Accurate identification of oxygen desaturation status in COPD by using classifier ensemble. by Yue-Fang Wu, Xin Shu, Shiqi Wang, Xiaojun Xu, Pei-Li Sun

“…We propose a new and effective EIOD status identification method by using classifier ensemble strategy. In the proposed method, five different features of each data point from the time series of SpO2 and pulse are extracted and then combined to form the discriminative feature of the corresponding data point; then, multiple base classifiers with different balanced training subsets are trained and then integrated by using AdaBoost Algorithm. …”
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Neuronal Ensemble Decoding Using a Dynamical Maximum Entropy Model by Duho Sin, Jinsoo Kim, Jee Hyun Choi, Sung-Phil Kim

“…As advances in neurotechnology allow us to access the ensemble activity of multiple neurons simultaneously, many neurophysiologic studies have investigated how to decode neuronal ensemble activity. …”
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A deep ensemble learning framework for glioma segmentation and grading prediction by Liang Wen, Hui Sun, Guobiao Liang, Yue Yu

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Vivre ensemble. Conflit et cohabitation à Ceuta et Melilla by Alicia Fernández García

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Crowd Density Estimation of Scenic Spots Based on Multifeature Ensemble Learning by Xiaohang Xu, Dongming Zhang, Hong Zheng

“…To deal with these problems, an ensemble learning (EL) method using support vector regression (SVR) is proposed in this study for crowd density estimation (CDE). …”
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Fault Identification of UHVDC Transmission Based on DF-AD and Ensemble Learning by Qingsheng Zhao, Xinyu Yang, Xiaoqing Han, Dingkang Liang, Xuping Wang

“…Next, the entropy features of these signals were computed, and the Random Forest-Recursive feature elimination with cross-validation (RF-RFECV) algorithm was used to select a high-quality feature subset. Finally, an ensemble classifier consisting of Light Gradient Boosting Machine (LightGBM), K Nearest Neighbor (KNN), and Naive Bayes (NB) classifiers was utilized to identify UHVDC faults. …”
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Enhanced framework for ensemble effort estimation by using recursive‐based classification by Azath Hussain, Maheswari Raja, Pandimurugan Vellaisamy, Sangeetha Krishnan, Lakshminarayanan Rajendran

“…Software effort estimation (SEE) plays an essential role in reusable service for ensembling the effort estimation of the software development. …”
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Attention-enhanced optimized deep ensemble network for effective facial emotion recognition by Taimoor Khan, Muhammad Yasir, Chang Choi

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Modeling and analysis of ensemble average solvation energy and solute–solvent interfacial fluctuations by Shao Yuanzhen, Chen Zhan, Zhao Shan

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X-Ray Cross-Correlation Analysis of Disordered Ensembles of Particles: Potentials and Limitations by R. P. Kurta, M. Altarelli, I. A. Vartanyants

“…Results of our simulations demonstrate the application of XCCA to two- and three-dimensional (2D and 3D) disordered ensembles of particles. We show that the structure of a single particle can be recovered using X-ray data collected from a 2D disordered system of identical particles. …”
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The Advantage of Using International Multimodel Ensemble for Seasonal Precipitation Forecast over Israel by Amir Givati, Mashor Housh, Yoav Levi, Dror Paz, Itzhak Carmona, Emily Becker

“…The six National Multimodel Ensemble (NMME) models and the ECMWF seasonal model were used to calculate an International Multimodel Ensemble (IMME). …”
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Enhancing lane detection in autonomous vehicles with multi-armed bandit ensemble learning by J. Arun Pandian, Ramkumar Thirunavukarasu, L. Thanga Mariappan

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Holographic Renyi entropy of 2d CFT in KdV generalized ensemble by Liangyu Chen, Anatoly Dymarsky, Jia Tian, Huajia Wang

“…Previous works have demonstrated that primary CFT eigenstates have flat entanglement spectrum, which is very different from the microcanonical ensemble. This result is an apparent contradiction to conventional ETH, which does not take KdV charges into account. …”
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Uncertainty Assessment: Reservoir Inflow Forecasting with Ensemble Precipitation Forecasts and HEC-HMS by Sheng-Chi Yang, Tsun-Hua Yang

“…It found that using the ensemble-mean had less uncertainty than randomly selecting individual member. …”
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Detection of UAV GPS Spoofing Attacks Using a Stacked Ensemble Method by Ting Ma, Xiaofeng Zhang, Zhexin Miao

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Prenatal depression level prediction using ensemble based deep learning model by Abinaya Gopalakrishnan, Xujuan Zhou, Revathi Venkataraman, Raj Gururajan, Ka Ching Chan, Guohun Zhu, Niall Higgins

“…Results:: We subsequently applied the ensemble based deep learning model on a testing dataset and our method proved to be 93.87 percent accurate, proving its superiority over the standard supervised classification models. …”
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Fake Detect: A Deep Learning Ensemble Model for Fake News Detection by Nida Aslam, Irfan Ullah Khan, Farah Salem Alotaibi, Lama Abdulaziz Aldaej, Asma Khaled Aldubaikil

“…In this study, we proposed an ensemble-based deep learning model to classify news as fake or real using LIAR dataset. …”
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Two mechanisms of membrane digestion: enzymatic-transport ensemble exists for oligopeptides as well by S. T. Metelsky, V. T. Ivashkin

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Ensemble machine learning-based extrapolation of Penman-Monteith-Leuning evapotranspiration data by Vahid Nourani, Ramin Ahmadi, Yongqiang Zhang, Dominika Dąbrowska

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Remote cooling of spin-ensembles through a spin-mechanical hybrid interface by Yang Wang, Durga Bhaktavatsala Rao Dasari, Jörg Wrachtrup

“…Abstract We present a protocol for the ground-state cooling of a tripartite hybrid quantum system, in which a macroscopic oscillator acts as a mediator between a single-probe spin and a remote spin ensemble. In the presence of weak dispersive coupling between the spins and the oscillator, cooling of the oscillator and the ensemble spins can be achieved by exploiting the feedback from frequent measurements of the single-probe spin. …”
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