Two-Sample Multivariate Test of Homogeneity by Ali S. Barakat

“…Consider the k • (n1+n2) possible ways of choosing one observation from the combined samples and then one of its k nearest neighbors, and let Sk be the proportion of these choices in which the point and neighbor are in the same sample. …”
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A Sampling of 10 Years of YAL by Terri Suico, Kathryn Caprino, Ann Marie Smith

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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

“…Therefore, the RSS estimators were more efficient than the SRS estimators.…”
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Does learning more about others impact liking them? Replication and extension Registered Report of Norton et al.’s (2007) lure of ambiguity by Zöe Horsham, Ashleigh Nicola Haydock-Symonds, Hirotaka Imada, Hiu Ching Tai, Wing Lam Lau, Tsz Lui Shum, Yuqing Zeng, Hiu Tung Kristy Chow, Gilad Feldman

“…., 2007, demonstrated a counterintuitive phenomenon that knowing other people better and/or having more information about them is associated with decreased liking. …”
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An Examination of Support for More Diverse Alcohol Warning Labels (AWLs) in Ireland by Frank Houghton, Jennifer Moran Stritch, Anne Campbell, Gillian Shorter

“…Additionally, there was considerable support for a broader range of AWLs. More than half of the respondents supported the introduction of bland packaging on alcohol containers, and over 60% supported the introduction of more explicit tobacco-style graphic warnings on alcohol. …”
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Attracting More Capital for Biodiversity Finance: The Case of Debt-for-Nature Instruments by Lauren Olsen, Frederic de Mariz

“…Can debt-for-nature instruments attract more capital for biodiversity finance? Debt-for-nature instruments first appeared in the market in the 1980s; however, they have seen a recent surge in popularity, with transactions predominantly focused on marine conservation. …”
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More than meets the eye: phenomenological insights into the functioning of people with lipoedema by Lise Maren Kloosterman, Renske Eilers, Aldo Scafoglieri, Ad Hendrickx, Rienk Dekker, Harriët Jager-Wittenaar

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Life Gets Even More Beautiful, During Extended 90 + Minutes by Engin Kocakarın

“…In this research, Frequencies Analysis chosen from statistical analyses, Paired Sample t-Test and Pearson Correlation Analysis were used. …”
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Somatic Comorbidity in Chronic Constipation: More Data from the GECCO Study by Paul Enck, Johannes Leinert, Menno Smid, Thorsten Köhler, Juliane Schwille-Kiuntke

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Aggregative Sampling Performs Similar to Composite Produce Samples to Recover Quality and Safety Indicators Throughout Romaine Lettuce Production by Jorge Quintanilla Portillo, Rachel J. Gathman, Jiaying Wu, Eric Wilhelmsen, Matthew J. Stasiewicz

“…Aggregative sampling using polymer cloth swabs is a nondestructive, potentially more representative food safety sampling alternative for leafy greens. …”
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SCREENING FOR ANTIBIOTIC RESISTANT BACTERIA IN URINE SAMPLES

“…Theresultsshowed that about 92% of the total isolates were related to the Enterobacteriacae group and more than 94% of these strains were resistant to two or more antibiotics simultaneously. …”
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Determination of hybrid rate of silkworm by sampling test by DING Nong, ZHONG Bo-xiong, TAO Jing-ya, YAO Yao-tao, SHEN Jian-hua

“…The technique of sampling test and DNA fingerprinting were employed to test the hybrid rate of silkworm (Bombyx mori). …”
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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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GRAIN QUALITY OF COLLECTION SAMPLES OF WINTER BARLEY by E. G. Filippov, A. A. Dontsova, D. P. Dontsov, A. A. Bulanova, N. G. Ignatieva

“…The purpose of the study was to determine biochemical and technological properties of grain that meet certain requirements to brewing barley varieties. 31.2% of the studied varieties have been found correspondent to the trait ‘protein content in kernels’ (GOST 5060-86 ‘Brewing barley’). 7.8% of the samples have more than 60% starch in kernels. 57% of the collection varieties possess high extractivity (more than 78%). 13% of the studied varieties have husk content of kernels that meet the brewing requirements. 88% of all varieties correspond the GOST 5060-86 requirements in the trait ‘1000-kernel weight’. 64% of the samples significantly exceed productivity of the standard variety. …”
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Approach-Induced Biases in Human Information Sampling. by Laurence T Hunt, Robb B Rutledge, W M Nishantha Malalasekera, Steven W Kennerley, Raymond J Dolan

“…One such behavior is sampling from options that will eventually be chosen, even when other sources of information are more pertinent for guiding future action.…”
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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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Air Monitoring: New Advances in Sampling and Detection by Nicola Watson, Stephen Davies, David Wevill

“…As the harmful effects of low-level exposure to hazardous organic air pollutants become more evident, there is constant pressure to improve the detection limits of indoor and ambient air monitoring methods, for example, by collecting larger air volumes and by optimising the sensitivity of the analytical detector. …”
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Etching Ceramic Samples with Fast Argon Atoms by Alexander S. Metel, Sergey N. Grigoriev, Marina A. Volosova, Yury A. Melnik, Enver S. Mustafaev

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Context-Aware Negative Sampling for Sequential Recommendation by Jinseok Seol, Jaesik Choi

“…Based on this observation, we propose two novel negative sampling methods: context-aware hard negative item sampling and negative context sampling. …”
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Discovering biological progression underlying microarray samples. by Peng Qiu, Andrew J Gentles, Sylvia K Plevritis

“…SPD assumes that individual samples of a microarray dataset are related by an unknown biological process (i.e., differentiation, development, cell cycle, disease progression), and that each sample represents one unknown point along the progression of that process. …”
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