Data-Centric Fine-Tuning of Small Language Models for Automatic Extraction of Technical Requirements by Leopold Muller, Nina Schwarz, Lars Bocking, Andreas Bereczuk, Hanno Stagge, Wolfgang Kratsch, Niklas Kuhl

“…These results underscore the potential of data-centric fine-tuning for adapting small language models to high-stakes, privacy-sensitive tasks, offering a scalable alternative to LLMs enabling their applications to real-world use cases.…”
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A Multiphysics Dataset Generation Procedure for the Data-Driven Modeling of Traction Electric Motors by Simone Ferrari, Luigi Solimene, Riccardo Torchio, Costanza Anerdi, Fabio Freschi, Luca Giaccone, Gianmarco Lorenti, Francesco Lucchini, Piergiorgio Alotto, Gianmario Pellegrino, Maurizio Repetto

“…To address these challenges, the paper presents an open-source dataset that provides a reliable foundation for the multi-physical analysis of electric motors used in traction applications. One of the main novelties of this approach is that geometrical and physical data of the motor configuration are shared among different analysis codes. …”
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Remotely geolocating static events observed by citizens using data collected by mobile devices by Jacinto Estima, Ismael Jesus, Cidália C. Fonte, Alberto Cardoso

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Auto-negotiation time division MAC protocol for periodical data gathering in sensor networks by ZENG Yi, HU Bo, LIU Shun-jia

“…On the analysis of data flow characteristics in periodical data gathering applications in wireless sensor net- works, an auto-negotiation time division MAC protocol based on auto-negotiation slot allocation scheme was proposed. …”
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Natural language processing in Alzheimer's disease research: Systematic review of methods, data, and efficacy by Arezo Shakeri, Mina Farmanbar

“…Machine learning and neural networks were primarily applied to speech, EHR, and social media data, while rule‐based methods were used to analyze literature datasets. …”
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Advanced Machine Learning Methodology for Earthquake Magnitude Forecasting Using Comprehensive Seismic Data by Subhieh El-Salhi, Bashar Igried, Sari Awwad

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Remote Sensing of Grasslands: Performance Comparison of Radar and Optical Data in Machine Learning Classification by K. Christofi, C. Chrysostomou, I. Tsardanidis, M. Mavrovouniotis, G. Guerrisi, C. Kontoes, D. G. Hadjimitsis, D. G. Hadjimitsis

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OBTAINING A UNIQUE SPLINE FUNCTION TO INTERPOLATE A POLYNOMIAL WITH LACUNARY DATA VALUES by Pankaj Kumar Tripathi, Kulbhushan Singh

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A Collaborative Data Gathering Mechanism Based on Fuzzy Decision for Wireless Sensor Networks by Wen Si, Hui-yuan Shi, Pan Liu

“…This paper proposes collaborative data gathering mechanism based on fuzzy decision for wireless sensor networks. …”
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Big Data and AI Algorithms for Sustainable Development Goals: A Topic Modeling Analysis by Prema Nedungadi, Simi Surendran, Kai-Yu Tang, Raghu Raman

“…Using BERTopic modeling, a machine learning technique, this research systematically analyzes literature from 2013 to 2024, providing an overview of AI and big data applications mapped to SDGs which is a first. …”
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From data extraction to analysis: a comparative study of ELISE capabilities in scientific literature by Maxime Gobin, Muriel Gosnat, Seindé Toure, Lina Faik, Joel Belafa, Antoine Villedieu de Torcy, Florence Armstrong

“…Epsilon, Humata, and SciSpace/Typeset exhibit moderate performance, with variability affecting their reliability in critical applications. In conclusion, while AI tools such as ELISE enhance literature review, regulatory writing, and clinical data interpretation, human oversight remains essential to validate AI outputs and ensure compliance with scientific and regulatory standards. …”
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Estimation of state of health for lithium-ion batteries using advanced data-driven techniques by Smitanjali Rout, Sudhansu Kumar Samal, Demissie Jobir Gelmecha, Satyasis Mishra

“…The proposed framework incorporates optimized pre-processing techniques, including normalization, to improve data quality and ensure consistency across varying battery conditions. …”
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An improved Red-billed blue magpie feature selection algorithm for medical data processing. by Chenyi Zhu, Zhiyi Wang, Yinan Peng, Wenjun Xiao

“…These results demonstrate the potential and wide applicability of IRBMO in feature selection for medical data.…”
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Robust confinement state classification with uncertainty quantification through ensembled data-driven methods by Yoeri Poels, Cristina Venturini, Alessandro Pau, Olivier Sauter, Vlado Menkovski, the TCV Team, the WPTE Team

“…The automated labeling of these confinement states is crucial to enable large-scale analyses or for real-time control applications. While this task becomes difficult to automate near state transitions or in marginal scenarios, much success has been achieved with data-driven models. …”
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Modeling to Engineering and Failure Times Data: Using the Marshall–Olkin Extended Exponential Distribution by Ibrahim E. Ragab, Najwan Alsadat, Mustapha Muhammad, Suleman Nasiru, Mohammed Elgarhy

“…In the final analysis, we demonstrate the significance of the novel model by examining practical data applications, thus, showing the adaptability and potential of the MO-ExE model.…”
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Multi-UAV assisted air-to-ground data collection for ground sensors with unknown positions by Cheng Yiran, Dong Yangrui

“…Utilizing UAVs for data collection from wireless ground sensors is an efficient, convenient, and cost-effective approach. …”
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India Policy Insights: A geospatial and temporal data science and visualization platform and architecture by Devika Jain, Joaquin Kachinovsky, Gonzalo Rodriguez, Junyi Chen, Rockli Kim, S V Subramanian

“…Built on an open-source stack with React,.NET, and PostGIS, it processes, stores, visualizes, and queries geospatial big data. This paper highlights IPI's architecture and methodologies for tackling public policy challenges.…”
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IoTKITs: A novel dataset for IoT education kit recognitionMendeley Data by Thanh-Thien Nguyen, Anh-Tuan Nguyen Do, Duc-Lung Vu

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On the Existence and Uniqueness of the Maximum Likelihood Estimators of Normal and Lognormal Population Parameters with Grouped Data by Jin Xia, Jie Mi, YanYan Zhou

“…Lognormal distribution has abundant applications in various fields. In literature, most inferences on the two parameters of the lognormal distribution are based on Type-I censored sample data. …”
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LSTM model to predict missing data of dissolved oxygen in land-based aquaculture farm by Sang-Yeon Lee, Deuk-Young Jeong, Jinseo Choi, Seng-Kyoun Jo, Dae-Heon Park, Jun-Gyu Kim

“…The proposed LSTM model trained on DO data has a high applicability and may support water quality control in aquaculture farms.…”
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