Large Language Models (LLMs) are rapidly transforming multiple sectors, including healthcare, finance, and cybersecurity, by enabling advanced data-driven insights and automation. However, the scale and complexity of LLMs introduce significant challenges in...
Computerization in medical services is rapidly transforming the landscape of modern healthcare, particularly within critical environments such as the Operating Room (OR) and Intensive Care Unit (ICU). The integration of advanced digital technologies has led...
The need for computing capacity is skyrocketing, thus we need to find ways to meet this need while keeping costs down. In this sense, Grid technology is emerging from the realm of academia and making its way into the business world. In this model, users...
In this article, we take a look at how AI is changing the legal sector, particularly how lawyers do research and prepare contracts. The article will begin by discussing how AI might change the legal industry as we know it. Second, it will explore what AI...
Motion planning and robotics: To build the controller for a rational agent, such a robot, we need to find a good way to describe the problem. To put it plainly, we need to learn how to simplify difficult real-world issues into more manageable computer-based...
In 1956, during a workshop in Dartmouth that John McCarthy had arranged, the phrase artificial intelligence was established. All present consented to use McCarthy's proposed term, "Artificial Intelligence," to describe the emerging discipline. There was a...
Rule-based transaction monitoring systems remain the default anti-money-laundering (AML) control at most deposit-taking institutions, yet they are widely reported to generate false-positive alert rates in excess of 95 percent. For large banks this...
The essay delves deep into the potential for artificial intelligence in advertising from a business perspective. The groundbreaking possibilities of AI in marketing and its significance to the study are emphasized in the introduction. The literature review...
Data validation is a critical yet resource-intensive component of citizen science projects. As the volume and complexity of citizen science data continue to grow, traditional approaches to quality assurance—relying on expert review or simple filtering rules...
The need for computing capacity is skyrocketing, thus we need to find ways to meet this need while keeping costs down. In this sense, Grid technology is emerging from the realm of academia and making its way into the business world. In this model, users...
Vehicle automation signifies a novel safety paradigm that may require a reevaluation of current safety supervision frameworks. This white paper provides an overview of the technical and regulatory framework regarding the safety of autonomous driving systems...
This paper presents a cybersecurity-aware, risk-based quality assurance (QA) methodology for healthcare software platforms. Building on the AI and IoT-enabled monitoring system introduced by Kothamali et al. [1], this study introduces a QA framework that...
Through a data utilisation value chain, AI/Data commons will promote the construction of an open collaborative ecosystem based on PCI (Participation- Collaboration-Incentives). This will be accomplished by preserving data sovereignty and protecting...
An emerging technology, grid computing pools resources from multiple locations to tackle massive problems. The term "peer to peer" (P2P) computing refers to a method of computing in which a network of interconnected computers pool their resources to tackle...
When it comes to grid computing, resource scheduling is all about efficiently matching workloads with resources. Grid computing's varied environment makes resource scheduling a challenging undertaking. At its heart, Grid resource management systems are...
One of the best aspects of reverse engineering is software architecture recovery, which is an abstract. There is a lot of literature on recovering software architecture using a variety of methods. Clustering is one method; it finds parts of the program that...
An Approach to Managing Requirements Volatility in Writing Quality Standards (SRS) considered a subset of requirements overall, quality requirements provide a wide range of characteristics applicable to the system as a whole, including robustness,...
Community financial institutions, banks, credit unions, and Community Development Financial Institutions (CDFIs) alike, remain structurally disadvantaged in detecting cross-institutional fraud and financial-distress patterns: FinCEN's Section 314(b)...
Spatial data mining is a method for extracting useful information from geographical databases. Collecting massive volumes of geographical data for uses as diverse as geospatial analysis and biomedical research has made this a very demanding area of study....
In a context of more complex and globally integrated financial systems, issues of harmonisation in cross-border reporting are intensifying. Regulatory disparities, linguistic variations, data compartmentalisation, and the continued emergence of unstructured...
The main aim of the International Journal of Modern Computing (IJMC) is to publish refereed, well-written original research articles...
Haleema Tayyab
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