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
Harnessing Big Data Analytics for Large-Scale Farms: Insights from IoT Sensor Networks
Large farms experience the need to produce sustainable food from limited resources while facing uncertain climate conditions. The- Internet of Things (IoT) and Big Data Analytics are recent developments that propose solutions to these problems. Sensor networks powered by IoT technology in extensive agricultural areas monitor soil moisture levels, temperature, and nutrient conditions while tracking weather patterns. Cloud-based platforms and on-premise systems analyze the collected data using statistical methods, machine learning approaches, and geospatial analysis to produce decision-supporting insights. Through data-driven strategies, farmers achieve exact control over irrigation practices, fertilizer application, and pest management, re- resulting in reduced waste output while increasing crop yields. The review highlights large farm operations adopting IoT integration, data pipeline operations, and advanced analytical methods. The research reveals two main areas of challenge: limited connectivity, data security, and high scaling costs. The improved applications section investigates which specific regions need these solutions most. The path forward for smart farming development includes AI-enabled automation and blockchain-tracing systems.
Published by: Muhammad Saqib, Shubham Malhotra, Rahmat Ali, Hassan Tariq
Author: Muhammad Saqib
Paper ID: V11I1-1361
Paper Status: published
Published: February 17, 2025
The Viability of the US Cybercrime Laws in Protecting Digital Trade Space: A Critique
This paper critically examines the effectiveness and limitations of U.S. cybercrime laws in safeguarding the digital trade space. As the global economy increasingly relies on digital platforms, cybercrime poses a significant threat to online business operations, intellectual property, and personal data security. The study explores the key components of U.S. legislation, such as the Computer Fraud and Abuse Act (CFAA) and the Cybersecurity Information Sharing Act (CISA), assessing their scope, enforcement, and adaptability in responding to the ever-evolving nature of cyber threats. This critique highlights the gaps in current legal frameworks by analyzing case studies, legal challenges, and the intersection of cybercrime laws with international regulations. It offers recommendations for strengthening protections in the digital trade space. Ultimately, it seeks to provide insights into how U.S. policies can evolve to address the complexities of modern cyber threats better while balancing innovation, privacy, and global cooperation in digital commerce.
Published by: Sultan Alaaya Adebayo
Author: Sultan Alaaya Adebayo
Paper ID: V11I1-1366
Paper Status: published
Published: February 15, 2025
