One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

Hiding technique for dynamic encryption text using encoding table and symmetric encryption method (AES algorithm) is presented in this paper. The encoding table is generated dynamically from MSB of the cover image points that used as the first phase of encryption. The Harris corner point algorithm is applied on cover image to generate the corner points which are used to generate dynamic AES key to second phase of text encryption. The embedded process in the LSB for the image pixels except the Harris corner points for more robust. Experimental results have demonstrated that the proposed scheme have embedding quality, error-free text recovery, and high value in PSNR.

In this work, results of a mathematical analysis of the role of workpiece preheating in laser keyhole welding were presented. This analysis considered the steady-state welding as well as certain range of boundary conditions over which preheating effect would be indicated. This work is an attempt to interpret the role of preheating to increase welding depth and perform keyhole welding with high quality using physical and thermal properties of steel alloys.

Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar

This search is field research, which aims to explore the trends of students in media department toward specialized Satellite Channels and identify the knowledge capacity and its role in the development of their knowledge’s, represented by watching those channels as well as media students' habits exposed by those channels. As to the public is a key element in the process and substantive communication, the Sociological studies information on that article information is not complete its work, but that he was receiving from before receiving, and send every piece of information content in order to achieve a certain goal, therefore, is the future of receiving such information in order to achieve a particular goal, which is

This study aims to identify the role of satellite channels in imparting behavior to children from the point of view of their parents in Tulkarm city. The researcher used a descriptive technique. A sample of (18000) males and females married couples was used above 20 years old in the city of Tulkarm. The study sample size is (201) married couples. It took place in September 2020. The questionnaire was the main tool for collecting data. The study found that the total degree of satellite channels contribution in imparting negative behaviors to children was high, as it reached (72.20%). The total degree of the role of satellite channels in imparting positive behaviors to children was medium, reaching (69.20%). Moreover, the results also indi