Chemometric and computational modeling of polysaccharide coated drugs for colonic drug delivery by Ahmad Khaleel AlOmari, Khaled Almansour

“…Parity plots and learning curves further validate MLP’s predictive reliability, demonstrating close alignment between actual and predicted values and efficient learning with minimal overfitting. Consequently, the MLP model emerges as the most effective approach for this predictive task, offering a robust tool for accurately modeling complex spectral data. …”
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Faster, more accurate? A feasibility study on replacing human judges with artificial intelligence in video review for the Paris Olympics Taekwondo competition by Yuncheng Zhang, Ruojie Qu, Olivier Girard

“…Additionally, the AI system reduced average review time by approximately 81% by automatically identifying critical frames.DiscussionWhile AI significantly improved efficiency and showed high consistency with expert judgments, human oversight remains crucial for ambiguous or complex cases. …”
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Nuevos modelos para la Caracterización, Detección y Diagnóstico de Fallas en Máquinas Eléctricas Rotativas by Jair Elías Araujo Vargas, Dilan Yesid Franklin Coronel, Victor Manuel Arias Ruiz

“…Physical methods and vibration analysis are currently used to detect problems, although these approaches present limitations in both accuracy and efficiency due to the subjectivity of each case and the loss of information in each case. …”
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A Review: The Application of Path Optimization Algorithms in Building Mechanical, Electrical, and Plumbing Pipe Design by Ruijun Deng, Xiaoliang Li, Yuhua Tian

“…This review systematically integrates recent advancements in path optimization algorithms for the automated layout of mechanical, electrical, and plumbing (MEP) systems within complex building environments. A hybrid optimization framework is introduced, combining the global search capability of Ant Colony Optimization (ACO) with the local refinement efficiency of the A* algorithm, enhanced by dynamic weight adjustment and context-aware mechanisms. …”
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Application of double-error correction codes to protect configuration programmable logic memory against space radiation by E. S. Lepeshkina, N. D. Kustov, V. K. Khanov

“…Due to the known SEC-DED-DAEC codes having a non-zero probability of erroneous detection and subsequent erroneous correction of a double non-adjacent error, as well as various redundancy and implementation complexities, a study was made of the most efficient code for internal scrubbing.Results. …”
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Research on the Real-Time Scoring of Chest Ring Target Based on Transfer Learning and Improved Lightweight Neural Network by Minghui Meng, Chuande Zhou

“…First, the Repvit-MobileNet block (re-parameterized depth wise separable mobile network module) is introduced into its backbone network to reduce model size and computational complexity while improving detection speed. Then, grouped shuffle convolution (GSConv) is used to reconstruct the standard down sampling convolutions in the PANFPN structure, promoting feature information extraction and fusion at bullet hole edges, reducing model computational complexity, and maintaining detection accuracy. …”
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Toward sustainability and digital resilience: A circular economy cybersecurity framework for seaports by Chalermpong Senarak

“…Notably, the deployment of modular detection systems and energy-efficient tools extends the lifecycle of technological assets, reducing environmental impact and aligning with CE objectives. …”
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Machine vision-based testing action recognition method for robotic testing of mobile application by Tao Zhang, Zhengqi Su, Jing Cheng, Feng Xue, Shengyu Liu

“…However, the difficulty of estimating multi-dimensional gestures in 2D images leads to complex algorithm steps, including tracking, detection, and recognition of dynamic gestures. …”
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Improving Malaria diagnosis through interpretable customized CNNs architectures by Md. Faysal Ahamed, Md Nahiduzzaman, Golam Mahmud, Fariya Bintay Shafi, Mohamed Arselene Ayari, Amith Khandakar, M. Abdullah-Al-Wadud, S. M. Riazul Islam

“…The SPCNN model, with 2.207 million parameters and a size of 26 MB, is more complex than PCNN but simpler than SFPCNN. Despite this, SPCNN exhibited the fastest testing times (0.00252 s), making it more computationally efficient than both PCNN and SFPCNN. …”
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Simple Yet Powerful: Machine Learning-Based IoT Intrusion System With Smart Preprocessing and Feature Generation Rivals Deep Learning by Kazim Kivanc Eren, Kerem Kucuk, Fatih Ozyurt, Omar H. Alhazmi

“…With the rapid advancements in deep learning, IoT intrusion detection systems have increasingly adopted deep learning models as the state-of-the-art solution due to their ability to handle complex data patterns. …”
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On-site quantitative analysis of As(III) and As(V) in aqueous phase using portable laser-induced fluorescence platform by Lixia Feng, Qilong Bian, Shujun Wu, Tianyu Gao, Pei Zhang, Shujian Dai, Zebing Zeng, Sheng Xie

“…Here, a fluorogenic method is developed for the efficient detection of arsenite and arsenate ions using a portable platform directly in an aqueous phase. …”
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An antifouling polydopamine-based fluorescent aptasensor for determination of arginine kinase by Yanbo Wang, Huan Li, Jinru Zhou, Fangting Wang, Yifan Qian, Linglin Fu

“…Simple yet efficient detection methods for food allergens are in urgent need to help people avoid the risks imposed by allergenic food. …”
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Algorithm for Processing X-ray Images Using Fuzzy Logic by A. S. Mannaa

“…The new system provides high accuracy, acceptable efficiency, and does not require manual correction of images. …”
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BTCP: Binary Temporal Convolutional Network-Based Data Prefetcher for Low Inference Latency and Storage Overhead by Chang Ho Ryu, Tae Hee Han

“…The efficiency of BTCP is fundamentally attributed to its binary temporal convolutional network architecture, which achieves low inference latency and storage overhead by processing memory patterns through efficient binary operations. …”
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LeafDNet: Transforming Leaf Disease Diagnosis Through Deep Transfer Learning by Tofayet Sultan, Mohammad Sayem Chowdhury, Nusrat Jahan, M. F. Mridha, Sultan Alfarhood, Mejdl Safran, Dunren Che

“…These results emphasize the potential of this advanced deep learning framework as a scalable, efficient, and highly accurate solution for early plant disease detection, providing substantial benefits for plant health management and supporting sustainable agricultural practices.…”
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Raman‐Enabled Predictions of Protein Content and Metabolites in Biopharmaceutical Saccharomyces cerevisiae Fermentations by Jeppe Hagedorn, Guilherme Ramos, Miguel Ressurreição, Ernst Broberg Hansen, Michael Sokolov, Carlos Casado Vázquez, Christos Panos

“…Its ability to provide detailed information about molecular vibrations makes it ideal for the detection and quantification of therapeutic proteins and critical control parameters in complex biopharmaceutical mixtures. …”
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Recent advances in bio-microsystem integration and Lab-on-PCB technology by Sotirios Papamatthaiou, Pavlos Menelaou, Bilal El Achab Oussallam, Despina Moschou

“…Lab-on-Printed Circuit Board (Lab-on-PCB) technology has emerged as a transformative solution, leveraging the cost-efficiency, scalability, and precision of PCB fabrication techniques. …”
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Intelligent Perception and Seam Tracking System for Thick Plate Weldments Based on Constant-Focus Optical Path by Lei Zhai, Wenze Ren, Fei Li, Rong Wu, Jinsong Lin, Jiahui Feng, Jun Zheng, Yang Liu

“…To achieve efficient and accurate thick plate welding, as well as to precisely extract and plan the paths of complex three-dimensional weld seams in large steel structures, this study introduces a novel vision-guided approach for robotic welding systems utilizing a constant-focus laser sensor. …”
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Cyberattack Resilience of Autonomous Vehicle Sensor Systems: Evaluating RGB vs. Dynamic Vision Sensors in CARLA by Mustafa Sakhai, Kaung Sithu, Min Khant Soe Oke, Maciej Wielgosz

“…We then equip each sensor with tailored defenses (e.g., adaptive median filtering for RGB and spatial clustering for DVS) and integrate a unsupervised anomaly detector (EfficientAD from anomalib) trained exclusively on benign data. …”
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Exploiting Artificial Neural Networks for the State of Charge Estimation in EV/HV Battery Systems: A Review by Pierpaolo Dini, Davide Paolini

“…Specifically, ANN models excel at detecting subtle, complex patterns that reflect battery health and performance, crucial for accurate SOC estimation. …”
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