Integrating Machine Learning Techniques for Enhanced Safety and Crime Analysis in Maryland by Zeinab Bandpey, Soroush Piri, Mehdi Shokouhian

“…Our models’ performance was extensively validated across various train–test split ratios, utilizing R-squared and RMSE metrics to confirm their efficacy and reliability for practical applications. The findings from this study contribute significantly to the field by offering new insights into localized crime patterns and demonstrating how tailored, data-driven strategies can effectively enhance public safety. …”
Get full text

Predicting the anion conductivities and alkaline stabilities of anion conducting membrane polymeric materials: development of explainable machine learning models by Yin Kan Phua, Tsuyohiko Fujigaya, Koichiro Kato

Get full text

Enhancing Multi-User Activity Recognition in an Indoor Environment with Augmented Wi-Fi Channel State Information and Transformer Architectures by MD Irteeja Kobir, Pedro Machado, Ahmad Lotfi, Daniyal Haider, Isibor Kennedy Ihianle

“…Human Activity Recognition (HAR) is crucial for understanding human behaviour through sensor data, with applications in healthcare, smart environments, and surveillance. …”
Get full text

Hyperspectral signature-band extraction and adaptation for sugar content prediction on Ziziphus mauritiana and Syzygium samarangense by Yung-Jhe Yan, Jen-Tzung Chien, Zi-Yin Hong, Wen-Li Lee, Kuo-Dung Chiou, Chi-Cho Huang, Mang Ou-Yang

“…The proposed method was evaluated on two fruit species, Ziziphus mauritiana and Syzygium samarangense. Hyperspectral image data consist of hundreds of spectral bands, resulting in large data volumes that are not suitable for rapid detection applications. …”
Get full text

Quantification of Flavonoid Contents in Holy Basil Using Hyperspectral Imaging and Deep Learning Approaches by Apichat Suratanee, Panita Chutimanukul, Kitiporn Plaimas

“…However, effectively linking hyperspectral data to flavonoid levels remains a challenge for developing early detection tools before harvest. …”
Get full text

Developing a Novel Adaptive Double Deep Q-Learning-Based Routing Strategy for IoT-Based Wireless Sensor Network with Federated Learning by Nalini Manogaran, Mercy Theresa Michael Raphael, Rajalakshmi Raja, Aarav Kannan Jayakumar, Malarvizhi Nandagopal, Balamurugan Balusamy, George Ghinea

“…The working of the Internet of Things (IoT) ecosystem indeed depends extensively on the mechanisms of real-time data collection, sharing, and automatic operation. …”
Get full text

Deep Learning to Estimate Model Biases in an Operational NWP Assimilation System by Patrick Laloyaux, Thorsten Kurth, Peter Dominik Dueben, David Hall

“…Despite different origins and applications, data assimilation (DA) and Deep Learning are both able to learn about the Earth system from observations. …”
Get full text

An Assessment of Measuring Local Levels of Homelessness Through Proxy Social Media Signals by Yoshi Bird, Sarah Grobe, Michael Arnold, Sean Rogers, Mikaela Fudolig, Julia Zimmerman, Christopher Danforth, Peter Sheridan Dodds

Get full text

Multi-View Cluster Structure Guided One-Class BLS-Autoencoder for Intrusion Detection by Qifan Yang, Yu-Ang Chen, Yifan Shi

“…Intrusion detection systems are crucial for cybersecurity applications. Network traffic data originate from diverse terminal sources, exhibiting multi-view feature spaces, while the collection of unknown intrusion data is costly. …”
Get full text

Cascade Learning Early Classification: A Novel Cascade Learning Classification Framework for Early-Season Crop Classification by Weilang Kong, Xiaoqi Huang, Jialin Liu, Min Liu, Luo Liu, Yubin Guo

“…Accurate early-season crop classification is critical for food security, agricultural applications and policymaking. However, when classification is performed earlier, the available time-series data gradually become scarce. …”
Get full text

25 years of research and regulation: Is nanotechnology safe to commercialize? by Kirsten Rasmussen, Phil Sayre, Andrej Kobe, Mar Gonzalez, Hubert Rauscher

“…Challenges arose due to the unique physico-chemical properties of some nanomaterials and included the lack of i) a regulatory definition, ii) applicable regulatory test methods, including methods for physico-chemical characterization and for ecotoxicological effects, as well as sample preparation and dosimetry, iii) assessment and modelling of human, especially occupational, and environmental exposure to nanomaterials, iv) quantification of nanomaterial in complex media, v) systems for collecting the data generated and ensuring FAIR (Findable, Accessible, Interoperable and Re-usable) and quality data, vi) reference nanomaterials, and vii) a frame for nanotechnology governance. …”
Get full text

A Comparison of Inversion Methods for Surrogate‐Based Groundwater Contamination Source Identification With Varying Degrees of Model Complexity by Zhenbo Chang, Zhilin Guo, Kewei Chen, Zibo Wang, Yang Zhan, Wenxi Lu, Chunmiao Zheng

“…To evaluate the applicability of these methods, we chose one representative inversion algorithm from each category, namely the Improved Butterfly Optimization Algorithm (IBOA) for simulation optimization, the Ensemble Smoother with Multiple Data Assimilation (ES‐MDA) for data assimilation, and the DiffeRential Evolution Adaptive Metropolis with a Snooker Update and Sampling from a Past Archive (DREAM(ZS)) for Bayesian inference. …”
Get full text

Leveraging Digital Twin for operational resilience in the oil and gas industry by Giovanni Mazzuto, Ilaria Pietrangeli, Marco Ortenzi, Filippo Emanuele Ciarapica, Maurizio Bevilacqua

“…The model was validated using real data, focusing on two key components: the ejector-pump system and the vertical tank. …”
Get full text

Magnetotelluric Sampling and Geoelectric Hazard Estimation: Are National‐Scale Surveys Sufficient? by Benjamin S. Murphy, Greg M. Lucas, Jeffrey J. Love, Anna Kelbert, Paul A. Bedrosian, E. Joshua Rigler

“…We also provide a cautionary example in the use of electrical conductivity models to predict dense MT data; although valuable for hazard applications, models may only be able to reproduce surface geoelectric fields as captured by the MT data from which they were derived.…”
Get full text

Do feed-in tariffs unlock green finance? A panel study of banking sector assets and renewable energy consumption across 66 countries around the world by Olena Shcherbakova

Get full text

Enhancing AI-driven forecasting of diabetes burden: a comparative analysis of deep learning and statistical models by Rasool Esmaeilyfard, Mohsen Bayati

“…While deep learning models have demonstrated superior predictive capabilities, their real-world applicability is constrained by computational complexity and data quality challenges. …”
Get full text

The Smart city vision: The internet-of-postal-things (iopt) approach by Maria PAVLOVSKAYA, Olga KONONOVA

“…Frequently Smart city projects are stalled at the initial stages due to insufficient data volume. Meanwhile, state Postal services remain outside the Smart cities concepts and models, despite the available resources to handle big data. …”
Get full text

Fault Diagnosis of Semi-Supervised Electromechanical Transmission Systems Under Imbalanced Unlabeled Sample Class Information Screening by Chaoge Wang, Pengpeng Jia, Xinyu Tian, Xiaojing Tang, Xiong Hu, Hongkun Li

“…Validation through two datasets, encompassing a total of 12 experimental scenarios, demonstrates that in scenarios with only a small amount of labeled data, the proposed method achieves a diagnostic accuracy increment exceeding 10% compared to existing typical methods, fully validating the effectiveness and superiority of the proposed method in practical applications.…”
Get full text

A Global Coseismic InSAR Dataset for Deep Learning: Automated Construction from Sentinel-1 Observations (2015–2024) by Xu Liu, Zhenjie Wang, Yingfeng Zhang, Xinjian Shan, Ziwei Liu

“…Following standardized preprocessing and data augmentation (DA), a large number of image samples were generated for model training. …”
Get full text

A Multicomponent Collaborative Fossil Fuel Power Plants Detection Framework Based on Geographic Analysis in Wide Areas by Ning Li, Min Jing, Wanxuan Geng, Shengkun Dongye, Hui Chen, Chen Ji, Liang Cheng

“…However, obtaining comprehensive geographic location data for FFPPs is challenging due to data availability and collection constraints. …”
Get full text