Geeta Sandeep Nadella

University of the Cumberlands · Department of Information Systems

The predictive correlational quantitative research study aimed to examine the effectiveness of existing Information System (IS) Tools, such as e-learning tools, in U.S. high schools, highlighting the gap between the notable performance of these IS tools and the definite educational outcomes they deliver, explicitly focusing on educators. Employing...

This research explores the integration of GPT-based language models in the healthcare sector, focusing on Adaptive Intelligence. It delves into the transformative possibilities and profound implications of incorporating these models into critical healthcare domains, such as clinical decision-making, medical imaging, and personalized medicine. Demon...

As organizations increasingly rely on cloud computing for storing and processing data, the security of cloud environments becomes a critical concern. This research paper explores the application of Artificial Intelligence (AI) technology in detecting and preventing cloud computing attacks. The paper introduces the significance of cloud security, a...

The advent of machine learning in personalized medicine has revolutionized the healthcare industry by providing an enhanced diagnosis and treatment regimen to patients based on their unique characteristics such as genetic predispositions, lifestyle variables, and medical history. Machine learning algorithms can analyze vast amounts of patient data...

Using quantum algorithms to improve deep learning models' capabilities is becoming increasingly popular as quantum computing develops. In this work, we investigate how quantum algorithms using quantum neural networks (QNNs) might enhance the effectiveness and performance of deep learning models. We examine the effects of quantum-inspired methods on...

Abstract— Machine Learning (ML) is pivotal in enhancing cybersecurity solutions, surpassing rule-based methods. The complexity of modern malware demands robust detection systems. Traditional signature-based approaches struggle with zero-day and polymorphic threats. Our study presents a versatile ML-based approach adept at identifying active malware...

Abstract— Using expert systems and relevant machine learning methods, automating network intrusion detection has become commonplace. However, the interconnectedness of many industrial control systems and the Internet of Things (IoT) has made cyber attacks on critical infrastructure communication networks a significant concern. These Critical Cyber-...

Given the current environment of constant cyber threats, it is crucial to emphasize the advancement of technologies such as Explainable AI and deep learning on risk assessment. Explainable AI helps explain the AI system's reasoning, the logic behind its predictions, insights, suggestions or decisions. This explanation allows an investigator to unde...

In the current digital environment, Cybersecurity is still a top priority because of the severe hazards that increasingly complex attacks pose to people, businesses, and even countries. This study provides a comprehensive analysis covering the distribution of cyberattacks, the performance of machine-learning models, and the legal frameworks control...

This study delves into the intricate dynamics of cybersecurity adoption within small and medium enterprises (SMEs), with a specific focus on the transformative potential of AI-driven solutions from a machine learning perspective. Leveraging a rich and diverse dataset of real-world cybersecurity incidents tailored to the SME context, the research me...

This research paper explores the nuances of optimizing large models of languages (LLMs) for the effective creation and retrieval of information. The current research investigation focuses on two main approaches: Knowledge Distillation (KD) and Retrieval-Augmented Generation (RAG), in addition to quantization and pruning strategies. KD reduces the s...

Telemedicine, telehealth, e-health, and other associated terms refer to the sharing of medical information or care through electronic contact, enabling safe, efficient, and available care in the changing post-pandemic healthcare environment. This study talks about the effect of telemedicine and information technology on disease protection and treat...

Edge computation (EC) represents a transformative architecture in which cloud computing services are decentralized to the locations where data originates. This shift has been facilitated by the integration of deep learning (DL) technologies, notably in eliminating latency issues commonly referred to as the "echo effect" across various platforms. In...

As the Internet of Things expands, the surge in connected devices presents significant cybersecurity challenges. The rapid digitization of governments, corporations, and personal life has escalated cyberattacks into a menace for individuals, organizations, and even entire nations. Predictive techniques are becoming increasingly necessary to counter...

With the escalating use of technology and major computer systems, cyberattack threats loom larger than ever. These attacks, categorized as any malicious attempt to gain unauthorized access to a computer system or network that intends to cause damage, necessitate the development of new security approaches. AI has emerged as a practical solution, ena...

This study investigates the indirect impact of Information and System Quality, specifically in the context of e-learning tools, and its influence on the overall impact of educators' utilization of these tools in U.S. high schools. Employing Gable's IS-Impact Measurement Model, this study conceptualizes Quality factors as first-order constructs and...

Abstract— This study investigates the indirect impact of Information and System Quality, specifically in the context of e-learning tools, and its influence on the overall impact of educators' utilization of these tools in U.S. high schools. Employing Gable's IS-Impact Measurement Model, this study conceptualizes Quality factors as first-order const...

Blockchain technology and artificial intelligence (AI) have been gaining much interest in the finance industry due to their potential to democratize access to financial services, especially in impoverished areas lacking traditional banking infrastructure. The current study adopts a research strategy that thoroughly examines and integrates existing...