Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification. by Jaipriya D, Sriharipriya K C

“…Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation. …”
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Evaluation of an Information Flow Gain Algorithm for Microsensor Information Flow in Limber Motor Rehabilitation by Naiqiao Ning, Yong Tang

“…After the noise is removed, the signal is extracted in the time domain and frequency domain, and the root mean square (RMS), absolute mean, median frequency in the time domain, and average power frequency in the frequency domain are selected and input to the classifier for pattern recognition. The support vector machine is used to classify the myoelectric signals and optimize the parameters in the support vector machine using the grid search method and particle swarm optimization algorithm and classify the test samples using the trained support vector machine. …”
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Toll-Like Receptor Signaling and Liver Fibrosis by Tomonori Aoyama, Yong-Han Paik, Ekihiro Seki

“…Toll-like receptors (TLRs) are pattern recognition receptors that sense pathogen-associated molecular patterns (PAMPs), which discriminate the products of microorganisms from the host. …”
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Establishment of fingerprint of phenolic compounds in Semen Ziziphi Spinosae and study on the spectrum-effect relationship based on different preceding cropping areas by Junfeng Jiang, Jun Luo, Wenyu Zheng, Jiayi Liu, Hui Jiang, Cuiyun Wu, Hongjin Bai

“…Variety differences were explored through chemical pattern recognition, and the spectrum-effect relationship between the fingerprint spectra of SZS and antioxidant activity was investigated using Pearson correlation analysis, grey relational analysis, and other methods. …”
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Machine Learning in Money Laundering Detection Over Blockchain Technology by Algimantas Venckauskas, Sarunas Grigaliunas, Linas Pocius, Rasa Bruzgiene, Andrejs Romanovs

“…Machine learning emerges as a powerful tool for analyzing and identifying illicit transactions within Blockchain networks; however, a significant challenge remains in the form of a gap in advanced pattern recognition algorithms. This paper introduces a novel machine learning-based approach called Value-driven-Transactional tracking Analytics for Crypto compliance (VTAC) for the detection of illegal crypto transactions via Blockchain. …”
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Combinations of TLR Ligands: A Promising Approach in Cancer Immunotherapy by Saskia Stier, Claudia Maletzki, Ulrike Klier, Michael Linnebacher

“…Toll-like receptors (TLRs), a family of pattern recognition receptors recognizing molecules expressed by pathogens, are typically expressed by immune cells. …”
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Serum and Brain Metabolomic Variations Reveal Perturbation of Sleep Deprivation on Rats and Ameliorate Effect of Total Ginsenoside Treatment by Xiao-jun Gou, Fang Cen, Zi-quan Fan, Ying Xu, Hong-yi Shen, Ming-mei Zhou

“…In this study, serum and brain metabolomic method based on gas chromatography coupled with mass spectrometry (GC/MS) was employed to evaluate the efficacy and study the mechanism of GS on a rat model of SD. With pattern recognition analysis of serum and brain tissue metabolite profile, a clear separation of the model group and control group was acquired for serum and brain tissue samples; the MGS (model + GS) group showed a tendency of recovering when compared to control group, which was consistent with behavioral and biochemical parameters. 39 and 40 potential biomarkers of brain tissues and serum samples, respectively, were identified and employed to explore the possible mechanism. …”
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Catastrophic and violent tornadoes: a detailed review of physical-mathematical models by Sergey A. Arsen’yev, Lev V. Eppelbaum

“…A method for nonstochastic long-term forecasting using the pattern recognition theory and Fourier analysis has recently been developed. …”
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Regulatory networks of mRNAs and miRNAs involved in the immune response of diamondback moth, Plutella xylostella to fungal infection by Mei-Qiong Xie, Long-Jiang Wang, Hua-Mei Xiao, Shu-Jun Wei

“…Among these DEGs, we found 28 immunity-related genes, which mainly include pattern recognition receptors, signal modulators, and immune effectors. …”
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The Walk of Guilt: Multimodal Deception Detection from Nonverbal Motion Behaviour by Sharifa Alghowinem, Sabrina Caldwell, Ibrahim Radwan, Michael Wagner, Tom Gedeon

“…From these baseline results, we can conclude that pattern recognition techniques could help in characterising deceptive behaviour, where future work will focus on exploring the tuning and enhancement of the results and techniques.…”
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Rolling Bearing Fault Diagnosis Based on Domain Adaptation and Preferred Feature Selection under Variable Working Conditions by Xiao Yu, Wei Chen, Chuanlong Wu, Enjie Ding, Yuanyuan Tian, Haiwei Zuo, Fei Dong

“…Furthermore, preferred feature selection by fault sensitivity and feature correlation (PSFFC) is embedded into this framework for selecting features which are more beneficial to fault pattern recognition and reduce the redundancy of feature set. …”
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Frequency and Texture Aware Multi-Domain Feature Fusion for Remote Sensing Scene Classification by Russo Ashraf, Kang-Hyun Jo

“…The proposed approach leverages the strengths of convolutional neural networks (CNNs) for spatial information extraction, a novel texture feature alignment block (TFAB) for nuanced texture differentiation, an efficient spectro-former block (ESFB) that uses spectral analysis for enhanced pattern recognition, a cross-domain fusion block (CDFB) and finally, an inception transformer block (iFB) that balances high and low-frequency information. …”
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Interleukin-18 Increases TLR4 and Mannose Receptor Expression and Modulates Cytokine Production in Human Monocytes by Luciane Alarcão Dias-Melicio, Reginaldo Keller Fernandes, Daniela Ramos Rodrigues, Marjorie Assis Golim, Angela Maria Victoriano Campos Soares

“…Taken together, these results show an important role of IL-18 on the early phase of inflammatory response by promoting the expression of some pattern recognition receptors (PRRs) that are important during the microbe recognition phase and by inducing some important cytokines such as TNF-α and IL-10.…”
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Anomaly Detection and Business Process Orchestration for Low-Code Platform in Power System Based on Deep-Cross Model With Data Balancing by Jin Huang, Ming Sheng Xu, Chang Ming Zhu, Guo An Wang

“…Third, we implement a hierarchical feature interaction mechanism that enables both explicit and implicit learning of high-order patterns, resulting in a 35% improvement in anomaly pattern recognition over traditional deep learning approaches. …”
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Adaptive Extraction of Oil Painting Texture Features Based on Reaction Diffusion Equation by Qicai Huang

“…The oil painting retrieval technology based on the reaction diffusion equation has attracted widespread attention in the fields of oil painting processing and pattern recognition. The description and extraction of oil painting information and the classification method of oil paintings are two important processes in content-based oil painting retrieval. …”
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Bounded multivariate contaminated normal mixture model with applications to skin cancer detection by Abbas Mahdavi

“…The model is well-suited for computer vision and pattern recognition problems due to its heavily-tailed and bounded nature, providing flexibility in modeling data in the presence of outliers. …”
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Th1/17-Biased Inflammatory Environment Associated with COPD Alters the Response of Airway Epithelial Cells to Viral and Bacterial Stimuli by Yifan Chen, Rakesh K. Kumar, Paul S. Thomas, Cristan Herbert

“…Furthermore, increased expression of pattern recognition receptors for viruses (TLR3, TLR7, IFIH1, and DDX58) was induced by Th1/17 cytokines, in both primary AECs and Calu-3 cells. …”
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Bearing Fault Classification Using Improved Antlion Optimizer and Extreme Learning Machine by Zhuanzhe Zhao, Yu Zhang, Qiang Ma, Yujian Rui, Guowen Ye, Mengxian Wang, Yongming Liu, Zhen Zhang, Neng Wei, Zhijian Tu

“…Secondly, in order to solve the disadvantage that extreme learning machine (ELM) network is easy to fall into local optimization, this ELALO algorithm is used to initialize the weights and thresholds of its network and to form the new pattern recognition model, ELALO-ELM. Finally, the bearing data of 8 patterns from Western Reserve University are decomposed by local mean decomposition (LMD), and then the symbolic entropy (SE) of the first three product function (PF) components signals is extracted and used as the input eigenvectors. …”
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Intelligent Turning Tool Monitoring with Neural Network Adaptive Learning by Maohua Du, Peixin Wang, Junhua Wang, Zheng Cheng, Shensong Wang

“…Based on LabVIEW and MATLAB hybrid programming, the waveforms of signals are observed and the significant characteristics of signals are extracted through the time-frequency domain analysis and then the calculation of the energy proportion of each frequency band obtained using 4 levels of wavelet packet decompositions of the vibration signal as well as 8 levels of wavelet multiresolution decompositions of the AE signal; the ensuing Relief-F algorithm is used to further reextract the features that are most relevant to the tool state as input of neural network pattern recognition. Through the BP neural network adaptive learning, tool state recognition model is finally established. …”
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The volatilome – investigation of volatile organic metabolites (VOM) as potential tumor markers in patients with head and neck squamous cell carcinoma (HNSCC) by Philipp Opitz, Olf Herbarth

“…For multivariate metabolite pattern recognition the hierarchical cluster analysis by Ward was applied, followed by the supervised partial least squares-discriminant analysis (PLS-DA). …”
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