Learning-Based Spectrum Sensing for Cognitive Radio Systems by Yasmin Hassan, Mohamed El-Tarhuni, Khaled Assaleh

“…This paper presents a novel pattern recognition approach to spectrum sensing in collaborative cognitive radio systems. …”
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Effects of Microbes on Insect Host Physiology and Behavior Mediated by the Host Immune System by Shan Zhang, Zhengyan Wang, Qiong Luo, Lizhen Zhou, Xin Du, Yonglin Ren

“…Insects recognize environmental pathogens through pattern recognition receptors, thus activating the innate immune system to eliminate pathogens. …”
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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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Spectral-Spatial Hyperspectral Image Semisupervised Classification by Fusing Maximum Noise Fraction and Adaptive Random Multigraphs by Eryang Chen, Ruichun Chang, Kaibo Shi, Ansheng Ye, Fang Miao, Jianghong Yuan, Ke Guo, Youhua Wei, Yiping Li

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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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Nuclear Alarmin Cytokines in Inflammation by Lili Jiang, Yijia Shao, Yao Tian, Changsheng Ouyang, Xiaohua Wang

“…Pathogen-associated molecular patterns (PAMPs) are some nonspecific and highly conserved molecular structures of exogenous specific microbial pathogens, whose products can be recognized by pattern recognition receptor (PRR) on innate immune cells and induce an inflammatory response. …”
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Stroke Lesion Prediction by Bille-Viper-Segmentation with Tandem-MU-net Model by Beevi Fathima, N Santhi Dr, N Ramasamy Dr

“…Existing methods struggle with flexibility in varying conditions; thus, the Trans-Lucent-Rich Reprise Pattern recognition algorithm for precise identification of infected areas is introduced. …”
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A New Fuzzy Logic-Based Similarity Measure Applied to Large Gap Imputation for Uncorrelated Multivariate Time Series by Thi-Thu-Hong Phan, André Bigand, Émilie Poisson Caillault

“…The completion of missing values is a prevalent problem in many domains of pattern recognition and signal processing. Analyzing data with incompleteness may lead to a loss of power and unreliable results, especially for large missing subsequence(s). …”
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An Integrated Fault Diagnosis Method for Rotating Machinery Based on Smoothness Priors Approach Fluctuation Dispersion Entropy and Density Peak Clustering by Hongping Ge, Zhaohui Huang, Huaying Liu

“…Finally, the eigenvector matrix was input into the density peak clustering algorithm for fault recognition and classification. The proposed novel algorithm was applied to the experimental data of the rotating machinery under various working conditions. …”
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Gait Perception via Actual and Estimated Pneumatic Physical Reservoir Output by Junyi Shen, Tetsuro Miyazaki, Swaninda Ghosh, Toshihiro Kawase, Kenji Kawashima

“…This enhanced clustering performance is subsequently leveraged in gait perception by incorporating Takagi–Sugeno fuzzy logic for joint angle estimation and a softmax activation function for walking condition recognition. The newly proposed time‐sequence processing approach facilitates the traditional PRC model to achieve higher accuracy in gait perception and greater robustness against the user's walking pattern variations while preserving PRC's hardware simplicity.…”
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Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification. by Jaipriya D, Sriharipriya K C

“…However, decoding EEG signals poses significant challenges due to their complexity, dynamic nature, and low signal-to-noise ratio (SNR). Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation. …”
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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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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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Discrimination of superficial lymph nodes using ultrasonography and tissue metabolomics coupled with machine learning by Lu Li, Xinyue Wang, Hongyan Deng, Wenjuan Lu, Yasu Zhou, Xinhua Ye, Yong Li, Jie Wang

“…Linear discriminant analysis coupled with these metabolites could be used for differentiating lymph nodes, achieving recognition rates ranging from 87.4% to 89.3%, outperforming ultrasonography (63.1% to 75.4%).DiscussionOur findings could contribute to a better understanding of malignant lymph node development and provide novel targets for therapeutic interventions.…”
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An Approach to Fall Detection Using Statistical Distributions of Thermal Signatures Obtained by a Stand-Alone Low-Resolution IR Array Sensor Device by Nishat Tasnim Newaz, Eisuke Hanada

“…Unlike camera-based systems, which can be privacy-intrusive, IR array sensors offer a non-invasive, reliable approach for fall detection and activity recognition while preserving privacy. This work proposes a novel method to distinguish between normal motion and fall incidents by analyzing thermal patterns captured by infrared array sensors. …”
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New Platform Technology for Comprehensive Serological Diagnostics of Autoimmune Diseases by Annika Willitzki, Rico Hiemann, Vanessa Peters, Ulrich Sack, Peter Schierack, Stefan Rödiger, Ursula Anderer, Karsten Conrad, Dimitrios P. Bogdanos, Dirk Reinhold, Dirk Roggenbuck

“…To address the limitations of IIF and to meet the demand for cost-efficient autoantibody screening, automated IIF methods employing novel pattern recognition algorithms for image analysis have been introduced recently. …”
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Phylogenomic analysis reveals exceptions to the co-evolution of ZAR1 and ZRK immune gene families in plants by Li Yang, Shengyi Liu, M. Eric Schranz, Klaas Bouwmeester

“…Abstract Background HOPZ-ACTIVATED RESISTANCE 1 (ZAR1) is a nucleotide-binding leucine-rich repeat (NLR) protein functioning as a recognition hub to initiate effector-triggered immunity against bacterial pathogens. …”
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Classification, Mechanisms of Action, and Therapeutic Applications of Inhibitory Oligonucleotides for Toll-Like Receptors (TLR) 7 and 9 by Petar S. Lenert

“…The innate force acts as an alarm mechanism that senses changes in the microenvironment through the recognition of common microbial patterns by Toll-like receptors (TLR) and NOD proteins. …”
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Decoding Gestures in Electromyography: Spatiotemporal Graph Neural Networks for Generalizable and Interpretable Classification by Hunmin Lee, Ming Jiang, Jinhui Yang, Zhi Yang, Qi Zhao

“…Our methodology exhibits remarkable efficacy, achieving state-of-the-art performance across five publicly available datasets, thus underscoring its prowess in gesture recognition tasks. Furthermore, our approach provides interpretable insights into muscular activation patterns, thereby reaffirming the practical effectiveness of our GCN model. …”
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Improved COVID-19 Diagnosis Using a Hybrid Transfer Learning Model with Fuzzy Edge Detection on CT Scan Images by Hassan Salarabadi, Mohammad Saber Iraji, Mehdi Salimi, Mehdi Zoberi

“…Medical specialists often recommend the use of CT scans for COVID-19 diagnosis, particularly in the second week of illness when there is a high suspicion of infection, due to the unique lung patterns observed in COVID-19 patients. Consequently, there is a need for a quick recognition system based on deep learning techniques to detect COVID-19 infection and prevent its spread. …”
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