Extracting moving object from video sequence is one of the most important steps
in the video-based analysis. Background subtraction is the most commonly used
moving object detection methods in video, in which the extracted object will be
feed to a higher-level process ( i.e. object localization, object tracking ).
The main requirement of background subtraction method is to construct a
stationary background model and then to compare every new coming frame with it
in order to detect the moving object.
Relied on the supposition that the background occurs with the higher appearance
frequency, a proposed background reconstruction algorithm has been presented
based on pixel intensity classification ( PIC ) approach.

In this paper a theoretical attempt is made to determine whether changes in the aorta diameter at different location along the aorta can be detected by brachial artery measurement.  The aorta is divided into six main parts, each part with 4 lumps of 0.018m length. It is assumed that a desired section of the aorta has a radius change of 100,200, 500%. The results show that there is a significant change for part 2 (lumps 5-8) from the other parts. This indicates that the nearest position to the artery gives the significant change in the artery wave pressure while other parts of the aorta have a small effect.

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Spraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore, researchers have been encouraged to...

Edge computing is proved to be an effective solution for the Internet of Things (IoT)-based systems. Bringing the resources closer to the end devices has improved the performance of the networks and reduced the load on the cloud. On the other hand, edge computing has some constraints related to the amount of the resources available on the edge servers, which is considered to be limited as compared with the cloud. In this paper, we propose Software-Defined Networking (SDN)-based resources allocation and service placement system in the multi-edge networks that serve multiple IoT applications. In this system, the resources of the edge servers are monitored using the proposed Edge Server Application (ESA) to determine the state of the edge s

In a connected graph , the distance function between each pair of two vertices from a set vertex  is the shortest distance between them and the vertex degree  denoted by  is the number of edges which are incident to the vertex  The Schultz and modified Schultz polynomials of  are have defined as:

 respectively, where the summations are taken over all unordered pairs of distinct vertices in  and  is the distance between  and  in  The general forms of Schultz and modified Schultz polynomials shall be found and indices of the edge – identification chain and ring – square graphs in the present work.

Artificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex

Objectives: As health care workers on the front line during the coronavirus (COVID-19) pandemic, dental practitioners are amongst those at risk due to their close contact with potentially infected individuals. The aim of the current study was to assess the anxiety, awareness practice modification, and economic impact amongst Iraqi dentists whilst working during the outbreak.

Methods: This study was performed using an online survey questionnaire with aid of Google forms from 2nd to 23rd July 2020. A total of 484 clinicians responded. The questionnaire was composed of open end, closed end, and Likert five-point scale questions to assess anxiety, awareness and financial impa