A Novel Real-Time Battery State Estimation Using Data-Driven Prognostics and Health Management by Juliano Pimentel, Alistair A. McEwan, Hong Qing Yu

“…This paper presents a novel data-driven framework for real-time State of Charge (SOC) estimation in lithium-ion battery systems using a data-driven Prognostics and Health Management (PHM) approach. …”
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MiTra: A Drone-Based Trajectory Data for an All-Traffic-State Inclusive Freeway with Ramps by Ankit Anil Chaudhari, Martin Treiber, Ostap Okhrin

“…The dataset provides stitched trajectory data, raw drone videos, and tracking logs. Comprehensive quality checks, including vehicle detection and video stitching validation, ensure its reliability for traffic modeling, autonomous driving research, and computer vision applications.…”
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Inferring End‐Members From Geoscience Data Using Simplex Projected Gradient Descent‐Archetypal Analysis by Zanchenling Wang, Tao Wen

“…SPGD‐AA is applicable to a wide range of geoscience data sets and beyond.…”
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Methods for detecting early warnings of critical transitions in time series illustrated using simulated ecological data. by Vasilis Dakos, Stephen R Carpenter, William A Brock, Aaron M Ellison, Vishwesha Guttal, Anthony R Ives, Sonia Kéfi, Valerie Livina, David A Seekell, Egbert H van Nes, Marten Scheffer

“…Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called 'early warning signals', and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. …”
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Improving polygenic prediction from summary data by learning patterns of effect sharing across multiple phenotypes. by Deborah Kunkel, Peter Sørensen, Vijay Shankar, Fabio Morgante

“…By using summary data, we achieve the twin goal of increasing the applicability of the mr.mash model to data sets that are not publicly available and making it scalable to biobank-size data. …”
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Evaluation of 2024 Meteorological Drought Forecasts for Türkiye: Using ECMWF SEAS5 Data and the SPEI Index by Gülten Çamalan, Sercan Akil

“…The motivation behind this research is to assess the applicability of SEAS5 for drought forecasting and its potential contribution to drought management and early warning systems. …”
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Seamless multi-skill learning: learning and transitioning non-similar skills in quadruped robots with limited data by Jiaxin Tu, Peng Zhai, Yueqi Zhang, Xiaoyi Wei, Zhiyan Dong, Lihua Zhang

“…Overall, this study confirms the SMSL framework’s capability in real robotic applications and underscores its potential for autonomous skill learning and generation from minimal data.…”
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Enhancing indoor place classification for mobile robots using RGB-D data and deep learning architectures by van Eden Beatrice, Botha Natasha

“…However, it is more common for mobile robot applications to rely on RGB data rather than RGB-D data for classifying indoor places. …”
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Interaction Prediction on BACE-1 Inhibitors Data for Alzheimer Disease using Message Passing Neural Network by Bihter Daş, Suat Toraman

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Large Language Model-Driven Structured Output: A Comprehensive Benchmark and Spatial Data Generation Framework by Diya Li, Yue Zhao, Zhifang Wang, Calvin Jung, Zhe Zhang

“…This work advances the field of LLM-based structured spatial data output generation and supports the seamless integration of LLMs into real-world applications.…”
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Strategy for Visual Measurement of Power Quality Based on Higher-Order Statistics and Exploratory Big Data Analysis by Juan-José González-de-la-Rosa, Olivia Florencias-Oliveros, Paula Remigio-Carmona

“…This article proposes a strategy for the visual characterization of power quality in big data analysis contexts, culminating in the development of a visualization tool based on higher-order statistics, which exhibits an efficiency between 83.33% and 100% in detecting 50 Hz synthetic and real-life simple and hybrid events, showing its significant potential for real-world applications marked by non-linear loads and non-Gaussian behaviors and surpassing the detection of traditional tools such as boxplot by up to 50%. …”
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Recognition of Underwater Engineering Structures Using CNN Models and Data Expansion on Side-Scan Sonar Images by Xing Du, Yongfu Sun, Yupeng Song, Lifeng Dong, Changfei Tao, Dong Wang

“…These findings highlight the importance of balanced datasets and effective data expansion strategies in overcoming data scarcity. …”
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TRUSTED: The Paired 3D Transabdominal Ultrasound and CT Human Data for Kidney Segmentation and Registration Research by William Ndzimbong, Cyril Fourniol, Loic Themyr, Nicolas Thome, Yvonne Keeza, Benoît Sauer, Pierre-Thierry Piéchaud, Arnaud Méjean, Jacques Marescaux, Daniel George, Didier Mutter, Alexandre Hostettler, Toby Collins

“…Abstract Inter-modal image registration (IMIR) and image segmentation with abdominal Ultrasound (US) data have many important clinical applications, including image-guided surgery, automatic organ measurement, and robotic navigation. …”
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From Data to Knowledge: A Knowledge Graph-Guided Framework to Deep Learning for Hyperspectral Image Classification by Runmin Lei, Yuchuan Zhou, Zixuan Wang, Xiang Zhang

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Real-Time Phase Tracking Scheme With Mismatched-Basis Data for Phase-Coding Quantum Key Distribution by Dong Wang, Xiaotian Song, Liangjiang Zhou, Yibo Zhao

“…In this paper, we propose a single-photon level real-time phase tracking scheme using only the estimated quantum bit error rate (QBER) and mismatched-basis data to acquire the phase drift parameter instead of a phase scanning process or reference light pulses, without extra hardware or interrupting the transmission of quantum signals. …”
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Visual Route Recognition in Urban Spaces: A Scalable Approach Using Open Street View Data by Menglin Wu, Qingren Jia, Anran Yang, Zhinong Zhong, Mengyu Ma, Luo Chen, Ning Jing

“…This article presents a novel pipeline for visual route recognition (VRR) in large-scale urban environments, leveraging open street view data. The proposed approach aims to identify the path of a video recorder by analyzing visual cues from continuous video frames and street landmarks, evaluated through datasets from New York and Taipei City. …”
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Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning. by Jiayi Wu, Yong-Bei Ma, Charles Congdon, Bevin Brett, Shuobing Chen, Yaofang Xu, Qi Ouyang, Youdong Mao

“…We show that unsupervised GTM clustering improves classification accuracy by about 40% in the absence of input references for data with lower SNRs. Applications to several experimental datasets suggest that our algorithm can detect subtle structural differences among classes via a hierarchical clustering strategy. …”
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A data-driven approach to prioritize MITRE ATT&CK techniques for active directory adversary emulation by Alshaimaa Abo-alian, Mahmoud Youssef, Nagwa L. Badr

“…The methodology evaluates techniques across three key dimensions: Active Directory Impact, Threat Score, and Security Control Gap, employing entropy-based weighting to ensure an objective and data-driven prioritization process. To validate the proposed framework, a real-world case study based on the APT3 threat group is presented, demonstrating the applicability and effectiveness of the prioritization strategy in aligning adversary emulation with real-world attack scenarios. …”
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Robust phylogenetic tree-based microbiome association test using repeatedly measured data for composition bias by Kangjin Kim, Sungho Won

“…However, this method of analysis is limited by compositional bias, and few statistical methods can estimate the effect of microbiota on host diseases with repeatedly measured 16S rRNA gene data. Herein, we propose mTMAT, which is applicable to longitudinal microbiome data and is robust to compositional bias. …”
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Integrating observational and modelled data to advance the understanding of heat stress effects on pregnant subsistence farmers in the gambia by Carole Bouverat, Jainaba Badjie, Tida Samateh, Tida Saidy, Kris A. Murray, Andrew M. Prentice, Neil Maxwell, Andy Haines, Ana Maria Vicedo Cabrera, Ana Bonell

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