Generalized Tolerance Optimization for Robust System Design by Adaptive Learning of Gaussian Processes by Julia Stecher, Lothar Kiltz, Knut Graichen

“…First, the achievable accuracy is investigated for a non-convex test function the analytical solution of which is known. …”
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Deep Recurrent Reinforcement Learning for Intercept Guidance Law under Partial Observability by Xu Wang, Yifan Deng, Yuanli Cai, Haonan Jiang

“…Artificial intelligence technologies, such as deep reinforcement learning (DRL), have been widely applied to improve the performance of guidance laws. …”
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ARM-IRL: Adaptive Resilience Metric Quantification Using Inverse Reinforcement Learning by Abhijeet Sahu, Venkatesh Venkatramanan, Richard Macwan

“…The method infers a reward function from expert control actions. Unlike previous approaches using static weights or fuzzy logic, this work applies adversarial inverse reinforcement learning (AIRL), training a generator and discriminator in parallel to learn the reward structure and derive an optimal policy. …”
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Navigating Data Corruption in Machine Learning: Balancing Quality, Quantity, and Imputation Strategies by Qi Liu, Wanjing Ma

“…Data corruption, including missing and noisy entries, is a common challenge in real-world machine learning. This paper examines its impact and mitigation strategies through two experimental setups: supervised NLP tasks (NLP-SL) and deep reinforcement learning for traffic signal control (Signal-RL). …”
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Artificial liver classifier: a new alternative to conventional machine learning models by Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid

“…IntroductionSupervised machine learning classifiers sometimes face challenges related to the performance, accuracy, or overfitting.MethodsThis paper introduces the Artificial Liver Classifier (ALC), a novel supervised learning model inspired by the human liver's detoxification function. …”
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Predictive Utility of the Functional Movement Screen and Y-Balance Test: Current Evidence and Future Directions by Adam C. Eckart, Pragya Sharma Ghimire, James Stavitz, Stephen Barry

“…This review analyzes the Functional Movement Screen (FMS) and the Y-Balance Test (YBT) landscape. …”
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Transfer of preclinical study data on the influence of cimicifuga racemosaon functional changes in the hippocampus during menopause by Petra Stute, Hans-Heinrich Henneicke-von Zepelin, Petra Nicken

“…Focus was laid on changes in the hippocampal function, that is disturbed by hormonal fluctuations, but can also be brought back into balance by iCR.…”
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Molecular typing of gliomas on the basis of integrin family genes and a functional study of ITGA7 by Hongxi Han, Peng Feng, Guoqiang Yuan

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Reconfigurable neuromorphic functions in antiferroelectric transistors through coupled polarization switching and charge trapping dynamics by Jing Gao, Yu-Chieh Chien, Jiali Huo, Lingqi Li, Haofei Zheng, Heng Xiang, Kah-Wee Ang

“…Additionally, we further demonstrate synaptic and neuronal functions for implementing unsupervised learning rules and spiking behavior in spiking neural networks. …”
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Development of advanced voice-supported simulators with the function of automated estimation of air traffic controllers skills by V. E. Borisov, V. A. Borsoev, A. A. Bondarenko

“…As a result, a conceptual design was formed and a promising simulator with the function of training automation and voice support was developed. …”
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Intelligent Dispatch Decision-Making for UHVDC Blocking Fault Based on Deep Learning by Xiaonan YANG, Bo SUN, Yansheng LANG

“…Thirdly, the back-propagation algorithm is used to construct the deep learning framework, and the effective fault-disposal strategy is automatically generated by continuously calculating the loss function and the accuracy correction training model. …”
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Learning Styles, Socio-Demographic Variables and Academic Performance of Building Engineering Students by Juan Manuel Alducin-Ochoa, Ana Isabel Vázquez-Martínez

“…The objectives guiding this research were to determine the dominant learning style of the first year Building engineering students (University of Seville), the influence of the style on the grades in each school subject, and if learning style is influenced by socio-demographic variables. …”
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Super-resolution mapping of anisotropic tissue structure with diffusion MRI and deep learning by Alfredo Ordinola, David Abramian, Magnus Herberthson, Anders Eklund, Evren Özarslan

“…The latter has prompted interest in quantitative mapping of the microstructural parameters, such as the fiber orientation distribution function (fODF), which is instrumental for noninvasively mapping the underlying axonal fiber tracts in white matter through a procedure known as tractography. …”
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Machine learning for QoS and security enhancement of RPL in IoT-Enabled wireless sensors by Abubakar Wakili, Sara Bakkali, Ahmed El Hilali Alaoui

“…Our approach integrates a random forest model for precise traffic classification, a reinforcement learning module for dynamic and adaptive routing, and a modified RPL objective function that incorporates classification outcomes into routing decisions. …”
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Optimal control of manipulator with joint clearance compensation via generalized policy learning by Wenting Liu, Qingliang Zeng, Zhiwen Wang, Jun Zhao, Lin Kong

“…The method simultaneously computes feedforward and feedback control actions through an enhanced system approach based on Adaptive Dynamic Programming (ADP) and a performance index function. To implement the optimal control strategy, a generalized policy learning algorithm is developed, which reduces the dependency on known system dynamics. …”
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Extending Power Electronic Converter Lifetime in Marine Hydrokinetic Turbines with Reinforcement Learning by Samuel Barton, Ted K. A. Brekken, Yue Cao

“…This work presents a reinforcement learning (RL) method built within a quadratic feedback torque control framework to balance energy generation with power electronic device lifetime. …”
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Plant Classification Method Using Histogram and Machine Learning for Smart Agriculture Applications by Orhan Yaman, Türker Tuncer

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A Fast Learning Method for Multilayer Perceptrons in Automatic Speech Recognition Systems by Chenghao Cai, Yanyan Xu, Dengfeng Ke, Kaile Su

“…A preadjusting strategy based on separation of training data and dynamic learning-rate with a cosine function is used to increase the accuracy of a stochastic initial MLP. …”
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Optimal Energy Management of Microgrids using Quantum Teaching Learning Based Algorithm by Zahra Esmaeili, Seyed Hamid Hosseini

“…The operation cost of the microgrid is considered as an objective function. The problem is formulated as a bi-level minimum-maximum optimization problem and is solved in two levels iteratively. …”
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A Mass‐Conserving‐Perceptron for Machine‐Learning‐Based Modeling of Geoscientific Systems by Yuan‐Heng Wang, Hoshin V. Gupta

“…The MCP exploits the inherent isomorphism between the directed graph structures underlying both PC models and GRNNs to explicitly represent the mass‐conserving nature of physical processes while enabling the functional nature of such processes to be directly learned (in an interpretable manner) from available data using off‐the‐shelf ML technology. …”
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