Deep Learning Approach for Classifying DDoS Attack Traffic in SDN Environments by Mohd Nadeem, Shweta Dwivedi, Rizwan Akhtar, Shameem Ahmad Ansari, Saumya Singh, Eram Fatima Siddiqui, Rajeev Kumar

“…The proposed method uses deep learning to distinguish legitimate traffic from malicious activities, leveraging key traffic flow features such as flow duration, packet size, protocol type, and byte counts. A neural network classifier analyzes this data to identify complex patterns and behaviors associated with DDoS attacks. …”
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Evaluation and Prediction of Wind Power Utilization Efficiency Based on Super-SBM and LSTM Models: A Case Study of 30 Provinces in China by Chengyu Li, Qunwei Wang, Peng Zhou

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Network analysis and experimental validation to investigate chenpi against functional dyspepsia through TLR4/MyD88 by regulating the gut microbial structure by Jinfang Hu, Jinfang Hu, Xu Wang, Xiaoqiu Guo, Wen Wen, Jin Xue, Zhengzheng Liao, Zhengzheng Liao, Lihua Chen

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Adverse childhood experiences and subsequent experiences of intimate partner violence in adulthood: a gender perspective by Zheng Tian, Nan Zhang, Yimiao Li, Yibo Wu, Lan Wang

“…‘ACE1 (Verbal abuse + physical abuse pattern)’–‘IPV3 (Partner does not care about me when I am in bad shape [not feeling well or in a bad mood])’, ‘ACE2 (Exposure to sexual assault pattern)’–‘IPV2 (Partner would have physical or sexual contact with me against my will)’, ‘ACE4 (Violent treatment of mother or stepmother + criminal acts in the family pattern)’–‘IPV1 (Partner has ever directly assaulted or hurt me with the help of an instrument)’ in the male network and ‘ACE1 (Verbal abuse + physical abuse pattern)’–‘IPV3 (Partner does not care about me when I am in bad shape [not feeling well or in a bad mood])’, ‘ACE4 (Violent treatment of mother or stepmother + criminal acts in the family pattern)’–‘IPV1 (Partner has ever directly assaulted or hurt me with the help of an instrument)’, ‘ACE3 (Substance abuse + mental illness + violent treatment of mother or stepmother pattern)’–‘IPV1 (Partner has ever directly assaulted or hurt me with the help of an instrument)’ in the female network are the three edges with the highest edge weights among the ACE and IPV edges in their networks, respectively, all displaying positive correlations. …”
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A Data-Driven Approach for Predicting Remaining Useful Life of Semiconductor Devices Based on Machine Learning and Synthetic Data Generation: A Review and Case Study on SiC MOSFETs by Yarens J. Yarenscruz, Fernando Castano, Alberto Villalonga, Madhav Mishra, Rodolfo E. Haber

“…Data-driven approaches, particularly those methods based on machine learning, are currently being used due to their ability to model complex degradation patterns without the need for explicit physical modeling. …”
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Graph-Attention Diffusion for Enhanced Multivariate Time-Series Anomaly Detection by Vadim Lanko, Ilya Makarov

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TRENDS IN HUMAN CAPITAL FORMATION AND EVALUATION OF THE INTERCONNECTION OF SOCIO-DEMOGRAPHIC PROCESSES IN RURAL AREA: A CASE STUDY OF VOLYN REGION, UKRAINE by Tetiana SHMATKOVSKA, Mykola DZIAMULYCH, Antonina GORDIICHUK, Nataliia MOSTOVENKO, Natallia CHYZH, Tetiana KOROBCHUK

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Combined metabolic phenotypes and gene expression profiles revealed the formation of terpene and ester volatiles during white tea withering process by Xuming Deng, Jun Wu, Tao Wang, Haomin Dai, Jiajia Chen, Bo Song, Shaoling Wu, Chenxi Gao, Yan Huang, Weilong Kong, Weijiang Sun

“…Three coexpression networks strongly correlated to the variation of volatile component content during withering were identified by weighted gene coexpression network analysis (WGCNA). …”
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Intrusion Detection and Mitigation Method for the Industrial Internet of Things Using Bidirectional Convolutional Long Short-Term Memory and Deep Recurrent Convolutional Q-Networks by Zhang Yan, Piyush Kumar Shukla, Prashant Kumar Shukla, Kanika Thakur, Anurag Sinha, Saifullah Khalid

“…A deep Q-network (DQN) handles attack mitigation and uses reinforcement learning to adjust to new threats. …”
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Pyramidal attention-based T network for brain tumor classification: a comprehensive analysis of transfer learning approaches for clinically reliable and reliable AI hybrid approach... by Tathagat Banerjee, Prachi Chhabra, Manoj Kumar, Abhay Kumar, Kumar Abhishek, Mohd. Asif Shah

“…To capture more prominent spatial-temporal patterns, we investigated hybrid networks, including NASNet with ANN, CNN, LSTM, and CNN-LSTM variants. …”
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Research trends among new investigators at ISOQOL: a bibliometric analysis from 2019 to 2023 by Jae-Yung Kwon, Manraj N. Kaur, Ellen B. M. Elsman, Ava Mehdipour, Lori Suet Hang Lo, Ahmed M. Y. Osman, Sandrine Herbelet, Carrie-Anne Ng, Lotte van der Weijst, on behalf of the New Investigators Special Interest Group Members

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Safety evaluation of irinotecan: a real-world disproportionality analysis using FAERS and JADER databases during the time period 2004-2024 by Siyu Lou, Huayou Chen, Zhiwei Cui, Xiyuan Zhang, Chengyu Zhu, Linmei Zhou, Yingyong Ou, Fan Zou

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Enhanced futures price-spread forecasting based on an attention-driven optimized LSTM network: integrating an improved grey wolf optimizer algorithm for enhanced accuracy by Yongli Tang, Zhenlun Gao, Zhongqi Cai, Jinxia Yu, Panke Qin

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Combining Ecological Momentary Assessment and Social Network Analysis to Study Youth Physical Activity and Environmental Influences: Protocol for a Mixed Methods Feasibility Study by Tyler Prochnow, Genevieve F Dunton, Kayla de la Haye, Keshia M Pollack Porter, Chanam Lee

“…Participants will first complete a baseline survey to report their general social network patterns and environmental perceptions. Then participants will wear an ActiGraph LEAP accelerometer and respond to EMA prompts via smartphone for 7 days. …”
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Evaluation and Optimization Strategies for Provincial Culture and Tourism Integration from the Perspective of Landscape Narrative: A Case Study of Anhui Province, China by Yunxi Hong, Li Tu, Minghe Wan

“…Based on these findings, this paper proposes targeted strategies such as building regional narrative networks, enhancing infrastructure and policy coordination, and fostering collaborative development. …”
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The Comprehensive Analysis of Weighted Gene Co-Expression Network Analysis and Machine Learning Revealed Diagnostic Biomarkers for Breast Implant Illness Complicated with Breast Ca... by Huang Z, Wang H, Pang H, Zeng M, Zhang G, Liu F

“…The validation of these results was conducted by examining gene expression patterns in the validation dataset, breast cancer cell lines, and BII-BC patients. …”
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Explainable fully automated CT scoring of interstitial lung disease for patients suspected of systemic sclerosis by cascaded regression neural networks and its comparison with expe... by Jingnan Jia, Irene Hernández-Girón, Anne A. Schouffoer, Jeska K. de Vries-Bouwstra, Maarten K. Ninaber, Julie C. Korving, Marius Staring, Lucia J. M. Kroft, Berend C. Stoel

“…Subsequently, for each level, the second network estimates the ratio of three patterns to the total lung area: the total extent of disease (TOT), ground glass (GG) and reticulation (RET). …”
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Traffic flow modelling of vehicles on a six lane freeway: Comparative analysis of improved group method of data handling and artificial neural network model by Isaac Oyeyemi Olayode, Alessandro Severino, Frimpong Justice Alex, Elmira Jamei

“…The primary objective of this study was to evaluate the predictive accuracy and efficacy of both models in replicating complex traffic patterns and to provide insights into their suitability for real-time traffic flow applications. …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…Despite advances in deep learning, existing forecasting models often struggle with the complex temporal dependencies and non-linear patterns in chiller operation data. This paper presents an innovative approach using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model optimized by the Barnacles Mating Optimizer (BMO). …”
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Evaluating Ionospheric Total Electron Content (TEC) Variations as Precursors to Seismic Activity: Insights from the 2024 Noto Peninsula and Nichinan Earthquakes of Japan by Karan Nayak, Rosendo Romero-Andrade, Gopal Sharma, Charbeth López-Urías, Manuel Edwiges Trejo-Soto, Ana Isela Vidal-Vega

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