Standards play a vital role in documenting the values ​​of new test results in the form of tables. They are one of the basic requirements that the standardization process aims for as a complement to standardizing test procedures, and contribute to knowing the current reality of the student. The degree of readiness and level as a result of practicing different exercises for sports activities, in addition to the possibility of adopting it for comparison with his group or similar groups, classification, prediction and selection. Developing the skill of handling the football in the educational field is an important matter for achieving distinguished performance among students. This skill requires a level of accuracy, speed and control, and

In this paper, compared eight methods for generating the initial value and the impact of these methods to estimate the parameter of a autoregressive model, as was the use of three of the most popular methods to estimate the model and the most commonly used by researchers MLL method, Barg method  and the least squares method and that using the method of simulation model  first order autoregressive through the design of a number of simulation experiments and the different sizes of the samples.

The current study was to examine the reliability and effectiveness of using most abundant, inexpensive waste in the form of scrap raw zero valent aluminum ZVAI and zero valent iron ZVI for the capture, retard, and removal of one of the most serious and hazardous heavy metals cadmium dissolved in water. Batch tests were conducted to examine contact time (0-250) min, sorbent dose (0.25-1 g ZVAI/100 mL and 2-8 g ZVI/100 mL), initial pH (3-6), pollutant concentration of 50mg/L initially, and speed of agitation (0-250) rpm . Maximum contaminant removal efficiency corresponding to (90 %) for cadmium at 250 min contact time, 1g ZVAI/ 6g ZVI sorbent mass ratio, pH 5.5, pollutant concentration of 50 mg/L initially, and 250 rpm agitation speed wer

<span lang="EN-US">This paper presents the comparison between optimized unscented Kalman filter (UKF) and optimized extended Kalman filter (EKF) for sensorless direct field orientation control induction motor (DFOCIM) drive. The high performance of UKF and EKF depends on the accurate selection of state and noise covariance matrices. For this goal, multi objective function genetic algorithm is used to find the optimal values of state and noise covariance matrices. The main objectives of genetic algorithm to be minimized are the mean square errors (MSE) between actual and estimation of speed, current, and flux. Simulation results show the optimal state and noise covariance matrices can improve the estimation of speed, current, t

The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

Comparison for the optical energy gap between pure
PMMA , PMMA-TiO2 micro composites and PMMA-TiO2 nano
composites have been investigated under uv – radiation , the
effect of time irradiation (0,6,12,24,48,72,96 and 120) have been
studied for these specimens to study the photic stability .The
results show that the photostability of the PMMA-TiO2
nanocomposite is higher than that of the pure PMMA and
PMMA-TiO2 micro composite under UV-light irradiation

The concept of the order sum graph associated with a finite group based on the order of the group and order of group elements is introduced. Some of the properties and characteristics such as size, chromatic number, domination number, diameter, circumference, independence number, clique number, vertex connectivity, spectra, and Laplacian spectra of the order sum graph are determined. Characterizations of the order sum graph to be complete, perfect, etc. are also obtained.