Forecasting Optimal Solar Energy Supply in Jiangsu Province (China): A Systematic Approach Using Hybrid of Weather and Energy Forecast Models by Xiuli Zhao, Henry Asante Antwi, Ethel Yiranbon

“…Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.…”
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Impact of COVID-19 vaccinations in India: a state-wise analysis by Abhigayan Adhikary, Manoranjan Pal, Raju Maiti

“…Objective In this work, the objective is to perform a state-wise analysis to assess the impact of vaccination in slowing down the spread of infections during the second COVID-19 wave (February – October 2021) in India. The prediction accuracy of the proposed model with the optimal lag length (in days) after including the impact of vaccination is evaluated and compared with a model without it. …”
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LeaData a novel reference data of leather images for automatic species identification by Anjli Varghese, Malathy Jawahar, A. Amalin Prince

“…The traditional identification techniques are prone to ambiguous predictions due to insufficient reference studies. Indeed, leather image analysis with big data can pave the way for automatic and objective analysis with accurate prediction. …”
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Spatial-Temporal Analysis of Particulate Matter (PM10) and Sulphur Dioxide (SO2) Concentrations in Ankara Using Climate Parameters by Olgu Aydın, Nussaïbah Begum Raja

“…When evaluating the performance of the prediction models for PM10 and SO2 concentrations, it is found that the PM10 model explains 66% and the SO2 model explains 78% of the variance. …”
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A Study of Coupling Parameter Estimation Implemented by 4D-Var and EnKF with a Simple Coupled System by Guijun Han, Xinrong Wu, Shaoqing Zhang, Zhengyu Liu, Ionel Michael Navon, Wei Li

“…These simple model studies provide some insights when parameter estimation is implemented with a coupled general circulation model for improving climate estimation and prediction initialization.…”
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Preference learning based deep reinforcement learning for flexible job shop scheduling problem by Xinning Liu, Li Han, Ling Kang, Jiannan Liu, Huadong Miao

“…First, a reward predictor based on preference learning is designed to model reward prediction by comparing random fragments, eliminating the need for complex reward function design. …”
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Artificial Intelligence-Based Classification of Chest X-Ray Images into COVID-19 and Other Infectious Diseases by Arun Sharma, Sheeba Rani, Dinesh Gupta

“…The combination of two best-performing models (each trained on 286 images, rotated through 120° or 140° angle) displayed the highest prediction accuracy for normal, COVID-19, non-COVID-19, pneumonia, and tuberculosis images. …”
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Structural and Functional Annotation of Hypothetical Proteins of O139 by Md. Saiful Islam, Shah Md. Shahik, Md. Sohel, Noman I. A. Patwary, Md. Anayet Hasan

“…The analysis revealed that these proteins might have antibiotic resistance activity, DNA breaking-rejoining activity, integrase enzyme activity, restriction endonuclease, etc. Structural prediction of these proteins and detection of binding sites from this study would indicate a potential target aiding docking studies for therapeutic designing against cholera.…”
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Enhancing Indoor mmWave Communication With ML-Based Propagation Models by Gustavo Adulfo Lopez-Ramirez, Alejandro Aragon-Zavala

“…This study focuses on demonstrating how machine learning (ML) techniques can be applied to predict path loss within the millimeter wave (mmWave) spectrum in a specific indoor environment. …”
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Changes of Soil Moisture from Multiple Sources during 1988–2010 in the Yellow River Basin, China by Dan Lou, Guojie Wang, Chan Shan, Daniel Fiifi T. Hagan, Waheed Ullah, Dawei Shi

“…The spatiotemporal variations of soil moisture from multiple sources during 1988–2010 are evaluated against in situ observations in the Yellow River basin, China, including the Essential Climate Variable satellite’s passive microwave product (SMECV), ERA-Interim reanalysis (SMERA), the National Centers for Environmental Prediction/Department of Energy’s Reanalysis-2 (SMNCEP), and the Variable Infiltration Capacity model products (SMVIC). …”
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Mapping Pituitary Neuroendocrine Tumors: An Annotated MRI Dataset Profiling Tumor and Carotid Characteristics by A. S. Pandit, A. Keenlyside, D. Z. Khan, G. Reischer, M. A. Kamal, N. Yoh, Z. Jaunmuktane, A. Borg, N. L. Dorward, S. E. Baldeweg, I. Davagnanam, H. Hyare, P. Nachev, H. J. Marcus

“…Our initiative addresses the need for standardized data in pituitary oncology, fosters collaboration and innovation, and enables the development and benchmarking of workflows that utilize pituitary radiomics for treatment planning and outcome prediction.…”
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Volatility characteristics and hyperspectral-based detection models of diesel in soils by Jihye Shin, Jaehyung Yu, Jihee Seo, Lei Wang, Hyun-Cheol Kim

“…Using the hull-quotient reflectance at 2236 nm, the diesel content prediction model derived from a stepwise multiple linear regression (SMLR) achieved satisfactory accuracy with sufficient statistical significance (R2 = 0.89, RPD = 2.52). …”
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Joint Analysis of Morphological Parameters and In Silico Haemodynamics of the Left Atrial Appendage for Thrombogenic Risk Assessment by Maria Isabel Pons, Jordi Mill, Alvaro Fernandez-Quilez, Andy L. Olivares, Etelvino Silva, Tom de Potter, Oscar Camara

“…Analyses based only on morphological or haemodynamic parameters are not precise enough to predict such a phenomenon, as demonstrated in our results; a better patient stratification can be obtained by jointly analysing morphological and haemodynamic features.…”
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Strain-Dependence of the Structure and Ferroic Properties of Epitaxial NiTiO3 Thin Films Grown on Different Substrates by Tamas Varga, Timothy C. Droubay, Mark E. Bowden, Libor Kovarik, Dehong Hu, Scott A. Chambers

“…Polarization-induced weak ferromagnetism has been predicted a few years back in perovskite MTiO3 (M = Fe, Mn, and Ni). …”
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Combined Effects of Sustained Loads and Wet-Dry Cycles on Durability of Glass Fiber Reinforced Polymer Composites by Mengting Li, Jun Wang, Weiqing Liu, Ruifeng Liang, Hota GangaRao, Yang Li

“…Based on Arrhenius method, a prediction model which accounted for the effects of postcure processes was developed. …”
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DMR: disentangled and denoised learning for multi-behavior recommendation by Yijia Zhang, Wanyu Chen, Fei Cai, Zhenkun Shi, Feng Qi

“…First, the irrelevant auxiliary behaviors that do not align with the target behavior, can negatively impact the prediction accuracy for user preference in the target behavior. …”
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FundusNet: A Deep-Learning Approach for Fast Diagnosis of Neurodegenerative and Eye Diseases Using Fundus Images by Wenxing Hu, Kejie Li, Jake Gagnon, Ye Wang, Talia Raney, Jeron Chen, Yirui Chen, Yoko Okunuki, Will Chen, Baohong Zhang

“…Additionally, the model’s high accuracy in predicting genetic risk suggests that its performance could be further enhanced with larger training datasets.…”
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Multimodal approach to public health interventions using EGG and mobile health technologies by Xiao Zhang, Han Liu, Mingyang Sun, Shuangyi Feng

“…IntroductionPublic health interventions increasingly integrate multimodal data sources, such as Electroencephalogram (EEG) data, to enhance monitoring and predictive capabilities for mental health conditions. …”
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Optimal Pathways to Lung Cancer Screening in Primary Care Settings: A Scoping Review by Emmanouil K. Symvoulakis, Izolde Bouloukaki, Antonios Christodoulakis, Antonia Aravantinou-Karlatou, Ioanna Tsiligianni

“…Important strategies for LCS included the use of shared decision-making tools, electronic health record (HER) prompts, risk prediction models, community outreach, and integration with smoking cessation programs. …”
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Experimental Research on Mechanical Property and Environmental Safety of an Industrial Residue Waste Subgrade Material by Yangpeng Zhang, Jianping Xiong, Qinglin Li, Jiuhui Cui

“…The aim of this paper is to study the mechanical behavior and environmental impact of SOF, which is regarded as the safety assessment and prediction for the application of this novel material. …”
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