Optimizing travel time reliability with XAI: A Virginia interstate network case using machine learning and meta-heuristics by Navid Khorshidi, Shahriar Afandizadeh Zargari, Soheil Rezashoar, Hamid Mirzahossein

“…LightGBM-GWO and CatBoost-GWO also demonstrated improvements, scoring up to 89 %. GWO outperformed other optimization methods, delivering superior accuracy with fewer control parameters. …”
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RETRACTED: Energy Efficient Digital Omnichannel Marketing Based on a Multidimensional Approach to Network Interaction by Sergey Evgenievich Barykin, Sergey Mikhailovich Sergeev, Vyacheslav Vasilyevich Provotorov, Kristina Konstantinovna Lavskaya, Andrey Viktorovich Kharlamov, Tatiana Lvovna Kharlamova

“…In this study, authors have developed omnichannel interaction algorithms based on mathematical models. The proposed approach supplements the digital twin model with economic indicators and methods. …”
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XSShield: Defending Against Stored XSS Attacks Using LLM-Based Semantic Understanding by Yuan Zhou, Enze Wang, Wantong Yang, Wenlin Ge, Siyi Yang, Yibo Zhang, Wei Qu, Wei Xie

“…Experimental evaluation shows that XSShield achieves 93% accuracy and an F1 score of 0.9266 on the GPT-4 model, improving accuracy by an average of 88.8% compared to existing solutions. …”
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Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies by Leonidas Theodorakopoulos, Aristeidis Karras, Alexandra Theodoropoulou, Georgios Kampiotis

“…Our findings ultimately inform practitioners about system efficiencies and limitations, but also the recent advances in hardware accelerators and algorithmic improvements aimed at shaping the new graph processing frontier in diverse technology domains.…”
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Research progress in predicting the conversion from mild cognitive impairment to Alzheimer’s disease via multimodal MRI and artificial intelligence by Min Ai, Yu Liu, Dan Liu, Chengxi Yan, Xia Wang, Xun Chen

“…Predicting the transition from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) has important clinical significance for dementia prevention and improving patient prognosis. Multimodal magnetic resonance imaging (MRI) techniques (including structural MRI, functional MRI, and cerebral perfusion MRI) can yield information on the morphology, structure, and function of the brain from multiple dimensions, providing a key basis for revealing the pathophysiological mechanisms during the conversion from MCI to AD. …”
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Joint Tomek Links (JTL): An Innovative Approach to Noise Reduction for Enhanced Classification Performance by Goksu Tuysuzoglu, Yunus Dogan, Elife Ozturk Kiyak, Mustafa Ersahin, Bita Ghasemkhani, Kokten Ulas Birant, Derya Birant

“…The results demonstrate that the JTL attains an average improvement of 5.33% in accuracy compared to the original classification with a random tree. …”
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MANS-Net: Multiple Attention-Based Nuclei Segmentation in Multi Organ Digital Cancer Histopathology Images by Ibtihaj Ahmad, Zain Ul Islam, Saleem Riaz, Fuzhong Xue

“…MANS-Net efficiently learns color-based, spatial, rough, and granular features, improving nuclei segmentation. We report that MANS-Net significantly outperforms state-of-the-art segmentation algorithms. …”
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Robust fault detection and classification in power transmission lines via ensemble machine learning models by Tahir Anwar, Chaoxu Mu, Muhammad Zain Yousaf, Wajid Khan, Saqib Khalid, Ahmad O. Hourani, Ievgen Zaitsev

“…This methodology provides significant advancements in fault detection capabilities, offering valuable insights for improving grid reliability and stability, and ensuring a more resilient power supply.…”
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Artificial Intelligence in Wound Care: A Narrative Review of the Currently Available Mobile Apps for Automatic Ulcer Segmentation by Davide Griffa, Alessio Natale, Yuri Merli, Michela Starace, Nico Curti, Martina Mussi, Gastone Castellani, Davide Melandri, Bianca Maria Piraccini, Corrado Zengarini

“…<b>Discussion:</b> AI-powered mobile apps offer significant potential for improving wound care by enhancing diagnostic accuracy and reducing the burden on healthcare professionals. …”
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Exploring commercial Global Navigation Satellite System (GNSS) radio occultation (RO) products for planetary boundary layer studies in the Arctic by M. Ganeshan, M. Ganeshan, D. L. Wu, J. A. Santanello, J. Gong, C. Ao, P. Vergados, K. J. Nelson

“…A minimum penetration threshold of 500 m generally suffices for determining Arctic PBLH, although a 300 m threshold improves performance of NASA-purchased Spire data. …”
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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence–Enabled ECGs by Scott Anjewierden, Donnchadh O'Sullivan, Kathryn E. Mangold, Grace Greason, Itzhak Zachi Attia, Francisco Lopez‐Jimenez, Paul A. Friedman, Samuel J. Asirvatham, Jason Anderson, Benjamin W. Eidem, Jonathan N. Johnson, Shisheer Havangi Prakash, Talha Niaz, Malini Madhavan

“…While adult‐trained models offer good performance, improvements are seen when training pediatric‐specific models.…”
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Smart Safety Helmets with Integrated Vision Systems for Industrial Infrastructure Inspection: A Comprehensive Review of VSLAM-Enabled Technologies by Emmanuel A. Merchán-Cruz, Samuel Moveh, Oleksandr Pasha, Reinis Tocelovskis, Alexander Grakovski, Alexander Krainyukov, Nikita Ostrovenecs, Ivans Gercevs, Vladimirs Petrovs

“…This paper compiles numerous industrial use cases, from bridges and tunnels to plants and power facilities, demonstrating significant improvements in inspection efficiency, data quality, and worker safety. …”
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PolSAR-MPIformer: A Vision Transformer Based on Mixed Patch Interaction for Dual-Frequency PolSAR Image Adaptive Fusion Classification by Xinyue Xin, Ming Li, Yan Wu, Xiang Li, Peng Zhang, Dazhi Xu

“…On the other hand, the DAF evaluates the classification confidence of each band and assigns different weights accordingly, which achieves reasonable utilization of the complementarity between dual-frequency data and improves classification accuracy. Experiments on four real dual-frequency PolSAR datasets substantiate the superiority of the proposed PolSAR-MPIformer over other state-of-the-art algorithms.…”
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GIS Analysis Model Integration and Service Composition Prospects by L. Ding, P. Cai, W. Huang, H. Zhang, F. Ding, W. Zhao, D. Tang, Z. Wang

“…Model ensemble techniques, rooted in machine learning and data mining, address limitations of single models by combining predictions from multiple base learners, thereby improving robustness and reducing overfitting. GIS model integration involves combining diverse spatial algorithms&mdash;such as buffer analysis, network analysis, spatial regression, and machine learning models&mdash;to tackle multifaceted geographic challenges. …”
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synax: A Differentiable and GPU-accelerated Synchrotron Simulation Package by Kangning Diao, Zack Li, Richard D. P. Grumitt, Yi Mao

“…We further demonstrate the potential of AD in enabling full posterior inference using gradient-based inference algorithms. Using synax with HMC to perform inference over a four-parameter test model, we attain a twofold improvement compared to standard random walk Metropolis–Hastings (RWMH). …”
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Advancements in Hyperspectral Imaging and Computer-Aided Diagnostic Methods for the Enhanced Detection and Diagnosis of Head and Neck Cancer by I-Chen Wu, Yen-Chun Chen, Riya Karmakar, Arvind Mukundan, Gahiga Gabriel, Chih-Chiang Wang, Hsiang-Chen Wang

“…This review underscores the transformative potential of HSI and CAD techniques in revolutionizing HNC diagnostics, facilitating more accurate and earlier detection, and improving patient outcomes.…”
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A Large-Scale Inter-Comparison and Evaluation of Spatial Feature Engineering Strategies for Forest Aboveground Biomass Estimation Using Landsat Satellite Imagery by John B. Kilbride, Robert E. Kennedy

“…We contextualize this improvement model performance by comparing to AGB models developed with multi-temporal features derived from the LandTrendr and Continuous Change Detection and Classification algorithms. …”
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A novel method for soil organic carbon prediction using integrated ‘ground-air-space’ multimodal remote sensing data by Yilin Bao, Xiangtian Meng, Huanjun Liu, Mengyuan Xu, Mingchang Wang

“…In addition, using UAV data as the baseline layer significantly improves prediction accuracy, with R2 and RPIQ increasing by 0.17 and 0.58, respectively, and RMSE decreasing by 1.09g kg−1. …”
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Validation of 12 years (2008–2019) of IASI-A CO with IAGOS aircraft observations by B. Barret, P. Loicq, E. Le Flochmoën, Y. Bennouna, J. Hadji-Lazaro, D. Hurtmans, B. Sauvage

“…This global TCC agreement between the algorithms hides significant vertical and geographical differences. …”
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FedDrip: Federated Learning With Diffusion-Generated Synthetic Image by Karin Huangsuwan, Timothy Liu, Simon See, Aik Beng Ng, Peerapon Vateekul

“…By leveraging this strategy, the pseudo-site improves model generalization across diverse datasets while preserving data privacy. …”
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