Classifying the Mortality of People with Underlying Health Conditions Affected by COVID-19 Using Machine Learning Techniques by Rami Mustafa A. Mohammad, Malak Aljabri, Menna Aboulnour, Samiha Mirza, Ahmad Alshobaiki

“…The best performance was demonstrated by the Bagging algorithm with an accuracy of 83.55% when using all the dataset features. …”
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The global invasion risk of rice yellow stem borer Scirpophaga incertulas Walker (Lepidoptera:Crambidae) under current and future climate scenarios. by Shravani Sanyal, A V M Subba Rao, H Timmanna, G Baradevanal, Santanu Kumar Bal, M A Sarath Chandran, P R Shashank, V K Singh, P K Ghosh

“…The pest identity was confirmed with morphological taxonomy, and the possible habitat distribution and further spread in future climate scenarios were modelled using the MaxEnt algorithm. The climate niche for S. incertulas was also established by analyzing the correlation between the pest occurrence data of 143 locations in India and seven bioclimatic variables viz., bio01, bio02, bio03, bio05, bio12, bio13, and bio15, were chosen for predicting the distribution of S. incertulas. …”
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Constructing a web recommender system using web usage mining and user’s profiles by T. Mombeini, A. Harounabadi, J. Rezaeian Sheshdeh

“…Experiments show that the proposed method of predicting user recent requested pages has more accuracy and cover than other methods.…”
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Incorporation of Sub‐Resolution Porosity Into Two‐Phase Flow Models With a Multiscale Pore Network for Complex Microporous Rocks by Sajjad Foroughi, Branko Bijeljic, Ying Gao, Martin J. Blunt

“…We then show that our model can successfully predict steady‐state relative permeability measurements on a water‐wet Estaillades carbonate sample within the uncertainty of the experiments and modeling. …”
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Quantitative structure-activity relationship study of some angiotensin-converting enzyme inhibitor drugs in the treatment of hypertension based on Monte Carlo optimization method by Shahram Lotfi, Shahin Ahmadi, Ali Azimi

“…Materials & Methods: In this study, quantitative structure-activity relationship to predict the inhibitory activity of the data set containing 255 angiotensin-converting enzyme inhibitor compounds based on the algorithm Monte Carlo was studied. …”
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Spatial transcriptomics and scRNA-seq: decoding tumor complexity and constructing prognostic models in colorectal cancer by Wei Song, Yatao Wang, Min Zhou, Fengqin Guo, Yanliang Liu

“…We developed a 13-gene prognostic signature (PS) using machine learning algorithm (StepCox backward), which predicts the prognosis of CRC patients. …”
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Estimation of drought-induced forest decline of Scots pine in the Navarrese Pyrenees (Spain) by Marina Rodes-Blanco, Paloma Ruiz-Benito, Miguel A. Zavala, Inmaculada Aguado, Mariano García

“…Identifying and predicting areas affected by drought-induced forest decline using remote sensing is key for monitoring forest-responses to drought, as well as for forest conservation and management. …”
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Data Balancing Techniques Using the PCA-KMeans and ADASYN for Possible Stroke Disease Cases by Uung Ungkawa, Muhammad Avilla Rafi

“…This condition can cause the minority class prediction to be wrong because the model tends to predict the majority class. …”
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Variance exchange process: overcoming the problem of singular information matrices in quadratic three−variable response designs by Okim Ikpan, Felix Nwobi

“…For such matrices, the variances of predicted responses at variance points cannot be evaluated, and the variance exchange process, not possible. …”
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A robust, deep learning-based analysis of time-domain signals for NMR spectroscopy by Kyungdoe Han, Eunhee Kim, Kyoung-Seok Ryu, Donghan Lee

“…As a proof of concept, we present the resulting spectra, along with peak lists predicted by supplying only FID input to the deep learning algorithm. …”
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Methodological levels of research the post-industrial development of the city by Olha Suptelo

“…A detailed study of these processes makes it possible to predict the possible paths of developed countries and individual territories. …”
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Bioinformatics analysis of potential targets influencing the prognosis of OSCC by ZOU Xian, SONG Tao

“…The prognostic model based on SPP1 and ITGA3 genes can effectively predict the prognosis of OSCC patients. [Conclusion:] ITGA3 and SPP1 may be biomarkers for the prognosis of OSCC patients. …”
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The J-PLUS collaboration. Additive versus multiplicative systematics in surveys of the large scale structure of the Universe by Carlos Hernández-Monteagudo, G. Aricò, J. Chaves-Montero, L. R. Abramo, P. Arnalte-Mur, A. Hernán-Caballero, Francisco José Galindo-Guil, C. López-Sanjuan, V. Marra, R. von Marttens, E. Tempel, J. Cenarro, D. Cristóbal-Hornillos, A. Marín-Franch, M. Moles, J. Varela, H. Vázquez Ramió, J. Alcaniz, R. Dupke, A. Ederoclite, L. Sodré Jr., R. E. Angulo

“…This model allows us devising a novel algorithm that addresses the identification and correction for either additive and/or multiplicative contaminants. …”
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Forecasting dengue in Bangladesh using meteorological variables with a novel feature selection approach by Mahadee Al Mobin

“…The study concludes that relative humidity is redundant in predicting dengue infection, while meteorological factors exhibit more significant short-term impacts compared to long-term and immediate impacts. …”
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Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice by G. Colas, V. Masson, F. Bouttier, L. Bouilloud, L. Pavan, V. Karsisto

“…We have developed an ice content prediction to account for the freezing and melting of the water content on the surface. …”
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Intelligent Resource Allocation for Immersive VoD Multimedia in NG-EPON and B5G Converged Access Networks by Razat Kharga, AliAkbar Nikoukar, I-Shyan Hwang

“…The SDN framework manages the entire network, predicts bandwidth requirements, and operates the immersive media dynamic bandwidth allocation (IMS-DBA) algorithm to efficiently allocate bandwidth to IVoD network traffic, ensuring that QoS metrics are met for IM services. …”
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The balance between traffic control and economic development in tourist cities under the context of COVID-19: A case study of Xi'an, China. by Wang Xiang, Zezhi Wang, Xin Pan, Xiaobing Liu, Xuedong Yan, Li Chen

“…The results show that the Pearson correlation coefficient between the predicted data of this improved model and the actual data is 0.996, the R-square in the regression analysis is 0.993, with a significance level of below 0.001, suggesting that the predicted data of the model are more accurate. …”
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The impact of quantitative platform on candidacy for bronchoscopic lung volume reduction: a multi-center retrospective cohort study by Max Wayne, Suchitra Pilli, Hee Jae Choi, Nathaniel Moulton, Praveen Chenna, Allen Cole Burks, Alexander Chen

“…Results: A total of 83 patients referred for BLVR across three centers were included; patients were a median 67 years old, had a median post bronchodilator FEV1 of 30% predicted (IQR: 25, 38), a median residual volume of 220% predicted (IQR: 185, 268), and 29 (34.9%) received endobronchial valves. …”
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Microseismic Signals in Heading Face of Tengdong Coal Mine and Their Application for Rock Burst Monitoring by JianJu Ren, Wenlong Zhang, Zheng Wu, Ji Li, Ying Shen

“…Through trial operation, it is found that large energy (three-channel and four-channel triggering) coal vibration events successfully predicted a rock burst. The MS system of 117 track gateway of Tengdong coal mine should be able to remove the interference signals in real time through the algorithm and take the number of large energy coal vibration signal rather than all coal vibration events as the predictor for rock burst risk monitoring.…”
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Analysis of a nonsteroidal anti inflammatory drug solubility in green solvent via developing robust models based on machine learning technique by Lijie Jiang, Qi Li, Huiqing Liao, Hourong Liu, Bowen Tan

“…Abstract This study develops and evaluates advanced hybrid machine learning models—ADA-ARD (AdaBoost on ARD Regression), ADA-BRR (AdaBoost on Bayesian Ridge Regression), and ADA-GPR (AdaBoost on Gaussian Process Regression)—optimized via the Black Widow Optimization Algorithm (BWOA) to predict the density of supercritical carbon dioxide (SC-CO2) and the solubility of niflumic acid, critical for pharmaceutical processes. …”
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