Empirical Analysis of Honeybees Acoustics as Biosensors Signals for Swarm Prediction in Beehives by Kainat Iqbal, Bayan Alabdullah, Naif Al Mudawi, Asaad Algarni, Ahmad Jalal, Jeongmin Park

“…On the other hand, CNN outperformed all the models and achieved an accuracy of 99%, using MFCC features as input data. …”
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Towards Parkinson’s Disease Detection Through Analysis of Everyday Handwriting by Jeferson David Gallo-Aristizabal, Daniel Escobar-Grisales, Cristian David Ríos-Urrego, Jesús Francisco Vargas-Bonilla, Adolfo M. García, Juan Rafael Orozco-Arroyave

“…<b>Methods:</b> Two approaches are considered: modeling of the images resulting from the strokes collected by the digital tablet and modeling of the time series yielded by the digital tablet while performing the strokes, i.e., time-dependent signals. …”
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Observation and Numerical Simulation of Cross-Mountain Airflow at the Hong Kong International Airport from Range Height Indicator Scans of Radar and LIDAR by Ying Wa Chan, Kai Wai Lo, Ping Cheung, Pak Wai Chan, Kai Kwong Lai

“…It is found that the mesoscale meteorological model alone is sufficient to capture some rapidly evolving airflow features, including the turbulence level, the waves, and the rapidly changing wind speeds. …”
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w2v-SELD: A Sound Event Localization and Detection Framework for Self-Supervised Spatial Audio Pre-Training by Orlem Lima Dos Santos, Karen Rosero, Bruno Masiero, Roberto de Alencar Lotufo

“…The proposed model follows a two-stage process: pre-training on large, unlabeled 3D audio datasets to capture high-level features, followed by fine-tuning with a smaller, labeled SELD dataset. …”
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Dynamic atrous attention and dual branch context fusion for cross scale Building segmentation in high resolution remote sensing imagery by Yaohui Liu, Shuzhe Zhang, Xinkai Wang, Rui Zhai, Hu Jiang, Lingjia Kong

“…Current Transformer-based approaches demonstrate superior long-range dependency modeling, but still suffer from the problem of progressive information loss during hierarchical feature encoding. …”
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Predictors of severe forms of rotaviral infection in children by K. D. Ermolenko, A. I. Konev, K. Yu. Ermolenko, Yu. V. Lobzin

“…The features included in the model were: the day of illness at admission, the patient’s age, prehospital prescription of antibacterial drugs, the absence of completed vaccination against RVI, and the severity of dehydration. …”
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In silico identification of potential calcium dynamics and sarcomere targets for recovering left ventricular function in rat heart failure with preserved ejection fraction. by Stefano Longobardi, Anna Sher, Steven A Niederer

“…Biomechanics were described by 16 parameters, corresponding to intracellular calcium transient, sarcomere dynamics, cardiac tissue and hemodynamics properties. The model simulated left ventricular (LV) pressure-volume loops that were described by 14 scalar features. …”
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Typology of Interaction between the International Financial Law and the EU Law by I. M. Lifshits

“…International financial law and the EU law use a model of interaction between general and special regime of international law as well as a model of implementation of international law in a domestic legal system. …”
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Physical-Abstract Bidirectional-Guided Learning for High-Resolution Radar Target Recognition by Yuying Zhu, Yinan Zhao, Zhaoting Liu, Meilin He

“…For that, this article proposes a physical-abstract bidirectional-guided learning network that leverages scattering center based physical characteristics to guide deep models training, thereby enhancing the robustness and interpretability of deep features. …”
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Prediction of Voice Therapy Outcomes Using Machine Learning Approaches and SHAP Analysis: A K-VRQOL-Based Analysis by Ji Hye Park, Ah Ra Jung, Ji-Na Lee, Ji-Yeoun Lee

“…This study aims to identify personal, clinical, and acoustic predictors of therapy outcomes based on changes in Korean voice-related quality of life (K-VRQOL) scores, as well as to compare the predictive performance of traditional regression and machine learning models. …”
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Semantic segmentation of mix loading at asphalt mixing plant based on improved U-Net by Li Dongli, Cheng Gaoli, Guo Tao, Xia Xiaohua

“…Finally, the standard convolution in the U-Net network is modified to depth-separable convolution in order to reduce the size and parameters of the model, so that the model has a lower resource consumption and a faster inference speed while maintaining a higher performance. …”
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Non-Subsampled Contourlet Transform-Based Domain Feedback Information Distillation Network for Suppressing Noise in Seismic Data by Kang Chen, Guangzhi Zhang, Cong Tang, Qi Ran, Long Wen, Song Han, Han Liang, Haiyong Yi

“…Seismic signal processing often relies on general convolutional neural network (CNN)-based models, which typically focus on features in the time domain while neglecting frequency characteristics. …”
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Deep Transfer Learning-Based Fault Diagnosis for Gearbox under Complex Working Conditions by Zitong Wan, Rui Yang, Mengjie Huang

“…In the large amount of available data, information insensitive to faults in historical data interferes in gear fault feature extraction. Furthermore, as most of the fault diagnosis models are learned from offline data collected under single/fixed working condition only, this may cause unsatisfactory performance for complex working conditions (including multiple and unknown working conditions) if not properly dealt with. …”
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Perceptually Correlated Parameters of Musical Instrument Tones by James W. BEAUCHAMP

“…Since musical signals are easier to understand in the frequency domain than the time domain, much effort has been made to perform spectral analysis and extract salient parameters, such as spectral centroids, in order to create simplified synthesis models for musical instrument sound synthesis. …”
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A Polyp Segmentation Algorithm Based on Local Enhancement and Attention Mechanism by Lanxi Fan, Yu Jiang

“…Existing methods often struggle with effective local feature extraction and modeling long-range dependencies. …”
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Proposal for an SDN-Like Innovative Metro-Access Optical Network Architecture by Tommaso Muciaccia, Vittorio M. N. Passaro

“…The present work introduces a unified metro-access optical network architecture based on some features inspired by SDN models. The essential aim is to enable bandwidth shared among different passive optical networks (PONs) in order to achieve higher adaptability to increasingly migratory and volatile traffic patterns. …”
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Hybrid Deep Learning Framework for Continuous User Authentication Based on Smartphone Sensors by Bandar Alotaibi, Munif Alotaibi

“…This research proposes a hybrid deep learning framework that combines techniques from computer vision and sequence modeling, namely, ViT-inspired patch extraction, multi-head attention, and BiLSTM networks, to authenticate users continuously from smartphone sensor data. …”
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Multistage fall detection framework via 3D pose sequences and TCN integration by Leitao Qi, Haibo Sun

“…To address this, we propose a novel multi-stage fall detection framework that integrates 3D pose sequences with temporal convolutional modeling. The framework first performs 2D human pose estimation to extract and enhance multi-scale spatial features. …”
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Automated mold defects classification in paintings: A comparison of machine learning and rule-based techniques. by Hilman Nordin, Bushroa Abdul Razak, Norrima Mokhtar, Mohd Fadzil Jamaludin, Adeel Mehmood

“…The technique leverages a feature extraction method called Derivative Level Thresholding to pinpoint suspicious regions within an image. …”
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SSATNet: Spectral-spatial attention transformer for hyperspectral corn image classification by Bin Wang, Gongchao Chen, Juan Wen, Linfang Li, Songlin Jin, Yan Li, Ling Zhou, Weidong Zhang

“…Compared to existing state-of-the-art classification methods, our model performs better on the hyperspectral corn image dataset, demonstrating its effectiveness.…”
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