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

“…In this study, we hypothesize that in addition to subject-specific components, sEMG signals also contain pattern-specific components, which is independent of individuals and solely related to gesture patterns. …”
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A weighted pattern matching approach for classification of imbalanced data with a fireworks-based algorithm for feature selection by N. K. Sreeja

“…This paper proposes a novel instance-based classification algorithm called Weighted Pattern Matching based Classification (PMC+) for classifying imbalanced data. …”
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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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Eye tracking in digital pathology: A comprehensive literature review by Alana Lopes, Aaron D. Ward, Matthew Cecchini

“…Thematic analysis was conducted to organize each study into one or more of the 10 themes identified to characterize the visual search patterns of pathologists: (1) effect of experience, (2) fixations, (3) zooming, (4) panning, (5) saccades, (6) pupil diameter, (7) interpretation time, (8) strategies, (9) machine learning, and (10) education. …”
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Technical parameters analyses of different types of impact-vibration soil compacting machines by I. S. Tyuremnov

“…This is a common pattern: as the mass of the machine increases, the excitation force increases, but the relative excitation force and frequency of oscillation decrease. …”
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In‐Situ Rheology Measurements via Machine‐Learning Enhanced Direct‐Ink‐Writing by Robert D. Weeks, Jennifer M. Ruddock, J. Daniel Berrigan, Jennifer A. Lewis, James. O. Hardin

“…However, an iterative approach, using random selection or constant expert guidance, is still used to create printable inks and optimize printing parameters by expending significant amounts of time, materials, and effort. Herein, a machine learning (ML) model that estimates ink rheology in‐situ from a simple printed test pattern is reported. …”
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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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Reverse Determination of Face-milling Cutter Radius of Curvilinear Cylindrical Gears Using Contact Pattern by Zhang Xuegang, Dong Yingjie

“…To design a curvilinear cylindrical gear with arbitrary tooth surface contact pattern, a method for determining the radius of a disc-shaped milling cutter for machining the curvilinear cylindrical gear was proposed based on the reverse determination of the required dimensions of the contact pattern. …”
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THE PRODUCTION OF COMPLEX PROFILE DETAILS BY COMBINED METHOD OF LOST-WAX CASTING AND OF CONSUMABLE PATTERN MODELS by O. I. Shinsky, I. I. Maksyuta, Yu. G. Kvasnitskaya, E. V. Mikhnyan, A. V. Neyma

“…Besides this method allows to receive figurine castings with minimization of an allowance for machining of details, to increase their geometrical accuracy and to lower a roughness.…”
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