Nowadays, human emotion recognition is a mandatory task for many human machine interaction fields. This paper proposes a novel multi-modal human emotion recognition framework. The proposed scheme utilizes first the 3D-Convolutional Neural Network (3D-CNN) deep learning architecture for extracting the spatio-temporal features from the electroencephalogram (EEG) signals, and the video data of human faces. Then, a combination of data augmentation, ensemble learning techniques is proposed to get the final fusion predictions. The fusion of the multi-modalities in the proposed scheme is carried out

This paper presents a generic model for material flow prediction based on the well-known Johnson-Cook model. The model is developed to precisely predict the flow behavior of various categories of alloys. The coupled effects between strain, strain rate, and temperature were taken into consideration. The proposed model is developed and assessed using the hot deformation data of four different categories of alloys; with four different base elements. Besides, the data of two different alloys under dynamic loading are used for assessment. The proposed modification is compared to the original

This paper presents a way to solve inverse kinematics of a 7-DOF manipulator using artificial neural networks. The manipulator consists of a 6-DOF articulated arm installed on a linear guide system to increase the workspace of the robot. The purpose of this paper is to provide an alternative to the traditional and complicated way to solve inverse kinematics by using artificial neural networks. The training data is generated from MATLAB after obtaining the DH parameters and workspace of the manipulator. Then, it was fed to the convolutional neural architecture to obtain a model for the

Serial manipulator robot is one of the most advanced robots in the last decade. The demand for this type of robot leads the researchers to develop and improve the robot to increase its workspace, speed and to minimize the control complexity. This paper presents a novel robot configuration that combines a 6 DOF serial manipulator with a 3 DOF spherical parallel wrist. The serial manipulator is KUKA kr6 R900 type, which is a real industrial robot. At the same time, the parallel spherical wrist is 3-RRS type (Revolute- Revolute-Spherical Joint), which can support one translation movement in the Z

The effect of different ventilation parameters on the infection potential of COVID-19 in a metro wagon is numerically studied. Two key indicators are used to quantify this potential. Based on the numerical results a regression analysis is performed to come up with the most suitable regression model for these key parameters. The proposed regression models are helpful in quantifying the infection risk at different ventilation scenarios. © 2021 IEEE.

The effect of the rate of change of fresh air inside passengers’ wagons for Underground Metro on the spreading of airborne diseases like COVID-19 is investigated numerically. The study investigates two extreme scenarios for the location of the source of infection within the wagon with four different air change rates for each. The first scenario considers the source of infection at the closest point to the ventilation system while the other places the infection source at the farthest point from the wagon ventilation system. The effect of the wagon windows’ status (i.e. closed or open) is also

Fuzzy C-Means clustering is among the most successful clustering techniques available in the literature. The capacitated vehicle routing problem (CVRP) is one of the most studied NP-hard problems. CVRP has attracted the attention of many researchers due to its importance within the supply chain management field. This study aims to develop a fuzzy c-means clustering heuristic to efficiently solve the CVRP with large numbers of customers by using cluster-first route-second method (CFRS). CFRS is a two-phase technique, where in the first phase customers are grouped into, and in the second phase

A new systematic decision-making framework for universities is presented. The framework avoids the disadvantages of the balanced score cards technique. A solid mathematical technique is provided for mapping processes and quality items. Application to the Egyptian system is fully explained. The footprint concept developed within an international initiative is introduced. The mathematical correlation algorithm main output is a decision matrix matching processes and quality aspects. Results illustrate automatic suitable matching between processes and quality standards. © 2021 IEEE.

Nature and biological creatures are some of the main sources of inspiration for humans. Engineers have aspired to emulate these natural systems. As rigid systems become increasingly limited in their capabilities to perform complex tasks and adapt to their environment like living creatures, the need for soft systems has become more prominent due to the similar complex, compliant, and flexible characteristics they share with intelligent natural systems. This review provides an overview of the recent developments in the soft robotics field, with a focus on the underwater application frontier. ©

The aim of the present work is to predict the flow field around an elliptic obstacle at different orientations inside a square Lid-Driven Cavity (LDC). The Lattice Boltzmann Method (LBM) is used to simulate the flow at a Reynolds number, Re, of 100, using the two-dimensional nine-velocity, (D2Q9) lattice configuration and the BGK collision operator. The in-house code is validated using data from the literature for the case of LDC with a central circular cylinder. Different ellipse orientations are tested (0°, 30°, 45°, 90°, 120°, 145°, and 150°) to check the effect of orientation on the vortex