Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

This study intends to examine the efficiency of student-centered learning (SCL) through Google classroom in enhancing the readiness of fourth stage females’ pre-service teachers. The research employs a quasi-experimental design with a control and experimental group to compare the teaching readiness of participants before and after the intervention. The participants were 30 of fourth stage students at the University of Baghdad - College of Education for Women/the department of English and data were collected through observation checklist to assess their teaching experience and questionnaires to assess their perceptions towards using Google Classroom. Two sections were selected, C as a control group and D as the experimental one each with (

This research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff

The purpose of this research is to demonstrate the impact of deposit insurance to reduce banking risks, as banks in various countries of the world face a variety of risks that led to banking and financial crises that led to the failure and bankruptcy of many of its bank, which led to the banks to find quick and appropriate solutions to get rid of these difficulties These solutions include the use of bank deposit protection system for the many risks and sequences of crises that accompanied the Iraqi banking work of thefts, forgery, embezzlement and changing and unstable circumstances. The importance of studying the subject of research through the theoretical framework of banking risks as well as the framework of consideration In order to

Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak

   Thsst researcher problem of delays faced by researchers are all waiting to evaluate their standards by the experts who must take their views to extract the truth Virtual important step first step in building standards whatsoever, then the difference of opinion among experts about the paragraphs Whatever the scope of their functions, leading to confusion in maintaining these paragraphs or delete? Or ignore the views and opinion of the researcher to maintain the same? Or as agreed upon with the supervisor if he was a student? Especially if the concepts of a modern new building.
   Therefore, the researcher sought to try to find a solution to her problem to conduct an experiment to test building steps

من خلال ملاحظة الباحثتين الميدانية لمستوى الأداء الفني لمنتخب ناشئات القطر بالجمناستك لمهارة قفزة اليدين الأمامية على جهاز منصة القفز الحديثة لاحظن وجود مشكلة تكمن في ضعف هذا الأداء والذي يؤثر على بعض المتغيرات البيوكينماتيكية لهذه المهارة مما يؤدي إلى عدم أداء المهارة بالشكل الصحيح ، وتعزو الباحثتان ذلك الضعف إلى قلة الدفع بالرجلين والذراعين . لذا ارتأت الباحثتان إجراء هذا البحث الذي يهدف إلى تنمية القوة

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol