Tachyon: Enhancing stacked models using Bayesian optimization for intrusion detection using different sampling approaches by T. Anitha Kumari, Sanket Mishra

“…To create a balanced dataset, a range of sampling techniques were used, including Oversampling, Undersampling, Synthetic Minority Oversampling Technique (SMOTE), Random Oversampling Examples (ROSE), Borderline Synthetic Minority Oversampling Technique (b-SMOTE), and Adaptive Synthetic (ADASYN). …”
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Aerial vertical‐looking infrared imagery to evaluate bias of distance sampling techniques for white‐tailed deer by Jared T. Beaver, Craig A. Harper, Robert E. Kissell Jr., Lisa I. Muller, Peyton S. Basinger, Matthew J. Goode, Frank T. Van Manen, Wes Winton, Michael L. Kennedy

“…Aerial vertical‐looking infrared imaging (aerial imaging) is not restricted to roads and therefore enables random sampling and detection. We compared estimates of population density and precision, and evaluated potential sources of bias for these 3 techniques for deer on Arnold Air Force Base in Tennessee, USA, during January–February 2010. …”
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Efficiency comparison of maximum likelihood estimation in log–logistic distribution using median ranked set sampling

“…The derived estimators based on MRSS are compared with conventional estimators in simple random sampling (SRS) and ranked set sampling (RSS), evaluating biases, mean squared errors, and relative efficiencies across various set and cycle sizes. …”
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Parameter estimation in the Farlie–Gumbel–Morgenstern bivariate Bilal distribution via multistage ranked set sampling by S. P. Arun, M. R. Irshad, R. Maya, Amer I. Al-Omari, Shokrya S. Alshqaq

“…Ranked set sampling is a well-known and efficient method compared to simple random sampling for estimating population parameters. …”
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Enhanced Estimation of the Unit Lindley Distribution Parameter via Ranked Set Sampling with Real-Data Application by Sid Ahmed Benchiha, Amer Ibrahim Al-Omari, Ghadah Alomani

“…This paper investigates various estimation methods for the parameters of the unit Lindley distribution (U-LD) under both ranked set sampling (RSS) and simple random sampling (SRS) designs. …”
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Mathematical modelling for vaccine efficacy trials during the future epidemics of emerging respiratory infections by Soyoung Kim, Sun Hee Park, Sunhwa Choi, Wanho Lee, Suein Choi, Sungpil Han, Seunghoon Han, Dong-Gun Lee

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Predictors of stress among nucleic acid sampling support nurses (NASSNs) during the COVID-19 pandemic by Ping Feng, Liyan Gu, Xiaoying Lu, Min Hu, Yanqiu Weng, Wenyao Chen

“…Material and methods Totally 388 NASSNs were recruited through cluster random sampling for the research. An online cross-sectional survey with structured questionnaires was used, including socio-demographic information, the stressor scale of nucleic acid sampling nurses (SSNASN), and the challenge–hindrance stress scale (CHSS). …”
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A Novel Strategy Coupling Optimised Sampling with Heterogeneous Ensemble Machine-Learning to Predict Landslide Susceptibility by Yongxing Lu, Honggen Xu, Can Wang, Guanxi Yan, Zhitao Huo, Zuwu Peng, Bo Liu, Chong Xu

“…Current methods rely on artificial prior knowledge to obtain negative samples from landslide-free regions or outside the landslide buffer zones randomly and quickly but often ignore the reliability of non-landslide samples, which will pose a serious risk of including potential landslides and lead to erroneous outcomes in training data. …”
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Spatial Distribution of Acromyrmex balzani (Emery) (Hymenoptera: Formicidae: Attini) Nests Using Two Sampling Methods by Leandro Sousa-Souto, Arleu Barbosa Viana Junior, Eduardo Silva Nascimento

“…Among the methods to describe the SD of sessile organisms, sampling by way of plots and transects are widely used. …”
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Faster Convergence With Less Communication: Broadcast-Based Subgraph Sampling for Decentralized Learning Over Wireless Networks by Daniel Perez Herrera, Zheng Chen, Erik G. Larsson

“…In each consensus iteration, one mixing matrix is randomly sampled, leading to a specific scheduling decision that activates multiple collision-free subsets of nodes. …”
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Comparing the Effectiveness of Local Heat and Foot Massage in Reducing the Pain Caused by Heel Blood Sampling in Neonates by Reyhaneh Barzegari, Seyed Hamid Seyed Bagheri, Hassan Khodadadi, Tabandeh Sadeghi

“…Neonates were selected through convenience sampling and randomly assigned to one of three groups: foot massage, local heat, or control. …”
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Optimizing Tongue Fluid Sampling and Testing Protocols for Enhanced PRRSV Isolation from Perinatal Swine Mortalities by Onyekachukwu Henry Osemeke, Isadora Machado, Elisa De Conti, Mariah Musskopf, Mafalda Pedro Mil-Homens, Samuel Stutzman, Baoqing Guo, Thomas Petznick, Gustavo De-Sousa-E Silva, Phillip Gauger, Jianqiang Zhang, Daniel C. L. Linhares

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A dissimilarity-adaptive cross-validation method for evaluating geospatial machine learning predictions with clustered samples by Yanwen Wang, Mahdi Khodadadzadeh, Raúl Zurita-Milla

“…DA-CV categorizes the prediction locations as “similar” and “different” groups according to the dissimilarity between their covariates and those of the sampled locations. DA-CV applies random CV to evaluate “similar” locations and spatial CV to evaluate “different” ones. …”
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Statistical Inference of Reliability Parameter for the Skew-Normal Distribution under Progressive Type-II Censored Samples by Salman Babayi, Mohammad Seidpisheh, Gholamhossein Gholami

“…This study investigates the inference of the reliability parameter R=PY<X for the skew-normal distribution based on progressively Type-II censored samples, where Y and X are two independent random variables. …”
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Impact of COVID-19 Vaccine on Hearing Status of Young Ages (Medical College Students as a Sample) by Mazin Kamil Hamid

“…A case-control analytic study was performed on a connivance sample of society of university students from a medical faculty. …”
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Prediction of water inrush from coal seam floor based on machine learning with small sample data by Chenxi LI, Haifeng LU

“…The influence rule of sample number on prediction accuracy was discussed, and the comparison study was conducted with the commonly used particle swarm, support vector machine, BP neural network, random forest and convolutional neural network. …”
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Study on a DFB Laser Diode Based on Sampled Grating Technique for Suppression of the Zeroth Order Resonance by Lianyan Li, Yuechun Shi, Yunshan Zhang, Hui Zou, Jianping Shen, Xiangfei Chen

“…The facet reflection can also be reduced due to the tilted waveguide to avoid the influence of random facet phase. As a result, good single longitudinal mode (SLM) property and high wavelength accuracy in the <inline-formula><tex-math notation="LaTeX">$ - 1{\rm{st}}$</tex-math></inline-formula>-order subgrating is achieved, even with a large sampling period. …”
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Design of an Efficient Model for Psychological Disease Analysis and Prediction Using Machine Learning and Genomic Data Samples by Alparthi Kumuda, Saroj Kumar Panigrahy

“…Therefore, this study developed the Psychological Disorders Machine Learning Genomic (PDMLG) model as an amalgamation of genetic algorithms and machine learning techniques in a predictive analysis model using genomic data samples. The two central components of the PDMLG model include the Genomic Fusion Model, which uses ensemble learning techniques like Random Forest, Gradient Boosting, and Neural Networks, and Deep Learning Model of Convolutional and Recurrent Neural Networks in processing genomic sequence data samples. …”
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Intimate partner violence and physical health in England: Gender stratified analyses of a probability sample survey by Ladan Hashemi, Anastasia Fadeeva, Nadia Khan, Sally McManus

“…Design: We used data from the 2014 Adult Psychiatric Morbidity Survey, a cross-sectional survey using a stratified, multistage random sampling design to cover the household population of England aged 16 years and older. …”
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Clinical metabolomics reveals potential diagnostic biomarkers in serum samples from patients with generalized ligamentous laxity by Yu Zhang, Yu Zhang, Xiaochao Hu, Feng Chen, Tongtong Liu, Ping Cai, Shijia Liu, Luning Sun

“…The present work aimed to determine serum biomarkers for GLL diagnosis and to unveil metabolic pathways linked to GLL.DesignProspective, observational cohort study.MethodsIn this study, serum sample collection was conducted from 65 GLL and 35 healthy control (HC) cases. …”
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