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

     Financial fraud remains an ever-increasing problem in the financial industry with numerous consequences. The detection of fraudulent online transactions via credit cards has always been done using data mining (DM) techniques. However, fraud detection on credit card transactions (CCTs), which on its own, is a DM problem, has become a serious challenge because of two major reasons, (i) the frequent changes in the pattern of normal and fraudulent online activities, and (ii) the skewed nature of credit card fraud datasets. The detection of fraudulent CCTs mainly depends on the data sampling approach. This paper proposes a combined SVM- MPSO-MMPSO technique for credit card fraud detection. The dataset of CCTs which co

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

The rental activity receives "significant" interest from accounting organizations interested in issuing accounting standards worldwide, such as the Financial Accounting Standards Board (FASB), the International Accounting Standards Board (IASB). As leases represents an important source of finance for economic units as an alternative to financing assets through purchase or borrowing. Professional organizations have focused on addressing the situation of extra-budgetary funding through which the lessee hides many leases that are classified as financing without It shows in the budget, which gives an incorrect picture of the reality of the financial situation of economic unity, IASB has issued IFRS 16, which terminates off- Balance s

RG Majeed, AS Ahmed, Jornal of Al-Muthanna for Agricultural Sciences, 2023

The bodies responsible for the organization of accounting in the world seek to keep abreast of repaid development, by provide the information required by users, which they need to make efficient decision that return them to the desired benefits, and avoid the risks they could face if they made their decision based on misleading information, or insufficient, or not accurate, Hence, the IASB has undertaken to review the standards, and make the necessary adjustment and clarifications to remove the ambiguities that some of the paragraphs may have in IFRS issued.

And the Iraqi Central Bank obliges banks to convert from local accounting standards to apply IFRS only a step towards keeping pace with developments