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

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

It is commonly known that Euler-Bernoulli’s thin beam theorem is not applicable whenever a nonlinear distribution of strain/stress occurs, such as in deep beams, or the stress distribution is discontinuous. In order to design the members experiencing such distorted stress regions, the Strut-and-Tie Model (STM) could be utilized. In this paper, experimental investigation of STM technique for three identical small-scale deep beams was conducted. The beams were simply supported and loaded statically with a concentrated load at the mid span of the beams. These deep beams had two symmetrical openings near the application point of loading. Both the deep beam, where the stress distribution cannot be assumed linear, and the ex

The research abstract included introduction and the importance of the research, also included display of the problem represented by weakness for the players when performing some of the basic skills in badminton and the shuttle not reaching to the back corners of the court which gives the player the opportunity to win through applying the pressure on the opponent and make him away from the control center(T) which definitely required level of a collection muscular strength contributed in performance perhaps this related to a number of reasons related with weakness in physical changes especially explosive and characterized by speed forces for the badminton players and be acquainted with them and knowing the extent of their effect in performanc

Background: Mini implant stability is primarily related to local bone density; no studies have evaluated bone density related to mini implant placement for orthodontic anchorage between different age groups in the maxilla and the mandible. The present research aims to evaluate side, gender, age, and regional differences in bone density of the alveolar bone at various orthodontic implant sites. Materials and method: Fifty three individuals who were divided into two groups according to their age into: group I (ages 16-20 years) and group II (ages 21-29 years) had subjected to clinical examination, then 64-multislice computed tomography scan data were evaluated and bone density was measured in Hounsfield unit at 102 points (51 in the maxilla

Globally, buildings use about 40% of energy. Many elements, such as the physical properties of the structure, the efficiency of the cooling and heating systems, the activity of the occupants, and the building’s sustainability, affect the energy consumption of a building. It is really difficult to predict how much energy a building will need. To improve the building’s sustainability and create sustainable energy sources to reduce carbon dioxide emissions from fossil fuel combustion, estimating the building's energy use is necessary. This paper explains the energy consumed in the lecture building of the Al-Khwarizmi College of Engineering, University of Baghdad (UOB), Baghdad, Iraq. The weather data and the building construction informati

Intestinal parasites present in freshwater from the Al- Fallujah, Al- Habbaniyah and Al-Alwarar, of the Euphrates river in Iraq are Cryptosporidium spp (25.3%), Giardia sp (3.3%), Eimeria sp (3.3%), Pinworm eggs (3.3%), Naegleria sp (15.3%), Lecane niwati (1.3%), Trichomonas hominis (19.3%), Acanthamoeba spp (24.6%), Entamoeba coli (20.6%), Balantidium coli (12%), Ascaris sp (3.3%), Volvox sp (26%), Chilomastix mesnili (4%), Pelomyxa palustris (2.6%), Trinema enchelys (2.6%), Actinophrys Sol (7.3%), Amobea Vespertilio (9.3%), Rhabditea (5.3%), paramecium bursaria (9.3%), cyst of cestode (6%), Oocyst protozoa (16%), Euglena gracilis (10.6%).were isolated. The study's goal was to isolate some of the parasites that pollute the Euphrat