Suvendu Kumar Jena

Adaptive Phi-Evolutionary Key Scheduling Framework for Hybrid and Lightweight Cryptosystems with Multi-Metric Cryptanalysis Validation

Suvendu Kumar Jena, Priyabrata Sahu, Rajesh Kumar Pati

This paper proposes an adaptive phi-driven evolutionary key scheduling framework that enhances the security of hybrid classical and lightweight cryptosystems. Unlike traditional approaches that rely on static key initialization, the proposed method introduces a dynamically evolving Golden Ratio (φ)-based mutation strategy integrated …

in (code pays fourni par la source)

Deep Neural Network–Based Identification of Protein Secondary Structures and Structural Complexities

Suvendu Kumar Jena

Proteins are essential biological macromolecules responsible for a wide range of cellular functions, including molecular transport, enzymatic catalysis, and signal regulation. Understanding protein structure is crucial for analyzing protein behavior and supporting drug discovery and biomedical research. Protein structure prediction (PSP) aims …

Multimodal Brain-Computer Interfaces Using Cross-Modal Transformer Fusion Framework

Sateesh Kumar Pradhan, Zabiha Khan, Priyabrata Sahu, Suvendu Kumar Jena

Recently, the Brain-Computer Interfaces (BCIs) are emerging as an important tool for neurorehabilitation, cognitive monitoring and human-machine interaction where the multimodal integration of neural signals improves system robustness. Among these available modalities, the Electroencephalography (EEG) provides high temporal resolution while functional Near-Infrared …

in (code pays fourni par la source)

Comprehensive Analysis on Feature Selection and Dimensionality Reduction in Big Data

Suvendu Kumar Jena, Taki Alrwbaye, Piyush Kumar Pareek, M. Nikitha et autres

From the past few years, massive volumes of structured, semi-structured and unstructured data are generated across various domains like healthcare, Internet of Things (IoT), finance and multimedia. Removing or ignoring irrelevant attributes from the data reduces the burden on Machine Learning (ML) …

in, iq (code pays fourni par la source)

Apple Leaf Disease Detection and Classification Using L1 Regularized Multi Head Vision Transformer

Gayatri Math, P Vishwanath, Zayd Ajsan Balsem, Supriya Supriya et autres

iq, in (code pays fourni par la source)

Plant Disease Classification Using Fusion Cauchy Reverse Learning Strategy Based Orca Predation Algorithm with DenseNet-121

Revati, P Vishwanath, B M Manjula, Saef Wbaid et autres

Plant diseases represents specific spots with various colors and locations, that have a significant impact on leaves lead to affect the plants and reduced the crop yield. Thus, an accurate plant disease classification is essential corresponding to the distinct spot shape, size, …

in, iq (code pays fourni par la source)

Graphical deep learning-based data-driven stock prediction model

Haewon Byeon, Mukesh Soni, Maher Ali Rusho, Suvendu Kumar Jena et autres

kr, in, us (code pays fourni par la source)

Harris Hawks Optimization Based Feature Selection on High Dimensional data

Suvendu Kumar Jena, Gotte Ranjith Kumar, Ramy Riad Al–Fatlawy, S. Rasheed Mansoor Ali et autres

In recent times, evolutionary algorithms have been demonstrating significant benefits in feature selection due to their simplicity and global search capability. However, most of the existing evolutionary algorithms are computationally intensive for high-dimensional data. In order to decrease computational costs, effective evaluation …

in, iq (code pays fourni par la source)

Dynamic Data Mining for Multidimensional Data Based On Machine Learning Algorithms

Suvendu Kumar Jena, Priyabrata Sahu, Sasmita Mishra

While existing data mining methods and machine learning algorithms need a substantial quantity of data to train, more data must be acquired before they can be used. The intricacy of the model affects the size of the file. when analyzing data, like …

in (code pays fourni par la source)