Cloth simulation and animation has been the topic of research since the mid-80's in the field of computer graphics. Enforcing incompressible is very important in real time simulation. Although, there are great achievements in this regard, it still suffers from unnecessary time consumption in certain steps that is common in real time applications.   This research develops a real-time cloth simulator for a virtual human character (VHC) with wearable clothing. This research achieves success in cloth simulation on the VHC through enhancing the position-based dynamics (PBD) framework by computing a series of positional constraints which implement constant densities. Also, the self-collision and collision wit

This paper presents the design and analysis of composite right left hand (CRLH) electromagnetic bandgap (EBG) structure. The proposed unit cell is consistent of a dielectric substrate with dimensions of 5×5×1 mm 3 made of FR4-Epoxy with εr = 4.4 underneath of a conductive patch with dimensions of 4.4×4.4mm 2 . The unit cell is structured to perform a negative permittivity (ε) and negative permeability (µ) in different bands. The proposed unit cell is developed to 5G systems in the sub-6GHz bands. In this work, a complete analysis of the unit cell in terms of Sparameters, constitutive parameters and refraction index are evaluated using HFSS simulation package based on Finite Element Method (FEM).

The regressor-based adaptive control is useful for controlling robotic systems with uncertain parameters but with known structure of robot dynamics. Unmodeled dynamics could lead to instability problems unless modification of control law is used. In addition, exact calculation of regressor for robots with more than 6 degrees of freedom is hard to be calculated, and the task could be more complex for robots. Whereas the adaptive approximation control is a powerful tool for controlling robotic systems with unmodeled dynamics. The local (partitioned) approximation-based adaptive control includes representation of the uncertain matrices and vectors in the robot model as finite combinations of basis functions. Update laws for the weighting matri

Objective: The present study investigates whether the exposure to low-power diode laser induces denaturation in red blood cell (RBC) membrane protein composition, and determines the irradiation time for when denaturation of membrane protein process begins. Background: A low-energy laser has been used extensively in medical applications. Several studies indicated significant positive effects of laser therapy on biological systems. In contrast, other studies reported that laser induced unwanted changes in cell structure and biological systems. The present work studied the effect of irradiation time of low-power diode laser on the structure of membrane proteins of human RBCs. Materials and methods: The RBC suspension was divided into five equa

Leap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

Background: Hand, foot, and mouth disease is viral disease caused commonly by coxsackie virus A₁₆ virus. It is a mild disease and children usually recover with no specific treatment within 7 to 10 days. Rarely, this illness may be associated with aseptic meningitis were patient may need hospitalization.

Objective: To determine significance of clinical features of hand, foot and mouth disease.

Methods: A cross sectional study of cases with clinical features of hand, foot and mouth disease visiting the dermatological consultation unit of Al Kindy teaching hospital. Sampling was for Zyona and Edressi Quarter patients over the period of 1^st December 2017

This paper presents a robust control method for the trajectory control of the robotic manipulator. The standard Computed Torque Control (CTC) is an important method in the robotic control systems but its not robust to system uncertainty and external disturbance. The proposed method overcome the system uncertainty and external disturbance problems. In this paper, a robustification term has been added to the standard CTC. The stability of the proposed control method is approved by the Lyapunov stability theorem.  The performance of the presented controller is tested by MATLAB-Simulink environment and is compared with different control methods to illustrate its robustness and performance.

The first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o