Experimental Study on Pore Structure Quantitative Characterization and Enhanced Oil Recovery During Air/CO2 Flooding of Shale Reservoir With Online NMR by Chuanyi Tang, Meng Du, Jiaxing Liu, Lei Bai, Hui Tian, Zhihong Li, Liang Xu, Qiang Luo, Hongxian Liu, Liguo Zhou, Zhengming Yang

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Spectroscopic and Imaging Technologies Combined with Machine Learning for Intelligent Perception of Pesticide Residues in Fruits and Vegetables by Haiyan He, Zhoutao Li, Qian Qin, Yue Yu, Yuanxin Guo, Sheng Cai, Zhanming Li

“…Pesticide residues in fruits and vegetables pose a serious threat to food safety. Traditional detection methods have defects such as complex operation, high cost, and long detection time. …”
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Development of a Machine‐Learning Model for Diagnosis of Pancreatic Cancer from Serum Samples Analyzed by Thermal Liquid Biopsy by Sonia Hermoso‐Durán, Nicolas Fraunhoffer, Judith Millastre‐Bocos, Oscar Sanchez‐Gracia, Pablo F. Garrido, Sonia Vega, Ángel Lanas, Juan Iovanna, Adrián Velázquez‐Campoy, Olga Abian

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Research and Experiment on a Chickweed Identification Model Based on Improved YOLOv5s by Hong Yu, Jie Zhao, Xiaobo Xi, Yongbo Li, Ying Zhao

“…This research can provide theoretical and technical support for efficient identification of weeds in complex field environments.…”
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Decoupling and Collaboration: An Intelligent Gateway-Based Internet of Things System Architecture for Meat Processing by Jun Liu, Chenggang Zhou, Haoyuan Wei, Jie Pi, Daoying Wang

“…This architecture is centered around an intelligently decoupled gateway design and edge-cloud collaborative intelligent meat inspection. Pork freshness detection is used as an example. In this paper, a high-precision and lightweight pork freshness detection model is developed by optimizing the MobileNetV3 model with Efficient Channel Attention (ECA). …”
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Deep Learning Techniques for Fault Diagnosis in Interconnected Systems: A Comprehensive Review and Future Directions by Nawel Said, Majdi Mansouri, Rami Al Hmouz, Atef Khedher

“…As systems in industry become increasingly interconnected and sophisticated, the task of fault detection and diagnosis becomes significantly more difficult. …”
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Class and Data-Incremental Learning Framework for Baggage Threat Segmentation via Knowledge Distillation by Ammara Nasim, Saad Mazhar Khan, Anum Abdul Salam, Arslan Shaukat, Taimur Hassan, Adeel M. Syed, Muhammad Usman Akram

“…Researchers have proposed multiple automated threat detection systems to enhance security screening efficiency; however, automated baggage threat segmentation remains a complex task, especially in the context of multi-class threat detection across diverse datasets. …”
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Brain functional connectivity analysis of fMRI-based Alzheimer's disease data by Maitha S. Alarjani, Badar A. Almarri

“…Feeding ELM with MVPA features yield decent outcomes given a generalizable and computationally-efficient model. This study underscores the effectiveness of the proposed approach in accurately distinguishing AD stages, offering potential improvements in AD and AD stages detection.…”
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Critical Role of Surface Properties in Passive Interstitial Fluid Extraction Using Polymeric Hollow Microneedles for Wearable Diagnostics by Ipek Atay, Emel Yilgör, Gürdeniz Neşer, Taher Abbasiasl, M. Baris Yagci, Iskender Yilgör, Levent Beker

“…Abstract Efficient sampling of dermal interstitial fluid (ISF) is essential for continuous monitoring of biomarkers for early detection and management of chronic diseases. …”
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Attribute-based lightweight reconfigurable access control policy by Rongna XIE, Hui LI, Guozhen SHI, Yunchuan GUO

“…Aiming at the severe challenges of access control policy redundancy and conflict detection,the efficiency of access control policy evaluation in complex network environment,an attribute-based lightweight reconfigurable access control policy was proposed.Taking the attribute-based access control policy as an example,the attribute-based access control policy was divided into multiple disjoint atomic access control rules according to the operation type,subject attribute,object attribute,and environment attribute in the access control policy.Complex access control policies were constructed through atomic access control rules and an algebraic expression formed by AND,OR logical relationships.A method for redundancy and collision detection of atomic access control rules was proposed.A method was proposed for decompose a complex access control policy into equivalent atomic access control rules and an algebraic expression.The method for redundancy and collision detection of complex access control policies were proposed through redundancy and collision detection of equivalent atomic access control rules and algebraic expressions.From time complexity and space complexity,the efficiency of the equivalent transformation access control policy was evaluated.It showes that the reconstruction method for access control policy greatly reduces the number,size and complexity of access control policy,improves the efficiency of access control policy redundancy and collision detection,and the efficiency of access control evaluation.…”
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Integrating Deep Transfer Learning and Image Enhancement for Enhancing Defective Photovoltaic Cells Classification in Electroluminescence Images by Hanim Suraya Mohd Mokhtar, Aimi Salihah Abdul Nasir, Mohammad Faridun Naim Tajuddin, Muhammad Hafeez Abdul Nasir, Kumuthawathe Ananda Rao

“…The rapid growth of photovoltaic (PV) systems has highlighted the need for efficient and reliable defect detection to maintain system performance. …”
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Autonomous vehicle surveillance through fuzzy C-means segmentation and DeepSORT on aerial images by Asifa Mehmood Qureshi, Moneerah Alotaibi, Sultan Refa Alotaibi, Dina Abdulaziz AlHammadi, Muhammad Asif Jamal, Ahmad Jalal, Bumshik Lee

“…After segmentation, we employed the YOLOv4 deep learning algorithm, which is efficient in detecting small-sized objects in vehicle detection. …”
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Bolt Anchorage Quality Levels Classification Method Based on HO‐VMD‐CNN‐BiLSTM by Fan Kesong, Zhang Can, Liu Shaowei, Feng Mengyin, Yan Ao, Fu Mengxiong, He Deyin, Nie Zhibin

“…The model accurately identifies internal defects in bolts through precise signal decomposition and feature extraction, achieving a high classification accuracy of 96.78% even in a complex noise environment. The model incorporates the Logistic‐Tent chaotic mapping optimization algorithm, which enhances global search capability, improves feature extraction, and increases detection efficiency and accuracy. …”
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Acoustic virtual sensors for industrial process monitoring using non-negative matrix factorization by Clara Luzon-Alvarez, Maximo Cobos, Jesus Lopez-Ballester, Ana M. Torres-Aranda, Francesc J. Ferri

“…Abstract In modern industrial environments, efficient and non-invasive monitoring of machinery operations is crucial for ensuring process optimization and early fault detection. …”
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Algorithm for pixel-level concrete pavement crack segmentation based on an improved U-Net model by Zixuan Zhang, Yike He, Di Hu, Qiang Jin, Manxu Zhou, Zongwei Liu, Hongli Chen, He Wang, Xinchen Xiang

“…Among the seven comparison models, U-Net-FML has the strongest overall performance, highlighting its engineering value for precise detection and efficient analysis of cracks.…”
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On the Usage of Deep Learning Techniques for Unmanned Aerial Vehicle-Based Citrus Crop Health Assessment by Ana I. Gálvez-Gutiérrez, Frederico Afonso, Juana M. Martínez-Heredia

“…This work proposes an end-to-end solution for leaf segmentation, disease detection, and damage quantification, specifically focusing on citrus crops. …”
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An intelligent prediction method for rock core integrity based on deep learning by Zhaoxia Hu, Hua Mei, Lei Yu

“…In IDA-RCF, a two-branch feature extraction network is firstly proposed, in which branch one is used to fully extract the complex and variable local detail fissure features by Deformable convolution, and branch two is used to capture the global context information of the rock core images by EfficientViT network based on the self-attention. …”
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Automated multi-class MRI brain tumor classification and segmentation using deformable attention and saliency mapping by Erfan Zarenia, Amirhossein Akhlaghi Far, Khosro Rezaee

“…This study presents a highly promising approach for the automated classification and segmentation of brain tumors in medical imaging, offering significant advancements for diagnostic imaging clinics and paving the way for more efficient, accurate, and scalable tumor detection methodologies.…”
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Tomato Yield Estimation Using an Improved Lightweight YOLO11n Network and an Optimized Region Tracking-Counting Method by Aichen Wang, Yuanzhi Xu, Dong Hu, Liyuan Zhang, Ao Li, Qingzhen Zhu, Jizhan Liu

“…Accurate and effective fruit tracking and counting are crucial for estimating tomato yield. In complex field environments, occlusion and overlap of tomato fruits and leaves often lead to inaccurate counting. …”
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A Facile Method for Screening DPP IV Inhibitors in Living Cell System Based on Enzyme Activity Probe by Shu-Mei Pan, Chun-Yu Xing, Hong-Wei Li, Rui-Min Wang, Xin-Yue Pu, Tie-Gang Wang, Dan-Dan Wang, Li-Wei Zou

“…In conclusion, a straightforward and user-friendly method has been developed for detecting DPP IV activity in live cells, enabling accurate assessment of DPP IV function and efficient screening of inhibitors. …”
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