MACA-Net: Mamba-Driven Adaptive Cross-Layer Attention Network for Multi-Behavior Recognition in Group-Housed Pigs by Zhixiong Zeng, Zaoming Wu, Runtao Xie, Kai Lin, Shenwen Tan, Xinyuan He, Yizhi Luo

“…Additionally, an Adaptive Multi-Path Attention (AMPA) mechanism integrates spatial-channel attention to enhance feature focus, ensuring robust performance in complex environments and low-light conditions. To further improve detection, a Cross-Layer Feature Pyramid Transformer (CFPT) neck employs non-upsampled feature fusion, mitigating semantic gap issues where small target features are overshadowed by large target features during feature transmission. …”
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Research on Calf Behavior Recognition Based on Improved Lightweight YOLOv8 in Farming Scenarios by Ze Yuan, Shuai Wang, Chunguang Wang, Zheying Zong, Chunhui Zhang, Lide Su, Zeyu Ban

“…A calf daily behavior dataset containing 2918 images is selected as the test benchmark through video frame extraction; a P2 small-target detection layer is introduced to improve the resolution of the input scene, which significantly improves the model recognition accuracy, and reduces the computational complexity and storage requirements of the model through the Lamp pruning method. …”
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Towards precision diagnosis: a novel hybrid DC-CAD model for lung disease detection leveraging multi-scale capsule networks and temporal dynamics by Esther Stacy E. B. Aggrey, Qin Zhen, Seth Larweh Kodjiku, Linda Delali Fiasam, Collins Sey, Chiagoziem C. Ukwuoma, Evans Aidoo, Emmanuel Osei-Mensah

“…Abstract The early detection of lung diseases, including cancer, is essential for improving patient outcomes. …”
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Enhancing Autonomous Truck Navigation in Underground Mines: A Review of 3D Object Detection Systems, Challenges, and Future Trends by Ellen Essien, Samuel Frimpong

“…Integrating autonomous haulage systems into underground mining has revolutionized safety and operational efficiency. However, deploying 3D detection systems for autonomous truck navigation in such an environment faces persistent challenges due to dust, occlusion, complex terrains, and low visibility. …”
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Highly efficient CRISPR/Cas9-RNP mediated CaPAD1 editing in protoplasts of three pepper (Capsicum annuum L.) cultivars by Hanyi Choi, Hyunjae Shin, Chan Yong Kim, Jeongbin Park, Hyeran Kim

“…We selected two sgRNAs, sgRNA2 and sgRNA5, which had high in vivo target efficiencies for the CaPAD1 gene across the three cultivars and were validated as potential off-targets in their genomes. …”
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Empirical analysis of control models for different converter topologies from a statistical perspective by Hole Shreyas Rajendra

“…Converter topologies including SEPIC, ZETA, etc. are controlled via selection of capacitive and inductive components, which assists in improving its conversion efficiency for different type of loads. …”
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Underwater Magnetic Sensors Network by Arkadiusz Adamczyk, Maciej Klebba, Mariusz Wąż, Ivan Pavić

“…This study explores the design and performance of an underwater magnetic sensor network (UMSN) tailored for intrusion detection in complex environments such as riverbeds and areas with dense vegetation. …”
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A Scalable Framework for Real-Time Network Security Traffic Analysis and Attack Detection Using Machine and Deep Learning by Zineb Maasaoui, Mheni Merzouki, Abdella Battou, Ahmed Lbath

“…This paper presents an advanced framework for real-time monitoring and analysis of network traffic and endpoint security in large-scale enterprises by addressing the increasing complexity and frequency of cyber-attacks. Our Network Security Traffic Analysis Platform employs a comprehensive technology stack including the Elastic Stack, ZEEK, Osquery, Kafka, and GeoLocation data. …”
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FED-GEM-CN: A federated dual-CNN architecture with contrastive cross-attention for maritime radar intrusion detection by Md. Alamgir Hossain

“…These findings substantiate the efficacy of the proposed system in delivering robust, energy-efficient, and privacy-aware intrusion detection tailored to the constraints of maritime radar networks. …”
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PerMSCA-YOLO: A Perceptual Multi-Scale Convolutional Attention Enhanced YOLOv8 Model for Rail Defect Detection by Jialiang Zhang, Ruiqi Zhang, Fengkai Luan, Hu Zhang

“…The innovative contribution of this research lies in its effective strategy for improving detection accuracy and real-time performance through multi-scale feature fusion and deep semantic alignment mechanisms, providing a solution that balances both precision and efficiency for defect detection in complex track environments, with substantial engineering application potential.…”
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SMS Scam Detection Application Based on Optical Character Recognition for Image Data Using Unsupervised and Deep Semi-Supervised Learning by Anjali Shinde, Essa Q. Shahra, Shadi Basurra, Faisal Saeed, Abdulrahman A. AlSewari, Waheb A. Jabbar

“…The rationale behind highlighting these models is their potential to significantly improve smishing detection rates. For instance, the high accuracy of the KNN-Flatten model suggests its applicability in real-time spam detection systems, but its computational complexity might limit scalability in large-scale deployments. …”
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Energy Distribution Optimization in Heterogeneous Networks with Min–Max and Local Constraints as Support of Ambient Intelligence by Alessandro Aloisio, Domenico D. Bloisi, Marco Romano, Cosimo Vinci

“…The approach centers on selecting the most appropriate communication protocols, such as Wi-Fi, Bluetooth, or 5G, to connect devices. …”
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Enhanced the Trans‐Cleavage Activity of CRISPR‐Cas12a Using Metal‐Organic Frameworks as Stimulants for Efficient Electrochemical Sensing of Circulating Tumor DNA by Shuai Wu, Yincheng Liu, Tianyu Zeng, Tianci Zhou, Yanting Sun, Ying Deng, Juan Zhang, Genxi Li, Yongmei Yin

“…Herein, an electrochemical biosensor based on manganese metal‐organic frameworks (MOFs)‐enhanced CRISPR (MME‐CRISPR) is proposed that enables the efficient detection of circulating tumor DNA (ctDNA). …”
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Optimal Planning of Wind-Based DG: A Two-Stage Approach Linking Penetration Factor, Turbine Type Selection, Capacity, and Power Factors to Minimize Line Losses by Sina Saboktakin, Tarek Medalel Masaud, Ehab F. El-Saadany

“…By aligning turbine type selection with the available wind resources at the site, the model maximizes energy production and operational efficiency. …”
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A Planar-Gate Graphene Field-Effect Transistor Integrated Portable Platform for Rapid Detection of Colon Cancer-Derived Exosomes by Zaiyu Zhang, Luyang Zhang, Yuting Huang, Ziran Wang, Zhongjing Ren

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Design Improvement of Permanent Magnet Motor Using Single- and Multi-Objective Approaches by Cvetkovski Goga, Petkovska Lidija

“…Engineers and academics have been actively involved in optimising these systems to achieve better performance, efficiency, and cost-effectiveness. Optimising electrical machines, including permanent magnet motors, is a complex task. …”
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An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…This approach of modifying neuron-level complexity, rather than network-level architecture, presents a potential direction for the design of future reservoir computing models for complex systems.…”
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Performance analysis of high-rate generalized space code index modulation system by BIAN Lina, ZHANG Qianyu, WU Jiayan

“…The traditional modulation symbols were replaced with the additional phase by the HR-GS-CIM system, and the genetic algorithm (GA) was used to optimize the design of the additional phase, which could acquire high energy efficiency advantage and performance advantage. At the same time, the methods of generalized and spatial indexing were introduced to jointly map select the additional phase, spreading code, and antenna lead, and a low-complexity joint mapping selection algorithm was adopted to greatly improve the system’s spectral efficiency. …”
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Individual Tree Segmentation Based on Region-Growing and Density-Guided Canopy 3-D Morphology Detection Using UAV LiDAR Data by Shihua Li, Shunda Zhao, Zhilin Tian, Hao Tang, Zhonghua Su

“…Next, the height and density information are combined to guide the selection of vertical profiles. Finally, a 3-D morphological detection is conducted on the profiles to extract the potential trees. …”
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BlockDroid: detection of Android malware from images using lightweight convolutional neural network models with ensemble learning and blockchain for mobile devices by Emre Şafak, İbrahim Alper Doğru, Necaattin Barışçı, İsmail Atacak

“…Because these methods can automatically extract meaningful features from data and efficiently learn complex relationships, they can achieve better performance in malware detection as well as in solving many other problems. …”
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