Detection and Pattern Recognition of Chemical Warfare Agents by MOS-Based MEMS Gas Sensor Array by Mengxue Xu, Xiaochun Hu, Hongpeng Zhang, Ting Miao, Lan Ma, Jing Liang, Yuefeng Zhu, Haiyan Zhu, Zhenxing Cheng, Xuhui Sun

“…Finally, principal component analysis (PCA) and machine learning algorithms were applied for CWA classification. …”
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Gender classification performance optimization based on facial images using LBG-VQ and MB-LBP by Faruq Abdul Hakim, Tio Dharmawan, Muhamad Arief Hidayat

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Stock Index Prices Prediction via Temporal Pattern Attention and Long-Short-Term Memory by Xiaolu Wei, Binbin Lei, Hongbing Ouyang, Qiufeng Wu

“…The study’s motivation is based on the notion that datasets of stock index prices involve weak periodic patterns, long-term and short-term information, for which traditional approaches and current neural networks such as Autoregressive models and Support Vector Machine (SVM) may fail. …”
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Healthy dietary patterns, biological aging, and kidney stones: evidence from NHANES 2007–2018 by Chengcheng Wei, Qian Yang, Qian Yang, Jingke He, Yu Luo, Kun Han, Junkun Li, Shuai Su, Shuai Su, Jindong Zhang, Hongxing Wang, Hongxing Wang, Delin Wang

“…Mediation analyses suggested that aging indicators significantly mediated the relationship between healthy dietary patterns and kidney stones. Machine learning with SHAP revealed the relative importance of dietary patterns and specific dietary components in this association. …”
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Understanding the role of eye movement pattern and consistency during face recognition through EEG decoding by Guoyang Liu, Yueyuan Zheng, Michelle Hei Lam Tsang, Yazhou, Zhao, Janet H. Hsiao

“…Temporal dynamics of neural representation quality for face recognition were assessed through decoding old vs new faces using a support vector machine classifier. Results showed that a more eye-focused pattern was associated with higher decoding accuracy in the high-alpha band, reflecting better neural representation quality. …”
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A Novel Improved Local Binary Pattern and Its Application to the Fault Diagnosis of Diesel Engine by Yanping Cai, Guanghua Xu, Aihua Li, Xu Wang

“…Aiming at the feature extraction difficulty of vibration signals, an improved local binary pattern- (ILBP-) based diesel engine fault diagnosis approach is proposed. …”
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Detection of failures in HV surge arrester using chaos pattern with deep learning neural network by Chun‐Chun Hung, Meng‐Hui Wang, Shiue‐Der Lu, Cheng‐Chien Kuo

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DNA methylation patterns and predictive models for metabolic disease risk in offspring of gestational diabetes mellitus by Na Wang, Suping Li, Li Yang

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Modification of the WaldBoost algorithm to improve the efficiency of solving pattern recognition problems in real-time by A. N. Chesalin, S. Ya. Grodzenskiy, M. Yu. Nilov, A. N. Agafonov

“…The paper studies modifications of compositions (ensembles) of algorithms for solving real-time pattern recognition problems. The aim of the study is to improve the known machine learning algorithms for pattern recognition using a minimum amount of time (the minimum number of used classifiers) and with a given accuracy of the results. …”
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Exploring pattern-specific components associated with hand gestures through different sEMG measures by Yangyang Yuan, Jionghui Liu, Chenyun Dai, Xiao Liu, Bo Hu, Jiahao Fan

“…Abstract For surface electromyography (sEMG) based human–machine interaction systems, accurately recognizing the users’ gesture intent is crucial. …”
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Comparison of the Effect of Resistance, Swimming, and Combination Training Patterns on Bone Density in Female Osteoporotic Rats by Fatemeh Zeidabadi, Maryam Banparvari, Omid Mohammaddoost

“…Introduction: The aim of the study was to compare the effects of resistance, swimming, and combined training patterns on L5 vertebral mineral density in osteoporotic rats. …”
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Spatial patterns of hepatocyte glucose flux revealed by stable isotope tracing and multi-scale microscopy by Aliyah Habashy, Christopher Acree, Keun-Young Kim, Ali Zahraei, Martin Dufresne, Sebastien Phan, Melanie Cutler, Emilee Patterson, Alexandra G. Mulligan, Kristopher Burkewitz, Charles Robert Flynn, Louise Lantier, Thomas Deerinck, Owen P. McGuinness, Jeffrey M. Spraggins, Mark H. Ellisman, Rafael Arrojo e Drigo

“…Here we show the application of multi-scale microscopy, machine learning-based image segmentation, and spatial analysis tools to quantitatively map the fate of nutrient-derived 13C atoms across spatiotemporal scales. …”
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Automated Identification of Cyclic Alternating Patterns of Sleep Using Fusion of VGG16 and Vision Transformer by Hardik Telangore, Ashutosh Kumar Jha, Prithviraj Verma, Manish Sharma, Chakka Sabareesh, Ankit A. Bhurane, Hasan S. Mir, U. Rajendra Acharya

“…An automated system is crucially needed to identify Cyclic Alternating Pattern (CAP) phases A and B, which are pivotal in assessing sleep depth and stability, enhancing the understanding of sleep and diagnosing sleep disorders. …”
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Exoskeleton-guided passive movement elicits standardized EEG patterns for generalizable BCIs in stroke rehabilitation by Xinyi Zhang, Lanfang Xie, Wanting Liu, Shaoying Liang, Liyao Huang, Mingjun Wang, Lingling Tian, Li Zhang, Zhen Liang, Hai Li, Gan Huang

“…Time and time-frequency domain analyses were performed to examine the event-related potential (ERP), event-related desynchronization (ERD), and synchronization (ERS) patterns. The performance of two BCI algorithms, Common Spatial Patterns (CSP) and EEGNet, was evaluated in both within-subject and cross-subject decoding tasks. …”
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Transcriptional Patterns of Nodal Entropy Abnormalities in Major Depressive Disorder Patients with and without Suicidal Ideation by Minxin Guo, Heng Zhang, Yuanyuan Huang, Yunheng Diao, Wei Wang, Zhaobo Li, Shixuan Feng, Jing Zhou, Yuping Ning, Fengchun Wu, Kai Wu

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Machine learning to identify environmental drivers of phytoplankton blooms in the Southern Baltic Sea by Maximilian Berthold, Pascal Nieters, Rahel Vortmeyer-Kley

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Machine learning for human mobility during disasters: A systematic literature review by Jonas Gunkel, Max Mühlhäuser, Andrea Tundis

“…However, existing models are limited in their applicability to disasters, as they are typically restricted to describing regular mobility patterns. Machine learning models trained to capture patterns observable in provided training data also face this limitation. …”
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An Investigation of Suicidal Ideation from Social Media Using Machine Learning Approach by Soumyabrata Saha, Suparna Dasgupta, Adnan Anam, Rahul Saha, Sudarshan Nath, Surajit Dutta

“…The machine learning algorithms showed high accuracy, precision, recall, and F1-score in detecting suicide patterns on social media data whereas SVM has the highest performance with an accuracy of 0.886.       …”
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Integrating remote sensing, GIS, and machine learning for zoonotic cutaneous leishmaniasis modelling by Fatemeh Parto Dezfooli, Mohammad Javad Valadan Zoej, Fahimeh Youssefi, Ebrahim Ghaderpour

“…Zoonotic Cutaneous Leishmaniasis (ZCL) is a vector-borne disease (VBD) characterized by distinct spatiotemporal patterns. Accurate evaluation of ZCL risk patterns necessitates the utilization of comprehensive epidemiological and ecological data. …”
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INCREASING OF DIMENSIONALLY-GEOMETRICAL PARAMETERS AND TECHNOLOGICAL CHARACTERISTICS OF INVESTMENT MOLDS IN CASTING UNDER DISPENSABLE PATTERNS by I. G. Sapchenko, S. G. Zhilin, G. M. Savastjanov

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