcat:z627dt4foncctmisjtyk7nylhy

Data-driven dynamic decision models

John J. Nay, Jonathan M. Gilligan
2015 2015 Winter Simulation Conference (WSC)  
We use an efficient model representation and a genetic algorithm-based estimation process to generate simple approximations that explain most of the structure of complex stochastic processes.  ...  We also demonstrate the method's ability to recover known data-generating processes by simulating data with agent-based models and correctly deriving the underlying decision models for multiple agent models  ...  ACKNOWLEDGMENTS We gratefully acknowledge the authors of R (R Core Team 2014). This manuscript was prepared using knitr (Xie 2014) .  ... 
doi:10.1109/wsc.2015.7408381 dblp:conf/wsc/NayG15 fatcat:vvkfas6yxzgt7eanxv6vn72tsq

A roller bearing fault diagnosis method using interval support vector deterministic optimization based on nested PSO

Yongqi Chen, Qinge Dai, Yang Chen
2018 Journal of Vibroengineering  
Thus, the nested particle swarm optimization (PSO) based on dynamic decreasing inertia weight is applied to select the optimal Lagrange multiplier vector of this model.  ...  An interval support vector deterministic optimization model (ISVD) is proposed for the fault classification problem of uncertainty samples in this paper.  ...  Of course, the PSO algorithm needs more iteration to reach the global optimal, and it is more likely not to find the global optimal.  ... 
doi:10.21595/jve.2018.19613 fatcat:llohabturvcglfz2gssdrpehzu

A new competitive algorithm for group testing

A. Bar-Noy, F.K. Hwang, I. Kessler, S. Kutten
1992 [Proceedings] IEEE INFOCOM '92: The Conference on Computer Communications  
number of tests required by an optimal algorithm when the number of defective items is known in advance.  ...  Algorithms for the group testing problem when there is no a priori information on the number of defective items are considered.  ...  Acknowledgments We would like to thank Moshe Sidi for valuable discussions.  ... 
doi:10.1109/infcom.1992.263516 dblp:conf/infocom/Bar-NoyKKH92 fatcat:344fn26djrcvzmv2sr3orqbhum

Two New Perspectives on Multi-Stage Group Testing

Peter Damaschke, Azam Sheikh Muhammad, Eberhard Triesch
2013 Algorithmica  
The group testing problem asks to find d n defective elements out of n elements, by testing subsets (pools) for the presence of defectives.  ...  In the strict model of group testing, the goal is to identify all defectives if at most d defectives exist, and otherwise to report that more than d defectives are present.  ...  The first author also received support from RWTH Aachen during a visit in 2011. We thank the referees of ICALP2001GT and of this Special Issue for their careful remarks and suggestions.  ... 
doi:10.1007/s00453-013-9781-4 fatcat:7zzjjcoy5fcxbglfnhwaecrfry

Combinatorial Pair Testing: Distinguishing Workers from Slackers [chapter]

David Eppstein, Michael T. Goodrich, Daniel S. Hirschberg
2013 Lecture Notes in Computer Science  
We give efficient adaptive and nonadaptive CPT algorithms and we show that our methods use an optimal number of testing rounds to within constant factors.  ...  We formalize a problem we call combinatorial pair testing (CPT), which has applications to the identification of uncooperative or unproductive participants in pair programming, massively distributed computing  ...  This research was supported in part by the National Science Foundation under grants 1011840, 1217322, and 1228639, and by the Office of Naval Research under MURI grant N00014-08-1-1015.  ... 
doi:10.1007/978-3-642-40104-6_28 fatcat:spz27kqu7featof2xu55yu3z6i

Group-Testing on Hypergraphs with Variable-Cost Tests: A Power Systems Case Study [article]

Laurence A. Clarfeld, Margaret J. Eppstein
2019 arXiv   pre-print
Thus, the relative speed of each algorithm depends on the relative cost of defective vs. non defective tests, a factor not previously considered in the group-testing literature.  ...  We compare RC to a proposed new alternative group-testing algorithm (SIGHT).  ...  Acknowledgment The authors thank Jeffrey S. Buzas and Damin Zhu for helpful discussions regarding group testing algorithms, which ultimately inspired the SIGHT algorithm. We also thank Paul D.H.  ... 
arXiv:1909.04513v1 fatcat:pngqjspc35bzfkto2c3apsbba4

Page 5073 of Mathematical Reviews Vol. , Issue 911 [page]

1991 Mathematical Reviews  
The problem is to classify all items, or find all the defectives with a minimum expected number of tests E(n, p).  ...  K. (1-BELL) On optimal nested group testing algorithms. J. Statist. Plann. Inference 24 (1990), no. 2, 167-175.  ... 
« Previous Showing results 1 — 15 out of 9,289 results