Travel Patterns Analysis Using Tensor-Based Model from Large-Scale License Plate Recognition Data by Zhaoxin Liu, Xiaolu Wang, Yufeng Bi, Jun Kong, Run Xu, Yuanpei Chen, Jinjun Tang

“…Then, the tensor decomposition and reconstruction algorithms are performed based on extracted feature variables to analyze their influence on travel patterns. …”
Get full text

Digits Recognition for Arabic Handwritten through Convolutional Neural Networks, Local Binary Patterns, and Histogram of Oriented Gradients by Bushra Mahdi Hasan, Zahraa Jasim Jaber, Ahmad Adel Habeeb

“…Specifically, the methods under consideration are Convolutional Neural Networks (CNNs), which have demonstrated their utility in diverse domains and offer effective solutions.  Local Binary Pattern (LBP) is a unique, efficient textural operator that finds widespread application in the area of computers such as biometric identification and detection of targets as feature extraction techniques. …”
Get full text

Dissipative Structures of the Kuramoto–Sivashinsky Equation by N. A. Kudryashov, P. N. Ryabov, B. A. Petrov

Get full text

Spatial point pattern analysis of urban retail stores: the case of twelve large- and medium-sized Greek cities by Michail-Christos TSOUTSOS, Yorgos N. PHOTIS

“…The type of retail activities was determined using the image of the ground-floor stores provided by the Google Street View (GSV) service and thus 7322 stores were recorded in a geodatabase as point features. The results reveal that the retail stores’ distribution has a clustered and random spatial pattern at least in one city, where the high population density and the increase in rental prices of premises for professional activities constitute the factors that form these spatial patterns respectively. …”
Get full text

Hybrid Deep Learning Framework for Continuous User Authentication Based on Smartphone Sensors by Bandar Alotaibi, Munif Alotaibi

“…This integrated pipeline effectively extracts local and global motion features specific to each user’s unique behavior, improving accuracy over conventional Transformer, Informer, CNN, and LSTM baselines. …”
Get full text

Circulated echovirus 18 strains in Guangdong Province and worldwide: A novel perspective on genetic diversity and recombination patterns by Zhiyu Li, Xiaohan Yang, Ru Bai, Ping Li, Yanting Qin, Mingyong Luo

“…Using this expanded dataset, we analysed the molecular epidemiological features, genetic characteristics, and recombination patterns of E18. …”
Get full text

Changes in objective characteristics in brain electrical activity in newborns as a function of birth weight by Anastasiya E. Runnova, Yuliya A. Zhuravleva, Evgeniy N. Egorov, Evgeniya E. Drozhdeva

“…The aim of the present study was to detect characteristic features of oscillatory electrical activity of the brain in the first day of postnatal life depending on the weight of newborns. …”
Get full text

Indonesian Adolescents’ Perceptions of Front-of-Package Labels on Packaged Food and Drinks by Wendy Gonzalez, Eny Kurnia Sari, Aang Sutrisna, Zineb Félix, Nabila Ernada, Adhika D Dibyareswati, Lindsey Smith Taillie

Get full text

AI-driven multi-agent reinforcement learning framework for real-time monitoring of physiological signals in stress and depression contexts by Thanveer Shaik, Xiaohui Tao, Lin Li, Haoran Xie, Hong-Ning Dai, Feng Zhao, Jianming Yong

“…Methods Our framework deploys multiple learning agents, each dedicated to monitoring specific physiological features such as heart rate, respiration, and temperature. …”
Get full text

Genome-wide identification and characterization of WRKYs family involved in responses to Cylindrocarpon destructans in Panax notoginseng by Manqiao Li, Xiaoli Che, Qiwen Liang, Kuixiu Li, Guisheng Xiang, Xuyan Liu, Yan Zhao, Fugang Wei, Shengchao Yang, Guanze Liu

Get full text

Research and optimization of a multilevel fire detection framework based on deep learning and classical pattern recognition techniques by Qi Liu, Hong Chen, Da Lin

“…Additionally, the use of Complete Local Binary Pattern (CLBP) technology for texture feature extraction, combined with VQGAN technology for accurate flame identification through sample reconstruction, underscores our innovative approach. …”
Get full text

Profiling urban water consumption patterns in Ho Chi Minh City using time series clustering method by Minh Trang Nguyen Thi, Minh Nguyet Nguyen, Quoc Thang Truong Tan, Le Ngoc Thien

“…By applying feature extraction and K-Means clustering, an unsupervised learning technique, this research identifies distinct water consumption patterns among 36 district metering areas in the study region. …”
Get full text

DriftShield: Autonomous Fraud Detection via Actor-Critic Reinforcement Learning With Dynamic Feature Reweighting by Jialei Cao, Wenxia Zheng, Yao Ge, Jiyuan Wang

“…This article presents DriftShield, a novel adaptive fraud detection framework that addresses these limitations through four key technical innovations: (1) the first application of Soft Actor-Critic (SAC) reinforcement learning with continuous action spaces to fraud detection, enabling simultaneous fine-grained optimization of detection thresholds and feature importance weights; (2) a dynamic feature reweighting mechanism that automatically adapts to evolving fraud patterns while providing interpretable insights into changing fraud strategies; (3) an adaptive experience replay buffer combining sliding windows with prioritized sampling to balance catastrophic forgetting prevention with rapid concept drift adaptation; and (4) an entropy-driven exploration framework with automatic temperature tuning that intelligently balances exploitation of known fraud patterns with discovery of emerging threats. …”
Get full text

Segmentalized amplitude normalization in feature extraction technique for diagnostics enhancement of bearing deterioration under varying speeds by Tian-Yau Wu, Yo-Sen Lin

“…In this paper, the research focuses on conducting an in-depth analysis of signal signatures, followed by providing a physical insight into feature extraction. Consequently, it enables the application of simple machine learning methods to accurately diagnose various bearing defects, even when dealing with significantly different patterns in training and testing data due to varying rotation speeds. …”
Get full text

Association Between Dietary Patterns and All-Cause Mortality in Individuals with Hypertension and Osteoporosis: A Retrospective Cohort Study by Guan J, Ding L, Wang Y, Zhu Z, Pan M, Du L, Yin N

“…The MeDS and AHEI-2010 were linked to overall mortality in adults without OS and HTN.Conclusion: The impacts of different dietary patterns were differences in multi-feature population. …”
Get full text

Integrating the Prior Shape Knowledge Into Deep Model and Feature Fusion for Topologically Effective Brain Tumor Segmentation by Salma Asif, Ahmad Raza Shahid, Kiran Aftab, Syed Ather Enam

“…By incorporating prior shape information, our proposed model guides the segmentation process, resulting in more precise delineation of tumor regions and mitigating the effect of fragmented structures or patchy patterns. The proposed technique leverages the strength of ConvNeXt to capture the local features and multi-headed self-attention to capture the global features without using the entire transformer encoder to keep the model less complex. …”
Get full text

Visualization of large-scale user association feature data based on a nonlinear dimensionality reduction method by Nong Linlin

“…Traditional linear dimensionality reduction methods often fail to obtain intuitive information and discover intrinsic connections and patterns in complex high-dimensional data. This study proposes a large-scale user association feature data (LSUAFD) visualization study based on nonlinear dimensionality reduction methods to address the complexity and high-dimensional issues of data. …”
Get full text

A Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization by Zeinab Hassani, vahid Hajihashemi, Keivan Borna, Iman Sahraei Dehmajnoonie

“…Nonetheless, in spam detection, there are a large number of features to attend as they play an essential role in detection efficiency. …”
Get full text

EEG-based epilepsy detection using CNN-SVM and DNN-SVM with feature dimensionality reduction by PCA by Yousra Berrich, Zouhair Guennoun

“…Abstract This study focuses on epilepsy detection using hybrid CNN-SVM and DNN-SVM models, combined with feature dimensionality reduction through PCA. The goal is to evaluate the effectiveness and performance of these models in accurately identifying epileptic patterns. …”
Get full text

RoBERTa-Based Multi-Feature Integrated BiLSTM and CNN Model for Ceramic Review Analysis by LiHua Yang, Jun Wang, WangRen Qiu

“…To address the limitation that the Robustly Optimized BERT Pretraining Approach (RoBERTa) may not effectively capture local dependencies and salient features within the text, we propose a feature fusion framework based on RoBERTa’s multi-output architecture. …”
Get full text