Enhancing prediction of fluid-saturated fracture characteristics using deep learning super resolution by Manju Pharkavi Murugesu, Vignesh Krishnan, Anthony R. Kovscek

“…There is a trade-off between spatial and temporal resolution that limits accurate characterization of dynamics in rock features that are below spatial resolution of CT. While past literature has offered solutions to improve resolution of CT rock images, including deep learning-based algorithms, our study uniquely focuses on improving dynamic, partially and fully fluid-saturated geological images. …”
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RICE AlgebraBot: Lessons learned from designing and developing responsible conversational AI using induction, concretization, and exemplification to support algebra learning by Chenglu Li, Wanli Xing, Yukyeong Song, Bailing Lyu

“…The importance and challenge of Algebra learning is widely recognized, with students across the U.S. facing difficulties due to the subject's complexity. While extensive research has focused on enhancing Algebra learning in K-12 education, the reusability, scalability, and effectiveness of the strategies employed (e.g., manual interventions and digital tutoring platforms) remain limited. …”
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Quantitative assessment and Kirschner-wire fixation of an isolated sustentaculum tali fracture in a 7-year-old girl—a case report by Fengyong Mao, Lei Ni, Li Ju

“…Although this investigation offers valuable technical insights, multi-institutional prospective studies are warranted to establish definitive surgical criteria and standardized management algorithms.…”
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Role of Roadside Units in Cluster Head Election and Coverage Maximization for Vehicle Emergency Services by Ravneet Kaur, Robin Doss, Lei Pan, Chaitanya Singla, Selvarajah Thuseethan

“…Efficient clustering algorithms are critical for enabling the timely dissemination of emergency messages across maximum coverage areas in vehicular networks. …”
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Post-Quantum Cryptography Resilience in Telehealth Using Quantum Key Distribution by Don Roosan, Rubayat Khan, Saif Nirzhor, Fahmida Hai

“…Methods A multi-layered design approach was adopted. PQC algorithms (e.g., CRYSTALS-Dilithium) were integrated at the blockchain consensus layer to resist quantum attacks. …”
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Sedimentary microfacies prediction based on multi-point geostatistics under the constraint of INPEFA curve by Xudong Wang, Zicheng Yang, Xibao Liu, Chengyuan Yuan

“…High-order compatibility algorithms constrained the simulations, with iterative human-computer interaction refining sedimentary microfacies models for three sand groups. …”
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Low-light image enhancement method based on retinex theory and dual-tree complex wavelet transform by Yuqian Zhang, Jie Jiang, Zhan Wang, Qi Zhang, Yudi Jiang, Jun Liu, Zeyao Hou

“…Unsupervised methods, while reducing dependency on paired images, often suffer from limited data priors, leading to artifacts and subpar image quality. …”
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Flood-tech frontiers: smart but just? A systematic review of AI-driven urban flood adaptation and  associated governance challenges by Johannes Bhanye

“…Key limitations include the poor transferability of AI models across geographies, a lack of participatory design, and risks of algorithmic exclusion in already marginalized urban areas. …”
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Secondary Migration Trend Based on Basin Modeling: A Case Study of the Cambrian Petroleum System in the Tarim Basin by Yong Yue, Bin Li, Peng Wei, Xin Zhang, Kun Zhang, Yang Suju, Xu Qingqi

“…Secondary hydrocarbon migration is an important aspect of oil-gas accumulation research. While previous studies have relied on geological and fluid geochemical characteristics to predict migration direction, these results are often limited by the number of samples. …”
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Modeling the variables that influence substance consumption of people who experience homelessness in Colombia by Leandro González Támara, Sandra Patricia Barragán Moreno

“…While results reveal strong associations, they do not imply causality. …”
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Architectural Exploration and Performance Enhancement of the CVA6 RISC-V Core Using the Gem5 Simulation Framework by Umer Shahid, Muhammad Tahir, Bilal Zafar, Ayesha Ahmad, Shanzay Wasim, Bisal Saeed

“…To further enhance the architecture, we integrated machine learning algorithms to optimize performance and resource efficiency. …”
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Real-Time Polarimetric Imaging and Enhanced Deep Learning Model for Automated Defect Detection of Specular Additive Manufacturing Surfaces by Dingkang Li, Xing Peng, Hongbing Cao, Yuanpeng Xie, Shiqing Li, Xiang Sun, Xinjie Zhao

“…Defect detection technology remains a research focus in AM process monitoring. While machine learning and neural network algorithms have recently achieved significant advancements in innovative applications for AM defect detection, practical implementations still face challenges, including insufficient detection accuracy and poor system robustness. …”
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Multimodal fusion radiomic-immunologic scoring model: accurate identification of prostate cancer progression by Zhonglin Zhang, Huan Liu, Xiling Gu, Yang Qiu, Jiangqing Ma, Guangyong Ai, Xiaojing He

“…This included the Akaike Information Criterion (AIC), Maximum Relevance Minimum Redundancy (mRMR), and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms, validated through 10-fold cross-validation. …”
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A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

“…Traditional energy management methods, based on static models or heuristic algorithms, often fail to handle real-time grid dynamics, leading to suboptimal energy distribution, high operational costs, and significant energy wastage. …”
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Evaluating Network Performance in a Web-Based Augmented Reality System for Lipmatte Color Recommendation by Zulfikri Paidi, Nurhanna Md Abd Wahid, Nurzaid Muhd Zain, Mahfudzah Othman

“…This research highlights the significant potential of AR technology in modernizing the beauty shopping experience while illustrating the critical role of network performance in achieving optimal user satisfaction. …”
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Enhancing seizure detection with hybrid XGBoost and recurrent neural networks by Santushti Santosh Betgeri, Madhu Shukla, Dinesh Kumar, Surbhi B. Khan, Muhammad Attique Khan, Nora A. Alkhaldi

“…This study investigates machine learning and deep learning algorithms for seizure prediction, comparing their effectiveness on a large EEG dataset of epileptic patients. …”
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Simplifying the calibration of ecological models by using the parameter estimation tool (PEST): The Curonian Lagoon case by Burak Kaynaroglu, Mindaugas Zilius, Rasa Idzelytė, Artūras Razinkovas-Baziukas, Georg Umgiesser

“…Data from the second-year were used for model calibration, while first-year observations served for the validation of the model's performance in simulating nutrient dynamics. …”
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Unveiling the role of oxidative stress in ANCA-associated glomerulonephritis through integrated machine learning and bioinformatics analyses by Liyuan Xie, Xianying Qiu, Junya Jia, Tiekun Yan, Pengcheng Xu

“…It’s to be noted that RAC2 and ITGB2 were associated with cyclophosphamide in the AAGN glomerular compartment, while VCAM1 and VEGFA were associated with dexamethasone in the tubulointerstitial compartment. …”
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Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…Hybrid models combine the strengths of different algorithms, achieving 80–90% accuracy on average, and are particularly effective in complex, multi-faceted projects. …”
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Analyzing Post-fire Vegetation Dynamics with Ultra-high Resolution Remote Sensing Data by O. Petrov, O. Petrov, A. Medvedev

“…Co-alignment was applied to multi-temporal UAV datasets, and tree segmentation was performed using the algorithms developed for Airborne Laser Scanning (ASL) forest point clouds. …”
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