The increase in obesity and the many accompanying diseases is attributed to the increased production and consumption of foods made of non-nutritive sweeteners without regard to the risks of consuming additional calories, and this in turn leads to hormonal imbalance and metabolic disorders and the resulting imbalance and ill health that have spread to all segments of society. During the research, 0.01, 0.02, 0.03, 0.04 and 0.05 % of stevia sweetener was added to the cream instead of the sugar used. Physical and chemical tests were performed for the stevia extract and the microbial content in the cream, as well as the sensory evaluation. It was noted that fortifying the cream with calorie-free stevia sugar led to the production of

The current research aims to identify the multiple intelligences in the fourth students’ acquisition of the literary processes of Arabic grammar and to identify the differences in multiple intelligence according to gender (males - females). The study was determined for students of the fourth literary preparatory Al-Hakim Preparatory (for males) and Rabat Preparatory (for females) of the Second Karkh Education Directorate, topics from the Arabic grammar subject (past tense, present tense, imperative, subject, and object) for the first semester of the academic year 2019-2020. The results showed that there were no statistically significant differences at the significance level (0.05) between the average scores of the students who were tau

Abstract

  The study aims to find out the impact of expectations and perceptions in determining the position of the customer service quality received by him. Represent the expectations and perceptions customer’s key of service quality determinants. The customer's requirements and needs main pivot, who must be built all events and activities and efforts of service organizations, including the hotel and organizations that operate in an environment known as highly competitive , intensification and  complexity of the conditions set by the customer and increasing day after day. The study sample of three Luxury hotels in Kurdistan region of Iraq a model. The use of service quality m

This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche

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

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

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

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