Evaluating Water Levels From the Surface Water and Ocean Topography (SWOT) Mission in a Hyper‐Tidal Coastal and Estuarine Environment by I. D. Lichtman, P. S. Bell, C. Gommenginger, C. Banks, F. M. Calafat, J. Brown, S. D. P. Williams

“…Here, this novel data set is evaluated in the hyper‐tidal coastal‐estuarine environment of the Bristol Channel‐Severn Estuary. …”
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Arrears behavior prediction of power users based on BP neural network and multi-scale feature learning: a refined risk assessment framework by Liang Yu, Yuanshen Hong, Hua Lin, Xu Jiang, Ziming Song

“…The experimental results demonstrate that the BP neural network model incorporating multi-scale features outperforms traditional BP neural network models and other control models in several evaluation metrics. …”
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Flow dynamics in a vertical pipe with internal fins exposed to sunlight – A machine learning based evaluation of thermal signature by Assmaa Abd-Elmonem, Zill E Shams, Mariam Imtiaz, Kashif Ali, Sohail Ahmad, Wasim Jamshed, Fayza Abdel Aziz ElSeabee, Neissrien Alhubieshi, Syed M. Hussain, Hijaz Ahmad

“…Finally, an artificial intelligence-based analysis is presented that correlates our research methodology with a Neural Fitting app. This neural network app is leveraged to enrich the accuracy of the present numerical technique and ensures a robust evaluation of the thermal signature of nanofluid flow within the pipe exposed to sunlight-induced heating.…”
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An Association Between Product Discount, Rating and Customer Service: An Empirical Study by Adeel Ansari, Seema Ansari, Ayesha Ghayas

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Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis by ShinYe Kim, Winson Fu Zun Yang, Zishan Jiwani, Emily Hamm, Shreya Singh

“…We also evaluated the predictive power of these linguistic features using machine learning and identified key thematic structures through semantic network analysis. …”
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Advancing Marine Surveillance: A Hybrid Approach of Physics Infused Neural Network for Enhanced Vessel Tracking Using Automatic Identification System Data by Tasmiah Haque, Md Asif Bin Syed, Srinjoy Das, Imtiaz Ahmed

“…This paper introduces a novel approach that leverages Long Short-Term Memory (LSTM), a type of recurrent neural network, renowned for its proficiency in recognizing patterns over extended periods. …”
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A Real-World Case Study Towards Net Zero: EV Charger and Heat Pump Integration in End-User Residential Distribution Networks by Thet Paing Tun, Oguzhan Ceylan, Ioana Pisica

“…This study evaluates the impact of heat pump and electric vehicle (EV) penetration on a UK residential distribution network, considering the highest coincident electricity demand and worst weather conditions recorded over the past decade. …”
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Mapping, intensities and future prediction of land use/land cover dynamics using google earth engine and CA- artificial neural network model. by Maysoon A A Osman, Elfatih M Abdel-Rahman, Joshua Orungo Onono, Lydia A Olaka, Muna M Elhag, Marian Adan, Henri E Z Tonnang

“…Therefore, the aims of the current study were to (1) evaluate LULC changes in the Gedaref state, Sudan for the past thirty years (1988-2018) using Landsat imageries and the random forest classifier, (2) determine the underlying dynamics that caused the changes in the landscape structure using intensity analysis, and (3) predict future LULC outlook for the years 2028 and 2048 using cellular automata-artificial neural network (CA-ANN). …”
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HCMMA-Net: A Hybrid Convolutional Multi-Modal Attention Network for Human Activity Recognition in Smart Homes Using Wearable Sensor Data by Nazish Ashfaq, Zeeshan Aziz, Muhammad Hassan Khan, Muhammad Adeel Nisar, Adnan Khalid

“…This study examines the role of multi-modalities in HAR using a hybrid convolutional multi-modal attention network (HCMMA-Net), designed to exploit spatial and temporal dependencies in sensor data. …”
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Enhancing Fault Detection and Classification in Wind Farm Power Generation Using Convolutional Neural Networks (CNN) by Leveraging LVRT Embedded in Numerical Relays by Tarek Kandil, Adam Harris, Remon Das

“…Numerical relays (NRs) are used to detect faults in power system networks and isolate the power to prevent grid instability in the event of a fault. …”
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Development of an MRI based artificial intelligence model for the identification of underlying atrial fibrillation after ischemic stroke: a multicenter proof-of-concept analysisRes... by Zijie Zhang, Yang Ding, Kaibin Lin, Wenli Ban, Luyue Ding, Yudong Sun, Chuanliang Fu, Yihang Ren, Can Han, Xue Zhang, Xiaoer Wei, Shundong Hu, Yuwu Zhao, Li Cao, Jun Wang, Saman Nazarian, Ying Cao, Lan Zheng, Min Zhang, Jianliang Fu, Jingbo Li, Xiang Han, Dahong Qian, Dong Huang

“…A combined classifier leveraging pre-defined radiomics features and de novo features extracted by convolutional neural network (CNN) was proposed to identify underlying AF in acute ischemic stroke patients. …”
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A Temporal Convolutional Network–Bidirectional Long Short-Term Memory (TCN-BiLSTM) Prediction Model for Temporal Faults in Industrial Equipment by Jinyin Bai, Wei Zhu, Shuhong Liu, Chenhao Ye, Peng Zheng, Xiangchen Wang

“…To address these issues, this paper proposes a combined prediction model based on an improved temporal convolutional network (TCN) and bidirectional long short-term memory (BiLSTM), referred to as the TCN-BiLSTM model. …”
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BlockDroid: detection of Android malware from images using lightweight convolutional neural network models with ensemble learning and blockchain for mobile devices by Emre Şafak, İbrahim Alper Doğru, Necaattin Barışçı, İsmail Atacak

“…This article presents BlockDroid, an approach that combines convolutional neural network (CNN) models, ensemble learning, and blockchain technology to increase the accuracy and efficiency of malware detection for mobile devices. …”
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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 method and application for in-situ stress in No. 8+9 coal seam, southern Shenfu block, northeastern margin of Ordos Basin by Jiawei WU, Wei TANG, Yanhe ZHU, Cunwu WANG, Yongjing TIAN, Jingyu ZI, Jianghao YANG, Xian SHI

“…The direction and magnitude of the present in-situ stress influence the propagation of hydraulic fractures in coal seams, making it a key geological parameter for coalbed methane (CBM) well network deployment and fracturing design. Accurate evaluation of the present in-situ stress direction and magnitude in coal seams is crucial for CBM exploration and development. …”
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CPS-IIoT-P2Attention: Explainable Privacy-Preserving With Scaled Dot-Product Attention in Cyber-Physical System-Industrial IoT Network by Yakub Kayode Saheed, Joshua Ebere Chukwuere

“…These mechanisms adaptively modify their emphasis to prioritize crucial features within the CPS-IIoT network traffic data, providing additional computational resources to data segments that are likely to include abnormalities and patterns that indicate security issues. …”
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Repeated net-tDCS of the hypothalamus appetite-control network enhances inhibitory control and decreases sweet food intake in persons with overweight or obesity by Theresa Ester-Nacke, Ralf Veit, Julia Thomanek, Magdalena Book, Lukas Tamble, Marie Beermann, Dorina Löffler, Ricardo Salvador, Giulio Ruffini, Martin Heni, Andreas L. Birkenfeld, Christian Plewnia, Hubert Preissl, Stephanie Kullmann

“…Conclusion: Our study suggests that modulating hypothalamic functional network connectivity patterns via net-tDCS may improve food choice and inhibitory control.…”
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Spatiotemporal data modeling and prediction algorithms in intelligent management systems by Xin Cao, Chunxiao Mei, Zhiyong Song, Hao Li, Jingtao Chang, Zhihao Feng

“…Finally, experiments were conducted using wireless network datasets to evaluate the performance of the model. …”
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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

“…The proposed approach was evaluated on a silicon carbide metal-oxide-semiconductor field-effect transistor dataset. …”
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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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