Group Testing Theory in Network Security

2012 ◽  
Author(s):  
My T. Thai
Keyword(s):  
Network Security ◽  
Group Testing ◽  
Testing Theory

scholarly journals Sample pooling methods for efficient pathogen screening: Practical implications

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0236849
Author(s):  
Tara N. Furstenau ◽  
Jill H. Cocking ◽  
Crystal M. Hepp ◽  
Viacheslav Y. Fofanov
Keyword(s):  
Human Error ◽  
Large Scale ◽  
Group Testing ◽  
Computational Simulations ◽  
Theoretical Approaches ◽  
Testing Theory ◽  
Large Populations ◽  
Sample Pooling ◽  
Pathogen Screening ◽  
Practical Implications

Due to the large number of negative tests, individually screening large populations for rare pathogens can be wasteful and expensive. Sample pooling methods improve the efficiency of large-scale pathogen screening campaigns by reducing the number of tests and reagents required to accurately categorize positive and negative individuals. Such methods rely on group testing theory which mainly focuses on minimizing the total number of tests; however, many other practical concerns and tradeoffs must be considered when choosing an appropriate method for a given set of circumstances. Here we use computational simulations to determine how several theoretical approaches compare in terms of (a) the number of tests, to minimize costs and save reagents, (b) the number of sequential steps, to reduce the time it takes to complete the assay, (c) the number of samples per pool, to avoid the limits of detection, (d) simplicity, to reduce the risk of human error, and (e) robustness, to poor estimates of the number of positive samples. We found that established methods often perform very well in one area but very poorly in others. Therefore, we introduce and validate a new method which performs fairly well across each of the above criteria making it a good general use approach.

scholarly journals Sample pooling methods for efficient pathogen screening: Practical implications

2020 ◽  
Author(s):  
Tara N. Furstenau ◽  
Jill H. Cocking ◽  
Crystal M. Hepp ◽  
Viacheslav Y. Fofanov
Keyword(s):  
Human Error ◽  
Large Scale ◽  
Group Testing ◽  
Computational Simulations ◽  
Theoretical Approaches ◽  
Testing Theory ◽  
Large Populations ◽  
Sample Pooling ◽  
Pathogen Screening ◽  
Practical Implications

AbstractDue to the large number of negative tests, individually screening large populations for rare pathogens can be wasteful and expensive. Sample pooling methods improve the efficiency of large-scale pathogen screening campaigns by reducing the number of tests and reagents required to accurately categorize positive and negative individuals. Such methods rely on group testing theory which mainly focuses on minimizing the total number of tests; however, many other practical concerns and tradeoffs must be considered when choosing an appropriate method for a given set of circumstances. Here we use computational simulations to determine how several theoretical approaches compare in terms of (a) the number of tests, to minimize costs and save reagents, (b) the number of sequential steps, to reduce the time it takes to complete the assay, (c) the number of samples per pool, to avoid the limits of detection, (d) simplicity, to reduce the risk of human error, and (e) robustness, to poor estimates of the number of positive samples. We found that established methods often perform very well in one area but very poorly in others. Therefore, we introduce and validate a new method which performs fairly well across each of the above criteria making it a good general use approach.

The implications of minority group testing for more effective learning

1971 ◽  
Author(s):  
Florence L. Denmark ◽  
Ethel Jackson Shirk ◽  
Leonard E. Bart ◽  
Bernice Baxter ◽  
Alfredo Casteneda ◽  
...  
Keyword(s):  
Minority Group ◽  
Group Testing ◽  
Effective Learning

Authorship Pattern and Collaborative Research in the Field of Network Security

2011 ◽  
Vol 3 (1) ◽  
pp. 52-54 ◽  
Author(s):  
N. Amsaveni N. Amsaveni ◽  
◽  
R. Vasanthi R. Vasanthi
Keyword(s):  
Network Security ◽  
Collaborative Research ◽  
Authorship Pattern

COMMUNICATIONS RECONSTRUCTION FOR A NETWORK SECURITY ANALYSIS

2010 ◽  
Vol 69 (7) ◽  
pp. 629-638
Author(s):  
J. Sisniega-Gonzalez ◽  
E. Aguirre-Anaya ◽  
Mariko Nakano-Miyatake ◽  
Hector Manuel Perez-Meana
Keyword(s):  
Network Security ◽  
Security Analysis

DESIGNING INTERACTIVE DIGITAL LEARNING MODULE IN BIOLOGY

TABULARASA ◽  
2015 ◽  
Vol 12 (2) ◽  
Author(s):  
Wenny Pintalitna ◽  
Herbet Sipahutar ◽  
Fauziyah Harahap
Keyword(s):  
Small Group ◽  
Group Testing ◽  
Quality Data ◽  
Digital Learning ◽  
Text Learning ◽  
Interactive Learning Environment ◽  
Learning Modules ◽  
Large Group ◽  
Learning Module ◽  
Medium Group

Interactive learning environment can substantially improve student learning and retention of key biology concepts. In this case report, we describe our approach for the design of interactive digital learning module to teach digestive system concepts in Grade 11 learners at SMAN 2 Balige with 180 subjects are selected according to total sampling method. The research method is the development with Dick and Carey model.  Subject of learning module assessment consists of two Biology matter experts, two learning module experts, one electronic media expert, three students for individual trials, ten students and teachers as small group testing, thirty students of SMAN 1 Berastagi for medium group testing, and 60 students of SMAN 2 Balige as large group testing. Quality data of product developed were collected using questionnaires. The results of developmental research showed that: (1) Module assessment by matter, learning modules and media experts were very decent criteria (88.30%, 93.98%, 88.25%); 2) Large group testing of interactive, electronic and text learning modules, respectively were 92.53%, 86.064%, 81.355% belong to very decent criteria; (3) Medium group testing respectively were 84.59%, 80.18%, 76.56% belong to decent criteria; (6) Small group testing respectively were 75.71%, 73.20%, 71.19% belong to decent criteria.

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