Incidence of primary care chest pain consultations during the COVID-19 pandemic: an interrupted time series analysis with routine care data by Simone van den Bulk, Jasper W. A. van Egeraat, Annelieke H. J. Petrus, Mattijs E. Numans, Tobias N. Bonten

“…However, the pattern of chest pain in primary care is not clear yet. …”
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Mapping soil salinity in irrigated areas using hyperspectral UAV imagery by ZHOU Shixun, YIN Juan, WANG Juntao, CHANG Buhui, YANG Zhen

“…Four models, including multiple linear stepwise regression (MLSR), partial least squares regression (PLSR), support vector machine regression (SVR), and backpropagation neural network (BPNN), were evaluated for their accuracy to estimate soil salinity. …”
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Enhanced Online Continuous Brain-Control by Deep Learning-Based EEG Decoding by Jiaheng Wang, Lin Yao, Yueming Wang

“…A newly proposed deep learning model named interactive frequency convolutional neural network (IFNet) is leveraged and rigorously compared with the prevailing benchmark namely filter-bank common spatial pattern (FBCSP) for online MI decoding. …”
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Metabolome Profiling and Predictive Modeling of Dark Green Leaf Trait in Bunching Onion Varieties by Tetsuya Nakajima, Mari Kobayashi, Masato Fuji, Kouei Fujii, Mostafa Abdelrahman, Yasumasa Matsuoka, Jun’ichi Mano, Muneo Sato, Masami Yokota Hirai, Naoki Yamauchi, Masayoshi Shigyo

“…This trait is regulated by a complex network of pigment interactions, which not only determine coloration but also serve as critical indicators of plant growth dynamics and stress responses. …”
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Dual-Path Interactive U-Net for Unsupervised Hyperspectral Image Super-Resolution by Wenchen Deng, Jianjun Liu, Jinlong Yang, Zebin Wu, Liang Xiao

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Extraction and location of subway shield tunnel segment joints from RMLS point clouds by Liying Wang, Ze You, Yong Feng, Chunxi Xie, Mahamadou Camara

“…Precisely extracting segment joints in subway shield tunnels is critical for automated safety evaluation such as segment assembly quality inspection, dislocation and deformation detection and lining surface defects diagnosis. …”
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Optimizing physical education schedules for long-term health benefits by Liang Tan, Qin Chen, Jianwei Wu, Mingbang Li, Tianyu Liu

“…The developed DL model integrates convolutional neural network (CNN) layers to capture spatial features and long short-term memory (LSTM) layers to extract temporal patterns from demographic and activity-related variables. …”
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Hidden in Plain Sight: A Data-Driven Approach to Safety Risk Management for Highway Traffic Officers by Loretta Bortey, David J. Edwards, Chris Roberts, Iain Rille

“…This research explores case study data from highway incident reports (held by National Highways, a UK government company) and employs deep neural network (DNN) in unearthing patterns which inform safety decision makers on pertinent safety challenges confronting HTOs. …”
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Federated hierarchical MARL for zero-shot cyber defense. by Adel Alshamrani

“…The zero-shot learning component allows the framework to recognize and response to previously unseen attack patterns through semantic mapping. Furthermore, the federated learning learning component facilitates for knowledge sharing across network domains while preserving data privacy, enabling collaborative defense without exposing sensitive information. …”
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Detection of venous thromboembolism by proteomic serum biomarkers. by Santhi K Ganesh, Yugal Sharma, Judith Dayhoff, Henry M Fales, Jennifer Van Eyk, Thomas S Kickler, Eric M Billings, Elizabeth G Nabel

“…Using this new method, we analyzed serum from inpatients undergoing radiographic evaluation for VTE. In a balanced cohort of 76 patients, a neural network-based prediction model was built using a training subset of the cohort to first identify proteomic patterns of VTE. …”
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A New Efficient Hybrid Technique for Human Action Recognition Using 2D Conv-RBM and LSTM with Optimized Frame Selection by Majid Joudaki, Mehdi Imani, Hamid R. Arabnia

“…To address these limitations, we propose a novel model combining a two-dimensional convolutional restricted Boltzmann machine (2D Conv-RBM) with a long short-term memory (LSTM) network. The 2D Conv-RBM efficiently extracts spatial features such as edges, textures, and motion patterns while preserving spatial relationships and reducing parameters via weight sharing. …”
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Ensemble of deep learning and IoT technologies for improved safety in smart indoor activity monitoring for visually impaired individuals by Mesfer Al Duhayyim

“…Furthermore, the ResNet50 model is employed for feature extraction to capture complex spatial patterns in visual data. For detecting indoor activities, an ensemble DL classifier contains three approaches: deep neural network (DNN), bidirectional long short-term memory (BiLSTM), and sparse stacked autoencoder (SSAE). …”
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Study on main controlling factors of CO2 huff-n-puff for enhanced oil recovery and storage in shale oil reservoirs by CHEN Jun, WANG Haimei, CHEN Xi, TANG Yong, TANG Liangrui, SI Rong, WANG Huijun, HUANG Xianzhu, LENG Bing

“…A composite discrete fracture network numerical model combining both artificial and natural fractures was established to analyze the oil recovery enhancement mechanisms of CO2 huff-n-puff. …”
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A benchmark for computational analysis of animal behavior, using animal-borne tags by Benjamin Hoffman, Maddie Cusimano, Vittorio Baglione, Daniela Canestrari, Damien Chevallier, Dominic L. DeSantis, Lorène Jeantet, Monique A. Ladds, Takuya Maekawa, Vicente Mata-Silva, Víctor Moreno-González, Anthony M. Pagano, Eva Trapote, Outi Vainio, Antti Vehkaoja, Ken Yoda, Katherine Zacarian, Ari Friedlaender

“…This makes it difficult to, for example, identify patterns in what works well for machine learning-based analysis of bio-logger data. …”
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IoT‐Based Elderly Health Monitoring System Using Firebase Cloud Computing by Adhan Efendi, Muhammad Imam Ammarullah, Indra Griha Tofik Isa, Meli Puspita Sari, Jasmine Nurul Izza, Yohanes Sinung Nugroho, Hamid Nasrullah, Denny Alfian

“…A comparative experiment is conducted to define the optimal supervised machine learning model to be deployed into the system by analysing evaluation metrics. Meanwhile, the user satisfaction aspect evaluated by the terms of usability, comfort, security, and effectiveness. …”
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Advantages and potentials of SuperDove imagery for fine monitoring of suspended particulate matter in estuaries and tidal channels by Peng Li, Shenliang Chen, Congliang Xu, Wenjuan Wu, Jiarui Qi, Yinghai Ke, Hongyu Ji, Shihua Li, Xiaojing Zhong

“…Suspended particulate matter (SPM) concentration is an essential biogeochemical parameter for water quality evaluation and morphodynamic researches. As the newest satellite in Planet family, SuperDove (SD) with eight spectral bands achieves observation to Earth with unprecedented temporal and spatial resolution. …”
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Calibration of Low-cost Gas Sensors for Air Quality Monitoring by Dimitris Margaritis, Christos Keramydas, Ioannis Papachristos, Dimitra Lambropoulou

“…Abstract Mobile monitoring devices equipped with low-cost gas sensors in fixed stations are an emerging solution to enhance the spatial coverage of air quality monitoring networks. We estimated the measurement accuracy of two AQMesh devices, evaluated their agreement, and examined the related calibration characteristics. …”
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MetaTrans-FSTSF: A Transformer-Based Meta-Learning Framework for Few-Shot Time Series Forecasting in Flood Prediction by Jiange Jiang, Chen Chen, Anna Lackinger, Huimin Li, Wan Li, Qingqi Pei, Schahram Dustdar

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Similarity Analysis of Upper Extremity’s Trajectories in Activities of Daily Living for Use in an Intelligent Control System of a Rehabilitation Exoskeleton by Piotr Falkowski, Maciej Pikuliński, Tomasz Osiak, Kajetan Jeznach, Krzysztof Zawalski, Piotr Kołodziejski, Andrzej Zakręcki, Jan Oleksiuk, Daniel Śliż, Natalia Osiak

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Transforming a Heritage Building into a Living Laboratory: A Case Study of Monitoring by Carlos Naya, Sara Dorregaray-Oyaregui, Fernando Alonso, Juan Luis Roquette, Jose María Yoldi, César Martín-Gómez

“…A methodology was employed, involving the strategic placement of sensors based on building use patterns, continuous data monitoring, and iterative sensor performance evaluation. …”
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