Countermeasuring Anti-Ship Missiles for Surface Naval Platforms: A Machine Learning Approach With Explainable Artificial Intelligence by Murat Ertop, Ali Oter, Ali Kara

“…Chaffs and flares can be launched from naval platforms as soft-kill countermeasures to address such threats within the context of conflict. …”
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Sentiment analysis of pilgrims using CNN-LSTM deep learning approach by Aisha Alasmari, Norah Farooqi, Youseef Alotaibi

“…The generated feature maps are passed to the SoftMax layer to classify final outputs. The proposed model is applied to a real case study of issues related to pre-prepared food at Hajj 1442. …”
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Jet substructure probe on scalar leptoquark models via top polarization by Anupam Ghosh, Partha Konar, Tousik Samui, Ritesh K. Singh

“…To enhance the efficacy of the analysis, we employ jet substructure techniques like Soft Drop, N-subjettiness, and our custom b-tagging method, along with other event variables. …”
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Intelligent Recognition and Automated Production of Chili Peppers: A Review Addressing Varietal Diversity and Technological Requirements by Sheng Tai, Zhong Tang, Bin Li, Shiguo Wang, Xiaohu Guo

“…., robotic systems incorporating diverse end-effectors like soft grippers or cutting mechanisms and motion planning algorithms such as RRT) as well as seed cleaning/separation techniques and simulations (e.g., CFD and DEM) for equipment optimization. …”
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Plantention: A general-purpose, lightweight and attention-based model for multi-crop leaf disease classification by Brindha Subburaj, Rohan M, Samhruth Ananthanarayanan, Daehan Won

“…Most computerized methods involve some form of Deep Learning algorithms and models to automate the detection process. …”
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AI‐Powered Multimodal Modeling of Personalized Hemodynamics in Aortic Stenosis by Caglar Ozturk, Daniel H. Pak, Luca Rosalia, Debkalpa Goswami, Mary E. Robakowski, Raymond McKay, Christopher T. Nguyen, James S. Duncan, Ellen T. Roche

“…The efficiency and reliability of these algorithms make them an ideal complementary tool for personalized high‐fidelity modeling of AS biomechanics, hemodynamics, and treatment planning.…”
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Joined Spatial and Spectral Segmentation of Hyperspectral Datasets on Historical Art Objects by Lingxi Liu, Aurore Malmert, Emeline Pouyet, Silvia Mirri, Giovanni Delnevo

“…This facilitates applying various machine learning algorithms, especially the soft clustering algorithms Fuzzy C-Means clustering (FCM) and Gaussian Mixture Models (GMM), to classify spectra into distinct colourant groups, identifying complex mixtures and areas of degradation. …”
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Overhead line path planning based on deep reinforcement learning and geographical information system by Jiahui Chen, Yi Yang, Ling Peng, Lina Yang, Yinhui Han, Xingtong Ge

“…Current overhead line planning primarily relies on manual labor, and existing automated algorithms have low adaptability, making it difficult to efficiently accomplish path planning tasks under various environments and objectives. …”
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Enhancing blockchain transaction classification with ensemble learning approaches by Amrutanshu Panigrahi, Abhilash Pati, Bibhuprasad Sahu, Rourab Paul, Ajit Kumar Nayak, Subrata Chowdhury, Ramya Govindaraj, J Shreyas

“…Various ML classification algorithms are applied to the selected features from two ensemble feature selection algorithms as the base learners to make initial predictions. …”
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Flexible Configurable Modular Neural Network-Based OFDM Receiver by A. B. Sergienko, P. V. Apalina, A. D. Lebedinskaya

“…The proposed OFDM receiver for all considered modulation types provided error rates comparable to those of the baseline algorithms under favorable channel conditions (moderate delay spread with low Doppler spread) and outperformed baseline algorithms in severe conditions (channel with a large delay spread and high Doppler spread). …”
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Combined Treatment of Giant Extra-Intracranial Arteriovenous Malformation by V. A. Lukyanchikov, V. A. Dalibaldyan, S. Yu. Roschin, I. I. Goncharova, G. K. Guseynova, S. V. Zhuravel, V. A. Karanadze, A. S. Koblik, V. E. Ryabukhin, A. V. Sachkov, A. A. Grin, V. V. Krylov

“…In addition, arteriovenous malformations can cause nutritional disorders (trophism) of the soft tissues located near them. Extracranial arteriovenous malformations are rare and dangerous vascular anomalies. …”
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AI-Guided Delineation of Gross Tumor Volume for Body Tumors: A Systematic Review by Lea Marie Pehrson, Jens Petersen, Nathalie Sarup Panduro, Carsten Ammitzbøl Lauridsen, Jonathan Frederik Carlsen, Sune Darkner, Michael Bachmann Nielsen, Silvia Ingala

“…The algorithms with the highest DSC deployed an encoder–decoder architecture. …”
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Machine learning for improved size estimation of complex marine particles from noisy holographic images by Zonghua Liu, Zonghua Liu, Marika Takeuchi, Yéssica Contreras, Thangavel Thevar, Alex Nimmo-Smith, John Watson, Sarah L. C. Giering

“…However, most standard algorithms fail to accurately size objects in reconstructed holograms owing to the high background noise. …”
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Automatic Differentiation‐Based Full Waveform Inversion With Flexible Workflows by Feng Liu, Haipeng Li, Guangyuan Zou, Junlun Li

“…The AD‐based framework not only includes forword modeling and associated gradient computations for wave equations in various types of media from isotropic acoustic to vertically or horizontally transverse isotropic elastic, but also incorporates a suite of objective functions, regularization techniques, and optimization algorithms. By leveraging state‐of‐the‐art AD, objective functions such as soft dynamic time warping and Wasserstein distance, which are difficult to apply in traditional FWI are also easily integrated into ADFWI. …”
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On the Synergy of IoMT Devices and Ceiling-Mounted Systems for Advanced Medical Data Analytics by Andreas Andreou, Constandinos X. Mavromoustakis, Evangelos K. Markakis, Athina Bourdena, George Mastorakis

“…Specifically, Twin-Delayed Deep Deterministic Policy Gradients (TD3) and Soft Actor-Critic (SAC) algorithms are adopted to optimize task scheduling and system decisions in dynamic, resource-constrained settings. …”
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Reconstruction of Tokamak Plasma Emissivity Distribution by Approximation with Basis Functions by Tomasz Czarski, Maryna Chernyshova, Katarzyna Mikszuta-Michalik, Karol Malinowski

“…The present study focuses on the development of a diagnostic system for measuring radiated power and core soft X-ray intensity emissions with the goal of detecting a broad spectrum of photon energies emitted from the central plasma region of the DEMO tokamak. …”
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Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model by Asadi Srinivasulu, Vanithamani Palanisamy

“…Here, the Random Forest Classifier, a soft computing tool, was utilized on a dataset encompassing 649 student records. …”
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Wave Attenuation by Australian Temperate Mangroves by Ruth Reef, Sabrina Sayers

“…Wave attenuation by natural coastal features is recognised as a soft engineering approach to shoreline protection from storm surges and destructive waves. …”
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Chondrogenic Cancer Grading by Combining Machine and Deep Learning with Raman Spectra of Histopathological Tissues by Gianmarco Lazzini, Mario D’Acunto

“…In particular, in the last years several studies have demonstrated how the diagnostic performances of RS can be significantly improved by employing machine learning (ML) algorithms for the interpretation of Raman-based data. …”
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Sweet Potato Yield Prediction Using Machine Learning Based on Multispectral Images Acquired from a Small Unmanned Aerial Vehicle by Kriti Singh, Yanbo Huang, Wyatt Young, Lorin Harvey, Mark Hall, Xin Zhang, Edgar Lobaton, Johnie Jenkins, Mark Shankle

“…Additionally, a soft-voting ML model ensemble approach is employed to improve performance of yield prediction. …”
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