EEG-based multi-modal emotion recognition using bag of deep features: An optimal feature selection approach

Much attention has been paid to the recognition of human emotions with the help of electroencephalogram (EEG) signals based on machine learning technology. Recognizing emotions is a challenging task due to the non-linear property of the EEG signal. This paper presents an advanced signal processing method using the deep neural network (DNN) for emotion recognition based on EEG signals. The spectral and temporal components of the raw EEG signal are first retained in the 2D Spectrogram before the extraction of features. The pre-trained AlexNet model is used to extract the raw features from the 2D Spectrogram for each channel. To reduce the feature dimensionality, spatial, and temporal based, bag of deep features (BoDF) model is proposed. A series of vocabularies consisting of 10 cluster centers of each class is calculated using the k-means cluster algorithm. Lastly, the emotion of each subject is represented using the histogram of the vocabulary set collected from the raw-feature of a single channel. Features extracted from the proposed BoDF model have considerably smaller dimensions. The proposed model achieves better classification accuracy compared to the recently reported work when validated on SJTU SEED and DEAP data sets. For optimal classification performance, we use a support vector machine (SVM) and k-nearest neighbor (k-NN) to classify the extracted features for the different emotional states of the two data sets. The BoDF model achieves 93.8% accuracy in the SEED data set and 77.4% accuracy in the DEAP data set, which is more accurate compared to other state-of-the-art methods of human emotion recognition. - 2019 by the authors. Licensee MDPI, Basel, Switzerland.Funding: This research was funded by Higher Education Commission (HEC): Tdf/67/2017.Scopu

Anticipation of e-learning acceptance through nursing students enthusiasm scale at Gonabad University of Medical Sciences in 2015

Introduction: Given the importance of using e-learning in medical education, this study aimed to Anticipate the e-learning acceptance according to &nbsp;nursing students enthusiasm scale at Gonabad University of Medical Sciences. Methods: This cross sectional study conducted on all undergraduate students of nursing and midwifery who were enrolled at Gonabad University of Medical Sciences in 2015. 172 students were recruited and enthusiasm and e-learning questionnaire were filled for them. SPSS V.16 package and the independent t-test, Pearson correlation and multiple regression model were used to analyse data. Results: The results showed there is no significant differenceهد &nbsp;the relation between male and female students' enthusiasm(P>0.05). There is a significant relationship between academic enthusiasm component with e-learning acceptance (p<0.01), and components of the behavioral, emotional and cognitive enthusiasm, with &nbsp;acceptance of e-learning. Conclusion: The findings showed that the components of academic enthusiasm is predicting acceptance of e-learning by students. Workshops and training courses may enhance students' enthusiasm. Stakeholders should also be organized by universities to enhance acceptance of e-learning

Determination of combined hardening material parameters under strain controlled cyclic loading by using the genetic algorithm method

In this paper, experimental and numerical investigations on mechanical behaviors of SS304 stainless steel under fully reversed strain-controlled, relaxation, ratcheting and multiple step strain-controlled cyclic loading have been performed. The kinematic and isotropic hardening theories based on the Chaboche model are used to predict the plastic behavior. An iterative method is utilized to analyze the mechanical behavior under cyclic loading conditions based on the Chaboche hardening model. A set of kinematic and isotropic parameters was obtained by using the genetic algorithm optimization approach. In order to analyze the effectiveness of this optimization procedure, numerical and experimental results for an SS304 stainless steel are compared. Finally, the results of this research show that by using the material parameters optimized based on the strain-controlled and relaxation data, good agreement with the experimental data for ratcheting is achieved

Ratcheting behavior of cylindrical pipes based on the Chaboche kinematic hardening rule

In this study, cyclic loading behavior of thick cylindrical pipes are described. Effects of internal pressure level and axial strain amplitude on the ratcheting rate under different types of loading histories are investigated. The kinematic hardening theory based on the Chaboche model is used to predict the plastic behavior of the structures. An iterative method is developed to analyze the structural behavior under cyclic loading conditions based on the Chaboche kinematic hardening model

Small scale effects on transient vibrations of porous FG cylindrical nanoshells based on nonlocal strain gradient theory

This research investigates transient vibrational characteristics of a porous functionally graded cylindrical nanoshell under different impulsive loadings with the use of nonlocal strain gradient theory (NSGT). Based on NSGT, two size parameters accounting for stiffness softening and hardening effects are incorporated in modeling of the nanoshell. Impulse forces have three forms of triangular, rectangular and sinusoidal. Two sorts of porosity distributions called even and uneven have been taken into account. Governing equations obtained for porous nanoshell have been solved through inverse Laplace transforms technique to derive dynamical deflections. It is shown that transient responses of a nanoshell are affected by the form and position of impulse loading, amount of porosities, porosities dispensation, nonlocal and strain gradient parameters.\Scopu

Nonlinear dynamic characteristics of nonlocal multi-phase magneto-electro-elastic nano-tubes with different piezoelectric constituents

Analysis of exact nonlinear dynamic behavior of multi-phase magneto-electro-elastic (MEE) nanoshells has been presented in this paper using Jacobi elliptic functions. Multi-phase MEE material is constructed form piezoelectric and piezo-magnetic constituents for which the material properties can be controlled based on the percentages of the constituents. Nonlinear governing equations are established for MEE nanoshell based on nonlocal elasticity theory and an exact solution is provided using Jacobi elliptic function method. This method gives an exact value of vibration frequency in nonlinear regime and overcomes the shortcomings of several approximate solutions applied in the studies on nanostructures. It will be shown that nonlinear vibration behavior of MEE nanoshell in electro-magnetic field depends on the constituent's percentages. Influences of nonlocal scale factor, piezoelectric reinforcement, magnetic field intensity, and electrical voltage on vibration frequencies of the nanoshell are also investigated. 2020, Springer-Verlag GmbH Germany, part of Springer Nature.Scopu

Platoon Transitional Maneuver Control System: A Review

Connectivity and autonomy are considered two of the most promising technologies to improve mobility, fuel consumption, travel time, and traffic safety in the automated transportation industry. These benefits can be realized through vehicle platooning. A vehicle platoon is composed of a group of connected automated vehicles (CAVs) traveling together at consensual speed, following the leading vehicle (leader) while maintaining a prespecified inter-vehicle distance. This paper reviews the different existing control techniques associated with the transitional platoon maneuvers such as merge/split and lane change. Different longitudinal and lateral vehicle dynamics that are mainly used in the transitional platoon maneuvers are discussed. The most used control algorithms for both longitudinal and lateral control used for transitional platoon maneuvers are reviewed and the advantages and limitations of each control strategy are discussed. The most recent articles on platoon control maneuvers have been analyzed based on the proposed control algorithm, homogeneously or heterogeneously of platoon members, type of platoon maneuver, the aim of control problem, type of implementation, and used simulation tools. This paper also discusses different trajectory planning techniques used in lateral motion control and studies the most recent research related to trajectory planning for automated vehicles and summarizes them based on the used trajectory planning technique, platoon or/and lane change, the type of traffic, and the cost functions. Finally, this paper explores the open issues and directions for future research.Scopu