This study aims to develop a recommendation engine methodology to enhance the model’s effectiveness and efficiency. The proposed model is commonly used to assign or propose a limited number of developers with the required skills and expertise to address and resolve a bug report. Managing collections within bug repositories is the responsibility of software engineers in addressing specific defects. Identifying the optimal allocation of personnel to activities is challenging when dealing with software defects, which necessitates a substantial workforce of developers. Analyzing new scientific methodologies to enhance comprehension of the results is the purpose of this analysis. Additionally, developer priorities were discussed, especially th

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

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

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

   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

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

<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

Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN