Lightweight SCD-YOLOv5s: The Detection of Small Defects on Passion Fruit with Improved YOLOv5s by Yu Zhou, Zhenye Li, Sheng Xue, Min Wu, Tingting Zhu, Chao Ni

“…Compared with manual detection, the proposed model enhances detection efficiency by reducing errors caused by subjective judgment. It also achieves faster inference speed (26.66 FPS), and reductions of 9.6% in parameters and 8.6% in weight size, while maintaining high detection performance. …”
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AI driven fault diagnosis approach for stator turn to turn faults in induction motors by Tamer A. Kawady, Wagdy M. Khater, Hagar G. Abu-Faty, Mohamed A. Izzularab, Mohamed E. Ibrahim

“…The proposed AI-based approach based on DNN offers high accuracy in fault detection and can effectively distinguish between ITFs and USV-induced anomalies, maintaining low estimation errors and robust performance across different operational conditions.…”
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State-of-the-Art Deep Learning Algorithms for Internet of Things-Based Detection of Crop Pests and Diseases: A Comprehensive Review by Jean Pierre Nyakuri, Celestin Nkundineza, Omar Gatera, Kizito Nkurikiyeyezu

“…Traditional inspection methods are time-consuming and prone to errors due to limited labor expertise. Therefore, to tackle these challenges, harnessing advanced technologies such as artificial intelligence (AI), Machine Learning/Deep Learning (ML/DL), and Internet of Things (IoT) is essential for managing and mitigating agriculture hazards. …”
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A Transformer–VAE Approach for Detecting Ship Trajectory Anomalies in Cross-Sea Bridge Areas by Jiawei Hou, Hongzhu Zhou, Manel Grifoll, Yusheng Zhou, Jiao Liu, Yun Ye, Pengjun Zheng

“…This approach significantly enhances the model’s ability to learn and reconstruct normal trajectory patterns, with reconstruction errors serving as the criterion for anomaly detection. …”
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Influences of noise on paddy chlorophyll mapping and associated uncertainty across heterogeneous landscapes using Sentinel-2 and hybrid models by Giang Thi Phuong Thao, Nguyen An Binh, Tong Si Son, Le Thi Thu Ha

“…With relative root mean square errors (RRMSE) below 5 %, all models provided high-fidelity mapping of paddy chlorophyll content (mean relative uncertainties below 22 %), compared to the lower confidence levels observed for non-vegetated objects (mean relative uncertainties exceeding 50 %). …”
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Outcome metrics in recommended performance measurement tools for emergency department performance evaluation: a systematic review by Tytti Kristiina Toukola, Reija Katri Kyllikki Mertanen, Johanna Marjut Kaartinen, Eeva Anneli Tuunainen, Maaret Kaarina Castrén, Paulus Mikael Torkki

“…The outcome metrics recommended can be divided into the following five dimensions: reattendances, mortality, diagnostic and procedural errors and complications, diagnosis-specific survival rates, and patient experience. …”
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Harnessing Meta-Reinforcement Learning for Enhanced Tracking in Geofencing Systems by Alireza Famili, Shihua Sun, Tolga Atalay, Angelos Stavrou

“…Our proposed meta-RL method addresses the NP-hard problem of determining an optimal placement of 5G Points to minimize spatial geometry-induced errors. Moreover, the meta-training approach enables the learned policy to quickly adapt to diverse new environments. …”
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ODD-Net: a hybrid deep learning architecture for image dehazing by C. S. Asha, Abu Bakr Siddiq, Razeem Akthar, M. Ragesh Rajan, Shilpa Suresh

“…This degradation in image quality can adversely affect various applications, including autonomous driving, object detection, and surveillance, where poor visibility may lead to navigation errors and obscure crucial details. …”
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Analog Computing for Nonlinear Shock Tube PDE Models: Test and Measurement of CMOS Chip by Hasantha Malavipathirana, Soumyajit Mandal, Nilan Udayanga, Yingying Wang, S. I. Hariharan, Arjuna Madanayake

“…Analog CMOS has power efficiency advantages over digital CMOS for low-precision applications in edge computing, scientific computing, and artificial intelligence/machine learning (AI/ML) verticals. …”
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Generalized Sampling Theory in the Quaternion Domain: A Fractional Fourier Approach by Muhammad Adnan Samad, Yuanqing Xia, Nader Al-Rashidi, Saima Siddiqui, Muhammad Younus Bhat, Huda M. Alshanbari

“…We illustrate the practical utility of the QFRFT-based GSE framework with a case study on signal denoising, demonstrating its effectiveness in noise reduction with the Mean Squared Error (MSE), highlighting the improvement in signal restoration.…”
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Ensemble-based multiclass lung cancer classification using hybrid CNN-SVD feature extraction and selection method. by Md Sabbir Hossain, Niloy Basak, Md Aslam Mollah, Md Nahiduzzaman, Mominul Ahsan, Julfikar Haider

“…The main contribution of this research lies in its use of a hybrid CNN-SVD (Singular Value Decomposition) method and the use of a robust voting ensemble approach, which results in superior accuracy and effectiveness for mitigating potential errors. By employing contrast-limited adaptive histogram equalization (CLAHE), contrast-enhanced images were generated with minimal noise and prominent distinctive features. …”
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Enhancing stochastic optimal power flow with modified cheetah optimizer for integrating renewable energy sources by Majid Saeidi, Taher Niknam, Mohsen Zare, Zulfiqar Ali Memon

“…A backward-forward correction method was used to correct errors in three types of reserves, improving the solution quality. …”
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Research on Robust Adaptive Model Predictive Control Based on Vehicle State Uncertainty by Yinping Li, Li Liu

“…The framework provides a practical solution for real-time applications in intelligent transportation systems.…”
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Do feed-in tariffs unlock green finance? A panel study of banking sector assets and renewable energy consumption across 66 countries around the world by Olena Shcherbakova

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Image-tag-based indoor localization using end-to-end learning by Mohammed Alarfaj, Zhenqiang Su, Raymond Liu, Abdulaziz Al-Humam, Huaping Liu

“…The performance of the proposed scheme is evaluated via a set of experiments in a real setting and has achieved less than 20 cm of positioning errors.…”
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Versatile waste sorting in small batch and flexible manufacturing industries using deep learning techniques by Arso M. Vukicevic, Milos Petrovic, Nebojsa Jurisevic, Marko Djapan, Nikola Knezevic, Aleksandar Novakovic, Kosta Jovanovic

“…The proposed approach has a high potential to facilitate deployment, increase productivity, lower expenses, and minimize errors in robotic waste sorting while enhancing overall recycling and material utilization in the manufacturing industry.…”
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Blockchain-Based Modified AES with Chaotic Random Key Generation for Secured E-Medical Data Sharing by Vinothkumar.M, R. Saravana Ram

“…It possesses numerous benefits like cost minimization, few medical errors with better healthcare access and tracking. …”
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The effects of limb position and grasped load on hand gesture classification using electromyography, force myography, and their combination. by Peyton R Young, Kihun Hong, Eden J Winslow, Giancarlo K Sagastume, Marcus A Battraw, Richard S Whittle, Jonathon S Schofield

“…While being well established in consumer, clinical, and research applications, this technique suffers from misclassification errors caused by limb movements and the weight of manipulated objects, both vital aspects of how we use our hands in daily life. …”
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Comparative analysis of lumped and semi-distributed hydrological models for an upland watershed in Ethiopia by Gebiaw T. Ayele, Bofu Yu

“…The model comparative analysis was supplemented by multi-model averaging using Sum of Squared Errors (SSEW) and Performance-Based Weights (PBW-NSE) to improve prediction reliability. …”
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Enhanced data-driven shear strength predictive modeling framework for RCDBs using explainable boosting-based ensemble learning algorithms coupled with Bayesian optimization by Imad Shakir Abbood, Noorhazlinda Abd Rahman, B.H. Abu Bakar

“…Consequently, the proposed data-driven framework could enhance the understanding of the SS of RCDBs and offer guidance for practical applications.…”
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