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 cameras system to capture the images and upload them to the Amazon Simple Storage Service (AWS S3) cloud. Then two detectors were running, Haar cascade and multitask cascaded convolutional neural networks (MTCNN), at the Amazon Elastic Compute (AWS EC2) cloud, after that the output results of these two detectors are compared using accuracy and execution time. Then the classified non-permission images are uploaded to the AWS S3 cloud. The validation accuracy of the offline augmentation face detection classification model reached 98.81%, and the loss and mean square error were decreased to 0.0176 and 0.0064, respectively. The execution time of all AWS cloud systems for one image when using Haar cascade and MTCNN detectors reached three and seven seconds, respectively.
This paper describes a microcontroller-based function generator system. By the function generator sine wave, square wave, quasi-square wave, saw-tooth and triangular waveforms are generated over a wide frequency range according to user requirements. By utilizing processing capabilities of the microcontroller the hardware is minimized exceedingly. The output waveform shapes are digitally-controlled to achieve the required wave shape. The single chip microcomputer of waveform generation equipment offers the possibility of improvements in manufacture reliability, maintenance and servicing and increased control flexibility. The system is built and tested. The results of test were satisfactory and appreciated by test engineers at different ce
... Show MoreThis work includes design, implementation and testing of a microcontroller – based spectrum analyzer system. Both hardware and software structures are built to verify the main functions that are required by such system. Their design utilizes the permissible and available tools to achieve the main functions of the system in such a way to be modularly permitting any adaptation for a specific changing in the application environment. The analysis technique, mainly, depends on the Fourier analysis based methods of spectral analysis with the necessary required preconditioning processes. The software required for waveform analysis has been prepared. The spectrum of the waveform has been displayed, and the instrument accuracy has been checked.
... Show MoreDoppler broadening technique is suggested to monitor the development of tumours. It depends on the sensitivity of positronium (Ps) annihilation parameters to the sub- microstructural changes in biological tissues. This technique uses high resolution HpGe detector to measure the lineshape parameters (S and W) in normal mice's mammary tissues and adenocarcinoma mammary tissues as a function of tumour growth. The results demonstrate that the central parameter (S) decreases and the wing parameter (W) increases as the tumour grow. It is found that the S parameter changes considerably with the distribution of voids which are affected by the tumour development. Therefore the present technique can successfully be employed to monitor the developm
... Show MoreECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.
The objective of the present study is to verify the actual carious lesion depth by laser
fluorescence technique using 650 nm CW diode laser in comparison with the histopathological
investigation. Five permanent molar teeth were extracted from adult individuals for different reasons
(tooth impaction, periodontal diseases, and pulp infections); their ages were ranging from 20-25 years
old. Different carious teeth with varying clinical stages of caries progression were examined. An
experimental laser fluorescence set-up was built to perform the work regarding in vitro detection and
quantification of occlusal dental caries and the determination of its actual clinical carious lesion depth by
650 nm CW diode laser (excitat
The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th
... Show MoreThe power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such ha
... Show MoreThe major of DDoS attacks use TCP protocol and the TCP SYN flooding attack is the most common one among them. The SYN Cookie mechanism is used to defend against the TCP SYN flooding attack. It is an effective defense, but it has a disadvantage of high calculations and it doesn’t differentiate spoofed packets from legitimate packets. Therefore, filtering the spoofed packet can effectively enhance the SYN Cookie activity. Hop Count Filtering (HCF) is another mechanism used at the server side to filter spoofed packets. This mechanism has a drawback of being not a perfect and final solution in defending against the TCP SYN flooding attack. An enhanced mechanism of Integrating and combining the SYN Cookie with Hop Count Filtering (HCF) mech
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