PM2.5 Forecasting at U.S. Embassies and Consulates Worldwide Using NASA Model Powered by Machine Learning by Junhyeon Seo, Alqamah Sayeed, Seohui Park, John Kerekes, Stephanie M. Christel, Mary T. Tran, Pawan Gupta

“…Hybrid monitoring (surface, satellite, and models) offers a scalable, cost‐effective solution for tracking pollution and trends. …”
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Improving SOC estimation in low-relief farmlands using time-series crop spectral variables and harmonic component variables based on minimum sample size by Chenjie Lin, Ling Zhang, Nan Zhong

“…Additionally, few studies have considered the sample size in modeling SOC estimation, which may lead to precision loss and cost waste. Therefore, this study proposed a novel method to improve SOC estimation in low-relief farmlands. …”
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Machine learning frameworks to accurately predict coke reactivity index by Ayat Hussein Adhab, Morug Salih Mahdi, Krunal Vaghela, Anupam Yadav, Jayaprakash B, Mayank Kundlas, Ankur Srivastava, Jayant Jagtap, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…Precisely forecasting coke reactivity index (CRI) plays a critical role in the metallurgical industry, as it enables optimization of coke quality, leading to cost-effective production and efficient resource utilization. …”
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Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders by Muhammad Sajid, Kaleem Razzaq Malik, Ateeq Ur Rehman, Tauqeer Safdar Malik, Masoud Alajmi, Ali Haider Khan, Amir Haider, Seada Hussen

“…In vision, attention is used in conjunction with convolutional networks or to replace individual convolutional network elements while preserving the overall network design. …”
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Explainable MRI-Based Ensemble Learnable Architecture for Alzheimer’s Disease Detection by Opeyemi Taiwo Adeniran, Blessing Ojeme, Temitope Ezekiel Ajibola, Ojonugwa Oluwafemi Ejiga Peter, Abiola Olayinka Ajala, Md Mahmudur Rahman, Fahmi Khalifa

“…Many approaches presented in the AI and medical literature for overcoming this critical weakness are sometimes at the cost of sacrificing accuracy for interpretability. …”
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A Study on the Lightweight and Fast Response GRU Techniques for Indoor Continuous Motion Recognition Based on Wi-Fi CSI by Kyongseok Jang, Chao Sun, Junhao Zhou, Yongbin Seo, Youngok Kim, Seyeong Choi

“…Additionally, it demonstrates comprehensively improved performance compared to other time-series models in terms of weight reduction, computational cost, and fast response (the model’s ability to respond quickly to input) speed. …”
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Joint Adaptive Resolution Selection and Conditional Early Exiting for Efficient Video Recognition on Edge Devices by Qingli Wang, Chengwu Yu, Shan Chen, Weiwei Fang, Naixue Xiong

“…Deep learning has shown its remarkable performance in video analytics, by applying 2D or 3D Convolutional Neural Networks (CNNs) across multiple video frames. …”
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A New Modeling Method for Meteorological Information of Regional Distributed Photovoltaic Power Generation Based on Multi‐Source Information Fusion by Yuhang Wang, Dengxuan Li, Wenwen Ma, Xi Zhang, Honglu Zhu

“…Consequently, developing effective, reliable, and cost‐efficient meteorological information computation methods for DPV has become a critical research focus. …”
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A Method for Recognizing Dead Sea Bass Based on Improved YOLOv8n by Lizhen Zhang, Chong Xu, Sai Jiang, Mengxiang Zhu, Di Wu

“…Existing object detection algorithms, when applied to the task of detecting dead sea bass, often suffer from excessive model complexity, high computational cost, and reduced accuracy in the presence of occlusion. …”
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Assessment of Vegetation Indices Derived from UAV Imagery for Weed Detection in Vineyards by Fabrício Lopes Macedo, Humberto Nóbrega, José G. R. de Freitas, Miguel A. A. Pinheiro de Carvalho

“…., Random Forest and Convolutional Neural Networks) to enhance robustness and generalization. …”
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Accelerating Deep Learning-Based Morphological Biometric Recognition with Field-Programmable Gate Arrays by Nourhan Zayed, Nahed Tawfik, Mervat M. A. Mahmoud, Ahmed Fawzy, Young-Im Cho, Mohamed S. Abdallah

“…It operates independently of an internet connection, making it a standalone system and saving costs.…”
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Enhancement and evaluation for deep learning-based classification of volumetric neuroimaging with 3D-to-2D knowledge distillation by Hyemin Yoon, Do-Young Kang, Sangjin Kim

“…However, due to the nature of the medical domain, there are limitations in the number of data available. This is because the cost of acquiring imaging is expensive and the use of personnel to annotate diagnostic labels is resource-intensive. …”
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Implementation of Chernobyl disaster optimizer based feature selection approach to predict software defects [version 2; peer review: 2 approved, 1 not approved] by Himansu Das, Ajay Kumar Jena, Kunal Anand

“…However, these models have drawbacks like high cost, local optima trap, lower convergence rate, and higher parameter tuning. …”
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YOLOv8-MFD: An Enhanced Detection Model for Pine Wilt Diseased Trees Using UAV Imagery by Hua Shi, Yonghang Wang, Xiaozhou Feng, Yufen Xie, Zhenhui Zhu, Hui Guo, Guofeng Jin

“…Compared to baseline models such as YOLOv8 and YOLOv10, our method achieves higher accuracy while maintaining acceptable computational cost (11.8 GFLOPs) and a compact model size (10.2 MB). …”
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Tunable Energy-Efficient Approximate Circuits for Self-Powered AI and Autonomous Edge Computing Systems by Shubham Garg, Kanika Monga, Nitin Chaturvedi, S. Gurunarayanan

“…However, the accuracy in computations came with an additional cost of increased computational resources and power consumption in traditional computing units. …”
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Harnessing clinical annotations to improve deep learning performance in prostate segmentation. by Karthik V Sarma, Alex G Raman, Nikhil J Dhinagar, Alan M Priester, Stephanie Harmon, Thomas Sanford, Sherif Mehralivand, Baris Turkbey, Leonard S Marks, Steven S Raman, William Speier, Corey W Arnold

“…<h4>Purpose</h4>Developing large-scale datasets with research-quality annotations is challenging due to the high cost of refining clinically generated markup into high precision annotations. …”
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Wheat Leaf Disease Detection: A Lightweight Approach with Shallow CNN Based Feature Refinement by Oumayma Jouini, Mohamed Ould-Elhassen Aoueileyine, Kaouthar Sethom, Anis Yazidi

“…In this paper, we propose CropNet, a hybrid method that utilizes Red, Green, and Blue (RGB) imaging and a transfer learning approach combined with shallow convolutional neural networks (CNN) for further feature refinement. …”
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Precision in practice: exploring the impact of ai and machine learning on ultrasound guided regional anaesthesia by Noor Ul Huda Bhatti, Syed Ghazi Ali Kirmani, Maryam Butt

“…Its benefits include, being non-invasive, cost-effective, readily accessible, and providing the anaesthetist with clear visualization of essential anatomical landmarks, needle progression, and the spread of local anaesthetic. …”
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Design and Research on a Reed Field Obstacle Detection and Safety Warning System Based on Improved YOLOv8n by Yuanyuan Zhang, Zhongqiu Mu, Kunpeng Tian, Bing Zhang, Jicheng Huang

“…Compared to other algorithms, the proposed model maintains an optimal balance between parameter efficiency, computational cost, detection speed, and accuracy, exhibiting distinct advantages. …”
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Revolutionizing sleep disorder diagnosis: A Multi-Task learning approach optimized with genetic and Q-Learning techniques by Soraya Khanmohmmadi, Toktam Khatibi, Golnaz Tajeddin, Elham Akhondzadeh, Amir Shojaee

“…However, diagnosing sleep disorders with high accuracy based solely on electroencephalogram (EEG) signals, rather than using various signals in a complex PSG, can reduce the time and cost required, and the need for specialized signal devices, as well as increase accessibility and usability. …”
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