Time-domain thermoreflectance technique using multiple delayed probe pulses for high-throughput data acquisition and analysis by Hiroto Arima, Yuichiro Yamashita, Takashi Yagi

“…Furthermore, we applied machine learning-based analysis and demonstrated the ability to determine thermophysical properties from measurement data consisting of only a few delay points. …”
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Utilizing machine and deep learning algorithms to identify learning-related features in electroencephalography data during second language acquisition by Talal A. Aldhaheri, Sonali B. Kulkarni, Pratibha R. Bhise, Mohammed Tawfik

“…This study investigates EEG-based neurolinguistic patterns during the process of learning Arabic and Hindi as second languages. EEG data were collected from 10 participants (6 males and 4 females; M = 34.1, SD = 4.7 years) engaged in language acquisition tasks, and the signals underwent preprocessing steps, including noise removal, independent component analysis (ICA), and spectral feature extraction. …”
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Machine Learning Models to Predict Individual Cognitive Load in Collaborative Learning: Combining fNIRS and Eye-Tracking Data by Wenli Chen, Zirou Lin, Lishan Zheng, Mei-Yee Mavis Ho, Farhan Ali, Wei Peng Teo

“…Effectively leveraging cognitive load predictions helps optimize collaborative learning design and implementation. This study explored the feasibility of predicting individual learners’ cognitive load during collaborative learning using a combination of functional near-infrared spectroscopy (fNIRS) and eye-tracking data. …”
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Pacing Patterns of Half-Marathon Runners: An analysis of ten years of results from Gothenburg Half Marathon by Johansson Moa, Atterfors Johan, Lamm Johan

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Enhancing Human Knowledge and Capabilities with Artificial Intelligence Tools for Education by Emerson Abraham Jackson, Hudson F. Jackson

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A Machine Learning-Based Intelligent Framework for Predicting Energy Efficiency in Next-Generation Residential Buildings by Hafiz Muhammad Shakeel, Shamaila Iram, Richard Hill, Hafiz Muhammad Athar Farid, Akbar Sheikh-Akbari, Farrukh Saleem

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Big Data Analytics in IoT, social media, NLP, and information security: trends, challenges, and applications by Kamal Taha

Subjects: “…Big Data Analytics…”
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Automatic location of relevant time slices and patterns in both signals and video-movies: real-time and off-line visualization by J. Vega, R. Castro

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A Hybrid Methodology of Data Science and Decision Making Techniques: Lessons from COVID-19 Pandemic Management by mehdi dadehbeigi, ali taherinezhad, alireza alinezhad

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AI-Driven Spatial Data Analysis of Groundwater Level and Gravimetric Data in Roorkee Region, India by H. Sarkar, C. S. P. Ojha, S. K. Ghosh

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Application of Artificial Intelligence to Support Design and Analysis of Steel Structures by Sina Sarfarazi, Ida Mascolo, Mariano Modano, Federico Guarracino

“…The review explores challenges such as data limitations, model generalization, engineering reliability, and the need for physics-informed learning while examining AI’s role in bridging research and real-world structural applications. …”
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Forest aboveground carbon storage estimation and uncertainty analysis by coupled multi-source remote sensing data in Liaoning Province by Hancong Fu, Hengqian Zhao, Ge Liu, Yujiao Zhang, Xiadan Huangfu, Jinbao Jiang

“…Traditional forest resource inventory methods pose limitations due to their sparse spatial coverage and time-consuming data collection. While satellite sensors offer extensive spatial and temporal coverage, their low spatial resolution often introduces significant errors when ground measurements are directly matched with satellite image pixels. …”
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Express Analysis of the Structural and Electronic Properties of Nanomaterials Using Big Data, Large Language Models and Generative Artificial Intelligence by N. A. Shymanski, A. V. Baglov, Kh. B. Musaev, O. N. Ruzimuradov, L. S. Khoroshko

Subjects: “…machine learning…”
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Predicting blood transfusion demand in intensive care patients after surgery by comparative analysis of temporally extended data selection by Seyedmostafa Sheikhalishahi, Sebastian Goss, Lea K. Seidlmayer, Sarra Zaghdoudi, Ludwig C. Hinske, Mathias Kaspar

“…The study included a primary analysis using data from 6 h before ICU admission up to 1, 2, 3, and 6 h after admission, and a secondary analysis using only the data from 6 h before ICU admission and only the data from the first hour after admission. …”
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Framework for investigating structure cracking using real engineering data combined with physics constraints by Han Si, Qidi Wang, Xin Ruan, Xingpo Fang

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Precise prediction of choke oil rate in critical flow condition via surface data by Qing Wang, Muntadher Abed Hussein, Bhavesh Kanabar, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Mohammad Mahtab Alam, Hojjat Abbasi

“…The novelty of this study lies in the comprehensive comparison of machine learning methods applied to real-world oil production data, with a particular focus on the impact of key well parameters on production efficiency. …”
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Integrative analysis of multi-omics data identified PLG as key gene related to Anoikis resistance and immune phenotypes in hepatocellular carcinoma by Xueyan Wang, Lei Gao, Haiyuan Li, Yanling Ma, Bofang Wang, Baohong Gu, Xuemei Li, Lin Xiang, Yuping Bai, Chenhui Ma, Hao Chen

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A Data Centric HitL Framework for Conducting aSsystematic Error Analysis of NLP Datasets using Explainable AI by Ahmed El-Sayed, Aly Nasr, Youssef Mohamed, Ahmed Alaaeldin, Mohab Ali, Omar Salah, Abdullatif Khalid, Shaimaa Lazem

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Unveiling the Impact of Socioeconomic and Demographic Factors on Graduate Salaries: A Machine Learning Explanatory Analytical Approach Using Higher Education Statistical Agency Dat... by Bassey Henshaw, Bhupesh Kumar Mishra, William Sayers, Zeeshan Pervez

“…This study investigates determinants of graduate salaries in the UK, utilising survey data from HESA (Higher Education Statistical Agency) and integrating advanced machine learning (ML) explanatory techniques with statistical analytical methodologies. …”
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Comparison of Deep Learning Sentiment Analysis Methods, Including LSTM and Machine Learning by Jean Max T. Habib, A. A. Poguda

“…The purpose of the study is to evaluate certain machine learning models in data processing based on speed and efficiency related to the analysis of sentiment or consumer opinions in business intelligence. …”
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