Comprehensive Performance Comparison of Signal Processing Features in Machine Learning Classification of Alcohol Intoxication on Small Gait Datasets by Muxi Qi, Samuel Chibuoyim Uche, Emmanuel Agu

“…Convenient, unobtrusive intoxication detection methods using equipment already owned by users are desirable. Recent research has explored machine learning-based approaches using smartphone accelerometers to classify intoxicated gait patterns. …”
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Lost in translation: using global fact-checks to measure multilingual misinformation prevalence, spread, and evolution by Dorian Quelle, Calvin Yixiang Cheng, Alexandre Bovet, Scott A. Hale

“…Abstract Misinformation and disinformation are growing threats in the digital age, affecting people across languages and borders. However, no research has investigated the prevalence of multilingual misinformation and quantified the extent to which misinformation diffuses across languages. …”
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A Novel PNDA-MMNet Model for Evaluating Dynamic Changes in the Brain State of Patients with PTSD During Neurofeedback Training by Peng Ding, Lei Zhao, Anmin Gong, Wenya Nan, Yunfa Fu

“…Conclusion: This research introduces a more effective approach for real-time monitoring and evaluation of PTSD patients’ brain states during NFT, offering a quantitative method for assessing treatment efficacy and guiding therapeutic interventions.…”
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Theory of Virtual Genre Studies: The Problem of Methodology by Tyukaeva Nadezhda

“…Its primary aim is to introduce the concept of web-idiom as a systemic language variant of the internet environment, encompassing stable grammatical, lexical, and pragmatic patterns adapted to digital spaces (platforms, algorithms, multimodality). …”
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Optimizing solar energy utilization in facilities using machine learning-based scheduling techniques: A case study by Hussam J. Khasawneh, Waseem M. Al-Khatib, Zaid A. Ghazal, Ahmad M. Al-Hadi, Zaid M. Arabiyat, Osama Habahbeh

“…Our approach overcomes these limitations by employing ML algorithms to accurately predict solar generation patterns, enabling more efficient scheduling of electrical appliances. …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…This work compares and reports the classification, machine learning, and deep learning algorithms that predict cardiovascular illnesses. For this study, articles from 2012 to 2023 were considered; after filtering, 82 articles were chosen for primary research. …”
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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…Additionally, clustering algorithms enabled user segmentation based on cookie data, identification of behavioral patterns, enhanced personalized web recommendations, and browsing experience optimization. …”
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Exploiting Artificial Neural Networks for the State of Charge Estimation in EV/HV Battery Systems: A Review by Pierpaolo Dini, Davide Paolini

“…By structuring insights from the extensive literature, this paper aims to establish ANNs as a foundational tool in next-generation battery management systems, ultimately supporting safer and more efficient EVs through real-time fault detection, accurate SOC estimation, and robust safety protocols. Future research directions include refining dataset quality, optimizing algorithm selection, and enhancing diagnostic precision, thereby broadening ANNs’ role in ensuring reliable battery management in electric vehicles.…”
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Machine Learning and Digital-Twins-Based Internet of Robotic Things for Remote Patient Monitoring by Sehat Ullah, Sangeen Khan, David Vanecek, Inam Ur Rehman

“…This research leverages the advantages of ML and DTs-based IoRT to remotely monitor chronic or infectious patients and predict their future status. …”
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Informational Approaches in Modelling Social and Economic Relations: Study on Migration and Access to Services in the European Union by Florentina-Loredana Dragomir-Constantin, Camelia Madalina Beldiman, Monica Laura Zlati

“…The applied methodology includes attribute distribution analysis, identification of hidden patterns through clustering algorithms (K-Means and Expectation-Maximisation) and training of classifiers using regression decision trees with linear leaf models (M5P) corresponding to interdependent data processing and integration modules, exploratory analysis module, machine learning and decision-making modules, oriented to support public policies through explainable scenarios and predictive-evaluative structures. …”
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A Flexible Constrained ICA Approach for Multisubject fMRI Analysis by Hanlu Yang, Trung Vu, Ehsan Ahmed Dhrubo, Vince D. Calhoun, Tülay Adali

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Trends in indirect liver function marker testing in Wales from 2000 to 2017 and their association with age and sex: an observational study by Joe West, Joanne R Morling, Trevor Alexander Hill, Colin John Crooks

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Enhancing ovarian cancer prognosis with an artificial intelligence-derived model: Multi-omics integration and therapeutic implications by You Wu, Kunyu Wang, Yan Song, Bin Li

“…MFAP4′s functionality and the influence of DNA methylation present opportunities for prospective research endeavors and potential therapeutic interventions.…”
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Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change by Robson Mateus Freitas Silveira, Angela Maria de Vasconcelos, Concepta McManus, Luiz Paulo Fávero, Iran José Oliveira da Silva

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From Words to Ratings: Machine Learning and NLP for Wine Reviews by Iliana Ilieva, Margarita Terziyska, Teofana Dimitrova

“…These findings can be applied by a wide range of stakeholders—researchers, producers, retailers, and marketing specialists.…”
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DIODEM – A Diverse Inertial and Optical Dataset of kinEmatic chain Motion by Simon Bachhuber, Dustin Lehmann, Ive Weygers, Thomas Seel

“…The dataset enables researchers to systematically study individual and combined IMT challenges, facilitating algorithm development for applications ranging from biomechanics to autonomous systems.…”
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The calcitron: A simple neuron model that implements many learning rules via the calcium control hypothesis. by Toviah Moldwin, Li Shay Azran, Idan Segev

“…Theoretical neuroscientists and machine learning researchers have proposed a variety of learning rules to enable artificial neural networks to effectively perform both supervised and unsupervised learning tasks. …”
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Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Identification of geochemical anomalies plays an essential role in mineral exploration. Recent research investigations have shown that Machine Learning (ML) algorithms can identify geochemical anomalies associated with mineralization that represent targets for mineral exploration. …”
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Prediksi Kesiapan Sekolah Menggunakan Machine Learning Berbasis Kombinasi Adam dan Nesterov Momentum by Indah Mustika Rahayu, Ahmad Yusuf, Mujib Ridwan

“…Based on the Chi-Square correlation, variables that have a strong significant relationship to school readiness test results are pre-elementary status, number of siblings and age with p<.05. The research used Artificial Neural Network algorithms with a combination of Adam and Nesterov Momentum optimization method. …”
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Development of a deep learning system for predicting biochemical recurrence in prostate cancer by Lu Cao, Ruimin He, Ao Zhang, Lingmei Li, Wenfeng Cao, Ning Liu, Peisen Zhang

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