Research on Chinese Stock Market during COVID-19—Based on Random Matrix Theory by Wu Yaojie, Fang Tianhui

“…The specific market performance is that the stock price fluctuations show a high degree of consistency. (4) In the sample interval, the financial industry has a restraining effect on the consumption industry in the short term, and the pharmaceutical industry has a promoting and then restraining effect on the consumption industry in the short term. …”
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Assessment of spatial autocorrelation and scalability in fine-scale wildfire random forest prediction models by Madeleine Pascolini-Campbell, Joshua B. Fisher, Kerry Cawse-Nicholson, Christine M. Lee, Natasha Stavros

“…Machine learning methods such as random forests provide an empirical framework that are high-accuracy, computationally efficient, interpretable and able to model complex ecological relationships. …”
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Measurement-Induced Entanglement and Complexity in Random Constant-Depth 2D Quantum Circuits by Max McGinley, Wen Wei Ho, Daniel Malz

“…Our findings have consequences for the complexity of classically simulating sampling from random shallow circuits and of contracting tensor networks. …”
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Conditional Density Kernel Estimation Under Random Censorship for Functional Weak Dependence Data by Hamza Daoudi, Abderrahmane Belguerna, Zouaoui Chikr Elmezouar, Fatimah Alshahrani

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Implementation of SMOTE to Improve the Performance of Random Forest Classification in Credit Risk Assessment in Banking by Nafa Nur Adifia Nanda, Yuniar Farida, Wika Dianita Utami

“…Methods: This study uses the Random Forest technique to categorize credit risk evaluation. …”
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IMPACT OF FEATURE SELECTION ON DECISION TREE AND RANDOM FOREST FOR CLASSIFYING STUDENT STUDY SUCCESS by Firdaus Amruzain Satiranandi Wibowo, Heri Retnawati, Muhammad Lintang Damar Sakti, Asma Khoirunnisa, Angella Ananta Batubara, Miftah Okta Berlian, Zulfa Safina Ibrahim, Jailani Jailani, Sumaryanto Sumaryanto, Lantip Diat Prasojo

“…To address data imbalance, Synthetic Minority Over-sampling Technique (SMOTE) was applied, improving the representation of underrepresented classes. …”
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DSLE2 random-effects meta-analysis model for high-throughput methylation data by Nan Wang, Yang Zhou, Fengping Zhu, Shuilin Jin

“…Meta-analysis can quantitatively combine high-throughput sequencing data from the the same topic. It increases the sample size for data analysis, enhances statistical power, and results in more consistent and reliable conclusions. …”
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Random shear resistance of a headed-stud connector in composite steel-concrete beam by Tomasz Domański, Mariusz Maślak

“…If, however, both combined strengths are treated as the random variables and a statistically homogeneous sample grouping potentially possible implementations of this type is taken into account, then the design resistance PR;d = [min (PRs, PRc )]d, representative for the verification of ultimate limit state for the considered connection, will be quantitatively different from the value PR,d = [min (PRs,d, PRc,d ) recommended for use in this regard in the standard EN 1994-1-1. …”
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Random vibration study of cold rolling mill excited by different morphology of strip surface by Sun Weiquan, Yan Xiaoqiang, Wang Shen, Xuan Lijian, Yun Weijing, Chen Yuchen

“…The 3D scanning equipment was used to collect the surface morphology of the slab and the height data of the vibration marks on the surface of the slab were obtained by reverse engineering, and the random function Gaussian distribution method was used to regress the surface morphology of the continuous casting slab, and the sample collection of different morphologies of the strip surface was realized. …”
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Regulatory enforcement and corporate ESG performance: evidence from the random inspection system in China by Jiabao Fei, Ming Zhang, Kun Xiao, Wahid Ullah, Jianghan Wang

“…Taking A-share listed non-financial firms from 2009 to 2022 as a sample, we investigate the impact of this system on corporate ESG performance using a staggered difference-in-differences model. …”
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Random capillary blood glucose in the diagnosis of diabetes: a cross-sectional study in Bangladesh by Hajera Mahtab, Md Faruque Pathan, Md Robed Amin, Tasnima Siddiquee, Bishwajit Bhowmik, Sanjida Binte Munir, Shaila Parvin, Tareen Ahmed, Faria Afsana, Nazmul Kabir Qureshi, Ahmed Salam Mir, Rubayat Islam, Md Sarowar Uddin Milon, Rahat Iqbal Chowdhury, Rie Ozaki, Dulal Chandra Ray, Sumon Rahman Chowdhury, Sanjib Salah Aufi, Shamima Akhtar, Tamanna Afroz, Mohammad Abdus Samad, Abul Kalam Azad Khan

“…Objective To assess the effectiveness of random capillary blood glucose as a diagnostic tool for type 2 diabetes and determine optimal cut-off values for adults in Bangladesh.Design Cross-sectional diagnostic accuracy study.Setting 16 diabetes centres were selected randomly from all eight administrative divisions of Bangladesh.Participants A total of 3200 adults aged 18 years and older were recruited using systematic random sampling between May and September 2022.Primary and secondary outcome measures The primary outcome was the diagnostic accuracy of random capillary blood glucose compared to fasting plasma glucose, 2-hour plasma glucose after a 75-gram glucose load and glycated haemoglobin. …”
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Biomarkers and Mental Disorders: A Relevance Analysis Using a Random Forest Algorithm by Joice M. A. Rodolpho, Krissia F. Godoy, Bruna D. L. Fragelli, Jaqueline Bianchi, Fernanda O. Duarte, Luciana Camillo, Gustavo B. Silva, Paulo H. M. Andrade, Juliana A. Prado, Carlos Speglich, Fernanda F. Anibal

“…A single sample from each of the 96 participants was analyzed, consisting of 50 women and 46 men. …”
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Random vibration study of cold rolling mill excited by different hardness of strip steel by Weiquan Sun, Xiaoqiang Yan, Shen Wang, Lu Zhang, Weijing Yun, Yuchen Chen

“…This probabilistic characterization provided essential load input parameters (PSD data) for the cold rolling mill system’s finite element-based random vibration analysis. The established three-dimensional model was imported into ANSYS Workbench software to construct the framework for the random vibration analysis. …”
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Random PCR and ultracentrifugation increases sensitivity and throughput of VIDISCA for screening of pathogens in clinical specimens by Le Van Tan, H. Rogier van Doorn, Lia van der Hoek, Vo Minh Hien, Maarten F. Jebbink, Do Quang Ha, Jeremy Farrar, Nguyen Van Vinh Chau, Menno D. de Jong

“…Results: We showed that rPCR enhanced the sensitivity of VIDISCA by 100-fold for two out of four viruses in different clinical samples, and that the ultracentrifugation step allowed for analyzing samples of large volumes (4 ml) and simultaneous processing of multiple (~40) clinical specimens. …”
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Perbandingan Kinerja Naïve Bayes dan Random Forest dalam Mendeteksi Berita Palsu by William William, Teny Handhayani

“…The news samples are represented by four features: title, news content, subject, and news date. …”
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A novel multi-label classification algorithm based on -nearest neighbor and random walk by Zhen-Wu Wang, Si-Kai Wang, Ben-Ting Wan, William Wei Song

“…This method constructs the vertices set of a random walk graph for the K -nearest neighbor training samples of certain test data and the edge set of correlations among labels of the training samples, thus considerably reducing the overhead of time and space. …”
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Statistical Distributions of Genome Assemblies Reveal Random Effects in Ancient Viral DNA Reconstructions by Fernando Antoneli, Cristina M. Peter, Marcelo R. S. Briones

“…Ancient human viruses have been detected in ancient DNA (aDNA) samples of both Anatomically Modern Humans and Neanderthals. …”
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A Copula Based Approach for Design of Multivariate Random Forests for Drug Sensitivity Prediction. by Saad Haider, Raziur Rahman, Souparno Ghosh, Ranadip Pal

“…Ensemble based approaches such as Random Forests have been shown to perform well in both individual sensitivity prediction studies and team science based prediction challenges. …”
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A Discrete-Element-Based Approach to Generate Random Parameters for Soil Fatigue Models by Alessandro Tombari, Fedor Maksimov

“…Subsequently, variability in the initial particle size distribution functions is introduced to generate random soil samples, and triaxial simulations are repeated to quantify the dispersion of soil fatigue parameters. …”
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Estimation of Soil Cohesion Using Machine Learning Method: A Random Forest Approach by Hai-Bang Ly, Thuy-Anh Nguyen, Binh Thai Pham

“…In this study, machine learning models, namely, support vector machine (SVM), Gaussian regression process (GPR), and random forest (RF), were built based on a data set of 145 soil samples collected from the Da Nang-Quang Ngai expressway project, Vietnam. …”
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