Seamless Optimization of Wavelet Parameters for Denoising LFM Radar Signals: An AI-Based Approach by Talaat Abdelfattah, Ali Maher, Ahmed Youssef, Peter F. Driessen

“…Traditional denoising methods, including wavelet-based techniques, have been extensively used to address this issue, yet they often fall short in terms of optimizing performance due to fixed parameter settings. …”
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EMSAM: enhanced multi-scale segment anything model for leaf disease segmentation by Junlong Li, Quan Feng, Jianhua Zhang, Jianhua Zhang, Sen Yang

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Beyond the Exam Room: Teaching Intervisit Care to Internal Medicine Residents by Matthew J. Mulligan, Amanda B. Breviu, Sarah K. Hall, Karen E. Stenehjem, Anne C. Cioletti

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Seasonal quantile forecasting of solar photovoltaic power using Q-CNN-GRU by Louiza Ait Mouloud, Aissa Kheldoun, Samira Oussidhoum, Hisham Alharbi, Saud Alotaibi, Thabet Alzahrani, Takele Ferede Agajie

“…These datasets cover varied temporal horizons (1-hour, 6-hour, 12-hour, and 24-hour predictions) and seasonal conditions (summer, fall, spring, and winter), highlighting the model’s adaptability to different scenarios. …”
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From ESP to CLIL and back again: on linguistic aspects in vocational training by Zbigniew P. MOŻEJKO

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Image Analysis and Detection of Olive Leaf Diseases Using Recurrent Neural Networks by Mohsin Raad Kareem

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A Hybrid Adaptive Particle Swarm Optimization Algorithm for Enhanced Performance by Zhengfeng Jiang, Daoheng Zhu, Xiao-Yu Li, Ling-Bo Han

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Research on Interference Resource Optimization Based on Improved Whale Optimization Algorithm by Xuyi Chen, Mingxi Ma, Chengkui Liu, Haifeng Xie, Shaoqi Wang

“…Then, in the solution process, to address the issues of the Whale Optimization Algorithm (WOA) easily falling into local optima and low convergence accuracy, the BIO-WOA (Bernoulli Chaotic mapping In-nonlinear Factors and Opposition-based Learning Improved Whale Optimization Algorithm, BIO-WOA) is proposed. …”
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An intelligent algorithm for identifying dropped blocks in wellbores by Qian Wang, Zixuan Yang, Chenxi Ye, Wenbao Zhai, Xiao Feng

“…An intelligent, fully automated feature parameter extraction and classification system was developed and applied to classify the types of falling blocks in 12 sets of drilling field and laboratory experiments and to identify the causes of wellbore instability. …”
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Generalizing location-centric variations to enhance contactless human activity recognition by Fawad Khan, Syed Yaseen Shah, Jawad Ahmad, Alanoud Al Mazroa, Adnan Zahid, Muhammed Ilyas, Qammer Hussain Abbasi, Syed Aziz Shah

“…Contactless Human Activity Recognition (HAR) has played a critical role in smart healthcare and elderly care homes to monitor patient behavior, detect falls or abnormal activities in real time. The effectiveness of non-invasive HAR is often hindered by location-centric variations in Channel State Information (CSI). …”
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Strength prediction of ECC-CES columns under eccentric compression using adaptive sampling and ML techniques by Khaled Megahed

“…Subsequently, six machine learning models were used to predict the eccentric compressive capacity based on the generated FE database. …”
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A Hybrid Quantum-Classical Approach for Multi-Class Skin Disease Classification Using a 4-Qubit Model by Aravinda C V, Emerson Raja Joseph, Sultan Alasmari

“…Quantum machine learning (QML) presents a promising avenue for addressing complex classification challenges, yet its application in medical imaging remains largely unexplored. …”
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Impacts of Spatial Expansion of Urban and Rural Construction on Typhoon-Directed Economic Losses: Should Land Use Data Be Included in the Assessment? by Siyi Zhou, Zikai Zhao, Jiayue Hu, Fengbao Liu, Kunyuan Zheng

“…This reveals that implicitly classifying typhoon disaster loss types through prototype learning can significantly improve assessment accuracy in data-scarce scenarios. (2) By designing a dual-path uncertainty quantification mechanism, we realized high-reliability risk assessment, with 95.45% of actual loss values falling within predicted confidence intervals (theoretical expectation: 95%). …”
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Multisensor Remote Sensing and AI-Driven Analysis for Coastal and Urban Resilience Classification by Sumei Ren, Bushra Ghaffar, Muhammad Mubbin, Muhammad Haseeb, Zainab Tahir, Sher Shah Hassan, Dmitry E. Kucher, Olga D. Kucher, M. Abdullah-Al-Wadud

“…The static indicators and rule-based spatial frameworks that are the mainstays of traditional resilience assessment models frequently fall short of capturing the dynamic character of coastal and urban resilience. …”
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Improved identification and tracking of three-dimensional eddies in the Southern Ocean utilizing 3D-U-Res-Net by Chang Liu, Xiayan Lin, Xiayan Lin, Guangjun Xu, Guangjun Xu, Guoqing Han, Yu Liu

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A resource allocation algorithm based on improved salp swarm algorithm in cognitive smart grid by SHEN Hongting

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Equitable and effective clinical guidance development and dissemination: trauma aims to lead the way by Deborah M Stein, Elliott R Haut, Eileen M Bulger, Vanessa P Ho, Andres M Rubiano, Ashley Farley, Lacey N LaGrone, Danielle J Wilson, Maria Michaels, Meghan B Lane-Fall, Michael A Person, Linda Reinhart

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Cascaded Detection Method for Ship Targets Using High-Frequency Surface Wave Radar in the Time–Frequency Domain by Zhiqing Yang, Hao Zhou, Yingwei Tian, Gan Liu, Bing Zhang, Yao Qin, Peng Li, Weimin Huang

“…Due to noise interference, ship echoes in the noise region often fall below the detection threshold, leading to missed detections. …”
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Automatic detection of fake reviews at marketplaces using expert-based features and consumers’ reactions by A. N. Borodulina, E. V. Mikhalkova

“…Due to the abundance of fake reviews on marketplaces, consumer trust falls not only in the seller or platform, but in the genre itself. …”
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Parameter Identification of Permanent Magnet Synchronous Motor Based on LSOSMO Algorithm by Songcan Zhang, Zhuangzhuang Zhou, Yi Pu, Yan Li, Yingxi Xu

“…So as to solve the problems of slow PMSM parameter identification using the spider monkey algorithm, and easily falling into local optimal and having unstable identification results; the LSOSMO algorithm is put forward in this article, which combines logistic–sine chaotic mapping strategy, dynamic probability adaptive t-distribution method, and an opposition-based learning strategy to determine PMSMs’ electric parameters (stator resistance <i>R_s</i>, dq-axis inductance <i>L_d</i>, <i>L_q</i>, and flux linkage <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>ψ</mi><mi>f</mi></msub></mrow></semantics></math></inline-formula>). …”
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