D Shobana
YOU?
Author Swipe
View article: A STUDY ON THE EVALUATION OF GOVERNMENT SCHEMES FOR SHGS IN NAGALAND: EFFECTIVENESS AND CHALLENGES
A STUDY ON THE EVALUATION OF GOVERNMENT SCHEMES FOR SHGS IN NAGALAND: EFFECTIVENESS AND CHALLENGES Open
Self-Help Groups (SHGs) have emerged as a vital tool for socio-economic empowerment, particularly in rural areas. In Nagaland, government schemes aimed at strengthening SHGs play a crucial role in promoting financial inclusion, entrepreneu…
View article: Incorporation of NLP techniques to facilitate intuitive user interactions with prosthetic devices
Incorporation of NLP techniques to facilitate intuitive user interactions with prosthetic devices Open
The advancement of prosthetic technology has increasingly emphasized the integration of intelligent control systems to enhance user experience and functional adaptability. Traditional prosthetic devices rely on limited input modalities, of…
View article: Application of machine learning models for predicting failure and optimizing implant longevity
Application of machine learning models for predicting failure and optimizing implant longevity Open
The accurate prediction of implant failure is critical for enhancing patient outcomes, minimizing revision surgeries, and improving the longevity of biomedical implants. Traditional failure prediction methods, including statistical models …
View article: AI-powered biosensors for real-time physiological monitoring and response
AI-powered biosensors for real-time physiological monitoring and response Open
The integration of AI-powered biosensors into healthcare systems has transformed the landscape of real-time physiological monitoring, offering unprecedented opportunities for personalized health management. These adaptive systems, driven b…
View article: Data Encryption Methodologies Enhanced by Hybrid Machine Learning Models for Secured Communication
Data Encryption Methodologies Enhanced by Hybrid Machine Learning Models for Secured Communication Open
The rapid advancements in computing technologies, especially quantum computing, pose significant challenges to traditional encryption methods, compelling the need for more robust, adaptive, and scalable solutions. Hybrid machine learning (…
View article: Role of Feature Selection and Dimensionality Reduction in Hybrid Learning Systems for Threat Detection
Role of Feature Selection and Dimensionality Reduction in Hybrid Learning Systems for Threat Detection Open
In the rapidly evolving landscape of cybersecurity, the increasing volume and complexity of data present significant challenges in detecting novel threats and anomalies. Feature selection and dimensionality reduction techniques play a pivo…
View article: Hybrid Deep Learning Architectures for Scalable Security in IoT and Edge Computing Environments
Hybrid Deep Learning Architectures for Scalable Security in IoT and Edge Computing Environments Open
The proliferation of Internet of Things (IoT) and edge computing technologies has transformed digital ecosystems, enabling real-time data processing and intelligent decision-making. The massive interconnectivity and resource-constrained na…
View article: Neural Network Ensembles Combined with Statistical Models for Enhanced Encryption Algorithms
Neural Network Ensembles Combined with Statistical Models for Enhanced Encryption Algorithms Open
The rapid evolution of cryptographic systems has driven the need for innovative approaches to enhance data security, particularly in the context of modern technological landscapes such as Internet of Things (IoT) and edge computing environ…
View article: Adaptive Machine Learning Algorithms for Real-Time Detection of Zero-Day Vulnerabilities
Adaptive Machine Learning Algorithms for Real-Time Detection of Zero-Day Vulnerabilities Open
The detection of zero-day vulnerabilities remains one of the most critical challenges in modern cybersecurity. Traditional detection systems, primarily reliant on signature-based methods, are ineffective against unknown or novel attacks. T…
View article: Application of Transfer Learning in Multi-Domain Hybrid Cybersecurity Solutions
Application of Transfer Learning in Multi-Domain Hybrid Cybersecurity Solutions Open
The increasing sophistication and frequency of cyber-attacks necessitate advanced solutions for cybersecurity that can adapt to new and evolving threats across multiple domains. Transfer learning, a machine learning technique that leverage…
View article: Advanced Data Preprocessing and Feature Engineering Techniques for Infrastructure Risk Analysis
Advanced Data Preprocessing and Feature Engineering Techniques for Infrastructure Risk Analysis Open
Infrastructure risk analysis involves the integration and interpretation of diverse datasets to predict failures, assess vulnerabilities, and optimize system performance. These datasets often exhibit challenges such as temporal misalignmen…
View article: Multi-Modal Data Fusion with Deep Neural Networks for Holistic Security Assessments
Multi-Modal Data Fusion with Deep Neural Networks for Holistic Security Assessments Open
The rapid advancements in deep neural networks (DNNs) have revolutionized multi-modal data fusion, paving the way for transformative applications in holistic security assessments. This book chapter explores the integration of diverse data …
View article: Generative Adversarial Networks for Simulating Cyber-Attack Scenarios and Training Defense Systems
Generative Adversarial Networks for Simulating Cyber-Attack Scenarios and Training Defense Systems Open
Generative Adversarial Networks (GANs) have emerged as a transformative tool in simulating sophisticated cyber-attacks and enhancing defense strategies. This chapter explores the application of GANs in simulating various cyber-attack scena…
View article: Time Series Forecasting with Recurrent Neural Networks for Critical Infrastructure Failure Prediction
Time Series Forecasting with Recurrent Neural Networks for Critical Infrastructure Failure Prediction Open
Time series forecasting plays a pivotal role in ensuring the resilience and efficiency of critical infrastructure systems, including energy, water, and transportation networks. Accurate predictions of system behavior are crucial for mainta…
View article: Transfer Learning for Rapid Deployment of Predictive Models in Dynamic Security Environments
Transfer Learning for Rapid Deployment of Predictive Models in Dynamic Security Environments Open
Transfer learning has emerged as a transformative approach in the rapid deployment of predictive models within dynamic security environments, offering significant advantages in adapting pre-trained models to novel, domain-specific tasks. T…
View article: Foundations of Deep Neural Networks for Predictive Analytics in Critical Infrastructure Security
Foundations of Deep Neural Networks for Predictive Analytics in Critical Infrastructure Security Open
The integration of multimodal data has emerged as a pivotal approach to bolstering critical infrastructure security, enabling enhanced situational awareness and predictive analytics. This chapter delves into the foundational principles, ch…
View article: Ensemble Deep Learning Models for Proactive Threat Identification in Critical Systems
Ensemble Deep Learning Models for Proactive Threat Identification in Critical Systems Open
The dynamic evolution of cyber threats poses significant challenges to the security of critical systems, necessitating innovative and adaptive solutions. Deep learning models have demonstrated exceptional potential in identifying complex p…