Recommending Actionable Strategies: A Semantic Approach to Integrating Analytical Frameworks with Decision Heuristics by Renato Ghisellini, Remo Pareschi, Marco Pedroni, Giovanni Battista Raggi

“…The approach employs <b>vector space representations</b> and <b>semantic similarity calculations</b> to map framework parameters to heuristic patterns, supported by a computational architecture that combines deep semantic processing with constrained use of Large Language Models. …”
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Identifying Persons of Interest in Digital Forensics Using NLP-Based AI by Jonathan Adkins, Ali Al Bataineh, Majd Khalaf

“…The domain of NLP includes several tools to parse text, including topic modeling, pairwise correlation, word vector cosine distance measurement, and sentiment analysis. …”
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Predicting the Compression Capacity of Screw Piles in Sand Using Machine Learning Trained on Finite Element Analysis by David Igoe, Pouya Zahedi, Hossein Soltani-Jigheh

“…Following development of the numerical database, various machine learning methods such as linear regression, neural networks, support vector machines, and Gaussian process regression (GPR) models were trained and tested on the database in order to develop a prediction tool for the pile compression capacity. …”
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Detecting Fake News in Urdu Language Using Machine Learning, Deep Learning, and Large Language Model-Based Approaches by Muhammad Shoaib Farooq, Syed Muhammad Asadullah Gilani, Muhammad Faraz Manzoor, Momina Shaheen

“…This study aims to solve this problem by creating a detailed process and training models using machine learning, deep learning, and large language models (LLMs). …”
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Regression Model Employing Spiking Neural Network for Bio-Signal Analysis With Hardware Integration by Choongseop Lee, Geunbo Yang, Jaewoo Baek, Yuntae Park, Mingyu Cheon, Jongkil Park, Cheolsoo Park

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SOCIAL DIMENSION OF INNOVATION RESEARCH IN THE CONDITIONS OF SOCIAL TRANSFORMATIONS by Тетяна ЄРЕСКОВА, Олег МАЗУРИК

“… The article is devoted to understanding the social dimension of perception of innovations, which allows to determine the vector of perception of transformational changes in society. …”
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Low-Complexity Adaptive Chromatic Dispersion Estimation Scheme Using Machine Learning for Coherent Long-Reach Passive Optical Networks by Jin Li, Danshi Wang, Min Zhang

“…In the coherent long-reach passive optical networks (LRPON), it is crucial to propose cost-effective digital signal processing (DSP) technologies to reduce the overall complexity and power consumption. …”
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SpectroFusionNet a CNN approach utilizing spectrogram fusion for electric guitar play recognition by Ganesh Kumar Chellamani, Aishwarya N, Chandhana C, Kanwaljeet Kaur, Rakesh Thoppaen Suresh Babu

“…Then, the fused features are subsequently fed into nine machine learning classifiers, including Support Vector Machine (SVM), Multilayer Perceptron (MLP), Logistic Regression, Random Forest etc., for final classification. …”
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Machine learning for early detection of plant viruses: Analyzing post-infection electrical signal patterns by Elham Ghasemi, Esmaeil Ebrahimie, Ali Niazi

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Implementation of a Conditional Latent Diffusion-Based Generative Model to Synthetically Create Unlabeled Histopathological Images by Mahfujul Islam Rumman, Naoaki Ono, Kenoki Ohuchida, Ahmad Kamal Nasution, Muhammad Alqaaf, Md. Altaf-Ul-Amin, Shigehiko Kanaya

“…Initially, these images were embedded into a lower-dimensional latent space using a Vector Quantized Generative Adversarial Network (VQ-GAN). …”
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The Evolution of Machine Learning in Vibration and Acoustics: A Decade of Innovation (2015–2024) by Jacek Lukasz Wilk-Jakubowski, Lukasz Pawlik, Damian Frej, Grzegorz Wilk-Jakubowski

“…In the context of these processes, a review of machine learning techniques was conducted, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), autoencoders, support vector machines (SVMs), decision trees (DTs), nearest neighbor search (NNS), K-means clustering, and random forests. …”
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Estimation of Polarization and Spatial Parameters of a Radio Source Signal Using Triorthogonal Antenna by G. S. Gribov

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Accurate and Efficient Fluid Flow Regime Classification Using Localized Texture Descriptors and Machine Learning by Manimaran Renganathan, Palani Thanaraj Krishnan, C. Christopher Columbus, T. Sunil Kumar

“…These features are then classified using various machine learning models, namely Random Forest (RF), Support Vector Machines (SVM), and k-Nearest Neighbors (k-NN). …”
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#GAMEADDICTED: A Machine Learning Framework for Digital Game Addiction Detection and Early Intervention by Esra Kahya Ozyirmidokuz, Bekir Asim Celik, Eduard Alexandru Stoica

“…The study employed machine learning models to process unstructured data collected from online game platforms between May 1, 2023, and June 1, 2023. …”
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Study on Color Detection of Korla Fragrant Pears by Near-Infrared Spectroscopy Combined with PLSR by Yifan Xia, Yang Liu, Hong Zhang, Jikai Che, Qing Liang

“…The full-spectrum data were pre-processed using six methods: Savitzky–Golay convolution smoothing (SGCS), Savitzky–Golay convolution derivative (SGCD), multiplicative scatter correction (MSC), vector normalization (VN), min–max normalization (MMN), and standard normal variate transformation (SNV). …”
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The Potential for Hyperspectral Imaging and Machine Learning to Classify Internal Quality Defects in Macadamia Nuts by Michael B. Farrar, Marcela Martinez, Kim Jones, Negar Omidvar, Helen M. Wallace, Thomas Chen, Shahla Hosseini Bai

“…Combining images to form a pooled dataset also provided high accuracy (>90%) using artificial neural network and support vector machine models. Overall, HSI has great potential for commercial application in nut processing to detect internal brown centers using images of the outside kernel surface in the VNIR range. …”
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Parameters of oculomotor activity and cerebral hemodynamics in students with different types of autonomic reactivity while performing cognitive tasks by Anna I. Taleeva, Natalya V. Zvyagina, Olga E. Karyakina, Nikolay V. Popov, Tatyana V. Zotikova

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Use of artificial intelligence to support prehospital traumatic injury care: A scoping review by Jake Toy, Jonathan Warren, Kelsey Wilhelm, Brant Putnam, Denise Whitfield, Marianne Gausche‐Hill, Nichole Bosson, Ross Donaldson, Shira Schlesinger, Tabitha Cheng, Craig Goolsby

“…The majority used machine learning (88%) alone or in conjunction with DL or NLP, and the top three algorithms used were support vector machine, logistic regression, and random forest. …”
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Methods for Applying Matrices when Creating Models of Group Pursuit by A. A. Dubanov

“…There were cases when the speed vector of the pursuer was directed arbitrarily and to a point on the Apollonius circle. …”
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Artificial Intelligence-Based Prediction Model for Maritime Vessel Type Identification by Hrvoje Karna, Maja Braović, Anita Gudelj, Kristian Buličić

“…It incorporates both the deep learning techniques for initial image representation and traditional image processing and machine learning methods for subsequent image classification. …”
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