Making online polls more accurate: statistical methods explained by Alberto Arletti, Maria Letizia Tanturri, Omar Paccagnella

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Tripartite: Tackling Realistic Noisy Labels with More Precise Partitions by Lida Yu, Xuefeng Liang, Chang Cao, Longshan Yao, Xingyu Liu

“…Extensive experiments demonstrate that Tripartite can filter out noisy samples more precisely and outperforms most state-of-the-art methods on four benchmark datasets and especially real-world datasets.…”
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Parents of Child Psychiatric Patients Report More Adverse Childhood Experiences Compared with Community Samples by Adriana Altpeter, Andrea Dixius, Eva Möhler

“…In addition, the connection between parental negative traumatic experiences and their children’s reporting of these experiences should be examined in more detail. <b>Methods</b>: In total, 256 child psychiatric patients (73.8% female and 26.2% male) aged 4–18 years (mean [M] = 13.26 years, standard deviation [SD] = 2.73) were retrospectively examined for post-traumatic stress symptoms (using the CATS questionnaire). …”
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Methods to account for incomplete viewsheds in distance sampling by David M. Delaney, Tyler M. Harms, Jonathan P. Harris, Dan J. Kaminski, Jace R. Elliott, Stephen J. Dinsmore

“…Abstract Conventional distance sampling is a logistically feasible method for estimating densities of unmarked animals. …”
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IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
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Uncertainty Quantification and Assimilation Method Based on Evaluated Nuclear Data Sampling Method by HUANG Yihan, ZU Tiejun, LIU Zhengming, CAO Liangzhi, WU Hongchun

“…The sampling method developed based on evaluated nuclear data aims to more accurately quantify uncertainties and adjust prior nuclear data using measurement results and calculation uncertainties. …”

Lateral flow devices for samples collected by straw sampling method for postmortem canine rabies diagnosis. by Milagros R Mananggit, Daria L Manalo, Nobuo Saito, Kazunori Kimitsuki, Alyssa Marie G Garcia, Patricia Mae T Lacanilao, Joely T Ongtangco, Cornhlo R Velasco, Maria Victoria A Del Rosario, Maria Glofezita O Lagayan, Kentaro Yamada, Chun-Ho Park, Satoshi Inoue, Motoi Suzuki, Mariko Saito-Obata, Yasuhiko Kamiya, Catalino S Demetria, Beatriz P Quiambao, Akira Nishizono

“…However, because of our limited sample size, more data using fresh samples on-site and the optimizations are urgently needed for the further implementation in endemic areas.…”
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Comparison of Sample Preparation and Detection Methods for the Quantification of Synthetic Musk Compounds (SMCs) in Carp Fish Samples by Jungmin Jo, Eunjin Lee, Na Rae Choi, Ji Yi Lee, Jae Won Yoo, Dong Sik Ahn, Yun Gyong Ahn

“…This study deals with the separation and detection methods for 12 synthetic musk compounds (SMCs), which are some of the emerging contaminants in fish samples, are widely present in environmental media, and can be considered serious risks due to their harmful effects. …”
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New adjusted missing value imputation in multiple regression with simple random sampling and rank set sampling methods. by Juthaphorn Sinsomboonthong, Saichon Sinsomboonthong

“…This research compared the efficiency of several adjusted missing value imputation methods in multiple regression analysis. The four imputation methods were the following: regression-ratio quartile1,3 (R-RQ1,3) imputation of Al-Omari, Jemain and Ibrahim; adjusted regression-chain ratio quartile1,3 (AR-CRQ1,3) imputation of Kadilar and Cinji; adjusted regression-multivariate ratio quatile1,3 (AR-MRQ1,3) imputation of Feng, Ni, and Zou; and adjusted regression-multivariate chain ratio quartile1,3 (AR-MCRQ1,3) imputation of Lu for each simple random sampling (SRS) and rank set sampling (RSS). …”
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Optimizing collection methods for noninvasive genetic sampling of neotropical felids by Claudia Wultsch, Lisette P. Waits, Eric M. Hallerman, Marcella J. Kelly

“…ABSTRACT Field‐sampling methods for molecular scatology studies must be optimized, especially when working on elusive species in challenging tropical environments where rates of DNA degradation are elevated because of hot and humid weather conditions. …”
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ON SAMPLING BASED METHODS FOR THE DUBINS TRAVELING SALESMAN PROBLEM WITH NEIGHBORHOODS by Petr Váňa, Jan Faigl

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Optimal Imputation Methods under Stratified Ranked Set Sampling by Shashi Bhushan, Anoop Kumar

“… It is long familiar that the stratified ranked set sampling (SRSS) is more efficient than ranked set sampling (RSS) and stratified random sampling (StRS). …”
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Comparison of ASTM and in-line microplastic sampling methods for drinking water by Noah A. D’Ascanio, Judith Glienke, Husein Almuhtaram, Robert C. Andrews

“…The sieve stack method resulted in 8.6 × more non-spiked particles than the in-line filtration method. …”
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Homogenization of insect bulk samples yields more comprehensive yet comparable biodiversity data than non-destructive lysis by Lisa Wolany, Julian Enss, Florian Leese, Dominik Buchner

“…On average, homogenized samples yielded 3.8% more OTUs than non-destructive lysis samples. …”
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A novel method for precise endoscopic sampling of duodenal microbiota by Taotao Wei, Gaozhong Dai, Tianye Liu, Yaozhou Tian

“…Furthermore, the abundance of specific bacterial strains varied significantly between sampling methods. These findings suggest that the use of the channel plug enables more comprehensive microbiota sampling, providing data to support clinical diagnosis of gastrointestinal diseases.…”
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SUBSTANTIATION OF THE METHOD OF MEAT SAMPLE PREPARATION FOR INSTRUMENTAL DETERMINATION OF CONSISTENCY by Kirill I. Spiridonov, Victoria V. Nasonova, Elena K. Tunieva

“…In the study of samples without heat treatment, deviations from the average were more than 11%. …”
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Dialing for Videos: A Random Sample of YouTube by Ryan McGrady, Kevin Zheng, Rebecca Curran, Jason Baumgartner, Ethan Zuckerman

“…In providing basic information about YouTube as a whole, we not only learn more about an influential platform, but also provide baseline context against which samples in more focused studies can be compared. …”
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pyLAIS: A Python package for Layered Adaptive Importance Sampling by Ernesto Curbelo, Luca Martino, David Delgado-Gómez

“…The most famous families of MC methods are Markov Chain Monte Carlo (MCMC) and importance sampling (IS). …”
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A Benchmark of methods for SARS-CoV-2 whole genome sequencing and development of a more sensitive method by Anthony Bayega, Anthony Bayega, Sarah J. Reiling, Sarah J. Reiling, Ju Ling Liu, Ju Ling Liu, Isabelle Dubuc, Annie Gravel, Louis Flamand, Louis Flamand, Jiannis Ragoussis, Jiannis Ragoussis, Jiannis Ragoussis

“…Our results demonstrate the robustness of the ARTIC protocol and propose an improved method that could be useful for samples that routinely have limited SARS-CoV-2 RNA such as wastewater samples.…”
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Modern Bayesian Sampling Methods for Cosmological Inference: A Comparative Study by Denitsa Staicova

“…We present a comprehensive comparison of different Markov chain Monte Carlo (MCMC) sampling methods, evaluating their performance on both standard test problems and cosmological parameter estimation. …”
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