3D-BCLAM: A Lightweight Neurodynamic Model for Assessing Student Learning Effectiveness by Wei Zhuang, Yunhong Zhang, Yuan Wang, Kaiyang He

“…However, traditional evaluation methods suffer from one sidedness in feature extraction and high complexity in model construction, often making it difficult to fully explore the deep value of emotional data. …”
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Mean pulmonary artery pressure prediction with explainable multi-view cardiovascular magnetic resonance cine series deep learning model by Li-Hsin Cheng, Xiaowu Sun, Charlie Elliot, Robin Condliffe, David G. Kiely, Samer Alabed, Andrew J. Swift, Rob J. van der Geest, David G Kiely, Lisa Watson, Iain Armstrong, Catherine Billings, Athanasios Charalampopoulos, Robin Condliffe, Charlie Elliot, Abdul Hameed, Neil Hamilton, Judith Hurdman, Allan Lawrie, Robert A Lewis, Smitha Rajaram, Alex Rothman, Andy J. Swift, Steven Wood, AA Roger Thompson, Jim Wild

“…Our aim was to estimate RHC parameters non-invasively from cardiac magnetic resonance (MR) data using deep learning models and to identify key contributing imaging features. Methods: We constructed an explainable convolutional neural network (CNN) taking cardiac MR cine series from four different views as input to predict mean pulmonary artery pressure (mPAP). …”
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Brain-Shapelet: A Framework for Capturing Instantaneous Abnormalities in Brain Activity for Autism Spectrum Disorder Diagnosis by Yijie Ren, Zhengwang Xia, Yudong Zhang, Zhuqing Jiao

“…Brain-Shapelet places greater emphasis on short-term brain activity alterations, allowing it to capture instantaneous abnormalities more effectively. It is evaluated on the ABIDE dataset and achieves a classification accuracy of 82.8%, significantly outperforming traditional brain network modeling methods. …”
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Flat-Panel-Rectenna With Broad RF Energy Harvesting Coverage for Wireless-Powered Sensor Applications by Yan Han, Eunji Kim, Han Lim Lee

“…The proposed compact rectenna is designed with a planar antenna featuring wide beamwidth and an RF-to-DC conversion network that includes a dual-voltage rectifier architecture and a customized matching network to optimize RF-to-DC conversion efficiency. …”
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Action unit based micro-expression recognition framework for driver emotional state detection by Parul Malik, Jaiteg Singh, Farman Ali, Sukhjit Singh Sehra, Daehan Kwak

“…The proposed method combines a Residual Network (ResNet18) for spatial feature extraction with a Bidirectional Long Short-Term Memory (Bi-LSTM) network for temporal pattern learning. …”
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The application of machine learning approaches to classify and predict fertility rate in Ethiopia  by Ewunate Assaye Kassaw, Biruk Beletew Abate, Bekele Mulat Enyew, Ashenafi Kibret Sendekie

“…Predictors of fertility rate were determined using the feature important techniques. The performance of models was evaluated using accuracy, area under the curve (AUC), precision, recall, F1-score, specificity, and sensitivity. …”
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Low‐Frequency Reconstruction for Full Waveform Inversion by Unsupervised Learning by Ningcheng Cui, Tao Lei, Wei Zhang

“…In this study, we employed an unsupervised learning method, namely cycle‐consistent adversarial networks (CycleGAN), to reconstruct large‐scale‐feature related low‐frequency information based on the high‐frequency input data. …”
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Forecasting Short- and Long-Term Wind Speed in Limpopo Province Using Machine Learning and Extreme Value Theory by Kgothatso Makubyane, Daniel Maposa

“…This study investigates wind speed prediction using advanced machine learning techniques, comparing the performance of Vanilla long short-term memory (LSTM) and convolutional neural network (CNN) models, alongside the application of extreme value theory (EVT) using the r-largest order generalised extreme value distribution (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>G</mi><mi>E</mi><mi>V</mi><msub><mi>D</mi><mi>r</mi></msub></mrow></semantics></math></inline-formula>). …”
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DBSF: dual-branch boundary-supplemented framework for photovoltaic power station extraction by Bo Yu, Cheng Chen, Fang Chen, Huichen Zhao, Lei Wang

“…The dual-branch boundary-supplemented framework (DBSF) is proposed to extract PV power stations from Landsat 8 imagery. DBSF features a dual-branch architecture that integrates convolutional neural networks (CNNs) for local feature extraction and transformers for global feature learning. …”
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A Contrastive Learning Framework for Vehicle Spatio-Temporal Trajectory Similarity in Intelligent Transportation Systems by Qiang Tong, Zhi-Chao Xie, Wei Ni, Ning Li, Shoulu Hou

“…The rapid development of vehicular networks has facilitated the extensive acquisition of vehicle trajectory data, which serve as a crucial cornerstone for a variety of intelligent transportation system (ITS) applications, such as traffic flow management and urban mobility optimization. …”
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Skincare Recommendation System Based on Facial Skin Type with Real-Time Weather Integration by Gabrielle Sheila Sylvagno, Theresia Herlina Rochadiani

“…The dataset exhibits diversity in skin types, allowing for a more valid evaluation of the CNN model. The training and testing process involved splitting the data into training and testing sets, with augmentation applied to the training data to enhance the feature diversity across classes. …”
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Mapping cation-eutaxy ternary with a phenomenological model by Jongbum Won, Taeyoung Kim, Minwoo Lee, Daniel W. Davies, Giyeok Lee, Aron Walsh, Aloysius Soon, Jong-Young Kim, Wooyoung Shim

“…Abstract Predicting the stability of ternary compounds poses a significant challenge due to the complex interplay of atomic features. Existing approaches often struggle to integrate these parameters into a unified framework, particularly for cation-eutaxy ABX ternary systems, where subtle compositional and bonding interactions govern the dimensionality and stability of III‒V networks. …”
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IoT enabled health monitoring system using rider optimization algorithm and joint process estimation by J. Prabin Jose, G. Jaffino, Mohammed Al Awadh, Koppula Srinivas Rao, Yan Yafang, Krishna Moorthy Sivalingam

“…The performance of the proposed method is compared with other five machine learning algorithms, including Support Vector Machine, Random Forest, Gradient Boosting, Naive Bayes, and Multilayer Perceptron neural networks. The proposed method also evaluated using PTB Diagnostic dataset signals. …”
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Automatic cervical tumors segmentation in PET/MRI by parallel encoder U-net by Shuai Liu, Zheng Tan, Tan Gong, Xiaoying Tang, Hongzan Sun, Fei Shang

“…Conclusions The networks with multi-modality input outperformed those with single-modality images as input. …”
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Classification of <i>Verticillium dahliae</i> Vegetative Compatibility Groups (VCGs) with Machine Learning and Hyperspectral Imagery by Sudha GC Upadhaya, Chongyuan Zhang, Sindhuja Sankaran, Timothy Paulitz, David Wheeler

“…Multiple machine learning algorithms, including random forest and artificial neural networks (ANNs), were trained and evaluated on previously unseen isolates. …”
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Stock movement prediction with multimodal stable fusion via gated cross-attention mechanism by Chang Zong, Jian Wan, Lucia Cascone, Hang Zhou

“…The MSGCA framework consists of three integral components: (1) a trimodal encoding module, responsible for processing indicator sequences, dynamic documents, and a relational graph, and standardizing their feature representations; (2) a cross-feature fusion module, where primary and consistent features guide the multimodal fusion of the three modalities via a pair of gated cross-attention networks; and (3) a prediction module, which refines the fused features through temporal and dimensional reduction to execute precise movement forecasting. …”
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Exploring Mental Health Content Moderation and Well-Being Tools on Social Media Platforms: Walkthrough Analysis by Zoë Haime, Lucy Biddle

“… BackgroundSocial networking site (SNS) users may experience mental health difficulties themselves or engage with mental health–related content on these platforms. …”
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Efficient Dynamic Performance Prediction of Railway Bridges Situated on Small-Radius Reverse Curves by Yumin Song, Bin Hu, Xiaoliang Meng

“…Bridges situated on small-radius reverse curves play a pivotal role within some railway networks, exerting influence over project-wide design progress. …”
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Automated violence monitoring system for real-time fistfight detection using deep learning-based temporal action localization by Baolong Qi, Baoyuan Wu, Bailing Sun

“…The RGB module uses a combination of spatial and temporal transformers to model contextual relationships and individual actions, while the bodypose-point module processes skeletal data to capture the fine-grained motion of individuals. We conduct evaluations on two public datasets: the Surveillance Camera Fight Dataset (SCFD) and the RWF-2000 dataset, which feature complex real-world scenarios. …”
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D-YOLO: A Lightweight Model for Strawberry Health Detection by Enhui Wu, Ruijun Ma, Daming Dong, Xiande Zhao

“…Key innovations include (1) replacing the original backbone with MobileNetv3 to optimize computational efficiency; (2) implementing a Bidirectional Feature Pyramid Network for enhanced multi-scale feature fusion; (3) integrating Contextual Transformer attention modules in the neck network to improve lesion localization; and (4) adopting weighted intersection over union loss to address class imbalance. …”
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