MDP-AD: A Markov decision process-based adaptive framework for real-time detection of evolving and unknown network attacks by Fucai Luo, Tingfa Xu, Jianan Li, Fengxiang Xu

“…Traditional network security measures often struggle to detect and respond to rapidly evolving attack patterns in real time. …”
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A novel wind speed prediction model based on neural networks, wavelet transformation, mutual information, and coot optimization algorithm by Faezeh Amirteimoury, Farshid Keynia, Elaheh Amirteimoury, Gholamreza Memarzadeh, Hanieh Shabanian

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scGraphformer: unveiling cellular heterogeneity and interactions in scRNA-seq data using a scalable graph transformer network by Xingyu Fan, Jiacheng Liu, Yaodong Yang, Chunbin Gu, Yuqiang Han, Bian Wu, Yirong Jiang, Guangyong Chen, Pheng-Ann Heng

“…This comprehensive approach enables the identification of subtle and previously obscured cellular patterns and relationships. Evaluated on multiple datasets, scGraphformer demonstrates superior performance in cell type identification compared to existing methods and showcases its scalability with large-scale datasets. …”
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GenCoder++: A Protocol-Aware and Adversarially Robust Adaptive Intrusion Detection Framework for Hybrid CAN-Ethernet Vehicular Networks by Mikhail Smolin

“…This paper presents GenCoder++, a robust and adaptive Intrusion Detection System (IDS) framework designed for hybrid vehicular networks that incorporates the Controller Area Network (CAN) and Ethernet protocols. …”
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Body image flexibility and embodiment in eating disorders: a mixed-methods approach combining network analysis and pilot exposure protocol by Paolo Meneguzzo, Chiara Cazzola, Francesca Buscaglia, Anna Pillan, Filippo Pettenuzzo, Patrizia Todisco

“…Network analysis revealed distinct patterns of partial correlations between variables within each group, with higher centrality for body image concerns and weight phobia in EDs. …”
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High resistance fault detection in DC microgrid using Hilbert Huang transform and vector-based ensemble optimized LSTM networks by H. K. Prashanth Kumar, Ritesh Dash, K. Jyotheeswara Reddy, Nageswara Rao Atyam, Bhabasis Mohapatra

“…This research paper investigates the integration of Long Short-Term Memory (LSTM) networks with the Hilbert-Huang Transform (HHT) model to address these limitations. …”
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Investigating the impact of the future road networks on the spatial integrations in a multicultural Pattani City, Thailand: a space syntax approach by Chompoonut Kongphunphin, Manat Srivanit, Chakarin Bejrananda, Damrongsak Rinchumphu

“…Therefore, the implications of future road network planning for the locational patterns of land-use zoning in the neighborhood centers of Pattani are vital for the development of sustainable urban centers.…”
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High-speed threat detection in 5G SDN with particle swarm optimizer integrated GRU-driven generative adversarial network by R. Shameli, Sujatha Rajkumar

“…The attack detection in 5G SDN involves Machine learning (ML) and Deep learning (DL) algorithms to analyze large volumes of network data and identify patterns indicative of attacks. …”
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Effects of different exercise modalities on blood pressure and endothelial function in prehypertension individuals: a systematic review and network meta-analysis by Yingtian Yang, Qianyu Lv, Xinzheng Hou, Yanfei Lv, Xirui Zhang, Qian Wu, Xuejiao Ye, Chenyan Yang, Mingyu Huang, Shihan Wang

“…ObjectiveTo evaluate the relative impacts of various exercise protocols on blood pressure (BP) and endothelial function in prehypertension individuals.MethodsIn this systematic review and network meta-analysis (NMA), PubMed, Cochrane Library, Web of Science, Embase, CINAHL, SPORTDiscus, and Rehabilitation & Sports Medicine databases were searched until September 12, 2024. …”
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Resting-State Brain Network Characteristics Related to Mild Cognitive Impairment: A Preliminary fNIRS Proof-of-Concept Study by Guohui Yang, Chenyu Fan, Haozheng Li, Yu Tong, Shuang Lin, Yashuo Feng, Fengzhi Liu, Chunrong Bao, Hongyu Xie, Yi Wu

“…Subject sRSFC strength and dRSFC variability coefficients were evaluated via fNIRS. The study evaluated the feasibility of using fNIRS to measure these connectivity metrics and compared resting-state brain network characteristics between the two groups. …”
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The data mining and high-performance network model of tourism electronic word of mouth for analysis of factors influencing tourists’ purchasing behavior by Wei Chen

“…The relationship among tourists, products, and word of mouth (WOM) is represented as a complex network to analyze and predict event occurrence patterns and influencing factors in tourism electronic word-of-mouth (EWOM) data. …”
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D4Care: A Deep Dynamic Memory-Driven Cross-Modal Feature Representation Network for Clinical Outcome Prediction by Binyue Chen, Guohua Liu

“…To address these challenges, we propose a deep dynamic memory-driven cross-modal feature representation network for clinical outcome prediction. Specifically, we use a Bi-directional Gated Recurrent Unit (BiGRU) network to capture dynamic features in time series data and a dual-view feature encoding model with sentence-aware and entity-aware capabilities to extract clinical text features from global semantic and local concept perspectives, respectively. …”
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Detection and Mitigation of Distributed Denial of Service Attacks Using Ensemble Learning and Honeypots in a Novel SDN-UAV Network Architecture by Mohamed Amine Ould Rabah, Hamza Drid, Yasmine Medjadba, Mohamed Rahouti

“…The combination of Software-Defined Networking (SDN) with Unmanned Aerial Vehicles (UAVs) has transformed wireless communication and data transmission. …”
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Identification of MYC and STAT3 for early diagnosis based on the long noncoding RNA-mRNA network and bioinformatics in colorectal cancer by Kunhou Yao, Hao Fan, Tiancheng Yang, Can Yang, Guibin Wang, Xingwang Li, Xin-Ying Ji, Qun Wang, Shaojiang Lv, Shihao Guo

“…Bioinformatics analysis was performed to explore lncRNA-mRNA networks, leading to the identification of five potential blood biomarkers. …”
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Automated diagnosis and classification of metacarpal and phalangeal fractures using a convolutional neural network: a retrospective data analysis study by Michael Axenhus, Anna Wallin, Jonas Havela, Sara Severin, Ablikim Karahan, Max Gordon, Martin Magnéli

“…We aimed to train and evaluate a convolutional neural network (CNN) model to diagnose metacarpal and phalangeal fractures using plain radiographs according to the AO/OTA classification system and custom classifiers. …”
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A Hybrid Method Combining Variational Mode Decomposition and Deep Neural Networks for Predicting PM2.5 Concentration in China by Senlin Li, Bo Tang, Xiaowu Deng

“…A single deep learning architecture often struggles to achieve satisfactory results for PM2.5 prediction due to the difficulty in accurately capturing hidden spatio-temporal patterns within time series. To address this issue, this study introduces a hybrid parallel method (VDPS) that combines variational mode decomposition (VMD) with single deep neural networks for PM2.5 concentration prediction. …”
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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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Understanding the ancient classic and famous prescriptions via the property of Chinese materia medica by Dan Qin, Dan Qin, He Zhang, Bin Du, Hui Wang, Ligang Liu, Yun Wang

“…Existing research predominantly focuses on individual prescriptions, and there is lack of systematic exploration of medication patterns within the official ACFPs catalog. The property of Chinese materia medica (PCMM), a multidimensional representation of medicinal properties, offers a novel perspective for systematically analyzing TCM formulas.ObjectiveIn this study, we aim to investigate the implicit medication patterns of ACFPs from the PCMM perspective, establish a feature extraction model based on the property combination of Chinese materia medica (PCCMM), and evaluate its effectiveness in representing and reconstructing ACFPs.MethodsBased on the Chinese Pharmacopoeia (ChP), we constructed a CMM–PCCMM network as the forward feature extraction process. …”
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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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Evaluating Adversarial Robustness of No-Reference Image and Video Quality Assessment Models with Frequency-Masked Gradient Orthogonalization Adversarial Attack by Khaled Abud, Sergey Lavrushkin, Dmitry Vatolin

“…Neural-network-based models have made considerable progress in many computer vision areas over recent years. …”
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