This article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.

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

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

ABSTRACT

This study was conducted to determine the effect of various levels of hump fat (HF) used in manufacturing of camel, beef and chicken sausage to understand the effect of (HF) on physicochemical composition sausage, Different levels of hump fat (5, 7, and 10 %) were used, physicochemical compositions like (moisture, protein, fat, Ash, water holding capacity, shrinkage, cooking loss and pH) were determined. Results of the study revealed that moisture content showed high significant differences (P≤0.01)among treatments groups, Camel sausage and beef sausage tended to have highest values while chicken sausage reported the lowest value. The study showed no significant difference (P≤0.05) among the

This study includes applying chemical tests on cow, sheep and chicken bones including both hallow and flat. The results of chemical tests on bones mentioned the moisture percentage which was between 4.95-7.32 %, and it was noticed the difference in protein percentage among different kinds of bones, The highest protien percentage was 39.62 % in hallow chicken bones and the lowest was in hallow sheep bones 20.31%, at the same time, the highest Ash percentage was in hallow sheep bones48.11% , whereas the highest percentage of fat was in hallow cow bones 30%. The chemical and physical tests were conducted for extracted fat from hallow and flat bones for cows, sheeps and chicken. It was found that peroxide values (PV), and free fatty acids (F

The Skyrme–Hartree–Fock (SHF) method with the Skyrme
parameters; SKxtb, SGII, SKO, SKxs15, SKxs20 and SKxs25 have
been used to investigate the ground state properties of some 2s-1d
shell nuclei with Z=N (namely; 20Ne, 24Mg, 28Si and 32S) such as, the
charge, proton and matter densities, the corresponding root mean
square (rms) radii, neutron skin thickness, elastic electron scattering
form factors and the binding energy per nucleon. The calculated
results have been discussed and compared with the available
experimental data.

This paper presents a vibration suppression control design of cantilever beam using two piezoelectric ‎patches. One patch was used as ‎an actuator element, while the other was used as a sensor. The controller design was designed via the balance realization reduction method to elect the reduced order model that is most controllable and observable. ‎the sliding mode observer was designed to estimate six states from the reduced order model but three states are only used in the control law. Estimating a number of states larger than that used is in order to increase the estimation accuracy. Moreover, the state ‎estimation error is proved bounded. An ‎optimal LQR controller is designed then using the ‎estimated states with the slid

Abstract  

Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned according to Taguchi orthogonal array (OA) L27 (3⁶) with three levels and six input parameters. Experimental estimation and optimization of input parameters for MAF process for stainless steel type 316 plate work piece, six input parameters including amplitude of tooth pole, and number of cycle between teeth, current, cutting speed, working gap, and finishing time, were performed by design of experiment