Falope Samson

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Verified

Falope verified their affiliation via an institutional email.

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• Bachelor of Science
• Student at University of Ibadan

This study investigates how blockchain technology enables "trustless" accounting transactions across organizational boundaries in supply chain finance. By analyzing 47 real-world implementations, we demonstrate how smart contracts and distributed ledgers reduce reconciliation costs by 62% and improve settlement speeds by 83% compared to traditional...

This study examines how blockchain technology can transform public sector accounting by creating corruption-resistant financial systems. Analyzing 32 government implementations across 18 countries, we demonstrate how distributed ledgers reduce procurement fraud by 57%, improve audit efficiency by 73%, and increase fiscal transparency by 84% compare...

High-speed broadband access depends heavily on the adoption of Gigabit Passive Optical Networks (GPON) technology. The rising need for data transmission has produced major energy consumption which threatens the sustainability of network operations. The research investigates power-saving data encoding approaches dedicated for GPON networks to reduce...

The rapid evolution of artificial intelligence (AI) has ushered in a transformative era for healthcare, particularly in the domain of patient care. Language models, once limited to simple chatbot functionalities, are now increasingly sophisticated, capable of assisting clinicians in diagnosis, treatment planning, and patient communication. This art...

Artificial Intelligence (AI)-powered language models are reshaping the landscape of medical research and healthcare by enhancing diagnostic accuracy, automating administrative processes, accelerating drug discovery, and improving patient engagement. These models analyze vast amounts of medical literature, assist clinicians in decision-making, and g...

The integration of Artificial Intelligence (AI) with multimodal interfaces is revolutionizing the field of 3D animation. By leveraging AI-driven tools, animators can interact with software using voice commands, gestures, and even eye-tracking, streamlining workflows and enhancing creative expression. AI-based animation systems are becoming more sop...

Engineers use multimodal interfaces to achieve seamless interaction between designers as well as engineers with digital modeling environments during engineering prototyping. The integration of various input modalities like speech, gesture, touch, and haptic feedback allows for a better intuitive prototype development process. Engineers achieve bett...

The e-commerce industry experiences a transformative impact through Artificial Intelligence (AI) because it modifies communications between businesses and customers alongside their tailored shopping experiences. Through machine learning and predictive algorithms with analytics on big data companies use AI-driven personalization to assess customers'...

Healthcare disparities remain a significant global challenge, disproportionately affecting marginalized populations who struggle with limited access to quality medical care. These disparities stem from social determinants of health (SDOH), including economic status, education level, geographic location, and systemic biases in healthcare systems. In...

Organizations now explore revolutionary operational improvements through the integration of Artificial Intelligence (AI) in supply chain management and inventory optimization processes which provides major benefits in operational efficiency as well as cost reduction and precise decision making. This paper demonstrates how AI applications improve su...

Augmented reality (AR) has emerged as a transformative technology that is reshaping how we interact with digital environments. In the realm of 3D conceptual modeling, AR interfaces provide an innovative approach to designing and visualizing complex structures in real-time, blending virtual and physical spaces seamlessly. By integrating AR into 3D m...

The field of Brain-Computer Interfaces (BCIs) enables immediate communication links to interface the brain neurons directly with external electronic devices. BCI technology development continues to expand past healthcare applications for assistive technology into fields that include design work and 3D modeling. The article investigates how Brain-Co...

The combination of Artificial Intelligence (AI) and the Blockchain has reportedly taken the next level as a perfect tool in business transformation. This paper aims to discuss the integration of AI and blockchain technology and the specific benefits each brings to the organizations in industries. There are various original questions, including tech...

The quickly changing environment of data management and analytics requires Business Intelligence (BI) systems to serve as essential tools for data-driven organizations who need evidence-based decision making. The existing constraints of traditional BI systems consist of performance problems related to delayed data access together with limitations r...

The integration of artificial intelligence (AI) in healthcare has led to significant advancements in telemedicine and remote patient care. Among these innovations, GPT-powered chatbots are transforming the way patients access medical information, receive preliminary diagnoses, and manage chronic conditions. These AI-driven systems utilize natural l...

The increasing complexity and frequency of cyber threats and financial fraud have necessitated the adoption of advanced technologies for real-time detection and mitigation. Artificial Intelligence (AI) has emerged as a transformative solution in fraud detection and cyber security, offering enhanced accuracy, adaptability, and efficiency in identify...

At present organizations require Business Intelligence (BI) systems as a necessary decision-making framework because of rapid technological development. The traditional constraints of Business Intelligence systems from previous times generate two fundamental issues because of delayed data processing and restricted system capacity growth. This paper...

As a part of business intelligence (BI), predictive analytics, enabled by machine learning (ML) has become critical to enterprises in predicting trends, to do optimization in operations, and making better decisions. In this paper, we analyze the use of the most appropriate ML techniques in business intelligence to predict upcoming trends and make b...

Artificial Intelligence (AI) and Blockchain technology together are indeed the new silk roads that are changing the way modern business applications are achieved, efficient, secure and automated. On the one hand, data integrity and decentralization are ensured by blockchain, and on the other, its limitations of high energy consumption, slow transac...

Today, Business Intelligence (BI) serves as a fundamental organizational resource that allows data analysis for better strategic decision support and market performance capabilities. Rising data analytics use in business practices gives rise to substantial issues about privacy protection combined with security matters as well as regulatory standard...

Business organizations use big data analytics to improve their operations and decision-making by linking them to Internet of Things systems (IoTs). This research paper studies how IoT works with big data analytics in real time and explains its effects on business sectors and technical hurdles. This document uses tables and diagrams to present infor...

Modern enterprises depend heavily on business intelligence (BI) as an essential component which revolutionizes their ability to use data for decision-making. BI systems face major limitations which prevent them from functioning effectively due to both security weaknesses and poor data quality problems. The article explores how using AI analytics wi...

Advanced technological improvement in the digital levels, the introduction of technological interconnectivity within data-related chains, and the enhancement of cloud services have altered cybersecurity standards. With threats emerging in sorts of techniques organizations have no option other than to take preventive measures against new emerging th...

The continuous threat of cyberattacks maintains an unchanging priority for industry stakeholders to minimize their destructive effects. The security methods used today depend on a rule-established framework which operates through static defense systems. A security system operating in this manner faces potential weaknesses because its persistent thr...

Integration of AI and Block chain technologies has been a revolutionary process in various fields as it has a wide range of impact on automation and security. Whereas AI enhances analytics and decision-making, blockchain amends accountability and decentralized reliability and integrity features. Although many organizations are embracing the concept...

In modern cybersecurity, predictive models play a crucial role in identifying and mitigating cyber threats. However, a significant challenge remains: the high incidence of false positives, which leads to unnecessary alerts, wasted resources, and decreased efficiency in threat detection. This study explores how anomaly detection algorithms contribut...

In the modern information security environment, most protective measures are incapable of withstanding new types of threats. Big data has turned out to be one of the significant tools for the better prediction of cybersecurity threats to an organization’s systems. Due to the real-time analysis of the masses of data with various characteristics, big...

This paper explores the crucial role of policy and regulatory frameworks in ensuring sustainable corporate governance in drilling operations within the oil and gas industry. As environmental concerns and the need for climate action become increasingly urgent, the paper examines how effective governance can help mitigate the environmental risks asso...

The selection of lubricants plays a crucial role in optimizing drilling efficiency, reducing friction, and minimizing equipment wear, especially in harsh drilling conditions. This study compares synthetic and green lubricants, analyzing their performance, environmental impact, and economic feasibility. Synthetic lubricants, derived from chemically...

High-angle and extended reach drilling (ERD) pose significant challenges due to frictional resistance between the drill string and borehole walls. Effective friction management is critical to optimizing drilling performance, reducing costs, and improving wellbore stability. This paper reviews various optimization techniques, including advanced lubr...

The oil and gas industry is shifting towards environmentally sustainable drilling practices, with a strong focus on biodegradable drilling fluid additives for friction reduction. Traditional friction-reducing agents often pose environmental hazards, necessitating the development of eco-friendly alternatives. This paper examines the latest advanceme...

The integration of homomorphic encryption (HE) and blockchain technology presents a groundbreaking approach to enhancing data security and privacy in healthcare insurance systems. Traditional encryption methods often pose limitations in processing encrypted data, requiring decryption that exposes sensitive information. HE allows computations to be...

Efficient data exchange in healthcare insurance systems is crucial for improving service delivery, reducing administrative overhead, and ensuring compliance with regulatory standards. This paper explores the development of a .NET Core-based API designed to enhance interoperability among various stakeholders, including insurance providers, healthcar...

Friction is a primary challenge in various industrial applications, including automotive, aerospace, and manufacturing sectors. Reducing friction improves efficiency, reduces energy consumption, and extends the lifespan of machinery. This paper explores hybrid friction reduction technologies that combine advanced lubricants with mechanical solution...

Fraud in healthcare insurance claims is a significant challenge, leading to billions of dollars in financial losses annually. Traditional fraud detection systems often rely on centralized databases, making them vulnerable to manipulation and security breaches. This research explores the integration of smart contract technology in fraud detection to...

The healthcare insurance sector faces significant challenges in ensuring the privacy, security, and efficiency of claim processing. Traditional centralized insurance systems are susceptible to data breaches, fraud, and inefficiencies. Blockchain technology offers a decentralized alternative, enhancing transparency and security. However, blockchain'...

The growing demand for energy has led to an increase in drilling activities in harsh environments, including deep-water, high-pressure, and high-temperature (HPHT) reservoirs. Traditional drilling fluids often fail to maintain operational efficiency under these extreme conditions, necessitating the development of advanced friction-reduction technol...

Serverless computing has emerged as a transformative paradigm for enterprise applications, offering scalability, reduced operational complexity, and a pay-per-use pricing model. However, enterprises often encounter challenges related to unpredictable costs and inefficiencies in managing serverless workloads. This paper explores various cost optimiz...

Cloud-native technologies have transformed software development and deployment, offering flexibility, scalability, and efficiency. Among these technologies, serverless computing and containerized architectures are prominent paradigms for building modern applications. While serverless abstracts infrastructure management entirely, containerized archi...

Friction and associated energy losses represent significant challenges in drilling operations, impacting efficiency and increasing costs. Nanotechnology has emerged as a promising solution to address these challenges through advanced lubricants, coatings, and materials tailored for drilling applications. This paper explores the role of nanotechnolo...

Friction during deep drilling operations represents a significant challenge, leading to increased energy consumption, equipment wear, and reduced efficiency. Real-time monitoring systems have emerged as a critical technology for measuring and managing friction reduction in such operations. This paper explores the design, implementation, and applica...

The performance and longevity of drill bits are critical in oil and gas, mining, and geothermal drilling operations. Excessive wear and friction lead to reduced efficiency, increased operational costs, and frequent tool replacement. Advanced coatings and materials play a vital role in mitigating these challenges by enhancing durability, reducing fr...

Efficient data exchange in healthcare insurance systems is crucial for improving claim processing, reducing administrative costs, and enhancing patient experiences. However, interoperability challenges due to disparate data formats, legacy systems, and compliance requirements hinder seamless data integration. This research presents a .NET Core-base...

The rapid adoption of artificial intelligence (AI)-driven security tools for enterprise data protection has revolutionized how organizations safeguard sensitive information. However, these advancements also introduce complex legal and ethical challenges, including regulatory gaps, algorithmic transparency, data privacy concerns, and potential misus...

The classical Darboux transformation is a powerful mathematical tool for obtaining exact solutions of integrable systems, particularly nonlinear evolution equations. This research extends the classical Darboux transformation to multidimensional complex pulse equations and applies it to analyze soliton dynamics. We systematically derive the extended...

Healthcare claim fraud is a significant issue impacting the sustainability of healthcare systems worldwide. The challenges posed by fraudulent claims necessitate sophisticated detection techniques capable of analyzing large datasets to discern anomalous behaviors. Advanced machine learning methods, particularly deep learning techniques like Convolu...

Healthcare claim fraud poses a formidable threat to the integrity and financial sustainability of the healthcare system, resulting in staggering annual losses estimated in the billions of dollars. The complexity and nuances of fraudulent activities necessitate the development of innovative and proactive solutions to detect and prevent such incident...

The healthcare industry is facing an unprecedented level of cyber security threats, with patient data being a prime target for hackers. The increasing adoption of digital technologies such as electronic health records (EHRs), telemedicine, and connected medical devices has created new vulnerabilities that cyber attackers are exploiting. Cyber secur...

Healthcare claim fraud poses a formidable threat to the integrity and financial sustainability of the healthcare system, resulting in staggering annual losses estimated in the billions of dollars. The complexity and nuances of fraudulent activities necessitate the development of innovative and proactive solutions to detect and prevent such incident...

The adoption of Zero Trust architectures has gained significant traction as organizations aim to enhance security in their cloud-native systems. Alongside robust security mechanisms, compliance with industry-specific regulatory requirements is a critical concern. This paper explores the intersection of Zero Trust principles and compliance, detailin...

In the fast-evolving world of software development, Secure DevOps practices have emerged as a cornerstone for modern cloud-native infrastructure. By integrating Zero Trust principles, organizations can enhance the security, reliability, and compliance of their development pipelines. This paper explores the synergy between Secure DevOps and Zero Tru...

Monitoring and incident response are critical components of security in Zero Trust cloud environments. With the increasing adoption of cloud-native architectures, the need for robust real-time visibility and effective threat mitigation strategies has become paramount. This research explores the integration of Zero Trust principles into monitoring f...

End-to-end encryption (E2EE) serves as a cornerstone in securing data against unauthorized access during transit and storage. When integrated within Zero Trust architectures for cloud systems, E2EE ensures data confidentiality, integrity, and regulatory compliance in highly dynamic and distributed environments. This paper explores various strategie...

The adoption of containerization and orchestration technologies has transformed the way modern applications are deployed and managed. As these technologies rise in popularity, securing such dynamic environments poses unique challenges. This research focuses on the application of Zero Trust principles to containerized and orchestrated systems, exami...

Zero Trust Network Access (ZTNA) represents a modern paradigm shift in securing access to resources in increasingly dynamic cloud-native environments. Unlike traditional VPNs, ZTNA enforces strict identity and context-based access control to minimize attack surfaces. This research evaluates the applicability, challenges, and benefits of ZTNA in clo...

Authentication and authorization mechanisms are critical components of Zero Trust cloud architectures, enabling secure and continuous verification of identities in dynamic and distributed environments. Unlike traditional models, Zero Trust emphasizes identity as the perimeter, leveraging advanced technologies such as multi-factor authentication (MF...

Zero Trust Architecture (ZTA) has emerged as a fundamental security paradigm in response to the growing complexity of multi-cloud environments. This paper explores the principles and implementation strategies of ZTA within multi-cloud ecosystems, emphasizing how it addresses identity, access management, and data protection. By evaluating case studi...

As organizations increasingly adopt cloud-native systems, securing these architectures becomes paramount. Zero Trust Architecture (ZTA) has emerged as a critical security framework tailored for this purpose. This research explores the design principles essential for implementing ZTA in cloud-native environments, addressing aspects like identity man...

Zero Trust Architecture (ZTA) has emerged as a leading approach to secure modern IT environments. While ZTA has clear applications for cloud-native systems, its implementation in legacy systems presents unique challenges and considerations. This paper conducts a comparative study of ZTA for cloud-native and legacy systems, focusing on design princi...

Serverless computing has revolutionized cloud-based application development, offering scalability, flexibility, and reduced operational complexity. However, the security challenges specific to serverless architectures remain underexplored. This study evaluates the unique security risks in serverless environments across major cloud providers such as...

Serverless applications provide flexibility and cost efficiency but require careful design to ensure scalability and resilience. This paper explores the most effective design patterns for building scalable serverless applications, including event-driven architectures, function composition, and data partitioning. Common pitfalls such as over-relianc...

Serverless computing has emerged as a transformative paradigm, enabling developers to deploy applications without managing underlying infrastructure. However, leveraging serverless architectures for real-time applications comes with unique performance considerations and trade-offs. This paper evaluates the latency, scalability, and operational comp...

As businesses increasingly adopt serverless computing, energy efficiency and sustainability have become essential considerations in architectural decisions. This paper evaluates the energy consumption of serverless architectures compared to traditional cloud and on-premises systems. By examining resource utilization, scaling strategies, and real-wo...

Serverless computing is reshaping the cloud landscape, offering flexibility, scalability, and operational efficiency. This paper investigates how serverless architectures empower multi-cloud strategies by enabling seamless workload distribution, reducing vendor lock-in, and enhancing fault tolerance. By analyzing use cases, design considerations, a...

Serverless architectures have revolutionized cloud computing by abstracting infrastructure management and enabling developers to focus on application logic. This paper investigates the impact of serverless computing on the development lifecycles of cloud applications. It explores key advantages such as rapid development, reduced operational costs,...

Serverless computing has emerged as a transformative model for deploying enterprise applications, offering unparalleled scalability and cost efficiency. However, without proper management, costs can spiral out of control due to factors such as over-provisioning and inefficient design patterns. This research explores cost optimization techniques spe...

Serverless computing frameworks have become a cornerstone of modern cloud-native development, offering developers a simplified and efficient method of deploying applications. However, the performance of these frameworks can vary significantly across major cloud providers, such as AWS, Azure, and Google Cloud. This study investigates and compares th...

The proliferation of cloud-native infrastructure has revolutionized application development and deployment, but it has also introduced complex security challenges. Traditional perimeter-based security models are no longer sufficient to address modern threats, prompting the rise of Zero Trust Architecture (ZTA). This research explores how Zero Trust...

Cloud computing has significantly evolved with the advent of serverless architectures, providing new paradigms for application development and deployment. This paper investigates the differences between serverless and traditional cloud architectures with a specific focus on latency and throughput. Through a series of empirical benchmarks conducted...

The drilling industry encounters formidable challenges when operating in harsh environments, where extreme temperatures, high pressures, and corrosive conditions prevail. Such conditions demand innovative solutions to ensure the performance, durability, and safety of drilling components. This study investigates the development and application of ad...

This study investigates the application of surface texturing techniques as a means to reduce friction in drilling operations, with the goal of improving operational efficiency and prolonging the lifespan of drilling equipment. Drilling operations often experience high friction and wear due to the harsh dynamic conditions, which can result in equipm...

Drilling in extreme temperature environments demands advanced fluid formulations capable of maintaining performance under harsh conditions. This study examines the tribological properties of synthetic, water-based, and oil-based drilling fluids, focusing on their ability to reduce friction, minimize wear, and resist thermal degradation. The researc...

Nanotechnology has emerged as a game-changer in the drilling industry, revolutionizing the performance and sustainability of tools used in high-stress, extreme environments. Nano-coatings, designed at the molecular level, have proven to be transformative in enhancing the efficiency, durability, and reliability of drilling tools. These advanced coat...

Audit trails are fundamental to financial integrity, compliance, and fraud detection. While traditional ledger systems have long dominated accounting practices, blockchain technology offers a decentralized, immutable alternative. This study conducts a comprehensive cost-benefit analysis comparing blockchain-based audit trails with conventional syst...

The coherence and creativity of generative AI models are vital metrics for assessing their practical utility in real-world applications. This study explores the comparative performance of ChatGPT-4 and Google Gemini AI, focusing on content coherence and creativity in various task scenarios, including narrative generation, argument development, and...

As generative AI models advance, their application in multilingual contexts grows increasingly important. This study investigates the performance of two leading generative AI models, OpenAI's ChatGPT-4 and Google Gemini AI, in executing multilingual tasks. Using a variety of benchmarks, including translation accuracy, contextual understanding, and...

Generative AI models like ChatGPT-4 and Google Gemini AI are at the forefront of transforming communication across industries. This study evaluates their effectiveness in enhancing communication efficiency through email drafting, professional reporting, and real-time multilingual dialogue. Using standard benchmarks and scenario-based testing, we co...

As generative AI models advance, their application in multilingual contexts grows increasingly important. This study investigates the performance of two leading generative AI models, OpenAI's ChatGPT-4 and Google Gemini AI, in executing multilingual tasks. Using a variety of benchmarks, including translation accuracy, contextual understanding, and...

The coherence and creativity of generative AI models are vital metrics for assessing their practical utility in real-world applications. This study explores the comparative performance of ChatGPT-4 and Google Gemini AI, focusing on content coherence and creativity in various task scenarios, including narrative generation, argument development, and...

With the increasing integration of Internet of Things (IoT) devices and the proliferation of autonomous vehicles, the need for robust real-time vehicle tracking and cybersecurity systems has never been more critical. This paper proposes a novel system that combines multi-vehicle, multi-camera tracking with real-time cybersecurity detection using gr...

In recent years, the landscape of marketing has dramatically shifted, with social media becoming a central platform for brands to connect with their audiences. In Nigeria, where digital adoption is rapidly growing, social media influencers have emerged as powerful voices that shape consumer opinions and behaviors. These influencers, with their vast...

Credit unions, as financial cooperatives, face a growing need for efficient fraud detection systems to safeguard member assets and maintain trust. Large Language Models (LLMs) have emerged as transformative tools in financial technology, offering nuanced insights into transaction patterns. However, deploying these models in resource-constrained env...

Large Language Models (LLMs) like ChatGPT-4 and Google Gemini AI have revolutionized many domains, including financial services. However, providing personalized financial advice requires fine-tuning these models for domain-specific requirements, member demographics, and regulatory compliance. This paper explores strategies for fine-tuning LLMs to d...

Credit unions prioritize personalized service to maintain member trust and satisfaction. As digital transformation accelerates, the adoption of chatbots for member engagement has gained traction. However, traditional chatbots often lack the contextual understanding needed for nuanced and effective interactions. Large Language Models (LLMs) have sho...

Credit unions thrive on member trust and satisfaction, making it critical to understand and address member feedback effectively. Sentiment analysis offers a systematic way to extract actionable insights from diverse feedback channels, including surveys, complaints, and reviews. Large Language Models (LLMs) have shown promise in understanding the nu...

Credit unions, with their focus on community-centric operations, face unique challenges in adopting advanced machine learning solutions due to resource constraints. Large Language Models (LLMs) offer significant potential for automating and optimizing credit union-specific tasks, but their computational requirements often exceed what smaller organi...

Credit unions face unique challenges in processing and analyzing unstructured loan application data due to limited computational resources and diverse membership demographics. Large Language Models (LLMs) offer significant potential to streamline this process by understanding narratives and income patterns embedded in loan applications. This paper...

Credit unions require transparent and accountable artificial intelligence (AI) tools to assist with decision-making in sensitive domains such as loan approvals and member segmentation. Explainable AI (XAI) has emerged as a critical area of research, emphasizing the interpretability and trustworthiness of AI models. By integrating fine-tuning strate...

Multi-task learning (MTL) enables the simultaneous training of machine learning models on multiple related tasks, improving performance and efficiency. For credit unions, MTL with scalable fine-tuning of Large Language Models (LLMs) offers a pathway to optimize diverse financial operations-from member engagement to compliance checks and credit scor...

Large Language Models (LLMs) are resource-intensive, often demanding significant computational power and energy consumption for fine-tuning and inference. For credit unions, which operate on limited budgets and are driven by community-oriented principles, optimizing LLM fine-tuning for economic and environmental sustainability is vital. This paper...

Transfer learning offers a powerful approach for adapting generic Large Language Models (LLMs) to specialized domains such as credit union financial data. By leveraging pre-trained knowledge, credit unions can efficiently fine-tune models for tasks like risk assessment, loan processing, and fraud detection. This paper explores strategies for adapti...

Large Language Models (LLMs) have the potential to transform how credit unions handle regulatory compliance. Adapting these models to specific regulations enables credit unions to streamline compliance tasks, enhance accuracy in documentation reviews, and mitigate risks associated with non-compliance. This paper explores fine-tuning strategies for...

Credit scoring is a vital process in financial decision-making for credit unions. Large language models (LLMs) offer transformative potential by analyzing unstructured data, improving accuracy, and fostering inclusivity. However, adapting LLMs to credit scoring presents challenges, including scalability, regulatory compliance, and computational eff...

Credit unions require transparent and accountable artificial intelligence (AI) tools to assist with decision-making in sensitive domains such as loan approvals and member segmentation. Explainable AI (XAI) has emerged as a critical area of research, emphasizing the interpretability and trustworthiness of AI models. By integrating fine-tuning strate...

Credit unions, with their focus on community-centric operations, face unique challenges in adopting advanced machine learning solutions due to resource constraints. Large Language Models (LLMs) offer significant potential for automating and optimizing credit union-specific tasks, but their computational requirements often exceed what smaller organi...

Credit unions prioritize personalized service to maintain member trust and satisfaction. As digital transformation accelerates, the adoption of chatbots for member engagement has gained traction. However, traditional chatbots often lack the contextual understanding needed for nuanced and effective interactions. Large Language Models (LLMs) have sho...