Transfer learning and multi-phase training for accurate diacritization of Arabic poetry by Gheith A. Abandah, Ashraf E. Suyyagh, Mohammad R. Abdel-Majeed

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An approach to arousal disorder classification using deformable convolution and adaptive multiscale features in EEG signals by Andia Foroughi, Fardad Farokhi, Fereidoun Nowshiravan Rahatabad, Alireza Kashaninia

“…To our knowledge, this is the first instance of such categorization achieved using a deformable convergence network. Our proposed model, a hierarchical multiscale deformable attention module, excels at detecting complex and abnormal patterns in EEG data. …”
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Soil moisture retrieval and spatiotemporal variation analysis based on deep learning by Zihan Zhang, Jinjie Wang, Jianli Ding, Jinming Zhang, Liya Shi, Wen Ma

“…Nine deep learning models, including three basic architectures (Convolutional Neural Networks (CNN), Long Short-Term Memory Networks (LSTM), Transformer) and six hybrid structures (CNN-LSTM, LSTM-CNN, CNN-with-LSTM, CNN-Transformer, GAN-LSTM, Transformer-LSTM), were systematically compared to evaluate the impact of neural network structure on model performance. …”
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AI-Driven Plant Health Assessment: A Comparative Analysis of Inception V3, ResNet-50 and ViT with SHAP for Accurate Disease Identification in Taro by Valeria Maeda-Gutiérrez, Juan José Oropeza-Valdez, Luis C. Reveles-Gómez, Cristian Padron-Manrique, Osbaldo Resendis-Antonio, Luis Octavio Solís-Sánchez, Hector A. Guerrero-Osuna, Carlos Alberto Olvera Olvera

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MangoLeafXNet: An Explainable Deep Learning Model for Accurate Mango Leaf Disease Classification by Md. Eshmam Rayed, Jamin Rahman Jim, Md Juniadul Islam, M. F. Mridha, Md Mohsin Kabir, Md. Jakir Hossen

“…Our study focuses on introducing MangoLeafXNet, a customized Convolutional Neural Network (CNN) architecture specifically tailored for the classification of mango leaf diseases, along with a healthy class. …”
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Time-Domain Versus Frequency-Embedded EEG Sequences for Sensorimotor BCI Using 1D-CNN by Simanto Saha, Mathias Baumert, Alistair Mcewan

“…This study proposed a motor imagery (MI) classification pipeline featuring a 1−dimensional convolutional neural network (1D-CNN) with different time/frequency feature representation techniques. …”
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Impact of fractures on convective-mixing characteristics of carbon dioxide in saline aquifers by Qigui TAN, Jian TIAN, Ruichao TIAN, Haoping PENG

“…It also examines CO2 behavior in large-scale fractured saline aquifers with a discrete fracture network. The results show that fractures located in the middle of saline aquifers have a dual, time-dependent effect on CO2 dissolution and diffusion, which becomes more pronounced as fracture width increases. …”
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Climate change–Drylands–Food Security Nexus in Africa: From the Perspective of Technical Advances, Challenges, and Opportunities. by Hirwa, Hubert, Fadong, Li, Qiao, Yunfeng, Measho, Simon, Muhirwa, Fabien, Tian, Chao, Leng, Peifang

“…To bridge the gap from science to policy making in the CDF nexus, it is vital to enhance the impacts and feedback of ecohydrological processes on agrarian production, ecosystem service tradeoffs and their effects on livelihoods, and regional development and preservation by optimization of the ecological water security pattern. This state-of-the-art assessment uses acquired information and knowledge to conceptually evaluate the past, current, and future impacts and risks and facilitates decision-making through the delivery of long-term sustainability and socio-ecological resilience.…”
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Water Accounting and Productivity Analysis to Improve Water Savings of Nile River Basin, East Africa: From Accountability to Sustainability. by Hirwa, Hubert, Zhang, Qiuying, Li, Fadong, Qiao, Yunfeng, Measho, Simon, Muhirwa, Fabien, Xu, Ning, Tian, Chao, Cheng, Hefa, Chen, Gang, Ngwijabagabo, Hyacinthe

“…To bridge the gap from science to policy making in the CDF nexus, it is vital to enhance the impacts and feedback of ecohydrological processes on agrarian production, ecosystem service tradeoffs and their effects on livelihoods, and regional development and preservation by optimization of the ecological water security pattern. This state-of-the-art assessment uses acquired information and knowledge to conceptually evaluate the past, current, and future impacts and risks and facilitates decision-making through the delivery of long-term sustainability and socio-ecological resilience.…”
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A Deep Learning Model for NOx Emissions Prediction of a 660 MW Coal-Fired Boiler Considering Multiscale Dynamic Characteristics by Jianrong Huang, Yanlong Ji, Haiquan Yu

“…This study applies a Multiscale Graph Convolutional Network (MSGNet) designed to capture multiscale dynamic relationships among operational parameters of a 660 MW coal-fired boiler. …”
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Prediction of Reservoir Flow Capacity in Sandstone Formations: A Comparative Analysis of Machine Learning Models by Micheal Ayodeji Ogundero, Taiwo Adelakin, Kehinde Orolu, Isaac Femi Johnson, Theophilus Akinfenwa Fashanu, Kingsley Abhulimen

“…Given a large number of input variables that enclose geological and environmental factors, the study set the correlation of these conditions to provide profound analysis and reveal profound patterns within the data. With the following supervised machine learning algorithms: Random Forest, Artificial Neural Network (ANN) and Support Vector Regression (SVR); the study modeled RFC. …”
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Qualitative changes in clinical records after implementation of pharmacist-led antimicrobial stewardship program: a text mining analysis by Keisuke Sawada, Shuji Kono, Ryo Inose, Yuichi Muraki

“…Using Python-based text mining with standardized technical terms and compound word extraction, we performed morphological analysis, co-occurrence network analysis, and hierarchical clustering to evaluate documentation patterns before and after ASP implementation in April 2018. …”
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Raman spectroscopy and bioinformatics-based identification of key genes and pathways capable of distinguishing between diffuse large B cell lymphoma and chronic lymphocytic leukemi... by Haoyue Liang, Haoyue Liang, Zhijie Cao, Zhijie Cao, Yansong Ren, Yansong Ren, Yihan Li, Yihan Li, Haoyu Wang, Haoyu Wang, Fanfan Sun, Fanfan Sun, Mei Xue, Guoqing Zhu, Guoqing Zhu, Yuan Zhou, Yuan Zhou

“…PPI network analyses and the evaluation of clustered network modules indicated the top 10 up- and down-regulated genes involved in disease onset and development. …”
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Artificial Intelligence in the New Era of Decision-Making: A Case Study of the Euro Stoxx 50 by Javier Parra-Domínguez, Laura Sanz-Martín

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Federated learning-enhanced generative models for non-intrusive load monitoring in smart homes by Yuefeng Lu, Shijin Xu, Yadong Liu, Xiuchen Jiang

“…In our method, each client trains its own generative neural network to estimate load power, while a discriminator network evaluates these estimates. …”
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An Investigation into the Utilisation of CNN with LSTM for Video Deepfake Detection by Sarah Tipper, Hany F. Atlam, Harjinder Singh Lallie

“…The integration of Convolutional Neural Network (CNN) with Long Short-Term Memory (LSTM) has proven to be a promising approach for improving video deepfake detection, achieving near-perfect accuracy. …”
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Not seeing the trees for the forest. The impact of neighbours on graph-based configurations in histopathology by Olga Fourkioti, Matt De Vries, Reed Naidoo, Chris Bakal

“…By incorporating neighboring tiles into the analysis, we examined whether contextual information improves or impairs the network’s ability to identify patterns and features critical for accurate classification. …”
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Combining Circular and Gauss-Markov Mobility Models for FANET Enhancement  by Suhad Faisal Behadili, Alyaa Safaa Abdulhameed

“…To achieve this realism and improve network performance metrics of the network, multiple Mobility Models (MMs) can be integrated, allowing UAVs to exhibit complex movement patterns that reflect real-world dynamics. …”
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Deep learning based identification of rock minerals from un-processed digital microscopic images of undisturbed broken-surfaces by M.A. Dalhat, Sami A. Osman

“…This study employed convolutional neural networks (CNNs) for the classification of rock minerals based on 3179 RGB-scale original microstructural images of undisturbed broken surfaces. …”
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A Novel Framework for Saraiki Script Recognition Using Advanced Machine Learning Models (YOLOv8 and CNN) by Hafiz Muhammad Raza Ur Rehman, Syed Arfan Haider, Hiba Faisal, Kook-Yeol Yoo, M. Z. Jhandir, Gyu Sang Choi

“…The study used Convolutional Neural Networks (CNNs) in conjunction with YOLOv8 models to address the problems of recognizing Saraiki alphabets’ primary and secondary components. …”
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