Non-complete mappings characteristics of RSA by XU Jie-l? XU Han-liang, HUANG Hong-mei, LV Shu-wang

“…On the basis of the complete mappings concept, this paper gives difference value characteristics between image and inverse image of random permutation. Through giving lower bound of the number of some same difference value between image and inverse image, it is proved that RSA encryption function is not a complete mappings. …”
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Topology control based on dynamic graph embedding in Internet of vehicles by Yanfei SUN, Jiazheng YIN, Jin QI, Xiaoxuan HU, Mengting CHEN, Zhenjiang DONG

“…Finally, based on the application environment of the IoV, the LRGE method was used to perform random walk among vehicle nodes, and then the established random walk was optimized according to the LRGE model to determine the adjacency matrix. …”
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The clinical prediction model to distinguish between colonization and infection by Klebsiella pneumoniae by Xiaoyu Zhang, Xifan Zhang, Deng Zhang, Jing Xu, Jingping Zhang, Xin Zhang

“…Six predictive models were constructed using 15 key influencing factors, including Classification and Regression Trees (CART), C5.0, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), Random Forest (RF), and Nomogram. The Random Forest model performed best among all indicators (accuracy 0.93, precision 0.98, Brier Score 0.06, recall 0.72, F1 Score 0.83, AUC 0.99). …”
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Probable Relationship between COVID-19, Pollutants and Meteorology: A Case Study at Santiago, Chile by Giovanni A. Salini, Patricio R. Pacheco, Eduardo Mera, María C. Parodi

“…Finally, the correlation dimension was less than 5, revealing that new time-series constructed are not random.…”
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Monitoring Soil Salinity in Arid Areas of Northern Xinjiang Using Multi-Source Satellite Data: A Trusted Deep Learning Framework by Mengli Zhang, Xianglong Fan, Pan Gao, Li Guo, Xuanrong Huang, Xiuwen Gao, Jinpeng Pang, Fei Tan

“…The study applied four types of feature selection algorithms: Random Forest (RF), Competitive Adaptive Reweighted Sampling (CARS), Uninformative Variable Elimination (UVE), and Successive Projections Algorithm (SPA). …”
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Identifikasi dan Penentuan Kadar Boraks dalam Lontong yang Dijual di Pasar Raya Padang by Rizki Amelia, Endrinaldi ., Zulkarnain Edward

“…The identification and determination of borax on 10 samples of lontong taken by random. The method used is titration method using a standard solution of NaOH. …”
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Decentralized Frequency Regulation by Using Novel PID Sliding Mode Structure in Multi-Area Power Systems With Hydropower Turbines by Dao Trong Tran, Anh-Tuan Tran, van van Huynh, Ton Duc do

“…Despite the presence of parameter variations and random load conditions, the control objectives remain achievable, highlighting the robustness of the proposed method. …”
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STI/HIV risk prediction model development—A novel use of public data to forecast STIs/HIV risk for men who have sex with men by Xiaopeng Ji, Zhaohui Tang, Sonya R. Osborne, Thi Phuoc Van Nguyen, Amy B. Mullens, Judith A. Dean, Yan Li

“…The experimental results of these models demonstrate that the Random Forest algorithm yields the best results on HIV prediction, whereby the highest accuracy, and AUC are 0.99 and 0.99, respectively. …”
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Investigation of alpha-glucosidase inhibition activity of Artabotrys sumatranus leaf extract using metabolomics, machine learning and molecular docking analysis. by Dela Rosa, Berna Elya, Muhammad Hanafi, Alfi Khatib, Eka Budiarto, Syamsu Nur, Muhammad Imam Surya

“…After performance comparisons with other machine learning methods, random forest was chosen to make predictive model for the activity of the extract samples. …”
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Effects of Central Cut Width on the Dynamical Characteristics of Box Assembly Structure by Christopher Padilla, Antonio Flores, Ezekiel Granillo, Jonah Madrid, Abdessattar Abdelkefi

“…This trend did not continue, though, in the random and harmonic testing, possibly due to the added stiffness of the test setup with the slip table and stinger. …”
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Evaluation of the Effectiveness of Multiple Machine Learning Methods in Remote Sensing Quantitative Retrieval of Suspended Matter Concentrations: A Case Study of Nansi Lake in Nort... by Xiuyu Liu, Zhen Zhang, Tao Jiang, Xuehua Li, Yanyi Li

“…Then, seven methods such as linear regression, BP neural network (BP), KNN, random forest (RF), and random forest based on genetic algorithm optimization (GA_RF) are used to construct the inversion model of TSM concentration. …”
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Comparison of Satellite-based PM2.5 Estimation from Aerosol Optical Depth and Top-of-atmosphere Reflectance by Heming Bai, Zhi Zheng, Yuanpeng Zhang, He Huang, Li Wang

“…For both reflectance-based and AOD-based approaches, our cross validated results show that random forest algorithm achieves the best performance, with a coefficient of determination (R2) of 0.75 and root-mean-square error (RMSE) of 18.71 µg m−3 for the former and R2 = 0.65 and RMSE = 15.69 µg m−3 for the later. …”
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Fair Business Leadership: Is Protecting Minority Investors Important to the Development of Start-Ups in Clean and Digital Energy? by Dmytro Halynskyi, Oleksandr Telizhenko

“…With panel data from 19 countries over 7 years, this research applies three econometric models – the pooling model, fixed effects model, and random effects model – to capture the influence of investor protection on start-up growth while accounting for country- and time-specific variations. …”
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Multimodal consumer choice prediction using EEG signals and eye tracking by Syed Muhammad Usman, Shehzad Khalid, Aimen Tanveer, Ali Shariq Imran, Muhammad Zubair

“…Multimodal feature space representation was generated by performing feature-level fusion for EEG and ET, which was later fed into a meta-learner-based ensemble classifier with three base classifiers, including Random Forest, Extended Gradient Boosting, and Gradient Boosting, and Random Forest as the meta-classifier, to perform classification between buy vs. not buy. …”
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SYNTHESIS OF DESIGN PARAMETERS OF MULTI-PURPOSE DYNAMIC SYSTEMS by Oleksandr Kutsenko, Mykhailo Alforov, Andrii Alforov

“…As a special case, the problem of multi-objective optimization of a linear system according to an integral quadratic criterion with a given random distribution of initial deviations is considered. …”
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Performance modulations phase-locked to action depend on internal state by Tommaso Tosato, Guillaume Dumas, Gustavo Rohenkohl, Pascal Fries

“…These effects were significant in random effects tests, suggesting that they generalize to the population. …”
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The Impact of Critical Listening and Critical Reading on Critical Thinking by Yasemin Baki

“…The study group of this study was determined through simple random sampling, one of the random sampling methods. …”
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Testing Phylogenetic Placement Accuracy of DNA Barcode Sequences on a Fish Backbone Tree: Implications of Backbone Tree Completeness and Species Representation by M. A. Thanuja M. Fernando, Jinzhong Fu, Sarah J. Adamowicz

“…Additionally, stratified sampling outperforms random sampling in most cases, and biased sampling has the worst performance. …”
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Current prevalence and determinants of generalized anxiety disorder from a nationally representative, population-based survey of India by Pavithra Jayasankar, Satish Suhas, Lakshmi P. Nirisha, Sharad Philip, Narayana Manjunatha, Girish N. Rao, Gopalkrishna Gururaj, Mathew Varghese, Vivek Benegal, NMHS National Collaborators Group

“…NMHS is a multi-stage, stratified, random cluster sampling with random selection based on probability proportional to size at each stage. …”
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A two-step machine learning approach for predictive maintenance and anomaly detection in environmental sensor systems by Saiprasad Potharaju, Ravi Kumar Tirandasu, Swapnali N. Tambe, Devyani Bhamare Jadhav, Dudla Anil Kumar, Shanmuk Srinivas Amiripalli

“…The models confirmed the proposed framework's accuracy, whereas Random Forest 99.93 %, Neural Network 99.05 %, and AdaBoost 98.04 % validated the effectiveness of the suggested framework. …”
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