Modeling and Evaluating a Cache System in ICN Routers Using a Programmable Switch and Computers by Junji Takemasa, Yuki Koizumi, Toru Hasegawa

“…Information-centric networking (ICN) is one of promising networking architectures to replace IP because its notable feature, in-network caching, is expected to reduce about a one-third of the forever increasing Internet traffic. …”
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Binarized Neural Networks for Resource-Efficient Spike Sorting by Luca M. Meyer, Majid Zamani, Andreas Demosthenous

“…The novelty of this work resides in the developed network architecture. In comparison to previous research, this work presents a deep binarized neural network featuring two hidden layers, each containing 256 units to effectively capture the spike characteristics of complex neural data. …”
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Behavior Coding of Adolescent and Therapy Dog Interactions During a Social Stress Task by Seana Dowling-Guyer, Katie Dabney, Elizabeth A. R. Robertson, Megan K. Mueller

“…Future research should focus on identifying specific patterns of interactive behaviors between dogs and humans that predict anxiolytic outcomes.…”
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Design Guidelines for Material Extrusion of Metals (MEX/M) by Karim Asami, Mehar Prakash Reddy Medapati, Titus Rakow, Tim Röver, Claus Emmelmann

“…Geometric accuracy was quantitatively assessed through a 3D scan by comparing the manufactured parts to their original CAD models, allowing the identification of deformation patterns and shrinkage rates. Finally, the practical utility of the developed guidelines was demonstrated by successfully manufacturing an impeller designed according to the established geometric constraints. …”
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Methanol crossover and selectivity of nafion/heteropolyacid/montmorillonite nanocomposite proton exchange membranes for DMFC applications by M. Azimi, S.J. Peighambardoust

“…Methanol crossover through polymer electrolyte membranes is a critical issue and causes an important reduction of performance in DMFCs. The developed intercalated nafion/CsPW/MMT nanocomposite membranes have successfully improved the membrane barrier properties due to the unique feature of MMT which contributed to the formation of a longer pathway towards methanol across the membrane. …”
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Prediction of antibiotic resistance from antibiotic susceptibility testing results from surveillance data using machine learning by Swetha Valavarasu, Yasaswini Sangu, Tanmaya Mahapatra

“…Abstract Antimicrobial resistance is a growing global health threat, and artificial intelligence offers a promising avenue for developing advanced tools to address this challenge. …”
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lexible sensors for food monitoring. Part II: Applications by D. Luo, M. A. Nikitina, X. Xiao

“…This article attempts to critically review the present state-of-arts developments in relation to the materials, manufacturing techniques and sensing mechanisms of the devices, as well as the applications of the electrically-transduced flexible sensors. …”
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Addressing Sensor Data Heterogeneity and Sample Imbalance: A Transformer-Based Approach for Battery Degradation Prediction in Electric Vehicles by Bi Wu, Shi Qiu, Wenhe Liu

“…To tackle data heterogeneity, we developed a multimodal feature fusion strategy that effectively integrates battery sensor data from different sources and formats, including time-series charge-discharge sensor data and spectral impedance sensor measurements. …”
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Advancing sedimentation modeling in large reservoir systems: Insights from multi-scale process coupling and machine learning by Yuning Tan, Huaixiang Liu, Yongjun Lu, Zhili Wang, Wenjie Li

“…Random Forest outperformed XGBoost, Support Vector Regression, and Artificial Neural Network, demonstrating the most robust performance and the clearest feature attribution. Our climate scenario simulations revealed uneven sedimentation patterns and projected declining sedimentation rates over the next 30 years. …”
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NPP estimation by fusing geodetector and deep spatio-temporal networks by Xiaohui He, Chenqiao Yuan, Panle Li, Xijie Cheng, Mengjia Qiao, Xiaoyu He, Nan Yang, Guangsheng Zhou, Jiandong Shang

“…Specially, the IGDSNet uses the geodetector to explore geographic mechanism of NPP and then introduces the spatio-temporal long- and short-term memory networks (ST-LSTM) to obtain the deep spatio-temporal feature of NPP. Finally, we develop a novel decoder by combining self-attention unit (SAU) and 3D convolution (Conv3D) to produce the spatio-temporal distribution of NPP. …”
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Tricho-Vision: The use of computer vision in trichotaxonomy for enhancing wildlife conservation of priority species by Alloy Das, Priyanka Banerjee, Sanket Biswas, Manokaran Kamalakannan, Joydev Chattopadhyay, Dhriti Banerjee, Tanoy Mukherjee

“…The methodology integrates automated feature extraction of cuticle patterns and medulla structures, enabling high-precision species differentiation. …”
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Optimizing Sensitivity in Machine Learning Models for Pediatric Post-operative Kyphosis Prediction by Raja Ayu Mahessya, Dian Eka Putra, Rostam Ahmad Efendi, Rayendra, Rozi Meri, Riyan Ikhbal Salam, Dedi Mardianto, Ikhsan, Ismael, Arif Rizki Marsa

“…This study demonstrates the capacity of decision tree models to extract clinically meaningful patterns from small, imbalanced surgical datasets that elude conventional statistical approaches.…”
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A Hybrid Security Framework for Train-to-Ground (T2G) Communication Using DOA-Optimized BPNN Detection, Bayesian Risk Scoring, and RL-Based Response by Chaoyuan Sun, Weijiao Zhang, Peng Sun, Hui Wang, Chunhui Yang

“…This paper presents an intelligent security defense framework that integrates intrusion detection, risk scoring, and response mechanisms to enhance the security and responsiveness of the T2G communication system. First, feature selection is performed on the TON_IoT dataset to develop a Dream Optimization Algorithm (DOA)-optimized backpropagation neural network (DOA-BPNN) model for efficient anomaly detection. …”
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Predicting female football outcomes by machine learning: behavioural analysis of goals as high stress events by Aratz Olaizola, Ibai Errekagorri, Elsa Fernández, Julen Castellano, John Suckling, Karmele Lopez-de-Ipina

“…We applied a comprehensive approach that integrates spatiotemporal and behavioural data during the transitional period following goals focusing on team dynamics, including chaotic and collective behavioural analysis with entropy and fractality, spatial area, movement trajectories, and locomotor patterns. Several well-established ML models and feature extraction techniques were deployed with overall good performance of greater than 70% accuracy, with some specific methodology combinations have superior performance. …”
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Distinct Neural Activities in Hippocampal Subregions Revealed Using a High-Performance Wireless Microsystem with PtNPs/PEDOT:PSS-Enhanced Microelectrode Arrays by Peiyao Jiao, Qianli Jia, Shuqi Li, Jin Shan, Wei Xu, Yu Wang, Yu Liu, Mingchuan Wang, Yilin Song, Yulian Zhang, Yanbing Yu, Mixia Wang, Xinxia Cai

“…A custom NeuroWireless platform was developed for seamless data reception and storage. …”
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Concrete Dam Deformation Prediction Model Based on Attention Mechanism and Deep Learning by ZHANG Hongrui, CAO Xin, JIANG Chao, ZU Anjun, XU Mingxiang

“…The model successfully captures nonlinear and time-varying characteristics in concrete dam deformation processes, showing high consistency with measured deformation patterns and demonstrating excellent engineering practicality. …”
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Improving ICESat-2 photon classification and tree height estimation using Moran's I and machine learning by Mei-Kuei Lu, Sorin Popescu, Lonesome Malambo

“…Random Forest models were developed and compared, with one model incorporating Moran's I to capture spatial patterns. …”
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Examining the role of semiotics in social media-driven information campaigns by Mayor Inna Gurung, Nitin Agarwal

“…Engagement was measured by likes, while diffusion patterns followed the SEIZ epidemiological model. Findings show that posts featuring SCP symbols consistently received more interaction, even when follower counts were equal. …”
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Advances in Bract Coloration: Diversity, Pigment Synthesis, and Regulatory Mechanisms in Ornamental Plants by Xiaoyang Li, Yang Liu, Zhiquan Cai, Yiwei Zhou

“…Despite these advances, significant knowledge gaps remain in genetic inheritance patterns, epigenetic regulation, cross-pigment pathway crosstalk, and environmental modulation. …”
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An Explainable Hybrid CNN–Transformer Architecture for Visual Malware Classification by Mohammed Alshomrani, Aiiad Albeshri, Abdulaziz A. Alsulami, Badraddin Alturki

“…Visual malware classification, which transforms malware binaries into grayscale images, has emerged as a promising alternative for recognizing patterns in malicious code. This study presents a hybrid deep learning architecture that combines the local feature extraction capabilities of ConvNeXt-Tiny (a CNN-based model) with the global context modeling of the Swin Transformer. …”
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