A Dynamic Hierarchical Clustering Data Gathering Algorithm Based on Multiple Criteria Decision Making for 3D Underwater Sensor Networks by Xiaoying Song, Wei Sun, Qilong Zhang

“…Data gathering is the basis of monitoring applications in an underwater sensor network, and excellent network coverage and data transmission reliability are the guarantees for the quality of monitoring tasks. …”
Get full text

A Cloud-Based Framework for Creating Scalable Machine Learning Models Predicting Building Energy Consumption from Digital Twin Data by Elham Mahamedi, Alaeldin Suliman, Martin Wonders

“…Although machine learning (ML) techniques are increasingly used to predict building energy consumption from this DT data, existing approaches often lack scalability in handling data growth (data scalability) and/or adapting to evolving data patterns (model scalability). …”
Get full text

Reserve Estimation from Early Time Production Data in Geopressured Gas Reservoir: Gas Production of Cumulative Unit Pressure Drop Method by Hongfeng Wang, Xiaoping Li, Hedong Sun, Guangren Meng, Wen Cao, Songbai Zhu

Get full text

The impact of PCR duplication on RNAseq data generated using NovaSeq 6000, NovaSeq X, AVITI, and G4 sequencers by Natalia Zajac, Ioannis S. Vlachos, Sija Sajibu, Lennart Opitz, Shuoshuo Wang, Sridar V. Chittur, Christopher E. Mason, Kevin L. Knudtson, John M. Ashton, Hubert Rehrauer, Catharine Aquino

“…Results For broader applicability, we sequenced the data on four short-read sequencing platforms: Illumina NovaSeq 6000, Illumina NovaSeq X, Element Biosciences AVITI, and Singular Genomics G4. …”
Get full text

Integrated process-property modeling of YBa2Cu3O7 superconducting film for data and model driven process design by Tomoya Horide, Shin Okumura, Shunta Ito, Yutaka Yoshida

“…Our integrated process and property modelling strategy enables data/model-driven process design for YBa2Cu3O7 film fabrication for coated conductor applications.…”
Get full text

Cross-Attention-Based High Spatial-Temporal Resolution Fusion of Sentinel-2 and Sentinel-3 Data for Ocean Water Quality Assessment by Yanfeng Wen, Peng Chen, Zhenhua Zhang, Yunzhou Li

“…Current marine research that leverages remote sensing data urgently requires gridded data of high spatial and temporal resolution. …”
Get full text

Modeling Ocean Wave Conditions at a Shallow Coast Under Scarce Data Availability: A Case Study in the Mekong Delta, Vietnam by Hoang Thai Duong Vu, Moritz Zemann, Roderick van der Linden, Trinh Cong Dan, Peter Oberle, Frank Seidel, Nguyet Minh Nguyen, Le Xuan Tu

“…However, it requires a much broader amount of input parameters and more complex boundary conditions. Then, SwanOne was applicable to calculate nearshore wave characteristics based on the input parameters extracted from the statistical analysis of long-term ERA5 data. …”
Get full text

Advancing Early Detection of Major Depressive Disorder Using Multisite Functional Magnetic Resonance Imaging Data: Comparative Analysis of AI Models by Masab Mansoor, Kashif Ansari

“…ObjectiveThis study aimed to develop and validate ML models using multisite functional magnetic resonance imaging data for the early detection of MDD, compare their performance, and evaluate their clinical applicability. …”
Get full text

A Methodology for Turbine-Level Possible Power Prediction and Uncertainty Estimations Using Farm-Wide Autoregressive Information on High-Frequency Data by Francisco Javier Jara Ávila, Timothy Verstraeten, Pieter Jan Daems, Ann Nowé, Jan Helsen

“…These results demonstrate that the methodology enables interpretable, data-efficient, and uncertainty-aware turbine-level power predictions, suitable for advanced wind farm monitoring and control applications, enabling a more sensitive underperformance detection.…”
Get full text

Enhancing cold storage efficiency: Continuous deep deterministic policy gradient approach to energy optimization utilizing strategic sensor input data by Jong-Whi Park, Young-Min Ju, Hak-Sung Kim

“…The foundational framework, reward function, and data communication methods, previously optimized for small-scale facilities, were adjusted to suit the requirements of the extended cold storage settings. …”
Get full text

Boosting all-optical wavelength conversion efficiency using an AlGaAs-on-insulator Fabry–Perot microresonator without data rate limits by Chaochao Ye, Ping Zhao, Yang Liu, Xinda Lu, Chanju Kim, Kresten Yvind, Peter A. Andrekson, Minhao Pu

“…We also demonstrate a continuously tunable wavelength conversion system, showcasing its potential to support high signal data rates. Our approach provides a promising pathway for on-chip laser-driven nonlinear signal processing, enabling efficient high-speed wavelength conversion and applications where both high CE and data rate are crucial.…”
Get full text

Evaluating Population Normalization Methods Using Chemical Data for Wastewater-Based Epidemiology: Insights from a Site-Specific Case Study by Marco Verani, Ileana Federigi, Alessandra Angori, Alessandra Pagani, Francesca Marvulli, Claudia Valentini, Nebiyu Tariku Atomsa, Beatrice Conte, Annalaura Carducci

“…Wastewater-based epidemiology (WBE) has been widely employed to track the spread of human pathogens; however, correlating wastewater data with clinical surveillance remains challenging due to population variability and environmental factors affecting wastewater composition. …”
Get full text

eLogUp! A precise, affordable and open-source IoT data logger to scale-up long-term environmental monitoring by Franck Perret, Ilane Cherif, Frédéric Cherqui, Nicolas Walcker, Adrien Barra, Bastien Bourjaillat, Laëtitia Bacot, Oldrich Navratil

“…is a low-cost, modular, and open-source data logger designed to support both research and operational environmental monitoring applications requiring accurate data recording and storage, efficient power management, and reliable data transmission. …”
Get full text

End-to-end 3D instance segmentation of synthetic data and embryo microscopy images with a 3D Mask R-CNN by Gabriel David, Emmanuel Faure

“…In recent years, the exploitation of three-dimensional (3D) data in deep learning has gained momentum despite its inherent challenges. …”
Get full text

Estimating fine age structure and time trends in human contact patterns from coarse contact data: The Bayesian rate consistency model. by Shozen Dan, Yu Chen, Yining Chen, Melodie Monod, Veronika K Jaeger, Samir Bhatt, André Karch, Oliver Ratmann, Machine Learning & Global Health network

“…The Bayesian rate consistency model provides a model-based, non-parametric, computationally tractable approach for estimating the fine structure and longitudinal trends in social contacts and is applicable to contemporary survey data with coarsely reported age of contacts as long as the exact age of survey participants is reported.…”
Get full text

Development of Novel Soil Salinity Spectral Index Using Remotely Sensed Data: A Case Study on Balod District, Chhattisgarh, India by Deshpande Vaibhav Prakashrao, Ahmad Ishtiyaq, Singh Chandan Kumar

“…This study demonstrates a strong correlation between reflectance values and field EC data with an R2 value of 0.83 and a mean relative error of 10 %. …”
Get full text

A mathematical framework for estimating pathogen transmission fitness and inoculum size using data from a competitive mixtures animal model. by James M McCaw, Nimalan Arinaminpathy, Aeron C Hurt, Jodie McVernon, Angela R McLean

“…The model is applied to data from "competitive mixtures" experiments in which animals are co-infected with a mixture of two strains. …”
Get full text

Feature-based ensemble modeling for addressing diabetes data imbalance using the SMOTE, RUS, and random forest methods: a prediction study by Younseo Jang

Get full text

SE-COLLAB: Achieving Fine-Grained and Efficiently Verifiable Searchable Encryption With Boolean Multi-Keyword Search for Collaborative IIoT Data Sharing by Somchart Fugkeaw, Jirakit Deevijit

“…In Industrial Internet of Things (IIoT) environments, the secure and efficient retrieval of sensitive data from outsourced storage remains a critical challenge, especially under collaborative and multi-authority settings. …”
Get full text

Prediction of persistent type II endoleak after endovascular aortic repair using machine learning based on preoperative clinical data and radiomic by Jinqing Mo, Qi Liu, Kangjie Wang, Lin Huang, Chen Yao

“…Preoperative clinical data were collected, and radiomic features were extracted from the segmented thrombus in the aneurysm sac of preoperative CTA. …”
Get full text