A novel research on network security situation prediction based on iteratively optimized RBF-NN by Yuqin Wu, Congqi Shen, Shungen Xiao, Wei Feng, Yexian Fan, Xiuzhuang Zhou

“…These improvements are achieved within a tolerable training time, making our method both efficient and effective for real-world NSS prediction tasks.…”
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Engineering a multi model fallback system for edge devices by Gaurav Kadve, Abishi Chowdhury, Vishal Krishna Singh, Amrit Pal

“…The growing deployment of machine learning applications in edge environments, such as IoT devices and embedded systems, has highlighted the need for efficient, resource-aware systems for edge environments. …”
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UAV-Based Structural Health Monitoring Using a Two-Stage CNN Model with Lighthouse Localization in GNSS-Denied Environments by Timothy Scott C. Chu, Joses Sorilla, Alvin Y. Chua

“…Two experiments were conducted: evaluating UAV localization accuracy and assessing the system’s ability to detect cracks and provide corresponding pose data. …”
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Anomaly Detection of Marine Diesel Engines: A Novel Approach using Transformer Neural Networks for Reconstruction and Residual Analysis by Qin Liang, Erik Vanem, Knut Erik Knutsen, Vilmar Æsøy, Houxiang Zhang

“…The test results demonstrate the ability of the proposed approach to accurately and efficiently detect anomalies in marine diesel engines. …”
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Comparison of Single-Trait and Multi-Trait GBLUP Models for Genomic Prediction in Red Clover by Johanna Osterman, Lucia Gutiérrez, Linda Öhlund, Rodomiro Ortiz, Cecilia Hammenhag, David Parsons, Mulatu Geleta

“…One solution to increase genetic gain by reducing time and increasing accuracy is genomic selection. Thus, efficient genomic prediction (GP) models need to be developed, which are unbiased to traits and harvest time points. …”
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Automated Pruning Framework for Large Language Models Using Combinatorial Optimization by Patcharapol Ratsapa, Kundjanasith Thonglek, Chantana Chantrapornchai, Kohei Ichikawa

“…The two optimizations, PSO and WOA, were evaluated for their ability to efficiently navigate the search space. …”
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Using Segmentation to Boost Classification Performance and Explainability in CapsNets by Dominik Vranay, Maroš Hliboký, László Kovács, Peter Sinčák

“…The method’s effectiveness is further highlighted by its ability to produce clear and interpretable segmentation masks, which can be used to validate the network’s focus during classification tasks. …”
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A Bacteroides thetaiotaomicron genetic locus encodes activities consistent with mucin O-glycoprotein processing and N-acetylgalactosamine metabolism by Didier A. Ndeh, Sirintra Nakjang, Kurt J. Kwiatkowski, Claire Sawyers, Nicole M. Koropatkin, Robert P. Hirt, David N. Bolam

“…Central to microbiota survival is the ability to metabolise complex dietary and host-derived glycans, including intestinal mucins. …”
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A Novel Dual-Channel Hybrid Attention Model for Wind Turbine Misalignment Fault Diagnosis by Tong Tong, Xiang Liu, Jia Zhang, Dian Long, Teng Fan, Xiangyang Zheng

“…The model innovatively introduces the multi-head attention mechanism (MHA) in the jump connection of the U-Net architecture to form hybrid U-Net and optimizes the feature fusion process with dynamically learnable weights, which significantly enhances the ability to capture local details and key fault features. …”
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Large-Scale Hyperspectral Image-Projected Clustering via Doubly Stochastic Graph Learning by Nian Wang, Zhigao Cui, Yunwei Lan, Cong Zhang, Yuanliang Xue, Yanzhao Su, Aihua Li

“…Therefore, our HPCDL has the ability to deal with large-scale HSI datasets. Experiments on three datasets demonstrate the superiority of our HPCDL for both clustering performance and the time burden.…”
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A Comparative Study of RANS and PANS Turbulence Models for Flow Characterization Around the Joubert BB2 Submarine by Changhun Lee, Hyeri Lee, Woochan Seok

“…The PANS model consistently outperformed RANS in accurately predicting total resistance and resolving wake asymmetry, especially at medium grid resolution, due to its ability to partially resolve turbulence without full reliance on eddy viscosity assumptions. …”
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TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…In automatic driving systems, accurate and efficient object detection is essential to ensure driving safety and improve the driving experience. …”
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The Effect of Processing of Hempseed on Protein Recovery and Emulsification Properties by Anne Pihlanto, Markus Nurmi, Nora Pap, Jarkko Mäkinen, Sari Mäkinen

“…Germinated samples demonstrated a higher ability to stabilise emulsions (15-20%) than other pretreated samples. …”
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Prospects of Hydrogels in Agriculture for Enhancing Crop and Water Productivity under Water Deficit Condition by Sanmay Kumar Patra, Ratneswar Poddar, Marian Brestic, Pravat Utpal Acharjee, Parijat Bhattacharya, Sudip Sengupta, Payel Pal, Nyape Bam, Barun Biswas, Viliam Barek, Peter Ondrisik, Milan Skalicky, Akbar Hossain

“…It has the extraordinary ability in improving different physicochemical, hydrophysical, and biological properties of soil, simultaneously decreasing irrigation frequency, enhancing the water and nutrient use efficiencies, and increasing the yield and quality of the field, plantation, ornamental, and vegetable crops. …”
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The impact of LLM chatbots on learning outcomes in advanced driver assistance systems education by Mohsin Murtaza, Chi-Tsun Cheng, Bader M. Albahlal, Muhana Magboul Ali Muslam, Mansoor Syed Raza

“…This adaptability was evident across diverse educational backgrounds among young adult participants, showcasing the tool’s ability to bridge knowledge gaps more efficiently than conventional methods. …”
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Spatial-temporal upsampling graph convolutional network for daily long-term traffic speed prediction by Song Zhang, Yanbing Liu, Yunpeng Xiao, Rui He

“…Therefore, STUGCN not only preserves the local spatial-temporal correlations, but also has the ability to learn global spatial-temporal correlations. …”
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Physicochemical characterization of oxisol subjected to succession culture by Adryel K. O. A. Laurindo, Alex O. Smaniotto, Lucas M. de Morais, Thiago L. Silva, Darly G. de Sena Júnior, Simério C. S. Cruz

“…Pearl millet cycled K efficiently, providing the soil with K concentrations equivalent to those of the K fertilization treatments. …”
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Machine learning for detoxification of aflatoxin M1 by Lactococcus lactis probiotic in kashk production by Maryam Jafari, Roshanak Rafiei Nazari, Mohammad Rezaei, Mojtaba Moazzen, Nabi Shariatifar

“…A model of ANN (Artificial Neural Network) and PCA (principal component analysis) are employed to efficiently address the intricate challenge of detoxifying AFM1 with the aid of L. lactis. …”
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Reinforcement Learning-Based Control for Robotic Flexible Element Disassembly by Benjamín Tapia Sal Paz, Gorka Sorrosal, Aitziber Mancisidor, Carlos Calleja, Itziar Cabanes

“…Traditional control systems struggle to handle these tasks efficiently, requiring adaptable solutions that can operate in unstructured environments that provide online adaptation. …”
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A Multimodal Large Language Model Framework for Intelligent Perception and Decision-Making in Smart Manufacturing by Tianyu Wang, Bowen Zhang, Daqi Jiang, Dong Li

“…In modern manufacturing, making accurate and timely decisions requires the ability to effectively handle multiple types of data. …”
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