Identification of Depression Patients Using LIF Spiking Neural Network Model From the Pattern of EEG Signals by Rekha Sahu, Prasant Kumar Pattnaik, Kalaiarasi Sonai Muthu Anbananthen, Saravanan Muthaiyah

“…Interpreting electroencephalography signals and the abnormality of the signals can help to find the specific pattern for specific diseases like depression. A Spiking Neural Network is a machine learning approach that emphasizes the data value and manipulates the value to find the particular signal feature. …”
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Spatiotemporal patterns of water and vegetation in Poyang Lake from 2013 to 2021 using remote sensing data. by Zhigang Lu, Zihao Chen, Meng Zhou, Daxing Lei, Yifan Chen

“…We used a combination of Maximum Likelihood Classification (MLC) and Support Vector Machine (SVM) to preprocess and classify 42 Landsat 8 OLI images. …”
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LSTM-based framework for predicting point defect percentage in semiconductor materials using simulated XRD patterns by Mehran Motamedi, Reza Shidpour, Mehdi Ezoji

“…This LSTM-based method offers a novel approach to predicting defect percentages using simulated XRD patterns of materials.…”
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Changes in Land Use and Land Cover Patterns in Two Desert Basins Using Remote Sensing Data by Abdullah F. Alqurashi, Omar A. Alharbi

“…A combination of object-based image analysis and a support vector machine classifier was used to produce LULC thematic maps. …”
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Feature Extraction using Histogram of Oriented Gradients and Moments with Random Forest Classification for Batik Pattern Detection by Wafiq Azizah, Soffiana Agustin

“…The preservation of traditional batik patterns, often transmitted orally and through direct practice across generations, faces significant challenges in the modern era. …”
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Near Infrared Spectroscopy Based on Supervised Pattern Recognition Methods for Rapid Identification of Adulterated Edible Gelatin by Hao Zhang, Haifeng Sun, Ling Wang, Shun Wang, Wei Zhang, Jiandong Hu

“…The aim of this work is to identify the adulteration of edible gelatin using near-infrared (NIR) spectroscopy combined with supervised pattern recognition methods. The spectral data obtained from a total of 144 samples consisting of six kinds of adulterated gelatin gels with different mixture ratios were processed with multiplicative scatter correction (MSC), Savitzky–Golay (SG) smoothing, and min-max normalization. …”
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Mitigating the Concurrent Interference of Electrode Shift and Loosening in Myoelectric Pattern Recognition Using Siamese Autoencoder Network by Ge Gao, Xu Zhang, Xiang Chen, Zhang Chen

“…The objective of this work is to develop a novel myoelectric pattern recognition (MPR) method to mitigate the concurrent interference of electrode shift and loosening, thereby improving the practicality of MPR-based gestural interfaces towards intelligent control. …”
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Commonalities and differences in gene expression patterns in major depressive disorder and chronic spontaneous urticaria: implications for comorbidity by Yibo Jiang, Wen Li, Lihao Zheng, Nan Ba

“…Results indicated shared molecular patterns between CSU and MDD, with 26 key genes in the total population, 6 in males and 7 in females. …”
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Monitoring and Modeling Urban Temperature Patterns in the State of Iowa, USA, Utilizing Mobile Sensors and Geospatial Data by Clemir Abbeg Coproski, Bingqing Liang, James T. Dietrich, John DeGroote

“…With limited research on smaller cities, especially in the American Midwest, the goal of this research was to examine the spatial patterns of air temperature across multiple small to medium-sized cities in Iowa, a relatively rural US state. …”
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A Mean Weighted Squared Error-based Neural Classifier for Intelligent Pattern Recognition in Smart Grids by Mehdi Khashei, Mehrnaz Ahmadi, Fatemeh Chahkoutahi

“…Supervised learning is widely used in pattern recognition and classification due to its strong ability to enhance data accuracy. …”
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Classification patterns identification of immunogenic cell death-related genes in heart failure based on deep learning by Zhihui Ma, Shixin Ma, Bin Chen, Yongjun Zhang, Jinmei Zeng, Jianping Tao, Yu Hu

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Microbiome and metabolome patterns after lung transplantation reflect underlying disease and chronic lung allograft dysfunction by Christian Martin, Kathleen S. Mahan, Talia D. Wiggen, Adam J. Gilbertsen, Marshall I. Hertz, Ryan C. Hunter, Robert A. Quinn

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Landscape structure, climate variability, and soil quality shape crop biomass patterns in agricultural ecosystems of Bavaria by Maninder Singh Dhillon, Thomas Koellner, Sarah Asam, Jakob Bogenreuther, Stefan Dech, Stefan Dech, Ursula Gessner, Daniel Gruschwitz, Sylvia Helena Annuth, Tanja Kraus, Thomas Rummler, Christian Schaefer, Sarah Schönbrodt-Stitt, Ingolf Steffan-Dewenter, Martina Wilde, Martina Wilde, Tobias Ullmann

“…The RF-based approach improved predictive accuracy over the LUE model alone, particularly for winter wheat. Biomass patterns were shaped by both landscape configuration and climatic conditions. …”
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Real-time fMRI pattern decoding and neurofeedback using FRIEND: an FSL-integrated BCI toolbox. by João R Sato, Rodrigo Basilio, Fernando F Paiva, Griselda J Garrido, Ivanei E Bramati, Patricia Bado, Fernanda Tovar-Moll, Roland Zahn, Jorge Moll

“…In combination with improved computational approaches, such as pattern recognition analysis (e.g., Support Vector Machines, SVM), fMRI neurofeedback and brain decoding represent key innovations in the field of neuromodulation and functional plasticity. …”
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Anisotropic patterns of nanospikes induces anti-biofouling and mechano-bactericidal effects of titanium nanosurfaces with electrical cue by Eiji Kato, Masahiro Yamada, Eitoyo Kokubu, Hiroshi Egusa, Kazuyuki Ishihara

“…Two types of alkali-etched titanium nanosurfaces with isotropically or anisotropically patterned nanospikes had markedly denser surface protrusions, greater superhydrophilicity, and greater negative charge than machined or micro-roughened titanium surfaces. …”
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A machine learning approach to predict pancreatic islet grafts rejection versus tolerance. by Gerardo A Ceballos, Luis F Hernandez, Daniel Paredes, Luis R Betancourt, Midhat H Abdulreda

“…We created a locked software based on a support vector machine (SVM) technique for pattern recognition in electropherograms (EPGs) generated by micellar electrokinetic chromatography and laser induced fluorescence detection (MEKC-LIFD). …”
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CONSTRUCTING METAMORPHOSIS OF IMAGES FOR THE OBJECTS ON THE BASIS OF SOLVING EULER-POINCARE EQUATIONS by S. V. Leichter

“…The designed algorithms can be used through a biometrical system, in images and subjects classification systems, machine vision systems, images and patterns recognition, tracking systems.…”
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Glaucoma detection and staging from visual field images using machine learning techniques. by Nahida Akter, Jack Gordon, Sherry Li, Mikki Poon, Stuart Perry, John Fletcher, Thomas Chan, Andrew White, Maitreyee Roy

“…<h4>Purpose</h4>In this study, we investigated the performance of deep learning (DL) models to differentiate between normal and glaucomatous visual fields (VFs) and classify glaucoma from early to the advanced stage to observe if the DL model can stage glaucoma as Mills criteria using only the pattern deviation (PD) plots. The DL model results were compared with a machine learning (ML) classifier trained on conventional VF parameters.…”
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Feasibility of Using Wavelet Analysis and Machine Learning Method in Technical Diagnosis of Car Seats by Cezary BARTMAŃSKI, Alicja BRAMORSKA

“…The method is based on the analysis of acoustic signals produced during the operation of the drive. Pattern recognition and machine learning processes were used in the diagnosis. …”
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Deep Learning-Based Dzongkha Handwritten Digit Classification by Yonten Jamtsho, Pema Yangden, Sonam Wangmo, Nima Dema

“…With the advancement in deep learning technology, many machine learning algorithms were developed to tackle the problem of pattern recognition. …”
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