Nowadays, the robotic arm is fast becoming the most popular robotic form used in the industry among others. Therefore, the issues regarding remote monitoring and controlling system are very important, which measures different environmental parameters at a distance away from the room and sets various condition for a desired environment through a wireless communication system operated from a central room. Thus, it is crucial to create a programming system which can control the movement of each part of the industrial robot in order to ensure it functions properly. EDARM ED-7100 is one of the simplest models of the robotic arm, which has a manual controller to control the movement of the robotic arm. In order to improve this control s

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

The automatic estimation of speaker characteristics, such as height, age, and gender, has various applications in forensics, surveillance, customer service, and many human-robot interaction applications. These applications are often required to produce a response promptly. This work proposes a novel approach to speaker profiling by combining filter bank initializations, such as continuous wavelets and gammatone filter banks, with one-dimensional (1D) convolutional neural networks (CNN) and residual blocks. The proposed end-to-end model goes from the raw waveform to an estimated height, age, and gender of the speaker by learning speaker representation directly from the audio signal without relying on handcrafted and pre-computed acou

The current study examined the impact of using PowerPoint presentation on EFL student’s attendance, achievement and engagement. To achieve the aim of this study, three null hypotheses have been posed as follows: There is no statistically significant difference between the mean score of the experimental group attendance and that of the control one; there is no statistically significant difference between the mean score of the experimental group achievement and that of the control one, and there is no statistically significant difference between the mean score of the experimental group engagement and that of the control one. To verify a hypothesis, a sample of sixty students is chosen randomly from the third year, department of English,

The present work reports a direct experimental comparison of the catalytic hydrodesulfurization of
thiophene over Co-Mo/Al2O3 in fixed- and fluidized-bed reactors under the same conditions. An
experimental pilot plant scale was constructed in the laboratories of chemical engineering department,
Baghdad University; fixed-bed unit (2.54 cm diameter, and 60cm length) and fluidized-bed unit (diameter of 2.54 cm and 40 cm long with a separation zone of 30 cm long and 12.7 cm diameter). The affecting
variables studied in the two systems were reaction temperature of (308 – 460) oC, Liquid hourly space
velocity of (2 – 5) hr-1, and catalyst particle size of (0.075-0.5) mm. It was found in both operations that the
conversion

Micro metal forming has an application potential in different industrial fields. Flexible tool-assisted sheet metal forming at micro scale is among the forming techniques that have increasingly attracted wide attention of researchers. This forming process is a suitable technique for producing micro components because of its inexpensive process, high quality products and relatively high production rate. This study presents a novel micro deep drawing technique through using floating ring as an assistant die with flexible pad as a main die. The floating ring designed with specified geometry is located between the process workpiece and the rubber pad. The function of the floating ring in this work is to produce SS304 micro cups with profile

Recently, the internet has made the users able to transmit the digital media in the easiest manner. In spite of this facility of the internet, this may lead to several threats that are concerned with confidentiality of transferred media contents such as media authentication and integrity verification. For these reasons, data hiding methods and cryptography are used to protect the contents of digital media. In this paper, an enhanced method of image steganography combined with visual cryptography has been proposed. A secret logo (binary image) of size (128x128) is encrypted by applying (2 out 2 share) visual cryptography on it to generate two secret share. During the embedding process, a cover red, green, and blue (RGB) image of size (512