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

ZnIn2(Se1-xTex)4 (ZIST) chalcopyrite semiconductor thin films at various contents (x = 0.0, 0.2, and 0.4) are deposited on glass and p type silicon (111) substrate to produce heterojunction solar cell by using the thermal evaporation technique at RT where the thickness of 500 nm with a vacuum of 1×10-5 mbar and a deposited rates of 5.1 nm/s. This study focuses on how differing x content effect on the factors affecting the solar cell characteristics of ZIST thin film and n-ZIST/p-Si heterojunction. X-ray diffraction XRD investigation shows that this structure of ZIST film is polycrystalline and tetragonal, with (112) preferred orientation at 2θ ≈ 27.01. Moreover, atomic force microscopy AFM is studying the external morphology of

This paper proposes and tests a computerized approach for constructing a 3D model of blood vessels from angiogram images. The approach is divided into two steps, image features extraction and solid model formation. In the first step, image morphological operations and post-processing techniques are used for extracting geometrical entities from the angiogram image. These entities are the middle curve and outer edges of the blood vessel, which are then passed to a computer-aided graphical system for the second phase of processing. The system has embedded programming capabilities and pre-programmed libraries for automating a sequence of events that are exploited to create a solid model of the blood vessel. The gradient of the middle c

Field experiment was conducted by using two fertilization systems (i.e.) biofertilizers (inoculation with Pseudomonas putida and with Azotobacter chroococcum and non - inoculation) and chemical fertilization (100%, 50% and 25% of recommended by Ministry of Agriculture) to study the influence of these system and interaction on water and grain yield productivity, some growth phytohorones and number of bacterial cells in soil rizosphere of root of wheat crop under water scarcity. The result showed that the integrate fertilization (inoculation with Pseudomonas putida and Azotobacter chroococcum bacterial + 50% of the recommended chemical fertilizer) recorded 5.70 and 5.55 t ha^-1, respectively with reducing the chemical fertilizer app

         The present study was undertaken to study the effect of apigenin and luteolin on physiological and histological changes in rats treated with cytarabine drugs. Thirty-five albino healthy male adult rats with equal age weighing 250 -300g were enrolled. Rats were randomly divided into seven groups according to the treatment. Group “1” was treated with normal saline and served as the control group. Groups “2,3 and 4”  received cytarabine, apigenin, and luteolin respectively, while groups 5, 6, and 7 received a combination of “apigenin + cytarabine”, “luteolin + cytarabine”, and “apigenin + luteolin + cytarabine”, respectively.  After one week of treatment, all seven groups of rats were

Reliable estimation of critical parameters such as hydrocarbon pore volume, water saturation, and recovery factor are essential for accurate reserve assessment. The inherent uncertainties associated with these parameters encompass a reasonable range of estimated recoverable volumes for single accumulations or projects. Incorporating this uncertainty range allows for a comprehensive understanding of potential outcomes and associated risks. In this study, we focus on the oil field located in the northern part of Iraq and employ a Monte Carlo based petrophysical uncertainty modeling approach. This method systematically considers various sources of error and utilizes effective interpretation techniques. Leveraging the current state of a