Heart abnormality classification using ECG and PCG recordings with novel PJM-DJRNN by Nadikatla Chandrasekhar, Sujatha Canavoy Narahari, Sreedhar Kollem, Samineni Peddakrishna, Archana Penchala, Babji Prasad Chapa

“…The proposed method involves noise removal from ECG and PCG signals separately using the Brownian Functional-based BesseL Filter (BrF-BLF) and Frequency Ratio-based Butterworth Filter (FR-BWF), decomposition of the signals using Hamming-based Ensemble Empirical Mode Decomposition (HEEMD), and clustering of the signals as normal and abnormal using Root Farthest First Clustering (RFFC). …”
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The Ripple Effect of Climate Change: Assessing the Impacts on Water Quality and Hydrology in Addis Ababa City (Akaki Catchment) by Thandile T. Gule, Binyam Tesfaw Hailu, Brook Lemma

“…This was performed using the soil and water assessment tool (SWAT) model and an ensemble of four global climate models under two Shared Socioeconomic Pathways (SSP) emission scenarios from Coupled Model Intercomparison Project Phase 6 (CMIP6). …”
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Are women leaders significantly better at controlling the contagion during the COVID-19 pandemic? by Maxwell SALVATORE, Bhramar MUKHERJEE

“…The aim of this paper is to examine an ensemble of public he- alth metrics to assess the control of COVID-19 epidemic in women- versus men-led countries worldwide based on data available up to June 3. …”
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Prediction of Current and Future Distributions of Chalcophora detrita (Coleoptera: Buprestidae) Under Climate Change Scenarios by Arif Duyar, Muhammed Arif Demir, Mahmut Kabalak

“…This species of both saproxylic and economic importance, was modelled under current environmental conditions, climate change scenarios and possible future conditions by ecological niche modelling (ENM). An ensemble model was created by using 11 different algorithms (Artificial Neural Network, Classification Tree Analysis, eXtreme Gradient Boosting, Flexible Discriminant Analysis, Generalised Additive Model, Generalised Boosting Model, Generalised Linear Model, Multivariate Adaptive Regression Splines, Maximum Entropy, Random Forest, Surface Range Envelope) to predict the potential suitable habitats of C. detrita. …”
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Prediction of Visual Acuity after anti-VEGF Therapy in Diabetic Macular Edema by Machine Learning by Ying Zhang, Fabao Xu, Zhenzhe Lin, Jiawei Wang, Chao Huang, Min Wei, Weibin Zhai, Jianqiao Li

“…The VA predicted by machine learning was compared with the ground truth. Results. The ensemble algorithm (linear regression + random forest regressor) performed best in VA and VA variance predictions. …”
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A propos de l'extension complète des doigts longs et des 4 derniers orteils des primates by J Norbert Kuhlmann

“…Rappel de la morphologie de l'ensemble de ces muscles et exposé des mécanismes qui permettent une action combinée réalisant l'extension complète des phalanges grâce à la mise en tension des bandelettes collatérales. …”
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Un outil éthique, automatisé et totalement autonome pour étudier la cognition chez les primates by Jonas Fizet, Adam Rimele, Thierry Pebayle, Jean Christophe Cassel, Christian Kelche, Helene Meunier

“…Il apparaît que les taux de réussite sont largement sensibles à la variation des paramètres de difficultés pour l’ensemble des tâches. Ces derniers résultats sont cohérents avec les données obtenues chez l’Homme et chez d’autres modèles animaux (rats, souris, poissons). …”
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Frequency anomalies and characteristics of extratropical cyclones during extremely wet, dry, windy, and calm seasons in the extratropics by H. Binder, H. Wernli

“…This study therefore uses 1050 years of present-day (1990–1999) climate simulations of the Community Earth System Model Large Ensemble (CESM-LE) and 71 years (1950–2020) of ERA5 reanalyses to systematically identify extremely wet, dry, windy, and calm seasons in the extratropics during winter and summer and to quantify the role of extratropical cyclones in their occurrence. …”
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Voice analysis and deep learning for detecting mental disorders in pregnant women: a cross-sectional study by Hikaru Ooba, Jota Maki, Hisashi Masuyama

“…The hyperparameters were optimized using Optuna, and an ensemble learning approach was used for the final predictions. …”
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The Optimization of Carbon Emission Prediction in Low Carbon Energy Economy Under Big Data by Ji Luo, Wuyang Zhuo, Siyan Liu, Bingfei Xu

“…This research first establishes a Multi-universe Quantum Harmony Search-Algorithm Dynamic Fuzzy System Ensemble (MUQHS-DMFSE) composite model for carbon emission prediction. …”
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Deep learning in gonarthrosis classification: a comparative study of model architectures and single vs. multi-model methods by Sahika Betul Yayli, Kutay Kılıç, Salih Beyaz

“…Future studies should explore ensemble modeling, advanced augmentations, and clinical validation to enhance applicability.…”
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Anthropogenic Disturbance and Climate Change Impacts on the Suitable Habitat of Sphenomorphus incognitus in China by Kai Chen, Li Ma, Weijun Jiang, Lijin Wang, Li Wei, Hongji Zhang, Ruhao Yang

“…The mean true skill statistic (TSS) and the area under the receiver operating characteristic curve (AUC) suggested that the ensemble model yield more precise predictions than those of individual models. …”
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Development of a Three-Stage Hybrid Model by Utilizing a Two-Stage Signal Decomposition Methodology and Machine Learning Approach to Predict Monthly Runoff at Swat River Basin, Pak... by Muhammad Sibtain, Xianshan Li, Ghulam Nabi, Muhammad Imran Azam, Hassan Bashir

“…To overcome this difficulty, this paper proposes a three-stage novel hybrid model, namely, CVS (CEEMDAN-VMD-SVM), by coupling the support vector machine (SVM) with a two-stage signal decomposition methodology, combining complete ensemble empirical decomposition with additive noise (CEEMDAN) and variational mode decomposition (VMD), to obtain inclusive information of the runoff time series. …”
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A data-driven intelligent fault diagnosis framework for permanent magnet in PMSM by Huizhen Wang, Lei Wang, QiYa Wu, Haoying Pei, Lijun Diao

“…First, the proposed approach anomaly detection requires only normal data during the training phase, addressing the practical issue of limited fault samples. Furthermore, ensemble learning integrates the outputs of multiple base learners to enhance generalization. …”
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Fully Automated Bone Age Assessment on Large-Scale Hand X-Ray Dataset by Xiaoying Pan, Yizhe Zhao, Hao Chen, De Wei, Chen Zhao, Zhi Wei

“…In the end, a variety of ensemble regression algorithms are applied to perform BAA. …”
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Performance Enhancement of NavIC With Low-Cost MEMS-IMU, Barometer, and Magnetometer by Saraswathi Sirikonda, Laxminarayana Parayitam, Hari B. Hablani

“…The heading accuracy for all three systems is ~0.73°. This last ensemble of devices meets the required accuracy for identification of the lane for autonomous navigation of land vehicles in Indian urban areas, where the lane span is 3.75 m. …”
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3D Gravity Modeling of Complex Salt Features in the Southern Gulf of Mexico by Mauricio Nava-Flores, Carlos Ortiz-Aleman, Mauricio G. Orozco-del-Castillo, Jaime Urrutia-Fucugauchi, Alejandro Rodriguez-Castellanos, Carlos Couder-Castañeda, Alfredo Trujillo-Alcantara

“…The inverted 3D density model successfully retrieves the synthetic salt body ensemble. Results highlight the significance of integrating high-resolution potential field data for salt and subsalt imaging in oil exploration.…”
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Impact of climate change over distribution and potential range of chestnut in the Iberian Peninsula by Pedro Álvarez-Álvarez, Adrián Aviñoa-Arias, Adrián Aviñoa-Arias, Emilio Díaz-Varela, José Vicente López-Bao, José Carlos Pérez-Girón

“…Future habitat suitability projections were based on an ensemble of five global circulation models (GCMs) for two climate change scenarios included in CMIP6. …”
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Multi-modal denoised data-driven milling chatter detection using an optimized hybrid neural network architecture by Haining Gao, Haoyu Wang, Hongdan Shen, Shule Xing, Yong Yang, Yinlin Wang, Wenfu Liu, Lei Yu, Mazhar Ali, Imran Ali Khan

“…A data denoising model combining Complementary Ensemble Empirical Mode Decomposition (CEEMD) and Singular Value Decomposition (SVD) is established. …”
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Modelling COVID-19 in the North American region with a metapopulation network and Kalman filter by Matteo Perini, Teresa K. Yamana, Marta Galanti, Jiyeon Suh, Roselyn Kaondera-Shava, Jeffrey Shaman

“…The model is informed by COVID-19 case data, which are assimilated using the Ensemble Adjustment Kalman filter (EAKF), a Bayesian inference algorithm. …”
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