An Adaptive Intrusion Detection System for Evolving IoT Threats: An Autoencoder-FNN Fusion by J. Jasmine Shirley, M. Priya

“…The Autoencoder captures and reduces the dimensionality of high-dimensional IoT network traffic data, and the FNN distinguishes between normal network behaviour and various intrusion patterns by leveraging its ability to model nonlinear relationships. …”
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A hybrid attack detection strategy for cybersecurity using moth elephant herding optimisation‐based stacked autoencoder by Abdullah Shawan Alotaibi

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Enhanced residual attention-based subject-specific network (ErAS-Net): facial expression-based pain classification with multiple attention mechanisms by Mahdi Morsali, Aboozar Ghaffari

“…This research aims to solve this issue by presenting ErAS-Net, an Enhanced Residual Attention-Based Subject-Specific Network that employs various attention mechanisms. …”
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Logging Evaluation of Mixed-sediments Reservoirs of the Lower Cambrian Canglangpu Formation in Penglai Gas Area, Central Sichuan Basin by WANG Haiqing, WANG Zeyu, LAI Qiang, LI Shurong, WU Yuyu, ZHANG Mingyong, WANG Yaqing

“…From an overall perspective, the regularity of porosity to permeability is poor, the electrical differentiation of gas abundance is fuzzy, so the traditional parameter calculation model is not applicable, and it is urgent to study an effective logging evaluation method. Using the core analysis data such as cast thin section, XRD, physical property, logging data and gas testing data, the paper studied a systematic evaluation method for calculating the mineral component by dimensionality reduction, neural network analysis and element content to mineral content inversion method, calculating porosity by variable matrix parameters on the basis of tri-porosity logging curves, calculating permeability by lithologic subdivision model, and quantitative evaluation of reservoir property, connectivity and permeability by array acoustic wave combined with electrical imaging logging, then determined the lower limit of effective reservoir and the classification standard of reservoir. …”
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A Comprehensive Method for Anomaly Detection in Complex Dynamic IoT Systems by Andrii Liashenko, Larysa Globa

“…Anomalies are subsequently identified through significant reconstruction errors, which serve as indicators of deviations from typical patterns. Experimental evaluations on the real-world PeMSD7 dataset demonstrate that the proposed TGNN + Autoencoder method improves detection accuracy by 17.33% compared to traditional methods, reduces false positives by 4.71%, and achieves a 6.02% higher F1-score relative to using TGNN or autoencoder individually. …”
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SH-SDS: a new static-dynamic strategy for substation host security detection by Yang Diao, Hui Chen, Wei Liu, Abdur Rasool

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Triboelectric Bending Sensors for AI‐Enabled Sign Language Recognition by Wei Wang, Xiangkun Bo, Weilu Li, Abdelrahman B. M. Eldaly, Lingyun Wang, Wen Jung Li, Leanne Lai Hang Chan, Walid A. Daoud

“…Herein, a smart wearable system is developed encompassing five arch‐structured self‐powered triboelectric sensors, a five‐channel data acquisition unit to collect finger bending signals, and an artificial intelligence (AI) methodology, specifically a long short‐term memory (LSTM) network, to recognize signal patterns. A slider‐crank mechanism that precisely controls the bending angle is designed to quantitively assess the sensor's performance. …”
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Pathways between childhood trauma, clinical symptoms, and functioning in new-onset psychosis: novel insights from a network analysis approach by Dimitrios Kiakos, Luis Alameda, Ines Lepreux, Caroline Conchon, Livia Alerci, Marianna Gorgellino, Nadir Mebdouhi, Teya Petrova, Philippe Golay, Lilith Abrahamyan Empson, Philippe Conus, Sandra Vieira

“…The aim of this study was to identify patterns of relationships between these three domains in first-episode psychosis (FEP). …”
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An Adaptive Convolutional Neural Network With Spatio-Temporal Attention and Dynamic Pathways (ACNN-STADP) for Robust EEG-Based Motor Imagery Classification by Aaqib Raza, Mohd Zuki Yusoff

“…Moreover, advanced deep learning models often utilize rigid architectures with fixed spatial-temporal filters, restricting their adaptability to dynamic EEG patterns. To address these challenges, this paper proposes an Adaptive Convolutional Neural Network with Spatio-Temporal Attention and Dynamic Pathways (ACNN-STADP), which introduces a novel dynamic pathway mechanism and adaptive attention strategy for robust MI-EEG decoding. …”
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Enhancing security in 6G-enabled wireless sensor networks for smart cities: a multi-deep learning intrusion detection approach by Waqar Khan, Muhammad Usama, Muhammad Shahbaz Khan, Oumaima Saidani, Hussam Al Hamadi, Noha Alnazzawi, Mohammed S. Alshehri, Jawad Ahmad

“…This hybrid approach captures spatial, temporal, and contextual patterns in network traffic, improving detection accuracy against botnets, denial-of-service (DoS) attacks, and reconnaissance threats.Results and discussionTo validate the proposed framework, we employ the Kitsune and 5G-NIDD datasets, which provide intrusion detection scenarios relevant to IoT-based and non-IP traffic environments. …”
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An Adaptive Graph Convolutional Network with Spatial Autocorrelation for Enhancing 3D Soil Pollutant Mapping Precision from Sparse Borehole Data by Huan Tao, Ziyang Li, Shengdong Nie, Hengkai Li, Dan Zhao

“…We propose an adaptive graph convolutional network with spatial autocorrelation (ASI-GCN) model to overcome this challenge. …”
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An Optimized Hybrid Framework Based on Long-Short Term Memory Neural Networks and Fourier SynchroSqueezed Transform for Photovoltaic Power Forecasting by Samer Rajah, Francisco J. Munoz, Alejandro Rodriguez

“…The model integrates the Fourier SynchroSqueezed Transform with the Long Short-Term Memory network to enhance the identification of very short-term patterns in photovoltaic power production. …”
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From improvements in accessibility to the impact on territorial cohesion: the spatial approach by Marcin Stępniak, Piotr Rosik

“…The fact that analyses conducted in the national and international dimension yielded opposite results supports the presented approach of a multidimensional evaluation of transport network development.…”
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Evaluating Time Series Models for Monthly Rainfall Forecasting in Arid Regions: Insights from Tamanghasset (1953–2021), Southern Algeria by Ballah Abderrahmane, Morad Chahid, Mourad Aqnouy, Adam M. Milewski, Benaabidate Lahcen

“…This is particularly important in arid regions like Tamanghasset, where precipitation is the primary driver of agricultural viability and water resource management. This study evaluates the performance of several time series models for monthly rainfall prediction, including the autoregressive integrated moving average (ARIMA), Exponential Smoothing State Space Model (ETS), Seasonal and Trend decomposition using Loess with ETS (STL-ETS), Trigonometric Box–Cox transform with ARMA errors, Trend and Seasonal components (TBATS), and neural network autoregressive (NNAR) models. …”
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Landslide Susceptibility Prediction Based on a CNN–LSTM–SAM–Attention Hybrid Model by Honggang Wu, Jiabi Niu, Yongqiang Li, Yinsheng Wang, Daohong Qiu

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Neural networking-based approach for examining heat transfer and bioconvection in Non-Newtonian fluid with chemical reaction over a stretching sheet by Sohaib Abdal, Talal Taha, Liaqat Ali, Rana Muhammad Zulqarnain, Se-Jin Yook

“…Afterward, an Artificial Neural Network (ANN) with Levenberg-Marquardt training evaluates the flow pattern. …”
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Morphological-Priors-Guided Network With Semantic Booster and Scalable Bins Module for Height Estimation From Single-View Remote Sensing Images by Tao Zhang, Furong Shi, Yuanping Zhu

“…Second, taking into account the height distribution priors, we propose a scalable bins module that can create fully adaptive bins within a flexible height range for each input image, leading a more accurate delineation of height distribution pattern. The proposed MPG-Net is comprehensively evaluated on two datasets of different scenes (i.e., ISPRS Vaihingen and Potsdam datasets). …”
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O PAPEL DAS INSTITUIÇÕES NO SUPORTE A INDIVÍDUOS NO DESENVOLVIMENTO DE INOVAÇÕES: by Camila Alves Damásio, Sergio Evangelista Silva, Alana Deusilan Sester Pereira

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Real-Time Co-Simulation Implementation for Voltage and Frequency Regulation in Standalone AC Microgrid with Communication Network Performance Analysis across Traffic Variations by Ola Ali, Osama A. Mohammed

“…This study employs a real-time co-simulation testbed setup that integrates OPAL-RT and network simulator (ns-3), supporting a rigorous evaluation of the interplay between the communication networks and control within the MG. …”
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PlantDeepMeth: A Deep Learning Model for Predicting DNA Methylation States in Plants by Zhongwei Guo, Wenyuan Fan, Chengcheng Cai, Kang Zhang, Xilin Hou, Ying Li, Feng Cheng

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