Review, Tutorials and Introduction to Cloud Platforms for Agentic GenAI: A Comparative Studies
This paper presents a comparative analysis of leading cloud platforms for Generative AI applications. We evaluate performance, scalability, cost, and ecosystem support for AI workloads. The rapid evolution of generative artificial intelligence (AI) has significantly increased the demand for scalable and robust cloud infrastructure. This paper presents a comparative analysis of major cloud platforms, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), focusing on their capabilities to support generative AI applications. We examine key aspects such as infrastructure scalability, cost efficiency, and the availability of specialized AI services. Furthermore, we discuss the importance of well-architected frameworks and best practices for deploying scalable AI solutions. The paper also explores the strategic collaborations and advancements in supercomputing infrastructure that are driving the future of generative AI. Generative AI (GenAI) is rapidly transforming various industries, demanding scalable and cost-effective infrastructure. Cloud platforms like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI) are vying to provide the necessary tools and services. This literature review examines recent publications and articles discussing the capabilities, architectures, and cost considerations of these platforms in the context of GenAI application development and deployment. We categorize these resources based on their focus: (1) comparative analyses of cloud platforms, (2) GenAI infrastructure and application development, (3) Retrieval-Augmented Generation (RAG) solutions, and (4) scalability and cost optimization strategies. This review aims to provide a comprehensive overview of the current state of GenAI in the cloud, highlighting the strengths and weaknesses of each platform and identifying key trends and challenges.
Published by: Satyadhar Joshi
Author: Satyadhar Joshi
Paper ID: V11I1-1395
Paper Status: published
Published: February 25, 2025
A Proposal to Innovate The Design of the Sudanese Vehicle Number Plates
Vehicle number plate display and recognition have been a lawful concern in all countries. Research into improving the quality of plates has been an interesting and challenging task. It is shown that the plates have different shapes and sizes and have assorted colours in different countries. In Sudan, the recent plates are of a white background with black text and numbers written in English and Arabic. This study proposes an innovative plate design that considers regional and international standards. The attempt incorporated the Sudanese flag, reduced the letter crowding and noise, enlarged the font and improved contrast, kept Arabic numbers, excluded the Indian numbers and included a logo for branding the plate. The study has considered both theoretical mathematical and experimental approaches. However, it is commissioned to facilitate the electronic identification of the plate, which is an issue. The experimental component proved a sizable visual difference between the old design and the proposed innovative design. Mainly assembled in two steps; firstly, the plate is visually identifiable from a longer distance than the existing plate; secondly, the segmentation allows a sustainable, better electronic recognition.
Published by: Galal Mohamed Ismail, Zoelfiqar Dafalla Mohamed, Jamal Uthman Nogoud, Nadir Kamal Salih Idries
Author: Galal Mohamed Ismail
Paper ID: V11I1-1350
Paper Status: published
Published: February 25, 2025
Realizing a Fully Functional CPU Using Multi-Layer Perceptrons
This research paper extends our previously introduced concepts of a multi-layer perceptron (MLP)-based CPU. We present exhaustive details on every facet of the design, from historical motivations and theoretical underpinnings to transistor-level implementations, advanced pipeline structures, memory hierarchies, and future-looking innovations such as approximate perceptron logic or on-chip training. While historically, threshold logic was overshadowed by the dominance of CMOS gate-level designs; this paper demonstrates that a fully perceptron-based CPU—dubbed IC 616 Ultra-MLP—can theoretically implement all standard computing tasks by assigning appropriate weights and biases to arrays of threshold units. We thoroughly analyze potential advantages, substantial challenges, and the interplay between neural and digital paradigms. This paper aims to be an exhaustive reference for researchers, students, and architects intrigued by bridging neural networks and CPU design in the most literal sense.
Published by: Adarsh Keshri
Author: Adarsh Keshri
Paper ID: V11I1-1380
Paper Status: published
Published: February 21, 2025
Diabetes Prognosis Using Machine Learning
Diabetes is a prolonged disorder brought on by above-normal blood glucose levels, leading to symptoms like frequent urination, thirst, and hunger. It can May cause significant complications, such as blindness, kidney failure, heart failure, and stroke. The pancreas usually produces insulin to help cells absorb glucose for energy, but this process fails in diabetes. Machine learning offers tools for early diabetes prediction. Various algorithms, such as KNearest Neighbors, Logistic Regression, Random Forest, and Decision Tree, are evaluated to select the most accurate model for diagnosis.
Published by: Anshika Sharma, Divasha alag, Atharva, Aditya Pratap Singh
Author: Anshika Sharma
Paper ID: V11I1-1376
Paper Status: published
Published: February 20, 2025
The Impact of Forensic Accounting on White-Collar Crimes
The growing frequency of white-collar crime presents international financial systems with a great threat, making forensic accounting a vital tool in the prevention of fraud as well as openness. The paper explores forensic accounting, from its history and methods to its applications in financial crime detection and techniques. The study has taken many past examples and well-known fraud cases such as the Satyam and Harshad Mehta scandals to highlight how vital forensic accountants are for corporate governance, fraud detection, and litigation. Besides covering Benford's law, ratio analysis, data mining, and other forensic accounting techniques, the paper includes various technologies that have transformed the industry into what it is today blockchain, artificial intelligence, and data analytics. These tools deal with the complexities of current financial environments and improve fraud detection and predictability. As it is gaining more importance, it is still full of challenges, such as an unskilled workforce, changing tactics of fraud, and the dangers of cybersecurity. This study indicates that more money must be spent to overcome these challenges by enhancing education for forensic accounting, introducing technology, and reorganizing systems. Forensic accounting is still an important tool in keeping the financial system sound and minimizing the risks of white-collar crimes in a world increasingly connected through fusing old-fashioned methods with the most advanced technological solutions.
Published by: Akshata Shukla
Author: Akshata Shukla
Paper ID: V11I1-1379
Paper Status: published
Published: February 19, 2025
Blockchain and It’s Applications
Blockchain technology, first introduced as the underlying technology for Bitcoin in 2008, has evolved into a transformative force across various industries. Blockchain is a decentralized, distributed ledger that records transactions securely, transparently, and immutable. Its core attributes— transparency, security, immutability, and decentralization— make it highly attractive for applications beyond cryptocurrency. One of the most notable applications of blockchain is finance, where it enables peer-to-peer payments, reduces fraud, and enhances security in digital transactions. Smart contracts, self-executing contracts with terms directly written into code, have found applications in legal agreements, insurance, and supply chain management. Blockchain is also being explored in healthcare to secure patient records, in voting systems to ensure election transparency, and in supply chain management to track the provenance of goods from production to delivery. In addition to finance, healthcare, and supply chains, blockchain is used in industries like real estate, energy, and gaming. Its decentralized nature allows for more equitable systems where trust is distributed among participants, reducing the reliance on intermediaries. As the technology matures, challenges like scalability, regulatory hurdles, and energy consumption are being addressed, paving the way for broader adoption. In conclusion, blockchain has the potential to revolutionize industries by providing secure, transparent, and decentralized solutions, with applications expanding rapidly as technology and regulatory frameworks evolve.
Published by: Raghuramireddy, B.Nikhil Praveen, K.V.V Raju
Author: Raghuramireddy
Paper ID: V11I1-1369
Paper Status: published
Published: February 17, 2025
