Impact of Public Space in Primary and Secondary Schools Based on Natural Visibility Ratio by Feng Liu, Hao Zhou, Jiangtao Xie, Yue Tang, Shuyu Liu

“…In recent years, the safety of primary and secondary schools has garnered considerable attention from policymakers and architects, necessitating rational design methods to develop effective strategies that optimize the campus environment. This study utilizes algorithmic simulations, spatial analysis, and statistical methods to examine the relationships between the layouts of buildings, public space morphology, and campus safety. …”
Get full text

Impacts of noise and interference on the bit error rate of the FBMC-OQAM modulation scheme in 5G systems by A. Androon, O. V. Tikhonova

“…The graphical and numerical data obtained through computer modeling demonstrates improved BER in 5G networks using FBMC-OQAM. …”
Get full text

Multi-Fidelity Machine Learning for Identifying Thermal Insulation Integrity of Liquefied Natural Gas Storage Tanks by Wei Lin, Meitao Zou, Mingrui Zhao, Jiaqi Chang, Xiongyao Xie

“…Three machine learning algorithms—Multilayer Perceptron, Random Forest, and Extreme Gradient Boosting—were evaluated to determine the optimal implementation. …”
Get full text

Remote Sensing Image Segmentation Using Vision Mamba and Multi-Scale Multi-Frequency Feature Fusion by Yice Cao, Chenchen Liu, Zhenhua Wu, Lei Zhang, Lixia Yang

“…Although segmentation algorithms based on convolutional neural networks (CNNs) or Transformers have achieved significant performance improvements, the trade-off between segmentation precision and computational complexity remains a key limitation for practical applications. …”
Get full text

Advancing Alzheimer's Therapy: Computational strategies and treatment innovations by Jibon Kumar Paul, Abbeha Malik, Mahir Azmal, Tooba Gulzar, Muhammad Talal Rahim Afghan, Omar Faruk Talukder, Samar Shahzadi, Ajit Ghosh

“…Moreover, machine learning algorithms enhance early diagnosis and enable precision medicine strategies by analyzing multi-modal datasets. …”
Get full text

The role of artificial intelligence in enhancing disaster preparedness and trauma care by Mohamad Sorani

“…Furthermore, ethical considerations such as data privacy, algorithmic bias, and equitable access are crucial to ensuring that AI-driven solutions are implemented responsibly and inclusively.This review also explores future directions for AI, including the development of sophisticated predictive models, autonomous systems for high-risk tasks, immersive training programs utilizing virtual and augmented reality, and global collaboration aimed at standardizing AI tools and practices. …”
Get full text

A Review of Vessel Time of Arrival Prediction on Waterway Networks: Current Trends, Open Issues, and Future Directions by Abdullah Al Noman, Aaron Heuermann, Stefan Wiesner, Klaus-Dieter Thoben

“…With the vast majority of global trade volume and value reliant on maritime transport, accurate prediction of vessel estimated time of arrival (ETA) is crucial for optimizing supply chain efficiency and managing logistical complexities in port operations. …”
Get full text

Workload Forecasting Methods in Cloud Environments: An Overview by Samah Aziz, Manar Kashmoola

“…We explore more sophisticated approaches like algorithms for deep learning (DL) and machine learning (ML) in addition to more conventional approaches like analysis of time series and models of regression. …”
Get full text

Intelligent gear decision method for vehicle automatic transmission system based on data mining by Yong Wang, Jianfeng Zeng, Pengfei Du, Huachao Xu

“…Subsequently, dynamic programming algorithms are employed to optimize intelligent gear decisions. …”
Get full text

Future of Alzheimer's detection: Advancing diagnostic accuracy through the integration of qEEG and artificial intelligence by Sahar Rezaei, Farzan Asadirad, Alireza Motamedi, Mohammadsadegh Kamran, Farzaneh Parsa, Haniyeh Samimi, Parna Ghannadikhosh, Mahdi Zahmatyar, Seyed Ali Hosseinzadeh, Hossein Arabi

“…This review highlights the significant potential of AI-enhanced qEEG as a non-invasive, cost-effective tool for the diagnosis of AD in its prodromal and dementia stages, while also identifying areas requiring further research to optimize its clinical application. These findings suggest that AI-enhanced qEEG analysis could revolutionize AD diagnosis, enabling earlier intervention and improved patient outcomes.…”
Get full text

Experimental and machine learning based analysis of pervious concrete enhanced with fly ash and silica fume by Siva Shanmukha Anjaneya Babu Padavala, Siva Avudaiappan, Venkatesh Noolu

“…Pervious concrete (PC) has quickly gained attention as an eco-friendly solution to urban stormwater management, offering improved drainage performance while decreasing environmental impact. …”
Get full text