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A Neuro-Fuzzy Based Approach for Energy Consumption and Profit Operation Forecasting

In recent years, the massive growth in the scale of data is being a key factor in the needed data processing approaches. The efficiency of the algorithms of knowledge extraction depends significantly on the quality of the raw data, which can be improved by employing preprocessing techniques. In the field of energy consumption, the forecasting of power cost needed plays a vital role in determining the expected profit. To achieve a forecasting with higher accuracy, it is needed to deal with the large amount of data associated with power plants. It is shown in the literature that the use of

Mechanical Design

Design and FEA-based Methodology for a Novel 3 Parallel Soft Muscle Actuator

Recently, soft robotics represents a new era of advanced robotics systems. Based on the flexible nature of soft robots, they are more adequate to have safe interaction with humans and handle complex or delicate objects. Due to the nature of soft robotics, there is a crucial need to propose new designs, fabrication, and control systems suitable for the flexibility nature. In this research project, a novel three parallel soft muscle actuator is proposed. The proposed design and analytical models for predicting actuation behavior are based on a set of design parameters. First, the actuator

Mechanical Design

Lid-Driven Cavity Flow with Elliptic Obstacle at Different Orientations

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

Mechanical Design

Underwater Soft Robotics: A Review of Bioinspiration in Design, Actuation, Modeling, and Control

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. ©

Mechanical Design

Systematic university decision making based on footprint identifiers

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.

Mechanical Design

Modified fuzzy c-means clustering approach to solve the capacitated vehicle routing problem

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

Artificial Intelligence
Software and Communications
Mechanical Design

Air change rate effects on the airborne diseases spreading in Underground Metro wagons

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

Healthcare
Mechanical Design

Regression Modeling for the Ventilation Effect on COVID-19 Spreading in Metro Wagons

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.

Healthcare
Software and Communications
Mechanical Design

Design, simulation, and kinematics of 9-DOF Serial-Parallel Hybrid Manipulator Robot

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

Software and Communications
Mechanical Design

Solving Inverse Kinematics of a 7-DOF Manipulator Using Convolutional Neural Network

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

Mechanical Design