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

Embedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

The effective surface area of drug particle is increased by a reduction in the particle size. Since dissolution takes place at the surface of the solute, the larger the surface area, the further rapid is the rate of drug dissolution. Ketoprofen     is class II type drug according to (Biopharmaceutics Classification System BCS) with low solubility and high permeability. The aim of this investigation was to increase the solubility and hence the dissolution rate by the preparation of ketoprofen     nanosuspension using solvent evaporation method. Materials like PVP K30, poloxamer 188, HPMC E5, HPMC E15, HPMC E50, Tween 80 were used as stabilizers in perpetration of differ

This study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d

A successful synthesis of SBA-15 with semi-spherical morphology and suitable texture properties was achieved using hydrothermal technique. Sodium silicate, derived from silica sand from Iraq, was used as a silica precursor, and Pluronic p123 triblock copolymer was used as a template with a strong acid media (pH < 1). The effect of adding (1–3) g of either polyvinyl alcohol (PVA), Polyvinyl pyrrolidone (PVP -k30), or Sodium dodecyl sulfate (SDS) dispersant agents on the texture properties of the synthesized SBA-15 was studied. The SBA-15 sample underwent various characterization techniques, including X-ray diffraction (XRD), Fourier transform infrared (FTIR), atomic force microscopy (AFM), nitrogen adsorption-desorption using Br

Vibration analysis plays a vital role in understanding and analyzing the behavior of the structure. Where, it can be utilized from this analysis in the design process of the structures in different engineering applications, check the quality and safety of the structure under different working conditions. This work presents experimental measurements and numerical solutions to an out of plane vibration of a rectangular plate with a circular hole. Free edges rectangular plates with different circular holes diameters were studied. The effects of hole location on the plate natural frequencies were also investigated. A finite element modeling (using ANSYS Software) has been used to analyze the vibration characteristics of the plates. A good agree