Koneru Lakshmaiah Education Foundation

Optimized bilateral segmentation deep learning network for wild animal detection

The use of Deep learning (DL) for recognition of wild animals has become an important development in wildlife monitoring. The advances will include the use of multimodal data for improved accuracy and development of lightweight models for use in edge devices. As a result, DL will...

An integrated framework for breast cancer diagnosis using adaptive DeepLabv3+ for segmentation and attention-based multiscale EfficientNetB7 for classification

Breast cancer is the primary health concern for women around the world. An advanced deep learning mechanism is proposed in this work for recognizing breast cancer disease. The proposed model initially processes image collection, where significant tomography images are gathered fr...

Recent advances in Label-Free plasmonic Biosensors: Focus on metal chalcogenides and ferroelectric oxides for biomedical and environmental applications

Label-free surface plasmon resonance (SPR) biosensors have become one of the most powerful platforms for real-time and high-sensitivity detection in biomedical diagnostics and environmental monitoring. We review the state of art of recent developments in SPR sensor design efforts...

An integrated passive reconnaissance and OSINT correlation framework for unified cyber intelligence gathering

Passive reconnaissance has become increasingly significant in helping analysts obtain intelligence about target systems without directly interacting with them. Open-Source Intelligence (OSINT) provides valuable information that can support security assessment, cyber investigation...

Comparative analysis of gradient boosting and random forest regressors for nutrient prediction in smart agriculture

Accurate estimation of nutrient concentrations can support monitoring in hydroponic systems. This study compares Random Forest Regressor (RFR) and Gradient Boosting Regressor (GBR) for predicting nitrogen, phosphorus, and potassium from pH, electrical conductivity, temperature, a...

Advances and projects of immunomodulatory biomaterials used for immunotherapy

Abstract Immunotherapy is employed to manage systemic hyperactivation or hypoactivation for the treatment of various diseases. Biomaterial-based immunotherapy systems have the potential to enhance therapeutic outcomes through mechanisms such as targeted drug delivery and immuno-e...

A trust-aware computational framework for mental health risk amplification and propagation in online social networks

Computational social systems are facing big challenges because of the rapid dissemination of inaccurate information, evidenced by the growing number of negative impacts on individual and collective mental health. Although extensive research has investigated the dissemination of f...

Rational design and analysis of SPR biosensor based on Ag/AlN/BlueP-MoS₂/BP heterostructure for ultrasensitive detection of basal cell carcinoma

Skin cancer is one of the most commonly occurring malignancies in the world whereby the abnormal development of the skin cells is achieved through lack of control, most frequently through long exposure to ultraviolet (UV) radiations. Timely and precise results are essential towar...

Radial-residual energy-aware deep learning framework for sustainable cloud–IoT intelligence in smart cities

Smart city Internet of Things (IoT) networks is generating a continuous stream of heterogeneous sensor data that tends to require a timely analysis under the strict energy, latency, and computational constraints. Existing cloud-edge learning approaches have improved IoT intellige...

Energy-efficient clustering and mobile sink routing in wireless sensor networks using quantum-inspired optimization and deep learning

Wireless sensor networks (WSNs) require energy-efficient clustering and adaptive routing to maintain reliable communication and prolong network lifetime under varying node density, initial energy, communication range, packet size, residual energy, routing distance, latency, and m...

Electrochemical Phosphorus Recovery as a Continuum: Integrating Electro-Oxidation, Electrodissolution, and Interfacial Crystallization

Electrochemical phosphorus recovery (EPR) provides a sustainable alternative to conventional chemical precipitation by generating in situ alkalinity, oxidants, and coagulating cations, thereby minimizing chemical reagent dosing. However, practical implementation remains constrain...

Determination of wear resistance ratio between A356–B4C and A356–B4C + graphite hybrid composites

This study investigates the tribological behavior of A356 aluminum alloy reinforced with boron carbide (B4C) and hybridized with graphite (Gr) to enhance wear resistance under varying operating conditions. The composites were fabricated using the stir casting technique with reinf...

Hybrid multilayer surface plasmon resonance sensor based on tantalum pentoxide and silver gallium sulfide for ultra-trace detection of lead (II) ions in environmental samples

pollution of water by lead ions (Pb 2 + ) presents a serious health risk and requires sensitive detection of Pb2 + ions based on refractive-index (RI) variations. Hence, the detection of this Pb 2+ ion has been done by employing a surface plasmon resonance (SPR) sensor with a six...

Graphene Photodetectors Toward Practical Technologies for Biosensing: Mechanisms, Architectures, Applications, and Integration Challenges

Graphene, with its 2D structure, zero bandgap, high carrier mobility, and broadband absorption, is an ideal platform for next-generation photodetectors with substantial promise for biosensing applications. This review summarizes recent progress in graphene photodetectors along th...

IoT-enabled smart home activity classification using BiLSTM and attention mechanisms

IoT-enabled smart homes require accurate activity classification to enhance safety, healthcare monitoring, and energy efficiency through continuous sensing and intelligent interpretation of human behavior. Common approaches employ wearable or ambient sensors, signal preprocessing...

Hierarchical machine learning and optimisation framework for intelligent energy management in smart distribution systems

Integrated energy management frameworks that can concurrently propagate forecast uncertainty into optimization constraints, couple fault detection with automated redispatch strategies, and enable repeatable solver benchmarking on a single testbed are still lacking in current smar...

EGFR-AI Drug Discovery Computational Workflow

This software repository contains the computational workflow developed for an EGFR-targeted artificial intelligence (AI)-assisted drug discovery study. The project includes source code and computational scripts for AI/ML-based analysis, molecular generation, molecular docking, mo...

Advanced multi-task learning for brain tumor diagnosis: joint segmentation and classification using attention-guided vision transformers and ensemble models

Accurate tumor delineation and reliable tumor subtype classification from multi-sequence magnetic resonance imaging (MRI) is required for accurate diagnosis of brain tumors. Current methods, however, tend to handle segmentation and classification separately with a limited number...

Event and Travel Booking & Management System: An Integrated Web-Based Platform for Unified Event and Travel Services

This research paper presents an integrated web-based platform for event and travel booking and management, combining event discovery, travel services, booking workflows, user management, and administrative functions within a unified architecture.

Event and Travel Booking & Management System: An Integrated Web-Based Platform for Unified Event and Travel Services

This research paper presents an integrated web-based platform for event and travel booking and management, combining event discovery, travel services, booking workflows, user management, and administrative functions within a unified architecture.