Optimizing RNNs for EMG Signal Classification: A Novel Strategy Using Grey Wolf Optimization.

Accurate classification of electromyographic (EMG) signals is vital in biomedical applications. This study evaluates different architectures of recurrent neural networks for the classification of EMG signals associated with five movements of the right upper extremity. A Butterworth filter was implemented for signal preprocessing, followed by segmentation into 250 ms windows, with an overlap of 190 ms.

Optimization of the Reduction of Shrinkage and Warpage for Plastic Parts in the Injection Molding Process by Extended Adaptive Weighted Summation Method.

The consumer market has changed drastically in recent times. Consumers are becoming more demanding, and many companies are competing to be market leaders. Therefore, companies must reduce rejects and minimize their operating costs.

Optimized Random Forest for Solar Radiation Prediction Using Sunshine Hours.

Knowing exactly how much solar radiation reaches a particular area is helpful when planning solar energy installations. In recent years the use of renewable energies, especially those related to photovoltaic systems, has had an impressive up-tendency. Therefore, mechanisms that allow us to predict solar radiation are essential.

Solar Energy-Based Future Perspective for Organic Rankine Cycle Applications.

This article explores the patents of solar energy technologies in the organic Rankine cycle (ORC) applications. The conversion of low-quality thermal energy into electricity is one of the main characteristics of an ORC, making efficient and viable technologies available today. However, only a few and outdated articles that analyze patents that use solar energy technologies in ORC applications exist.

Metaheuristic Parameter Identification of Motors Using Dynamic Response Relations.

This article presents the use of the equations of the dynamic response to a step input in metaheuristic algorithm for the parametric estimation of a motor model. The model equations are analyzed, and the relations in steady-state and transient-state are used as delimiters in the search. These relations reduce the number of random parameters in algorithm search and reduce the iterations to find an acceptable result.

Non-Linear Regression Models with Vibration Amplitude Optimization Algorithms in a Microturbine.

Machinery condition monitoring and failure analysis is an engineering problem to pay attention to among all those being studied. Excessive vibration in a rotating system can damage the system and cannot be ignored. One option to prevent vibrations in a system is through preparation for them with a model.