Reliability Assessment of Steel-Concrete Composite Beams considering Metal Corrosion Effects by Trong-Ha Nguyen, Duy-Duan Nguyen

“…The effects of the random input variables on the reliability of structures are evaluated by sensitivity analyses, which are calculated by the global sensitivity analysis using Sobol’s method and Monte Carlo simulation. …”
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Composite Differential Search Algorithm by Bo Liu

“…Differential search algorithm (DS) is a relatively new evolutionary algorithm inspired by the Brownian-like random-walk movement which is used by an organism to migrate. …”
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Investigating the contributors to hit-and-run crashes using gradient boosting decision trees. by Baorui Han, Haibo Huang, Gen Li, Chenming Jiang, Zhen Yang, Zhenjun Zhu

“…Crash Report Sampling System (CRSS) dataset, the model is trained and compared with the state-of-art methods (Classification and Regression Tree, Random Forest, and Logistic Regression). The results show that the GBDT outperforms other methods, achieving the lowest negative log-likelihood (0.282), misclassification rate (0.096), and the highest AUC (0.803). …”
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Denoising Method Based on Spectral Subtraction in Time-Frequency Domain by Lei Hao, Shuai Cao, Pengfei Zhou, Lei Chen, Yi Zhang, Kai Li, Dongdong Xie, Yijun Geng

“…In addition, simulation tests were conducted by using different S/R, which indicates the effectiveness of the TF-SS in removing the random noise.…”
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Rotating antibiotics selects optimally against antibiotic resistance, in theory by Robert E. Beardmore, Rafael Peña-Miller

“…In contrast, previous theoretical studies addressing this question have demonstrated that routinely changing the drug of choice for a given pathogenic infection may in fact lead to a greater incidence of drug resistance in comparison to the random deployment of different drugs.   Using mathematical models that do not explicitly incorporate the spatial dynamics of pathogen transmission within the ICU or hospital and assuming the antibiotics are from distinct functional groups, we use a control theoretic-approach to prove that one can relax the medical notion of what constitutes an antibiotic rotation and so obtain protocols that are arbitrarily close to the optimum.Finally, we show that theoretical feedback control measures that rotate between different antibiotics motivated directly by the outcome of clinical studies can be deployed to good effect to reduce the prevalence of antibiotic resistance below what can be achieved with random antibiotic use.…”
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New method for file deduplication in cloud storage by Chao YANG, Qian JI, Si-chun XIONG, Mao-zhen LIU, Jian-feng MA, Qi JIANG, Lin BAI

“…Deduplication is widely used in cloud storage service to save bandwidth and storage resources,however,the security of client deduplication still flaws in an external attack to access a user’s private data.Xu-CDE,a deduplication solution of encrypting data for multi-client was first proposed,which could protect the privacy of data from the external attackers and honest but curious server,with favorable theoretical meaning and representativeness.However,in Xu-CDE,the user ownership authentication credentials were lack of instantaneity protection,which could not resist replay attack.As an improvement to the flaw,the protocol MRN-CDE (MLE based and random number modified client-side deduplication of encrypted data in cloud storage) was proposed,adding random number in order to ensure the instantaneity of the authentication credentials,and using the algorithm of MLE-K_Pto extract key from original file to replace the file itself as an encryption key.As a consequence,the new protocol improved security while significantly reduced the amount of computation.After the safety analysis and the actual tests,results show that based on Xu-CDE,the proposed protocol MRN-CDE has stronger security of ownership,and improves time efficiency.Specially,the new protocol works better on large files in cloud with a certain value.…”
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Influence of Excitation on Dynamic System Identification for a Multi-Span Reinforced Concrete Bridge by M. Alwash, B. F. Sparling, L. D. Wegner

“…Comparisons were made between the dynamic responses due to vehicle loading, harmonic and random forcing, impact, and environmental excitation. …”
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Simultaneous Pose and Correspondence Estimation Based on Genetic Algorithm by Haiwei Yang, Fei Wang, Zhe Li, Hang Dong

“…First, a set of random initial guesses is generated as candidate solutions. …”
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Participatory Budgeting and Financial Accountability in Kabale District Local Government by Perpetua, Arinaitwe

“…A cross-sectional research design, based on both quantitative and qualitative approaches was used to collect and analyze data. Simple random and purposive random sampling techniques were used to select 117 respondents from 174 subjects. …”
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Asymptotical investigation of extreme terms of the variational series by Algimantas Aksomaitis

“…The volume of the sample is random and normalization or nonlinear. …”
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Predictive model for abdominal liposuction volume in patients with obesity using machine learning in a longitudinal multi-center study in Korea by Hyunji Sang, Jaeyu Park, Soeun Kim, Myeongcheol Lee, Hojae Lee, Sun-Ho Lee, Dong Keon Yon, Sang Youl Rhee

“…Fifteen variables related to patient profiles were integrated and applied to various ML algorithms, including random forest, support vector, XGBoost, decision tree, and AdaBoost regressors. …”
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Risk Factors and Clinical Predictors of Suicidal Behaviors and Non-Suicidal Self-Injury Among Pediatric Psychiatry Emergency Admissions Pre- and Post-Pandemic: A Retrospective Coho... by Roxana Șipoș, Tudor Văidean, Elena Predescu

“…Logistic regression and random forest models were used to identify predictors of SB and NSSI. …”
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A machine learning framework for short-term prediction of chronic obstructive pulmonary disease exacerbations using personal air quality monitors and lifestyle data by M. Atzeni, G. Cappon, J. K. Quint, F. Kelly, B. Barratt, M. Vettoretti

“…The best performing models were Random Forest in cluster 1, with area under the receiver operating characteristic curve (AUC) of 0.90, and area under the precision/recall curve (AUPRC) of 0.7; and Random Forest model in cluster 2, with AUC of 0.82 and AUPRC of 0.56. …”
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Evaluating Sampling Designs to Survey Fish Diversity in Lakes From Northern Temperate Zones by Erik García‐Machado, Eric Normandeau, Guillaume Côté, Isabeau Caza‐Allard, Charles Babin, Louis Bernatchez

“…However, we found that, under certain circumstances, stratified sampling outperformed random sampling, requiring lower numbers of samples to detect the same species diversity. …”
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A Novel Model Using ML Techniques for Clinical Trial Design and Expedited Patient Onboarding Process by Iyer A, Narayanaswami S

“…Five ML models—XGBoost, Random Forest, Support Vector Classifier (SVC), Logistic Regression, and Decision Tree—were applied to both datasets, alongside Artificial Neural Networks (ANN) for the second dataset. …”
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Developing a decision support tool to predict delayed discharge from hospitals using machine learning by Mahsa Pahlevani, Enayat Rajabi, Majid Taghavi, Peter VanBerkel

“…Data imbalance was addressed using class weights, random oversampling, and the Synthetic Minority Over-Sampling Technique (SMOTE). …”
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Medicinal plants used to treat human ailments in Wadla District, Northern Ethiopia: An ethnobotanical approach by Sara Yosef, Ermias Lulekal, Asfaw Debela, Muhidin Tahir

“…Methods: The data were collected using a combination of sampling techniques, including strict random sampling, stratified random sampling, (for general informants) and snowball sampling, purposive and random sampling (for key informants). …”
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Prediction of Later-Age Concrete Compressive Strength Using Feedforward Neural Network by Thuy-Anh Nguyen, Hai-Bang Ly, Hai-Van Thi Mai, Van Quan Tran

“…The results also indicated that the FNN model was superior to classical machine learning algorithms such as random forest and Gaussian process regression, as well as empirical formulations proposed in the literature.…”
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