Sensor Fusion for Enhancing Motion Capture: Integrating Optical and Inertial Motion Capture Systems by Hailey N. Hicks, Howard Chen, Sara A. Harper

“…This study aimed to create and evaluate an optimization-based sensor fusion algorithm that combines Optical Motion Capture (OMC) and Inertial Motion Capture (IMC) measurements to provide a more efficient and reliable gap-filling process for OMC measurements to be used for future research. …”
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Recognition and Parameter Extraction of One-Dimensional Electronic Scanning for 3D Radar by Cheng Li, Wei Wang, Longfei Shi, Xuesong Wang

“…This paper proposes a recognition and parameter extraction method of 1D ES for 3D radar, which employs both MS and ES. An ES pattern simulator is designed to synthesize pulse amplitude (PA) data first. …”
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Parameter estimation of submarine power cables in offshore applications using machine learning-based methods by Felipe P. de Albuquerque, Rafael Nascimento, Gabriel de Castro Biage, Rooney R.A. Coelho, Ronaldo F. Ribeiro Pereira, Eduardo C. Marques da Costa, Mario L. Pereira Filho, Cassio G. Lopes, José R. Cardoso

“…In practical conditions, the training dataset takes into account noise patterns using well-established modeling methods for phasor measurements. …”
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Identification of Perceptual Phonetic Training Gains in a Second Language Through Deep Learning by Georgios P. Georgiou

“…Results: The results demonstrated good model performance across a range of metrics, confirming that learners’ gains in phonetic training could be effectively detected by the algorithm. Conclusions: This research underscores the potential of deep learning techniques to track improvements in phonetic training, offering a promising and practical approach for evaluating language learning outcomes and paving the way for more personalized, adaptive language learning solutions. …”
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Multi-modal integration of MRI and global chamber charge density mapping for the evaluation of atrial fibrillation by Alexander J. Sharp, Michael T. B. Pope, Andre Briosa e Gala, Richard Varini, Timothy R. Betts, Abhirup Banerjee

“…We apply the CDM inverse algorithm to both sets of reconstructions in order to compare derived conductions across various heart rhythms and AF conduction patterns. …”
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Pseudo-Labeling and Time-Series Data Analysis Model for Device Status Diagnostics in Smart Agriculture by Minwoo Jung, Dae-Young Kim

“…This approach enables the efficient preparation of labeled data for applications such as anomaly detection, pattern recognition, and predictive modeling in smart agriculture. …”
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Enhancing No Reference Laparoscopic Video Quality Assessment with Evolutionary ANFIS by Biswas Sria, Palanisamy Rohini

“…Statistical parameters derived from luminance, local binary pattern and motion-vector maps of video frames are observed to effectively discern distortion types and severities. …”
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Artificial Intelligence in IVF Laboratories: Elevating Outcomes Through Precision and Efficiency by Yaling Hew, Duygu Kutuk, Tuba Duzcu, Yagmur Ergun, Murat Basar

“…AI’s data analysis and pattern recognition capabilities offer valuable predictive insights, enhancing personalized treatment plans and increasing success rates in fertility treatments. …”
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What can we learn about multi-hazard impacts from global disaster records? by W. S. Jäger, M. C. de Ruiter, T. Tiggeloven, P. J. Ward, P. J. Ward

“…The analysis suggests distinct patterns of compounding impacts, which vary depending on hazard and impact type. …”
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Inter-rater reliability of a newly developed gait analysis and motion score by Christina Dürregger, Klemens A Adamer, Michael Pirchl, Michael J Fischer

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Spatiotemporal assessment of ecological quality and driving mechanisms in the Beijing metropolitan area by Aibo Jin, Hui Li, Xiangrong Wang, Ziyao Wang

“…Ecological quality is quantitatively evaluated using the Remote Sensing Ecological Index (RSEI), leveraging MODIS imagery, climate data, land use patterns, and soil characteristics. Spatial clustering patterns of ecological quality are identified through RSEI calculations and spatial autocorrelation analyses, while future trends are projected utilizing the coefficient of variation, Sen and Mann–Kendall methods, and the Hurst index. …”
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Impact of Saharan Dust Intrusions on Atmospheric Boundary Layer Height over Madrid by Francisco Molero, Pedro Salvador, Manuel Pujadas

“…This behavior is further studied discriminating by season and synoptic patterns. These results are relevant for health advice during Saharan dust intrusion days.…”
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The Relationship Between Surface Meteorological Variables and Air Pollutants in Simulated Temperature Increase Scenarios in a Medium-Sized Industrial City by Ronan Adler Tavella, Daniele Feijó das Neves, Gustavo de Oliveira Silveira, Gabriella Mello Gomes Vieira de Azevedo, Rodrigo de Lima Brum, Alicia da Silva Bonifácio, Ricardo Arend Machado, Letícia Willrich Brum, Romina Buffarini, Diana Francisca Adamatti, Flavio Manoel Rodrigues da Silva Júnior

“…The lack of a correlation between temperature and pollutant levels, along with their relationship with other meteorological variables, explains the observed pattern in Rio Grande. This research provides important contributions to the understanding of the interactions between climate change, air pollution, and meteorological factors in similar contexts.…”
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Design optimization of university ideological and political education system based on deep learning by Shangle Ai, Huanhuan Ding

“…The advancement of deep learning technology offers new opportunities for IPE due to its powerful capabilities in feature extraction and pattern recognition. This research employs a CNN-LSTM hybrid model, integrating Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM). …”
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A Novel Aerosol Optical Depth Retrieval Method Based on SDAE from Himawari-8/AHI Next-Generation Geostationary Satellite in Hubei Province by Shiquan Deng, Ting Bai, Zhe Chen, Yepei Chen

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Urban land use function prediction method based on RF and cellular automaton model by Wenjun Song, Min Ling

“…Moreover, the study also integrates random forest algorithm and cellular automaton model, and finally proposes a new urban land use function prediction method based on random forest algorithm and cellular automaton model. …”
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Combining Near-Infrared Spectroscopy and Chemometrics for Rapid Recognition of an Hg-Contaminated Plant by Bang-Cheng Tang, Hai-Yan Fu, Qiao-Bo Yin, Zeng-Yan Zhou, Wei Shi, Lu Xu, Yuan-Bin She

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Examining Deep Learning Techniques for Ethical Artificial Intelligence: Cleansing Malicious Comments from Users by Ji Woong Yoo, Kyoung Jun Lee, Arum Park

“…This study adds to the existing research by showing how advanced deep learning techniques can effectively identify and classify harmful comments by analyzing complex language patterns.…”
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Computational Techniques for Analysis of Thermal Images of Pigs and Characterization of Heat Stress in the Rearing Environment by Maria de Fátima Araújo Alves, Héliton Pandorfi, Rodrigo Gabriel Ferreira Soares, Gledson Luiz Pontes de Almeida, Taize Calvacante Santana, Marcos Vinícius da Silva

“…The image analysis consisted of its pre-processing, followed by color segmentation to isolate the region of interest and later the extraction of the animal’s surface temperatures, from a developed algorithm and later the recognition of the comfort pattern through machine learning. …”
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Predicting Trip Duration and Distance in Bike-Sharing Systems Using Dynamic Time Warping by Ahmed Ali, Ahmad Salah, Mahmoud Bekhit, Ahmed Fathalla

“…The rationale for splitting the dataset into [Formula: see text] sub-datasets is to separate similar patterns in one sub-dataset. Second, the utilization of the dynamic time warping (DTW) algorithm on the BSSs data was proposed for the clustering purpose, as the DTW usage is very limited in the current literature of BSSs. …”
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