Cloud-enabled automatic modulation classification using deep feature fusion and Moth-Flame Optimized ELM approach Padma Charan Sahu, Bibhu Prasad, Ratnakar Dash, Debendra Muduli, D. Samuel Kollie, Rahul Priyadarshi, Rakesh Ranjan Scientific Reports, 2026 Automatic modulation classification (AMC) plays a vital role in modern wireless communication systems by enabling efficient spectrum utilization and ensuring reliable data transmission. With increasing complexity in communication signals, traditional AMC methods face challenges in accurately classifying modulation types, particularly when deployed in cloud-based environments with scalable resources. This study aims to develop a robust AMC method that leverages deep learning–derived features combined with an optimized Extreme Learning Machine (ELM) classifier to enhance classification accuracy and reliability. Features are extracted using pre-trained deep learning models–Inception V3, ResNet 50, and VGG 16–and concatenated into a comprehensive feature set. These features are input into an ELM whose hidden-node parameters are optimized via the Moth Flame Optimization (MFO) algorithm, resulting in the MFOP-ELM classifier. Additionally, explainable AI techniques, including SHAP value analysis, are applied to interpret model predictions. The approach is evaluated on three cloud-based virtual machines with configurations of vCPU-4/16GB RAM, vCPU-8/32GB RAM, and vCPU-16/64GB RAM. The proposed MFOP-ELM model achieves a classification accuracy of 94.19%, sensitivity of 89.56%, and specificity of 88.76% on the highest configuration (vCPU-16/64GB RAM). Performance comparisons demonstrate that this method outperforms existing state-of-the-art AMC approaches. The integration of deep learning features with an MFO-optimized ELM classifier provides a highly accurate and interpretable solution for automatic modulation classification, effective in both cloud and standalone environments.
High-Efficiency Optical Polarizer using Silicon based 2D Device for Photonic Integrated Circuits Dipan Kumar Dey, Bibhu Prasad, Gopinath Palai, Partha Sarkar Computing Communication and Intelligence, 2026 The present paper proposes an optical polarizer, based on a silicon-based 2D photonic crystal structure, demonstrates high efficiency and compatibility with photonic integrated circuits (PICs). The structure effectively polarizes the output signal across a wide range of input wavelengths (1500 nm to 1772 nm). The electric field distribution within the structure, analyzed using the Helmholtz wave equation, reveals a consistent diagonal polarization pattern. The electric field magnitudes vary with different input signals, but the overall polarization direction remains consistent. Evanescent waves are observed, but their intensity is less significant compared to the polarized component. The calculated optical bandwidths for both input and output signals confirm the efficiency of the proposed structure for polarizer applications. The input bandwidth ranges from 5 THz at 1500 nm to 3.4 THz at 1772 nm, while the output bandwidth ranges from 85,000 THz at 1500 nm to 50 THz at 1772 nm. In conclusion, the proposed silicon-based 2D photonic crystal structure offers a promising solution for high-efficiency optical polarization control in PICs, with potential applications in various optical communication and sensing systems.
Experimental Realization of DPS-URUK Quantum-Inspired Image Encryption on Raspberry Pi Prateek Dash, Bandana Mallick, Priyadarsan Parida, Bibhu Prasad, Chittaranjan Nayak, Manoj Kumar Panda, N. Sowmya 2026 International Conference on Recent Advances in Electrical Electronics Ubiquitous Communication and Computational Intelligence Raeeucci 2026, 2026 Numerous encryption approaches have been developed to maintain secrecy and privacy when transmitting images over networks. However, traditional encryption algorithms are sometimes ineffective in handling real-time image data due to their rigid structures and significant processing cost, making them unsuitable for dealing with the data's dynamic nature. We demonstrated the experimental implementation of a Raspberry Pi-based quantum-inspired image encryption system for secure, real-time embedded image communication. The proposed system improves key sensitivity, permutation complexity, and diffusion strength by combining Differential Phase Shift (DPS)-assisted key generation, QBRK-based pixel location representation, Quantum Bit-Plane Scrambling (QBPS), the 3D Non-Equilateral Arnold Transform (3D-NEAT), and the URUK chaotic map. A complete transmitter-receiver hardware prototype is developed to perform image encryption, encrypted transmission, and receiver-side decryption on a low-power embedded platform. Visual description and statistical analysis indicate the effectiveness of the proposed technique. Furthermore, the proposed system outperforms 11 cutting-edge techniques, ensuring secure image transfer.
Secure real-time transmission of multi-spectral satellite images inducing a 6D hyper-chaotic system and BB84 QKD protocol Bandana Mallick, Priyadarsan Parida, Chittaranjan Nayak, Nawaf Ali, Manoj Kumar Panda, Bibhu Prasad, Gupteswar Sahu, Gopinath Palai Alexandria Engineering Journal, 2025 As the field of remote sensing advances quickly, the images from satellites are mostly utilized for different applications such as environmental monitoring, navigation, surveillance, etc. The most common approach to delivering security to the satellite images throughout the propagation from unauthorized access is by using image encryption techniques. Real-time images are challenging to process with conventional technologies because they include a diversity of information with significant prolixity, high correlation among neighboring pixels, and high uncertainty due to sensor noise and environmental conditions. Therefore, the present work focuses on the secured transmission of real-time satellite images with a high Signal-to-Noise ratio. In this work, we have developed a novel hybrid encryption method that combines a six-dimensional (6D) hyper-chaotic system with the BB84 quantum key distribution (QKD) protocol for secure and efficient image transmission. The hyper-chaotic system enhances pixel scrambling and diffusion, reducing correlations in the image data, while BB84 ensures secure key exchange during transmission over Free Space Optics (FSO) channels. The integration of a 6D hyper-chaotic system with BB84 QKD protocol is capable of transmitting multichannel information in a single secured channel. The proposed technique is corroborated using a set of satellite images, as satellite images possess highly correlated information. In the proposed model, the original satellite images are taken for Gunupur, Odisha during the period of November 22, 2023, to January 23, 2024. These images’ information is confused by the hyper-chaotic system. Then, the permuted images are diffused to generate the scrambled image using the BB84 protocol. On the receiver side, the same information is recovered with reduced information loss using the proposed receiver module, which consists of an optical hard limiter followed by a low pass filter. The performance of the proposed scheme is tested via various quantitative assessments including entropy, mutual information, histogram, cross-correlation, and differential attack analysis. Performance metrics reveal robust security and high-quality reconstruction, achieving an entropy of 7.9976, a P S N R of 8.9967, and a B E R of 0.1111 for the Pepper image. Sensitivity analysis demonstrates resilience against differential attacks, with a U A C I of 34.6970 and an N P C R of 0.9973. The system is implemented using Optisystem 15.1 and MATLAB 2017a, and experimental results confirm superior performance compared to 22 existing techniques across various metrics, including entropy, mutual information, histogram analysis, and cross-correlation. This approach highlights the potential for secure real-time image transmission in optical networks while addressing challenges in satellite image encryption. • A unique image encryption algorithm is developed for real-time satellite image encryption using BB84 QKD protocol. • A 6D hyper-chaotic system is explored to provide a higher degree of security with reduced information loss. • A pixel scrambling process is performed using hyper-chaotic sequence to make the system more robust. • The performance of the network is analyzed under FSO channel for a link distance of 200 m.
Smart Devices for Effective Tuberculosis Diagnosis: A Comprehensive Survey Ranjita Rout, Priyadarsan Parida, Bibhu Prasad, Sonali Dash Smart Electronics Devices and Models for Healthcare Systems, 2025 Tuberculosis (TB) is a serious infectious disease generally caused by Mycobacterium tuberculosis (MTB). It is transmissible in nature that spreads through airborne droplets. It affects mainly the lungs and also to the other parts of the body such as kidneys, spine, brain, etc. The disease is more harmful and a life risk to people who are consuming tobacco or are affected by other diseases such as diabetes, HIV, etc. Chest pain, blood in the cough, discomfort when breathing, coughing from three weeks or longer are the general signs of TB. To identify TB, the number of tests, that is, skin, blood, sputum, chest x-ray, etc., are recommended by physicians. Generally, digital chest radiography, GeneXpert machine, and BacT/ALERT 3D devices are used for identification of TB. The smart devices play a crucial role in the medical applications by providing precise disease detection, treatment, patient monitoring, and healthcare management. Some of the advantages of the smart devices are they save time and give accurate results that helps both the experts and the patients. Taking into consideration the effects and causes of TB, this chapter focuses on the role of different smart devices for identification of TB along with its diagnosis. Considering the recent advancements of machine learning (ML) approaches for disease diagnosis, the chapter also provides the usage of ML approaches integrated with devices for effective diagnosis and therapeutics evaluation of TB.
Multi-Channel Multi-Protocol Quantum Key Distribution System for Secure Image Transmission in Healthcare Bandana Mallick, Priyadarsan Parida, Chittaranjan Nayak, Tarek Khalifa, Manoj Kumar Panda, Nawaf Ali, Gajanan Uttam Patil, Bibhu Prasad IEEE Access, 2025 Quantum key distribution (QKD) is a viable technique for safeguarding image transmission against numerous attacks. To address the limitations of existing methods in securing electronic medical records, we have explored an encryption technique using a set of real-time medical images along with existing standard images using QKD protocols including BB84 (Bennett-Brassard 1984), CASCADE (Cascading Error Correction Algorithm for Data Exchange), and differential-phase-shift (DPS) under the fiber-based (OFC) and free-space (FSO) channels. It utilizes the quantum bit-plane representation of the Real Ket (QBRK) model and a logistic chaotic system with XOR operation. The performance of the developed framework is tested via visual illustration and 11 different quantitative assessments. The average entropy of the scrambled image for the medical source image is 7.9896, which is quite near to the optimum value of 8. The UACI (Unified Averaged Changed Intensity) and the NPCR (Number of Pixels Change Rate) metric values lie between 33.7879 to 33.9711 and 99.6014 to 99.8000 for the FSO channel. The BB84 QKD protocol achieves a QBER (Quantum Bit Error Rate) of 0.0028 for an FSO channel with DCR (Dark Count Rate), which improves to 0.0012 when DCR is ignored for a 10 km link range. In addition, we analyzed and compared the effect of OFC on system output as the quantum channel. From several experiments, it is observed that the BB84 provides better results against CASCADE and DPS. The proposed work is validated using the OptiSystem 15.1 software under FSO and for OFC.
A Large Scale Analysis of Grey Wolf Optimization Techniques: Recent Trend 15th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2024, 2024
Improved long haul WDM framework utilizing wideband apodized chirped fbg dispersion compensator International Journal of Scientific and Technology Research, 2019
