Volume 14 Issue 3  ·  ISSN: 2319-4863  ·  Monthly Publication editor@ijdacr.com
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Current Issue — VOLUME 14 ISSUE 03 OCTOBER 2025

Peer-reviewed articles published in the current issue. All articles are open access.

ISSN: 2319-4863 Open Access Peer-Reviewed

Articles in This Issue

VOLUME 14 ISSUE 03 OCTOBER 2025

1

The Synergistic Convergence of Generative AI, Evolutionary Computing, and Edge Intelligence: A Unified Framework for Next-Generation Financial Systems

Dr. B. Suresh Babu

This detailed paper is a synthesis of three paradigm shifts in technology, including Generative Artificial Intelligence (GenAI), Evolutionary Strategies (ES) of optimization, and Internet of Things (IoT)-enabled edge computing, to provide a conceptual framework that aligns and enables the transforma...

2

A Comprehensive Survey of Radiomics and Machine Learning in Medical Image Processing

Ashutosh Kumar Singh

Radiomics, defined as the high-throughput extraction of quantitative features from medical images, represents a paradigm shift in diagnostic and prognostic medicine by enabling the discovery of imaging biomarkers beyond human perception. This review synthesizes existing literature on the integration...

3

Feature Extraction to Generative Intelligence: AI-Driven Advances in Computer Vision

Ashutosh Kumar Singh

Artificial Intelligence (AI) and Machine Learning (ML) have fundamentally transformed computer vision (CV), enabling machines to extract meaningful information from images and videos with unprecedented accuracy. This paper provides a comprehensive review of the evolution of AI/ML in CV, from early f...

4

An Integrated Framework Combining IoT, Financial Analytics, and Image Processing for Future Finance

Ashutosh Kumar Singh

The rapid digitization of financial services, combined with the expansion of the Internet of Things (IoT) and advances in computer vision, is creating new opportunities for data-driven innovation. This paper proposes an interdisciplinary framework integrating IoT sensor networks, real-time image pro...

5

A Cross-Domain Survey of Machine Learning: Methods, Applications, and Emerging Trends

Ashutosh Kumar Singh

Machine Learning (ML) has become one of the most disruptive technologies in such fields as finance, healthcare, disaster management, big data analytics, intelligent transportation systems, behavioral economics, radiomics, and human-computer interaction. The literature review is based on over forty p...

6

Evolutionary Hyperparameter Tuning for Deep Learning Models

Ashutosh Kumar Singh

The performance of deep learning (DL) models is highly dependent on hyperparameter selection, including learning rate, network depth, dropout, and optimizer choice. Traditional methods such as manual tuning and grid search are computationally expensive and ineffective in high-dimensional, non-convex...

7

Generative Artificial Intelligence in Finance: Applications, Opportunities, and Challenges

Ashutosh Kumar Singh

A paradigm shift is underway in banking and finance driven by artificial intelligence, with Generative AI (GenAI) emerging as a transformative force beyond traditional predictive analytics. This paper provides a comprehensive review of GenAI applications across the financial services ecosystem, exte...

8

Intelligent Decision-Making Across Computational Domains: A Review of AI, ML, and Generative Approaches

Ashutosh Kumar Singh

Machine Learning (ML) and Artificial Intelligence (AI) have become essential tools for intelligent decision-making in complex, data-intensive environments. Advances in supervised learning, deep learning, generative models, and signal processing have enabled effective solutions across domains such as...

9

Integrating Risk Awareness and Trust in AI: Learning, Generative, and Governance Perspectives

Ashutosh Kumar Singh

The increasing deployment of Artificial Intelligence (AI) in high-impact domains such as finance, healthcare, transportation, cybersecurity, and critical infrastructure has intensified the need for risk-aware, trustworthy, and reliable decision-making systems. Traditional machine learning models, wh...

10

Optimization-Driven and Generative-Assisted Adaptive Artificial Intelligence Systems: A Detailed Review of Methods, Architectures, and Governance

Ashutosh kumar singh

Artificial Intelligence (AI) systems are being instituted in dynamic, uncertain, and safety-critical systems like financial analytics, healthcare allotment, intelligent traffic, cybersecurity and cyber-physical infrastructures. In these directions, traditional machine learning models with fixed trai...

11

Optimization-Driven Adaptive Anomaly Detection for Financial and Cyber-Physical Systems

Ashutosh kumar singh

With the increasing reliance on data-driven decision systems in financial and cyber-physical infrastructures, detecting anomalous and high-risk events has become a critical challenge. Traditional statistical methods and static machine learning models often fail to adapt to evolving data distribution...

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