Automated Deadlift Techniques Assessment and Classification Using Deep Learning by Wegar Lien Grymyr, Isah A. Lawal

“…Furthermore, we designed an application that integrates keypoint visualizations with motion pattern classifications. This tool provides users with valuable feedback on their performance and includes a replay feature for self-assessment, helping lifters refine their technique and reduce the risk of injury.…”
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Distributed denial-of-service (DDoS) on the smart grids based on VGG19 deep neural network and Harris Hawks optimization algorithm by Abdurahim Alhashmi, H. Idwaib, Selçuk Alparslan Avci, Javad Rahebi, Raheleh Ghadami

“…The suggested approach uses the robust feature extraction capability of VGG19-DNN for network traffic pattern analysis to detect abnormal traffic flows indicative of DDoS attacks. …”
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The effect of motivation on movement: a study of bradykinesia in Parkinson's disease. by Tamara Shiner, Ben Seymour, Mkael Symmonds, Peter Dayan, Kailash P Bhatia, Raymond J Dolan

“…<h4>Background</h4>Bradykinesia is a cardinal feature of Parkinson's disease (PD). Despite its disabling impact, the precise cause of this symptom remains elusive. …”
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Flow simulation algorithm for gas gathering pipelines of natural gas fields by Yuling LYU, Zhenhe JIANG, Xiaowei LI, Jiakai SHI, Huaping CAO

“…MethodsBy integrating production data from a gas field with multiphase flow theory, hydraulic and thermodynamic calculation models were developed for gas gathering pipelines. A simulation algorithm was then proposed to analyze flow conditions, including fluid patterns, liquid holdup, pressure, and temperature at any cross-section of the pipeline. …”
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Eosinophilic esophagitis: literature review and original case presentation by V. T. Ivashkin, Ye. K. Baranskaya, V. O. Kaybysheva, Ye. V. Ivanova, Ye. D. Fedorov

“…The aim of publication. To show features of clinical pattern, difficulties of diagnostics and treatment of eosinophilic esophagitis at the example of clinical case.Features of clinical case. …”
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Novel machine learning-driven comparative analysis of CSP, STFT, and CSP-STFT fusion for EEG data classification across multiple meditation and non-meditation sessions in BCI pipel... by Nalinda D. Liyanagedera, Corinne A. Bareham, Heather Kempton, Hans W. Guesgen

“…For two of those pipelines, Common Spatial Patterns (CSP) and Short Time Fourier Transform (STFT) were successfully used as feature extraction algorithms where both these algorithms are significantly new for meditation EEG. …”
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Early detection of risky spatio-temporal congestion in urban traffic by Shaobo Sui, Dan Xu, Mingyang Bai, Xiaoke Zhang, Zhaojun Mao, Daqing Li

“…However, large-scale congestion in city exhibits an unique spatio-temporal growth pattern. In this article, we develop a detection method for risky congestion based on its spatio-temporal evolution feature, which can detect risky spatio-temporal congestion clusters (SCCs) when they are small. …”
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Enhanced Named Entity Recognition and Event Extraction for Power Grid Outage Scheduling Using a Universal Information Extraction Framework by Wei Tang, Yue Zhang, Xun Mao, Mingqi Shan, Kai Lv, Xun Sun, Zhenhuan Ding

“…Subsequently, a trigger-centric event extraction model is developed through feature learning of outage plan triggers and syntactic pattern entities. …”
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Research on the Seismic Response Law of Complete Morphology of Butted Well Salt Cavern for Large-Scale Underground Energy Storage by Haitao Li, Dewen Zheng, Kang Li, Qiqi Wanyan, Lina Ran, Yanxia Kou, Song Bai, Jianan Wu, Jianchao Jia, Yunfei Wen, Yuanqing Wang, Hongyan Xing, Kuoyuan Zhu, Jingen Deng

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High-resolution (10 m) dataset of multi-crop planting structure on the Loess Plateau during 2018–2022 by Xining Zhao, Jichao Wang, Yelu Ding, Xiaodong Gao, Changjian Li, Hongwei Huang, Xuerui Gao

“…The research methodology involved four key steps: (1) Enhancing the sample dataset using phenological indices and the Dynamic Time Warping (DTW) algorithm; (2) Identifying crop planting intensity based on phenological growth curves; (3) Developing independent random forest classifiers tailored to agricultural climate zones; and (4) Constructing an optimal feature subset for crop classification. …”
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Early Diagnosis of Alzheimer Disease from Mri Using Deep Learning Models by Apparna Allada, R. Bhavani, Kavitha Chaduvula, R. Priya

“…In addition, this study will present ideas for Haralick features, feature extraction from Local Binary Pattern (LBP), Artificial Neural Network (ANN), and Visual Geometry Group (VGG)-19 network techniques. …”
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The Extraction of <i>Torreya grandis</i> Growing Areas Using a Spatial–Spectral Fused Attention Network and Multitemporal Sentinel-2 Images: A Case Study of the Kuaiji Mountain Reg... by Yanyan Lyu, Yong Wang, Xiaoling Shen

“…This study utilized monthly Sentinel-2 imagery from 2023 to extract multitemporal spectral bands, vegetation indices, and texture features. Following minimum redundancy maximum relevance (mRMR) feature selection, a spatial–spectral fused attention network (SSFAN) was developed to extract the distribution of <i>T. grandis</i> in the Kuaiji Mountain area and to analyze the influence of topographic factors. …”
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Transgenic overexpression of LARGE induces α-dystroglycan hyperglycosylation in skeletal and cardiac muscle. by Martin Brockington, Silvia Torelli, Paul S Sharp, Ke Liu, Sebahattin Cirak, Susan C Brown, Dominic J Wells, Francesco Muntoni

“…Further detailed muscle physiological analysis demonstrated a loss of force in response to eccentric exercise in the older, but not in the younger mice, suggesting this deficit developed over time. However this remained a subclinical feature as no pathology was observed in older mice in any muscles including the diaphragm, which is sensitive to mechanical load-induced damage.…”
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Classification Modeling Method for Near-Infrared Spectroscopy of Tobacco Based on Multimodal Convolution Neural Networks by Lei Zhang, Xiangqian Ding, Ruichun Hou

“…In order to improve the accuracy of the tobacco origin classification, a near-infrared spectrum (NIRS) identification method based on multimodal convolutional neural networks (CNN) was proposed, taking advantage of the strong feature extraction ability of the CNN. Firstly, the one-dimensional convolutional neural network (1-D CNN) is used to extract and combine the pattern features of one-dimensional NIRS data, and then the extracted features are used for classification. …”
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Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. by Claudia Giambartolomei, Damjan Vukcevic, Eric E Schadt, Lude Franke, Aroon D Hingorani, Chris Wallace, Vincent Plagnol

“…The integration of multiple association datasets, including gene expression datasets, can contribute to this goal. We have developed a novel statistical methodology to assess whether two association signals are consistent with a shared causal variant. …”
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Hybrid mechanism‐data‐driven iron loss modelling for permanent magnet synchronous motors considering multiphysics coupling effects by Lin Liu, Wenliang Yin, Youguang Guo

“…Purely mechanistic models require detailed theoretical knowledge and exact parameters, often struggling to accurately describe complex systems, while purely data‐driven methods lack interpretability, which are susceptible to data noise and outliers in feature extraction and complicated pattern recognition. …”
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mzGroupAnalyzer--predicting pathways and novel chemical structures from untargeted high-throughput metabolomics data. by Hannes Doerfler, Xiaoliang Sun, Lei Wang, Doris Engelmeier, David Lyon, Wolfram Weckwerth

“…Pathways are extracted directly from the data and putative novel structures can be identified. The detected m/z features can be mapped on a van Krevelen diagram according to their H/C and O/C ratios for pattern recognition and to visualize oxidative processes and biochemical transformations. …”
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An Inverted Transformer Framework for Aviation Trajectory Prediction with Multi-Flight Mode Fusion by Gaoyong Lu, Yang Ou, Wei Li, Xinyu Zeng, Ziyang Zhang, Dongcheng Huang, Igor Kotenko

“…As globalization and rapid economic development drive a surge in air transportation demand, the need for enhanced efficiency and safety in flight operations has become increasingly critical. …”
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Graph-text contrastive learning of inorganic crystal structure toward a foundation model of inorganic materials by Keisuke Ozawa, Teppei Suzuki, Shunsuke Tonogai, Tomoya Itakura

“…We present a contrastive learning of inorganic crystal structure (CLICS) for embedding the geometric concepts, which contrasts texts representing the contextual patterns of geometries with the crystal graphs. We demonstrate that the geometric concepts are integrally embedded on the CLICS feature space, through experiments of concept prediction from crystal graphs, similar structure search, and few-shot/imbalanced crystal structure classification.…”
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Comparative evaluation of titanium-prepared platelet-rich fibrin with and without herbal extract: A histological study by Gummaluri Shiva Shankar, Gurumoorthy Kaarthikeyan, Damera Trinath Kishore, Boddeda Anusha, Kodem Tejaswi, Lekkala Sivaram

“…A statistically significant difference was shown in the packeting (p = 0.018) and layered (p = 0.028) patterns of the fibrin network, and there was no statistically significant difference in the scattered (p = 0.749) pattern among the examined groups. …”
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