Stability Optimization of Explicit Runge–Kutta Methods with Higher-Order Derivatives by Gerasim V. Krivovichev

“…In numerical experiments, optimal parameter values are used for the construction of high-order schemes for the method of lines for problems with partial differential equations. Problems for linear and nonlinear hyperbolic and parabolic equations are considered. …”
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Object Ontologies as a Priori Models for Logical-Probabilistic Machine Learning by D. N. Gavrilin, A.V. Mantsivoda

“…The combination of LPML and object ontologies is capable of solving the forecasting problems, the tasks of automated control, problem detection, decision making, and business process synthesis. …”
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L’estime de soi : un cas particulier d’estime sociale ? by Matteo Santarelli

“…Axel Honneth’s discussion of the relation between self esteem and social esteem represents an original feature of his intersubjective theory of recognition. …”
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Evaluation of the River Salinity Changes using Hydrochemical Method in Arid Area (Case Study: Namaklan River, Ilam) by Maryam Mousavi, Noredin Rostami, Haji Karimi

“…Extended Abstract 1-Introduction Increasing the salinity of natural sources of drinking water has been reported as one of the problems affecting low-income countries, but it has not yet been thoroughly investigated. …”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…The swarm intelligent optimization methods transform a complex problem of structural parameter identification into a constrained optimization problem. …”
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Instantaneous Frequency Analysis Based on High-Order Multisynchrosqueezing Transform on Motor Current and Application to RV Gearbox Fault Diagnosis by Shiyi Chai, Kai Xu

“…However, for gearboxes, the commonly used methods of detecting faulty frequency sidebands are easily disturbed by installation errors, inherent harmonics, and fundamental frequency with high amplitude. Aiming at this problem, this study presents instantaneous frequency polarview (IFpolarview), which diagnoses faults based on motor angle and motor current frequency modulation (FM) features. …”
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The value of the theoretical heritage of M. D. Kondratiev in the state regulation of the economy by O.O. Krynytska, T.I. Tkachuk

“…Emphasis is placed on the causal link between the creation of the «long wave» theory and Kondratiev's interest in the problems of combining the market and the plan, the problems of prediction and forecasting. …”
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Forecast distribution of cattle manure processing technologies in the Russian Federation by A. Yu. Briukhanov, E. V. Shalavina, E. V. Vasilev

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An evolutionary algorithm‐based classification method for high‐dimensional imbalanced mixed data with missing information by Yi Liu, Gengsong Li, Qibin Zheng, Guoli Yang, Kun Liu, Wei Qin

“…Multiple feature selection uses a two‐stage strategy to obtain stable relevant features. …”
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Semi-supervised gearbox fault diagnosis under variable working conditions based on masked contrastive learning by ZHANG Huiyun, ZUO Fangjun, LI Hang, YU Xi

“…Finally, during the fine-tuning phase, a domain-conditioned feature correction strategy was introduced to generate target domain feature corrections. …”
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CWMS-GAN: A small-sample bearing fault diagnosis method based on continuous wavelet transform and multi-size kernel attention mechanism. by Shun Yu, Zi Li, Jialin Gu, Runpu Wang, Xiaoyu Liu, Lin Li, Fusen Guo, Yuheng Ren

“…Specifically, this study proposes a continuous wavelet convolution strategy (CWCL) instead of the traditional convolution operation in GAN, which can additionally capture the signal's frequency domain features. Meanwhile, this study designed a new multi-size kernel attention mechanism (MSKAM), which can extract the features of bearing vibration signals from different scales and adaptively select the features that are more important for the generation task to improve the accuracy and authenticity of the generated signals. …”
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Bearing Compound Fault Diagnosis Based on Double-Domain Reweighted Adaptive Sparse Representation by Jing Meng, Jiawen Xu, Chang Liu, Chao Chen, Lili Liu

“…Diagnosing compound faults accurately is a thorny problem, which can ensure the normal operation of mechanical structure. …”
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A NOVEL VOICE-BASED SYSTEM FOR PARKINSON’S DISEASE DETECTION USING RNN-LSTM by Repudi Pitchiah, T. Sasi Rooba, Uma Pavan Kumar

“…For a range of prediction problems that are troubling medical practitioners, Deep Learning (DL) has gained popularity recently. …”
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Entrepreneurial Coenosis in View of Evolutionary Approach by A. N. Kuzminov, V. M. Dzukha, I. G. Paliy

“…Methodological solution of this problem is possible through identifying general features of complex systems’ shaping – both biological, technical and economic, which are capable of self-organization. …”
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Sequence-to-point learning based on spatio-temporal attention fusion network for non-intrusive load monitoring by Shiqing Zhang, Youyao Fu, Xiaoming Zhao, Jiangxiong Fang, Yadong Liu, Xiaoli Wang, Baochang Zhang, Jun Yu

“…Initially, a temporal feature extraction module is designed to extract temporal features over a large temporal receptive field. …”
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Fault diagnosis method for rigid guides in vertical shaft hoisting systems by WANG Jianfeng, JIN Yuanzhi, ZHANG Yong, WANG Yongzhen, HE Jiacong

“…At present, vibration detection methods are mostly used for rigid guide fault diagnosis, but the diagnostic accuracy is easily affected by operating conditions such as cage load and running speed. To address this problem, eddy current sensors are used to collect fault signals of the rigid guides, ensuring that the signal features are not affected by the cage's operating environment. …”
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Steganalysis Using KL Transform and Radial Basis Neural Network by Safwan Hasoon, Farhad Khalifa

“…The essential problem in the security field is how to detect information hiding. …”
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SlowFast-TCN: A Deep Learning Approach for Visual Speech Recognition by Nicole Yah Yie Ha, Lee-Yeng Ong, Meng-Chew Leow

“…To address this challenge, viseme classification must not only extract lip image spatial features, but also to handle visemes of varying durations and temporal features. …”
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Multistep Prediction Model for Photovoltaic Power Generation Based on Time Convolution and DLinear by WANG Shuyu, LI Hao, MA Gang, YUAN Yubo, BU Qiangsheng, YE Zhigang

“…First， it improves the complete ensemble empirical mode decomposition with adaptive noise and ICEEMDAN decomposes multivariate meteorological sequences to reveal their potential features and obtain multidimensional subsequences that make it easier to learn multiscale features. …”
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Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis. by Claudia Bühnemann, Simon Li, Haiyue Yu, Harriet Branford White, Karl L Schäfer, Antonio Llombart-Bosch, Isidro Machado, Piero Picci, Pancras C W Hogendoorn, Nicholas A Athanasou, J Alison Noble, A Bassim Hassan

“…The distribution of image features for biomarkers in the remaining high quality material (118 cases, 104 features per case) were analysed by RSF with feature selection, and performance assessed using internal cross-validation, rather than a separate validation cohort. …”
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