Pooling Strategies

2021 ◽  
pp. 45-55
Author(s):  
Osamu Komiyama ◽  
Shintaro Hiro ◽  
Nobushige Matsuoka ◽  
Hideharu Yamamoto
Keyword(s):  
Pooling Strategies

Building Cultural Heritage Reference Collections from Social Media through Pooling Strategies: The Case of 2020’s Tensions Over Race and Heritage

2022 ◽  
Vol 15 (1) ◽  
pp. 1-13
Author(s):  
David Otero ◽  
Patricia Martin-Rodilla ◽  
Javier Parapar
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Information Retrieval ◽  
Cultural Heritage ◽  
Digital Archives ◽  
Retrieval Method ◽  
Left Behind ◽  
Heritage Studies ◽  
Reference Collection ◽  
Pooling Strategies

Social networks constitute a valuable source for documenting heritage constitution processes or obtaining a real-time snapshot of a cultural heritage research topic. Many heritage researchers use social networks as a social thermometer to study these processes, creating, for this purpose, collections that constitute born-digital archives potentially reusable, searchable, and of interest to other researchers or citizens. However, retrieval and archiving techniques used in social networks within heritage studies are still semi-manual, being a time-consuming task and hindering the reproducibility, evaluation, and open-up of the collections created. By combining Information Retrieval strategies with emerging archival techniques, some of these weaknesses can be left behind. Specifically, pooling is a well-known Information Retrieval method to extract a sample of documents from an entire document set (posts in case of social network’s information), obtaining the most complete and unbiased set of relevant documents on a given topic. Using this approach, researchers could create a reference collection while avoiding annotating the entire corpus of documents or posts retrieved. This is especially useful in social media due to the large number of topics treated by the same user or in the same thread or post. We present a platform for applying pooling strategies combined with expert judgment to create cultural heritage reference collections from social networks in a customisable, reproducible, documented, and shareable way. The platform is validated by building a reference collection from a social network about the recent attacks on patrimonial entities motivated by anti-racist protests. This reference collection and the results obtained from its preliminary study are available for use. This real application has allowed us to validate the platform and the pooling strategies for creating reference collections in heritage studies from social networks.

scholarly journals Fixed-Cost Pooling Strategies

2019 ◽  
pp. 1-1 ◽  
Author(s):  
Aldo Lipani ◽  
David E. Losada ◽  
Guido Zuccon ◽  
Mihai Lupu
Keyword(s):  
Fixed Cost ◽  
Pooling Strategies

scholarly journals Horizontal Pyramid Matching for Person Re-Identification

2019 ◽  
Vol 33 ◽  
pp. 8295-8302 ◽  
Author(s):  
Yang Fu ◽  
Yunchao Wei ◽  
Yuqian Zhou ◽  
Honghui Shi ◽  
Gao Huang ◽  
...  
Keyword(s):  
Partial Information ◽  
Body Parts ◽  
Max Pooling ◽  
Feature Representations ◽  
The Arts ◽  
Pooling Strategies ◽  
Pyramid Matching ◽  
Type Of Failure ◽  
Remarkable Progress

Despite the remarkable progress in person re-identification (Re-ID), such approaches still suffer from the failure cases where the discriminative body parts are missing. To mitigate this type of failure, we propose a simple yet effective Horizontal Pyramid Matching (HPM) approach to fully exploit various partial information of a given person, so that correct person candidates can be identified even if some key parts are missing. With HPM, we make the following contributions to produce more robust feature representations for the Re-ID task: 1) we learn to classify using partial feature representations at different horizontal pyramid scales, which successfully enhance the discriminative capabilities of various person parts; 2) we exploit average and max pooling strategies to account for person-specific discriminative information in a global-local manner. To validate the effectiveness of our proposed HPM method, extensive experiments are conducted on three popular datasets including Market-1501, DukeMTMCReID and CUHK03. Respectively, we achieve mAP scores of 83.1%, 74.5% and 59.7% on these challenging benchmarks, which are the new state-of-the-arts.

Pooling strategies for call center agent cross-training

2009 ◽  
Vol 41 (6) ◽  
pp. 546-561 ◽  
Author(s):  
Eylem Tekin ◽  
Wallace J. Hopp ◽  
Mark P. Van Oyen
Keyword(s):  
Call Center ◽  
Cross Training ◽  
Pooling Strategies ◽  
Call Center Agent

scholarly journals Yeast two-hybrid screening of cyclic peptide libraries using a combination of random and PI-deconvolution pooling strategies

2012 ◽  
Vol 25 (9) ◽  
pp. 453-464 ◽  
Author(s):  
K. Barreto ◽  
A. Aparicio ◽  
V. M. Bharathikumar ◽  
J. F. DeCoteau ◽  
C. R. Geyer
Keyword(s):  
Cyclic Peptide ◽  
Peptide Libraries ◽  
Yeast Two Hybrid ◽  
Pooling Strategies ◽  
Two Hybrid ◽  
Hybrid Screening

scholarly journals On the utility of RNA sample pooling to optimize cost and statistical power in RNA sequencing experiments

2020 ◽  
Author(s):  
Alemu Takele Assefa ◽  
Jo Vandesompele ◽  
Olivier Thas
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Statistical Power ◽  
Dynamic Range ◽  
Substantial Reduction ◽  
Sequencing Depth ◽  
Rna Seq ◽  
Sample Pooling ◽  
Pooling Strategies ◽  
The Cost

Abstract Background: In gene expression studies, RNA sample pooling is sometimes considered because of budget constraints or lack of sufficient input material. Using microarray technology, RNA sample pooling strategies have been reported to optimize both the cost of data generation as well as the statistical power for differential gene expression (DGE) analysis. For RNA sequencing, with its different quantitative output in terms of counts and tunable dynamic range, the adequacy and empirical validation of RNA sample pooling strategies have not yet been evaluated. In this study, we comprehensively assessed the utility of pooling strategies in RNA-seq experiments using empirical and simulated RNA-seq datasets. Results: The data generating model in pooled experiments is defined mathematically to evaluate the the mean and variability of gene expression estimates. The model is further used to examine the trade-off between the statistical power of testing for DGE and the data generating costs. Empirical assessment of pooling strategies is done through analysis of RNA-seq datasets under various pooling and non-pooling experimental settings. Simulation study is also used to rank experimental scenarios with respect to the rate of false and true discoveries in DGE analysis. The results demonstrate that pooling strategies in RNA-seq studies can be both cost-effective and powerful when the number of pools, pool size and sequencing depth are optimally defined. Conclusion: For high within-group gene expression variability, small RNA sample pools are effective to reduce the variability and compensate for the loss of the number of replicates. Unlike the typical cost-saving strategies, such as reducing sequencing depth or number of RNA samples (replicates), an adequate pooling strategy is effective in maintaining the power of testing DGE for genes with low to medium abundance levels, along with a substantial reduction of the total cost of the experiment. In general, pooling RNA samples or pooling RNA samples in conjunction with moderate reduction of the sequencing depth can be good options to optimize the cost and maintain the power.

scholarly journals Pooling for SARS-CoV-2 Control in Care Institutions

2020 ◽  
Author(s):  
Jorge J. Cabrera Alvargonzalez ◽  
Sonia Rey Cao ◽  
Sonia Pérez Castro ◽  
Lucía Martínez Lamas ◽  
Olaia Cores Calvo ◽  
...  
Keyword(s):  
Scale Up ◽  
Positive Sample ◽  
Care Homes ◽  
Nasopharyngeal Swab ◽  
Rt Pcr ◽  
Average Delay ◽  
Global Rate ◽  
Local Experience ◽  
Expected Performance ◽  
Pooling Strategies

Abstract Background Workers and residents in Care Homes are considered at special risk for the acquisition of SARS-CoV-2 infection, due to the infectivity and high mortality rate in the case of residents, compared to other containment areas. The role of presymptomatic people in transmission has been shown to be important and the early detection these people is critical for the control of new outbreaks. Pooling strategies have proven to preserve SARS-CoV-2 testing resources.The aims of the present study, based in our local experience, were (a) to describe SARS-CoV-2 prevalence in institutionalized people in Galicia (Spain) during the Coronavirus pandemic and (b) to evaluate the expected performance of a pooling strategy using RT-PCR for the next rounds of screening of institutionalized people.Methods 25,386 Nasopharyngeal swab samples from the total of the residents and workers at Care Homes in Galicia (March to May 2020) were tested using RT-PCR. Prevalence and distribution of positive detection in Care Homes was calculated. Pools of 19 negative samples and one positive sample were tested using RT-PCR as well. Prevalence and distribution of positive detection in Care Homes was calculated. Results Distribution of SARS-CoV-2 infection at Care Houses was uneven. As the virus circulation global rate was low in our area, the number of people at risk of acquiring the infection continues to be very high. In this work, we have successfully demonstrated that pooling of different groups of samples at low prevalence clusters, can be done with a small average delay on quantification cycle (Cq) values. Conclusions A new surveillance system with guaranteed protection is required for small clusters, previously covered with individual testing. Our proposal for Care Houses, once prevalence zero is achieved, would include successive rounds of testing using a pooling solution for transmission control preserving testing resources. Scale-up of this method may be of utility to confront larger clusters to avoid the viral circulation and keeping them operative.

scholarly journals Investigation of pooling strategies using clinical COVID-19 samples for more efficient diagnostic testing

2020 ◽  
Author(s):  
Samantha H Adikari ◽  
Emily Z Alipio Lyon ◽  
Attelia D Hollander ◽  
Alina Deshpande ◽  
Elizabeth Hong-Geller
Keyword(s):  
Diagnostic Testing ◽  
Rna Extraction ◽  
Positive Sample ◽  
Viral Rna ◽  
Clinical Samples ◽  
Extraction Column ◽  
Diagnostic Assay ◽  
Significant Difference ◽  
Pooling Strategies ◽  
Single Positive

When testing large numbers of clinical COVID-19 samples for diagnostic purposes, pooling samples together for processing can offer significant reductions in the materials, reagents, time, and labor needed. We have evaluated two different strategies for pooling independent nasopharyngeal swab samples prior to testing with an EUA-approved SARS-CoV-2 RT-qPCR diagnostic assay. First, in the Dilution Study, we assessed the assay's ability to detect a single positive clinical sample diluted in multiple negative samples before the viral RNA extraction stage. We observed that positive samples with Ct values at ~30 can be reliably detected in pools of up to 30 independent samples, and positive samples with Ct values at ~35 can be detected in pools of 5 samples. Second, in the Reloading Study, we assessed the efficacy of reloading QIAamp viral RNA extraction columns numerous times using a single positive sample and multiple negative samples. We determined that one RNA extraction column can be reloaded with up to 20 clinical samples (1 positive and 19 negatives) sequentially without any loss of signal in the diagnostic assay. Furthermore, we found there was no significant difference in assay readout whether the positive sample was loaded first or last in a series of 20 samples. These results demonstrate that different pooling strategies can lead to increased process efficiencies for COVID-19 clinical diagnostic testing.

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