Rojalina Priyadarshini

Rolling Variables: Elevating Space Optimization to Standard Practice in Dynamic Programming -A Feasibility Approach

Subham Divakar, Rojalina Priyadarshini

Automatic lung cancer classification using histopathological images: A hybrid DenseNet121-slantlet transform framework

Biswaranjan Debata, Rojalina Priyadarshini, Sudhir Kumar Mohapatra

Accurate classification of histopathological images is essential in the early diagnosis and treatment of lung cancer. Conventional deep learning approaches often face the challenges of simulating fine-grained texture features of low-level features as well as high-level semantic features that can be observed …

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Explainable business intelligence for auditable vendor segmentation and payment-traceability monitoring in SAP cross-company check payments

Sanjib Kumar Mishra, Sasmita Mishra, Rojalina Priyadarshini, Zefree Lazarus Mayaluri

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T-RLAN: A Temporal-Regime-Linked Attention Network for Index Forecasting

Rasmi Ranjan Khansama, Rojalina Priyadarshini, Surendra Kumar Nanda

Forecasting financial market indices, including the NIFTY 50 and S&P 500, remains a challenging task because of the complex nonlinear behaviour, frequent structural changes, and evolving market regime characteristics of financial time series. While deep learning models such as LSTM have shown …

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Capturing Short- and Long-Term Temporal Dependencies Using Bahdanau-Enhanced Fused Attention Model for Financial Data—An Explainable AI Approach

Rasmi Ranjan Khansama, Rojalina Priyadarshini, Surendra Kumar Nanda, Rabindra K. Barik

Prediction of stock closing price plays a critical role in financial planning, risk management, and informed investment decision-making. In this study, we propose a novel model that synergistically amalgamates Bidirectional GRU (BiGRU) with three complementary attention techniques—Top-k Sparse, Global, and Bahdanau Attention—to …

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LiteSeqCNN + Multi-attention-Based Framework for Protein Function Prediction

Abhipsa Mahala, Ashish Ranjan, Rojalina Priyadarshini, Prabhat Dansena et autres

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A comprehensive review and comparative analysis of zero trust architecture: Evolution, implementation strategies, and key challenges

Ashutosh Soni, Surendra Kumar Nanda, Rojalina Priyadarshini, Ganapati Panda

With the rise and advancements of technology, digital security is facing unprecedented challenges. Traditional security measures, such as strong credentials and multi-factor authentication (MFA), are no longer sufficient to protect digital assets from attacks and unauthorized access or to effectively verify user …

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A Comprehensive Survey on Data Distillation: Techniques, Frameworks, and Future Directions

Qaiser Razi, Rojalina Priyadarshini, Vikas Hassija, GSS Chalapathi

The increased adoption of machine learning techniques has led to exponential growth in data generation and utilization. This growth has necessitated efficient storage, processing, and utilization of this data, which presents critical challenges, particularly in resource-constrained environments such as the Internet of …

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Hybrid Cryptosystem to Secure Access Policies for Zero Trust Environment

Ashutosh Soni, Jayanti Rout, Mrutyunjaya Sathua, Surendra Kumar Nanda et autres

SGR-Net: A Synergistic Attention Network for Robust Stock Market Forecasting

Rasmi Ranjan Khansama, Rojalina Priyadarshini, Rabindra K. Barik, Manob Jyoti Saikia

Owing to the high volatility, non-stationarity, and complexity of financial time-series data, stock market trend prediction remains a crucial but difficult endeavor. To address this, we present a novel Multi-Perspective Fused Attention model (SGR-Net) that amalgamates Random, Global, and Sparse Attention mechanisms …

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PlantFusion: A Novel Multimodal Dataset and Hybrid Multimodal Deep Learning Framework

Subham Divakar, Rojalina Priyadarshini, Satyaban Behera, Deepti Mishra et autres

Accurate plant disease detection is crucial for improving agricultural practices and ensuring food security. Traditional methods often rely on uni-modal datasets, which might focus solely on visual symptoms captured through images or on environmental and sensor data. However, these approaches can be …

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Secure and Scalable Data Integrity Verification for Multi-Cloud Storage Using Blockchain-Integrated IPFS

Swatisipra Das, Minati Mishra, Rojalina Priyadarshini

Cloud storage provides unlimited data storage space, convenient and secure access to files, efficient data management, offsite backup capabilities, and cost-effective usage. However, dependence on a single Cloud Storage Provider ($CSP$) introduces challenges such as vendor lock-in, security vulnerabilities, and cost-related issues. …

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