Performance of insulators under variation of pollution, inclined angle, and temperature based on the design of experiment by Ramy N.R. Ghaly, Sherif S.M. Ghoneim, Ali Ibrahim, Waldemar Ziomek, Prabhu Paramasivam, Hilmy Awad

“…The prediction error of the constructed equation was less than 5 % for a total number of 21 new data samples used to test and verify the robustness of the prediction equation.…”
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A Study of Determining Factors Influencing the Intention of Cryptocurrency Investors Using UTAUT 2 Approach by Ladia Puspanegara, Jono M. Munandar, Bagus Sartono

“…This study proposes the utilization of UTAUT 2 due to its robustness and enhanced explanatory capability compared to the original UTAUT model. …”
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Study of COVID-19 cases with real data analysis by Wedad Albalawi, Kottakkaran Sooppy Nisar, Nadir Omer, Adnan Aslam, Takasar Hussain, Muhammad Ozair, Shahid Hussain, Nida Hameed

“…After the calculation of reproduction number, global stability of disease free equilibrium is proved using Lyapunov function theory where as graph theoretic approach is utilized to discuss the ultimate behavior of infection present constant level. Moreover, robustness of the model has been verified by applying it on the real data of COVID-19. …”
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Investigation of the Effect of Integrated Offset, GPS, and InSAR Data in the Stochastic Source Modeling of the 2002 Denali Earthquake by Parva Shoaeifar, Katsuichiro Goda

“…Overall, based on the case study of the 2002 Denali earthquake, the combined use of all available datasets increases the robustness of the stochastic source modeling method in characterizing surface displacement. …”
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Perimeter-Area Soil Carbon Index (PASCI): modeling and estimating soil organic carbon using relevant explicatory waveband variables in machine learning environment by Eric Ariel L. Salas, Sakthi Subburayalu Kumaran

“…To help fill this gap, we developed the Perimeter-Area Soil Carbon Index (PASCI) that utilized optimal SOC spectral bands and then evaluated its robustness for SOC prediction and retrieval against other existing indices. …”
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Predictive modeling of soil profiles for precision agriculture: a case study in safflower cultivation environments by Megha Sharma, Shailendra Goel, Ani A. Elias

“…We collected soil from representative target environments (TE) of safflower cultivation and evaluated 14 soil physio-chemical features for constructing fine-resolution maps. The robustness, versatility, and predictive ability of two statistical learning models in correctly classifying the soil profile to clusters were tested. …”
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A Wavelet-Based Correlation Analysis Framework to Study Cerebromuscular Activity in Essential Tremor by Yifan Zhao, Ramon C. Laguna, Yitian Zhao, Jimmy Jiang Liu, Xiongxiong He, John Yianni, Ptolemaios G. Sarrigiannis

“…Results from both simulation and real data demonstrate the feasibility and robustness of the proposed framework. Significance. …”
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The dynamics of disposition: introducing a new scale for evaluating middle school attitudes towards blended learning by Merve Polat, Benay Yalçın Türkyılmaz

“…The scale demonstrated excellent statistical robustness, evidenced by a Kaiser-Meyer-Olkin value of .943 and a significant Bartlett's test of sphericity. …”
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Estimation of Sound Speed Profiles Using a Random Forest Model with Satellite Surface Observations by Zhenyi Ou, Ke Qu, Chen Liu

“…Sound speed profile (SSP) inversion is usually performed by linear statistical regression, such as the single empirical orthogonal function regression (sEOF-r) model. …”
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Utilization of deep learning in ideological and political education by Cai Sulong

“…The self-attention mechanism was applied to dynamically learn and distinguish the importance of different parts in the input sequence, better weighting key features such as student learning behavior and participation level, thereby enhancing the accuracy and robustness of effectiveness evaluation. Finally, the splicing method was adopted to integrate the LSTM model and self-attention mechanism for the experiment, and the teaching efficiency of different teaching methods was statistically analyzed through a questionnaire survey. …”
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Delay-sensitive traffic intellisense scheduling based on optimal decision tree by Xuerong WANG, Zhengzhi TANG, Yinchuan LI, Meiyu QI, Jianbo ZHU, Liang ZHANG

“…Currently, network traffic scheduling strategy cannot be intelligent and on-demand, especially in the congestion caused by sudden network failures and escort scenarios of high-value services.They cannot guarantee latency-sensitive service experience on demand.The delay-sensitive attribute requirements of different network traffic were analyzed and studied, and the internal correlation between the behavior characteristics of varying network traffic and its delay sensitivity requirements was explored.Then, AI technology was used to learn this inherent relationship and construct its mapping relationship, realizing a traffic scheduling technical solution based on the intelligent awareness of delay-sensitive traffic.At the same time, considering the practical issues of interpretability and deploy-ability of AI models, reinforcement learning (RL) technology was used to prune and optimize the interpretable decision tree model, which improved the robustness of the model and made model lighter and easier to implement in equipment deployment.Through experiments by the collected real network traffic, the decision tree model optimized by reinforcement learning could improve the awareness accuracy by 1.75% in a single inference case, and the inference performance was improved by about 30%.The experiment also proved that using micro-statistical features for multiple inferences could help improve the model accuracy; in all experiments, the scale of the decision tree model optimized by RL was reduced by about 60.0%～87.2%, and the Saras had better optimization performance than Q-learning.…”
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Big data tax collection and management, enterprise financialization and enterprise innovation: Quasi-natural test evidence based on the "Golden Tax Phase III". by Deliang Zhou, Zexuan Zhang

“…In this study, the quasi-natural test environment provided by the "Golden Tax Phase III" policy launched in 2013 and the method of propensity score matching and differentiation (PSM-DID) were used on combination of the samples of A-share listed enterprises in Shanghai and Shenzhen during 2010-2021 to analyze and demonstrate the impact of this policy on the innovation of the listed enterprises. To ensure the robustness of these findings, various statistical techniques such as parallel trend tests, placebo tests, and the explained variable replacement were employed. …”
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Differential Evolution Algorithm Combined with Uncertainty Handling Techniques for Stochastic Reentrant Job Shop Scheduling Problem by Rong Hu, Xing Wu, Bin Qian, Jianlin Mao, Huaiping Jin

“…Finally, the test results and comparisons manifest the effectiveness and robustness of the proposed DEA_UHT.…”
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Cannabis consumption and risk of asthma: a systematic review and meta-analysis by Ajay Malvi, Mahalaqua Nazli Khatib, Ashok Kumar Balaraman, R. Roopashree, Mandeep Kaur, Manish Srivastava, Amit Barwal, G. V. Siva Prasad, Pranchal Rajput, Rukshar Syed, Gajendra Sharma, Sunil Kumar, Mahendra Pratap Singh, Ganesh Bushi, Nagavalli Chilakam, Sakshi Pandey, Manvinder Brar, Rachana Mehta, Sanjit Sah, Abhay M. Gaidhane, Muhammed Shabil, Afukonyo Shidoiku Daniel

“…Data synthesis employed a random-effects meta-analysis to account for heterogeneity. R statistical software (version 4.4) was used for statistical analyses. …”
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Systemic doxycycline as an adjunct to nonsurgical periodontal therapy in diabetic patients with periodontitis: a systematic review and meta-analysis by Zheng Zhang, Zheng Zhang, Zhenyu Zhang, Guoquan Zhang

“…Heterogeneity was assessed using the Q test and the I2 statistic. Evaluation of publication bias was conducted using Egger’s and Begg’s tests.ResultsA total of 12 articles were included for meta-analysis. …”
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Nonlinear mixed models and related approaches in infectious disease modeling: A systematic and critical review by Olaiya Mathilde Adéoti, Schadrac Agbla, Aliou Diop, Romain Glèlè Kakaï

“…Nonlinear mixed effects models (NLMMs) constitute a specific statistical tool that can overcome these significant challenges. …”
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Direction Of Arrival Estimation in the Presence of Imperfect Waveforms for Multiple Targets in MIMO Radar by Sadiq Akbar, Fawad Zaman, Rizwan Ullah, Noor Gul, Ahmad Bala Alhassan, Gridsada Phanomchoeng

“…The deviation in MSE from the desired value is controlled through a penalty function which is the difference between the desired and actual responses of the system. A rigorous statistical analysis based on Monte Carlo simulations is carried out to validate the effectiveness of the proposed algorithm through histogram plots, box plots, Cumulative Distribution Function (CDF) plots, RMSE, robustness against noise, and estimation accuracy. …”
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Brain MRI Segmentation with Multiphase Minimal Partitioning: A Comparative Study by Elsa D. Angelini, Ting Song, Brett D. Mensh, Andrew F. Laine

“…This random initialization ensures robustness of the method with respect to the initialization and the minimization set up. …”
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Mesospheric tide comparisons at low latitudes observed by two collocated meteor radars by Jian Li, Wen Yi, XiangHui Xue, Jie Zeng, HaiLun Ye, JianYuan Wang, JinSong Chen, Na Li, TingDi Chen

“…Results of the comparative analysis specifically underscore the significant correlation in vertical wavelength measurements, validating the robustness of radar observations for tidal research.…”
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Association between tumour somatic mutations and venous thromboembolism in the 100,000 Genomes Project cancer cohort: a study protocol [version 2; peer review: 2 approved] by Naomi Cornish, Matthew T. Warkentin, Sarah K. Westbury, Andrew D. Mumford, Chrissie Thirlwell, Philip C. Haycock

“…Sensitivity analyses will be performed to examine the robustness of any associations, including adjustment for potentially correlated co-variates: tumour type, stage and systemic anti-cancer therapy. …”
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