The penalized least square method is a popular method to deal with high dimensional data ,where  the number of explanatory variables is large than the sample size . The properties of  penalized least square method are given high prediction accuracy and making estimation and variables selection

 At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and

Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp

As we live in the era of the fourth technological revolution, it has become necessary to use artificial intelligence to generate electric power through sustainable solar energy, especially in Iraq and what it has gone through in terms of crises and what it suffers from a severe shortage of electric power because of the wars and calamities it went through. During that period of time, its impact is still evident in all aspects of daily life experienced by Iraqis because of the remnants of wars, siege, terrorism, wrong policies ruling before and later, regional interventions and their consequences, such as the destruction of electric power stations and the population increase, which must be followed by an increase in electric power stations,

Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

الوصف Mixed ligand complexes of Cu (II), Co (II) and Zn (II) with 2-((4-(1-(4-chlorophenylimino) ethyl) phenylimino) methyl) phenol (L) and histidine (His) have been prepared and diagnosed by ¹H and13 C NMR, FT-IR and electronic spectral data, thermal gravimetric, molar conductance and metal analysis measurements. The ligand (L) shows a bidentate nature and the coordination occurs through N and O atoms of imine group and phenol group respectively whereas (His) behave as tridentate ligand, coordinating through the-NH2 group and carboxylate oxygen group and N atoms of imidazole ring. The analytical studies for three complexes have shown octahedral structure. The anticancer activity was screened against human cancer cell such Follicular

Calcium-Montmorillonite (bentonite) [Ca-MMT] has been prepared via cation exchange reaction using benzalkonium chloride [quaternary ammonium] as a surfactant to produce organoclay which is used to prepare polymer composites. Functionalization of this filler surface is very important factor for achieving good interaction between filler and polymer matrix. Basal spacing and functional groups identification of this organoclay were characterized using X-Ray Diffraction (XRD) and Fourier Transform Infrared (FTIR) spectroscopy respectively.  The (XRD) results showed that the basal spacing of the treated clay (organoclay) with the benzalkonium chloride increased to 15.17213 ⁰A, this represents an increment of about 77.9% in the

In the present investigation, bed porosity and solid holdup in viscous three-phase inverse fluidized bed (TPIFB) are determined for aqueous solutions of carboxy methyl cellulose (CMC) system using polyethylene and polypropylene as  a particles with low-density and diameter (5 mm) in a (9.2 cm) inner diameter with height (200 cm) of vertical perspex column. The effectiveness of gas velocity U_g , liquid velocity U_L, liquid viscosity μ_L, and particle density ρ_s on bed porosity B_P and solid holdups ε_g were determined. The bed porosity increases with "increasing gas velocity", "liquid velocity", and "liquid viscosity". Solid holdup decreases with increasing gas, liquid

The study aimed to investigate the effect of different times as follows 0.5, 1.00, 2.00 and 3.00 hrs, type of solvent (acetone, methanol and ethanol) and temperature (~ 25 and 50)ºc on curcumin percentage yield from turmeric rhizomes. The results showed significant differences (p? 0.05) in all variables. The curcumin content which were determined spectrophotometrically ranged between (0.55-2.90) %. The maximum yield was obtained when temperature, time and solvent were 50ºC, 3 hrs and acetone, respectively.

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

This paper investigates a new approach to the rapid control of an upper limb exoskeleton actuator. We used a mathematical model and motion measurements of a human arm to estimate joint torque as a means to control the exoskeleton’s actuator. The proposed arm model is based on a two-pendulum configuration and is used to obtain instantaneous joint torques which are then passed into control law to regulate the actuator torque. Nine subjects volunteered to take part in the experimental protocol, in which inertial measurement units (IMUs) and a digital goniometer were used to measure and estimate the torque profiles. To validate the control law, a Simscape model was developed to simulate the arm model and control law in which measurem