Dynamic Risk Assessment System for Power System Based on Multi-source Information of the Ubiquitous Power Internet of Things by Shenhua WANG, Xiangwei HE, Xiaofang FANG, Bingsong CHEN, Chuangxin GUO

“…Finally, based on the architecture, the corresponding software system is designed. The data source, data platform and main function modules of the system are also described. …”
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Qualidade do percolado de solos que receberam vinhaça em diferentes doses e tempo de incubação Quality of percolate from soils after application of different doses and incubation t... by Fabio L. Brito, Mario M. Rolim, Jose A. A. da Silva, Elvira M. R. Pedrosa

“…The results indicated that variations in the analyzed parameters, due to vinasse application in the soil, do not bring concerns in relation to environmental quality. …”
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LVRT Measurement Model and Transient Parameter Identification of Wind Turbine Based on Chaotic Particle Swarm by Dan LI, Shiyao QIN, Shaolin LI, Jing HE

“…In order to address the fault transient modeling problems of doubly-fed wind turbines, a measured data-based modeling and parameter identification method of doubly-fed wind turbines is proposed. …”
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Degradation Prediction of Proton Exchange Membrane Fuel Cell Based on Multi-Head Attention Neural Network and Transformer Model by Yikai Tang, Xing Huang, Yanju Li, Haoran Ma, Kai Zhang, Ke Song

“…Proton exchange membrane fuel cells are a clean energy technology with wide application in transportation and stationary energy systems. …”
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Decomposing the Sri Lanka Yield Curve Using Principal Component Analysis to Examine the Term Structure of the Interest Rate by K P N Sanjeewa Dayarathne, Uthayasanker Thayasivam

“…Our analysis encompasses data spanning from January 2010 to August 2022. The study applied several PCA variants such as multivariate PCA, Randomized PCA, Incremental PCA, Sparse PCA, Functional PCA, and Kernel PCA on smoothed data. …”
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Optimizing malicious website prediction: An advanced XGBoost-based machine learning model by Hussain Sumaira, Zada Islam, Alazab Moutaz, Alfraihi Hessa, Aldhayan Manal, Ullah Inam, Khan Mohammad Asmat Ullah

“…Our methodology includes data collection, data cleaning, and the application of the XGBoost classifier. …”
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Defining chronic pain impact levels: a patient-clinician approach using PROMIS® pain interference scores by Karon F. Cook, Dokyoung Sophia You, Michael Von Korff, Sean C. Mackey

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Research on Wellbore Trajectory Prediction Based on a Pi-GRU Model by Hanlin Liu, Yule Hu, Zhenkun Wu

“…The GRU network captures the temporal dependencies of sequence data (such as dip angle and azimuth angle), while the BP neural network extracts deep correlations from non-sequence features (such as stratum lithology), thereby achieving multi-source data fusion modeling. …”
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An Adaptive Variance Adjustment Strategy for a Static Background Error Covariance Matrix—Part I: Verification in the Lorenz-96 Model by Lilan Huang, Hongze Leng, Junqiang Song, Dongzi Wang, Wuxin Wang, Ruisheng Hu, Hang Cao

“…Accurate initial conditions are crucial for improving numerical weather prediction (NWP). Variational data assimilation relies on a static background error covariance matrix (<b>B</b>), yet its variance estimation is often inaccurate, affecting assimilation and forecast performance. …”
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Unmanned Aerial Vehicle Anomaly Detection Based on Causality-Enhanced Graph Neural Networks by Chen Feng, Jun Fan, Zhiliang Liu, Guang Jin, Siya Chen

“…As a direct representation of system health status, flight data contain critical status information, driving data-driven methods to gradually replace traditional dynamic modeling as the mainstream paradigm. …”
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Eficiência e impacto do contexto na gestão através do DEA: o caso da UEG Efficiency and impact of the context in the management through the DEA: case study of the UEG by Carlos Rosano-Peña

“…<br>This work shows the contribution of the method Data Envelopment Analysis (DEA) in the evaluation of the efficiency of organizations that operate in differentiated contexts. …”
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Employing combined spatial and frequency domain image features for machine learning-based malware detection by Abul Bashar

“…The ubiquitous adoption of Android devices has unfortunately brought a surge in malware threats, compromising user data, privacy concerns, and financial and device integrity, to name a few. …”
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GPE-DNeRF:Neural radiance field method for surface geological bodies reconstruction by Xinyi Wang, Weihua Hua, Xiuguo Liu, Peng Li, Guohe Li

“…Deep learning-based 3D reconstruction technologies offer highly automated approaches for recognizing complex data patterns and generating realistic reconstruction results. …”
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Spatiotemporal pattern evolution and quantitative prediction of electrical carbon emissions from a demand-side perspective in urban areas by Ying Tian, Hui Cao, Dapeng Yan, Jinmei Chen, Yayan Hua

“…Utilizing high-frequency monitoring data from  3000 distribution network stations (May–Sept 2018), it creates an integrated ’spatiotemporal evolution-data driven prediction’ framework to reveal emission dynamics and enhance forecast accuracy. …”
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What Is My Plaza for? Implementing a Machine Learning Strategy for Public Events Prediction in the Urban Square by Jumana Hamdani, Pablo Antuña Molina, Lucía Leva Fuentes, Hesham Shawqy, Gabriella Rossi, David Andrés León

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HYBRID WLS-KF APPROACH FOR REAL-TIME STATE ESTIMATION IN AUTOMATED DISTRIBUTION GRIDS by Abdulrafiu Yusuf, Olalekan Ogunbiyi, Lambe Mutalub Adesina, Bashiru Olalekan Ariyo

“…Methods: The methodology includes the integration of real-time data from Supervisory Control and Data Acquisition (SCADA) systems, smart meters, and Phasor Measurement Units (PMUs), followed by the application of WLS, KF, and a hybrid approach to estimate voltage magnitudes and phase angles. …”
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Multiplex Networks and Pan-Cancer Multiomics-Based Driver Gene Identification Using Graph Neural Networks by Xingyi Li, Junming Li, Jun Hao, Xingyu Liao, Min Li, Xuequn Shang

“…Identifying cancer driver genes has paramount significance in elucidating the intricate mechanisms underlying cancer development, progression, and therapeutic interventions. Abundant omics data and interactome networks provided by numerous extensive databases enable the application of graph deep learning techniques that incorporate network structures into the deep learning framework. …”
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Assessing glacier thickness changes with multi-temporal UAV-derived DEMs: The evolution of Forni Glacier over the period 2014–2022 by Valeria Belloni, Davide Fugazza, Kevin Hanson, Marco Scaioni, Martina Di Rita

“…However, multi-temporal UAV-based data usually must be improved in terms of consistency due to possible variable survey conditions, requiring precise co-registration. …”
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Journaling with large language models: a novel UX paradigm for AI-driven personal health management by Birger Moëll, Fredrik Sand Aronsson, Fredrik Sand Aronsson

“…The prototype combines a personal health record with an LLM assistant, allowing for reflective self-monitoring and aiming to combine patient-generated data with clinical insights. Key innovations include a three-panel interface for seamless journaling, AI dialogue, and longitudinal tracking, alongside specialized modes for interacting with simulated healthcare expert personas.ResultPreliminary insights from persona-based evaluations highlight the system's capacity to enhance health literacy through explainable AI responses while maintaining strict data localization and privacy controls. …”
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The possibilities of lineament analysis using for quantitative assessment of the areas prospectivity for the hydrocarbon deposits searching (on the example of the Dnieper-Donets de... by A. Ya. Khodorovskyi, O. A. Apostolov, L. O. Yelistratova, I. F. Romanciuc

“…The reliability of faults corresponding to zones of increased number of lineaments was assessed by their spatial coincidence with the faults identified by geophysical data. The lineament density maps of the Earth’s thermic field, established by remote sensing data, were analyzed. …”
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