The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

Modified algae with nano copper oxide (CuO) were used as adsorption media to remove tetracycline (TEC) from aqueous solutions. Functional groups, morphology, structure, and percentages of surfactants before and after adsorption were characterised through Fourier-transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Several variables, including pH, connection time, dosage, initial concentrations, and temperature, were controlled to obtain the optimum condition. Thermodynamic studies, adsorption isotherm, and kinetics models were examined to describe and recognise the type of interactions involved. Resultantly, the best operation conditions were at pH 7, contact time

The management of anger is problematic for many people and it is a particularly important issue for persons with substance use disorders (SUD). The paper reviews the research studies dating back to 2005 on how to help persons with SUD manage anger. The literature reveals that various pharmaceutical and non-pharmacological approaches have been studied to help persons with SUD manage their anger. In chronic and lower risk situations non-pharmacological are the first line approaches, they include anger management training, cognitive-behavioral based treatments, exercising and relaxing, music therapy and empathy. Atypical antipsychotic and medications for opioid use disorders (MOUD) are also widely used. In acute and high risk of violen

The complexes of Schiff base of 4-aminoantipyrine and 1,10-phenanthroline with metal ions Mn (II), Cu (II), Ni (II) and Cd (II) were prepared in ethanolic solution, these complexes were characterized by Infrared , electronic spectra, molar conductance, Atomic Absorption ,microanalysis elemental and magnetic moment measurements. From these studies the tetrahedral geometry structure for the prepared complexes were suggested.The prepared ligand of 4-aminoantipyrine was characterized by using Gc-mass spectrometer .

Salicylaldehyde was react with 4-amino-2,3-dimethyl-1-phenyl-3-Pyrazoline-5-on to produce the novel Schiff base ligand 2,3-dimethyl-1-phenyl-4-salicylidene-3-pyrazoline-5-on (HL). A new complexes of VO(II), Cr(Ш), Zn(II), Cd(II), Hg(II) and UO2(II) with mixed ligands of bipyridyl and new shiff base ( 2,3-dimethyl-1-phenyl-4-salicylidene-3-pyrazoline-5-on) (HL) were prepared . All prepared compounds were identified by atomic absorption, FT.IR , UV-Visable spectra and molar conductivity. From the above data, the proposed molecular structure for VO(II) complex is squre pyramidal while (Zn(II), Cd(II), Hg(II)) and ( UO2(II),Cr(III)) complexes are forming tetrahedral and octahedral geometry respectively.