Koneru Lakshmaiah Education Foundation

A secure optimal routing protocol for medical data transmission using IoMT

This paper presents that a secure optimal cluster-based (SOptC) routing system for the delivery of medical data is framed for secure medical data transmission. The Modified-Chaotic Mine Blast Optimization (M-CMBO) method is used to efficiently cluster the described SOptC, which i...

Federated MapReduce fractional deep learning for scalable and privacy-aware intrusion detection in cloud computing

Conventional intrusion detection systems (IDSs) are not suitable for large-scale, heterogeneous, and privacy-sensitive cloud environments, owing to the rapid adoption of cloud computing and Internet of Things (IoT) technologies, which have resulted in an increasing scale and comp...

Intelligent energy management in renewable-powered microgrid using Z-dualflux converter and RBFNN control

In this research, a sophisticated intelligent energy management framework that integrates wind, solar and battery energy storage devices is proposed for a grid-connected system. A Z-Dual Flux (Z-DF) converter which enhances the Photovoltaic (PV) system’s voltage with increased vo...

Energy Efficient Federated Graph Reinforcement Learning and Digital Twin Assisted Demand Response for Blockchain-Enabled Self-Healing Smart Grids

Abstract Smart grids today are highly decentralized and data-driven, with the growing incorporation of renewable energy resources, electric vehicles, distributed energy systems and intelligent edge devices. Energy efficiency, operational resilience, privacy protection and secure...

DAVis-Net: A Dual-Attention Deep Supervision Framework for Reliable Retinal OCT Image Classification with Integrated Explainability and Uncertainty Quantification

Classification accuracy in retinal optical coherence tomography (OCT) alone does not establish whether a model is reliable or whether to refer to a specialist. To address this, we propose DAVis-Net, a VGG16-based architecture that is equipped with two Convolutional Block Attentio...

Adaptive quantum-walk-inspired attack graph compiler for vulnerability-aware exploration and explainable cybersecurity attack path prioritization

Attack graph analytics plays a critical role in cybersecurity by enabling attack-path discovery, risk assessment, and security prioritization in complex network environments. However, existing attack graph frameworks often suffer from limited scalability, fixed exploration strate...

Efficient Resource Management in 6G for Sustainable Spectrum Allocation Using Dual‐Channel Temporal Convolutional Frequency‐Separated Attention Network with Generation Rights Trading Blockchain

ABSTRACT The need for effective spectrum allocation to guarantee highly reliable, minimal‐latency, and sustainable connections has increased due to the exponential expansion of wireless communications and the introduction of 6G technologies. In order to cope with these challenges...

Impact of Plot Dimensions on the Sky-View Factor of a Residential Canyon in Indian Cities: A Parametric Analysis

Abstract Numerous studies have assessed the impact of urban canopy parameters on the urban heat island (UHI) effect. However, no tool is available to predict the UHI intensity in yet-to-be-developed urban areas. Nevertheless, development can be predicted by analyzing the applicab...

The effects of hawthorn, Crataegus monogyna, berry (CMB) on growth, hematology, antioxidant, digestive enzyme activity, gut microbiota, and disease resistance of African catfish, Clarias gariepinus

This study evaluated the effects of dietary supplementation of hawthorn ( Crataegus monogyna ) berry (CMB) on growth performance, hematological parameters, antioxidant status, digestive enzyme activity, gut microbiota, and disease resistance of African catfish ( Clarias gariepinu...

Revolutionizing HD Diagnosis: Hybrid Deep Learning and Machine Learning Using ISV-CNN

Millions of people in worldwide suffers from Heart Disease (HD), in which Coronary Artery Disease (CAD) is the most prevalent kind. Timely and accurate diagnosis is essential for successful therapy and better patient outcomes. This study introduces a novel Integrated Stochastic V...

Low-loss dielectric radome with RFID for intelligent scanning in sub-THz, future autonomous defense systems

The proposed antenna design incorporates a 0.3 mm thick Roger substrate, a 0.00125 mm thick patch, and a cylindrical hollow radome made of Preperm HF H1500 material. The radome encloses a 1 × 11 linear array with a radius of 5.40 mm without affecting its radiation characteristics...

Titanium dioxide/zinc telluride/aluminium antimonide-assisted label-free plasmonic sensor for early detection of glucose in urine

Abstract The article presents a high multi-layered surface plasmon resonance (SPR) sensor for the detection of glucose in urine. This designed sensor consists of a K108 (LZOS) prism, a silver (Ag) layer, and dielectric layers of titanium dioxide (\(\:{TiO}_{2}\)), zinc telluride...

Hierarchical grouped convolution and multi-scale vision transformer for uncertainty-aware early breast cancer detection using mammography

Abstract Early breast cancer detection using mammography remains challenging because existing deep learning methods often emphasize either local lesion characteristics or global contextual information, while providing limited uncertainty quantification and clinically reliable pre...

FEA-Assisted nanostructured piezoelectric sensor and deep learning framework for noninvasive tumor detection and tissue stiffness analysis

Biosensors have long been used in environmental monitoring and clinical diagnostics for detecting harmful bacteria, viruses, and biomolecules, evolving from simple biological sensing systems to advanced nanofabrication-based devices. With help of nanotechnology, nano-biosensors h...

Evaluation of Method “Whiteness” in the Stability Analysis of Dexamethasone and PVP‐I Ophthalmic Suspensions: Synergizing LC‐MS/MS, In Silico Toxicology, and AGREE/GAPI Metrics

ABSTRACT This study presents a holistic “White Analytical Chemistry” approach for the stability‐indicating evaluation of dexamethasone in complex povidone‐iodine (PVP‐I) ophthalmic suspensions. Moving beyond traditional validation, the method's “whiteness” was quantitatively asse...

BODIPY-Integrated Porous Materials: Design Principles, Functional Architectures, and Emerging Applications

Abstract The incorporation of functional organic chromophores into porous architectures has emerged as a powerful strategy to bridge molecular photophysics with materials-level performance. Among these, boron-dipyrromethene (BODIPY) derivatives offer a unique combination of stron...

BioTwin-PE: An Uncertainty-Aware Multimodal State-Space Framework and Validation Protocol for Longitudinal Placental Monitoring

Placental assessment is necessarily intermittent, while ma- ternal and fetal physiology evolve continuously. This mis- match limits the ability of conventional visit-level prediction models to represent changes occurring between examinations. We present BioTwin-PE, a methods fram...

Structure-based discovery of phospholipase A1 (PlaF) inhibitors in Pseudomonas aeruginosa using integrated in silico and experimental approaches

Phospholipase A1 (PlaF) is a membrane-bound virulence factor in Pseudomonas aeruginosa, involved in glycerophospholipid remodeling and host-pathogen signaling. Inhibiting PlaF represents a promising strategy to reduce the virulence and pathogenesis of multidrug-resistant P. aerug...

BioTwin-PE: An Uncertainty-Aware Multimodal State-Space Framework and Validation Protocol for Longitudinal Placental Monitoring

Placental assessment is necessarily intermittent, while ma- ternal and fetal physiology evolve continuously. This mis- match limits the ability of conventional visit-level prediction models to represent changes occurring between examinations. We present BioTwin-PE, a methods fram...

A hybrid deep reinforcement learning framework for proactive cloud network intrusion detection using spatiotemporal feature learning

Traditional signature-based and static machine-learning-based intrusion detection systems (IDSs) have limited ability to adapt to changing traffic characteristics, and dynamic cloud-based infrastructures are increasingly vulnerable to new and zero-day attacks. Given this drawback...