In this research study the effect of irradiation by (CW) CO2 laser on some optical properties of (Cds) doping by Ni thin films of (1)µm thickness has been prepared by heat evaporation method. (X-Ray) diffraction technique showed the prepared films before and after irradiation are ploy crystalline hexagonal structure, optical properties were include recording of absorbance spectra for prepared films in the range of (400-1000) nm wave lengths, the absorption coefficient and the energy gap were calculated before and after irradiation, finally the irradiation affected (CdS) thin films by changing its color from the Transparent yellow to dark rough yellow and decrease the value absorption coefficient also increase the value of energy gap.

The current study was conductedas a pot experiment to determine the effect of soil texture on biological nitrogen fixation (BNF) of six most efficient local isolates, specified, of Bradyrhizobium. Cowpea (Vignaunguiculata L.), as a legume host crop, was used as a host crop and 15N dilution analysis was used for accurate determination of the amount of N biologically fixed under experimental parameters specified. Soils used are clay loam, sandy clay loam and sandy loam. Biological Nitrogen Fixation (BNF), in different soil textural classes, was as in the following order: medium texture soil > heavy texture soil > light textured soil. Statistical analysis showed that there is a significant variation in BNF % among six Iraqi isolates in the th

this research aims at a number of objectives including Developing the tax examination process and raise its efficiency without relying on comprehensive examination method using some statistical methods in the tax examination and Discussing the most important concepts related to the statistical methods used in the tax examination and showing its importance and how they are applied. the research represents an applied study in the General Commission of taxes. In order to achieve its objectives the research has used in the theoretical side the descriptive approach (analytical), and in the practical side Some statistical methods applied to the sample of the final accounts for the contracting company (limited) and the pharmaceutical industry (

Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .

                In this paper  a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering  and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

                 This study aims to identify the role of forensic accounting in the Iraqi environment, banking stability, and to achieve this goal, we used the field survey method, as it is the most appropriate for studying the phenomenon in question and achieving its objectives.

Where we selected a sample consisting of (50) male and female employees, distributed among five private banks in Baghdad governorate, namely (Ashur International Bank, Development Investment Bank, Iraqi Middle East Investment Bank, Hammurabi Commercial Bank, Khaleej Commercial Bank), and the questionnaire tool was applied to them Designed for this purpose, which consisted of