NEXORA : COMPUTATIONAL INTELLIGENCE & ENGINEERING AN INTERNATIONAL JOURNAL

ABOUT - NEXORA : COMPUTATIONAL INTELLIGENCE & ENGINEERING AN INTERNATIONAL JOURNAL

AIM OF THE JOURNAL

Nexora: Computational Intelligence & Engineering (NCIE) is an international, peer-reviewed, open-access journal dedicated to advancing scientific knowledge, driving technological innovation, and promoting sustainable engineering practices through computational intelligence.

The journal aims to provide a dynamic global platform for computer scientists, software engineers, data analysts, academicians, and industry experts to publish high-quality original research, comprehensive reviews, case studies, and technical communications. NCIE fosters interdisciplinary research that leverages smart algorithms, scalable architectures, and emerging digital technologies to solve complex real-world problems for the benefit of society, industry, and the digital economy.

SCOPE OF THE JOURNAL

The journal welcomes groundbreaking contributions from diverse areas of computer science, data engineering, and intelligent systems, including but not limited to the following tracks:

1. Computational Intelligence & Artificial Intelligence

• Machine learning algorithms and deep learning architectures
• Natural language processing (NLP) and computational linguistics
• Computer vision, image processing, and pattern recognition
• Evolutionary computing, genetic algorithms, and swarm intelligence
• Fuzzy logic, neural networks, and hybrid intelligent systems
• Knowledge representation, reasoning, and expert systems
• Human-computer interaction (HCI) and cognitive computing

2. Software Engineering & Advanced Computing

• Agile, DevOps, and automated software engineering methodologies
• Software architecture, quality assurance, and reliability engineering
• High-performance computing (HPC), parallel, and distributed systems
• Cloud, edge, and fog computing paradigms
• Quantum computing architectures and algorithms
• Compiler design, programming languages, and formal methods

3. Data Engineering & Knowledge Discovery

• Big data analytics, mining, and visualization
• Data warehousing, integration, and provenance
• Information retrieval and web mining
• Predictive modeling and stream data analysis
• Graph data management and social network analysis

4. Cyber-Physical Systems & IoT

• Internet of Things (IoT) architectures and smart sensor networks
• Embedded systems and real-time computing
• Smart cities, grid automation, and intelligent transportation systems
• Digital twins and industrial automation (Industry 4.0/5.0)

5. Cybersecurity, Privacy & Blockchain

• Cryptography, network security, and intrusion detection systems
• Privacy-preserving data mining and anonymization techniques
• Blockchain technologies, smart contracts, and decentralized finance (DeFi)
• Trustworthy AI and ethical algorithmic governance
• Forensics and cyber threat intelligence

6. Emerging Technology & Applied Engineering

• Robotics, autonomous systems, and unmanned aerial vehicles (UAVs)
• Bioinformatics, health informatics, and computational biology
• Computational finance, algorithmic trading, and e-commerce systems
• Green computing and energy-efficient data center design
• Technology management, digital transformation policies, and tech-ethics

TYPES OF MANUSCRIPTS ACCEPTED

The journal accepts the following article types:

• Original Research Articles: Full-length, innovative empirical or theoretical studies.
• Review Articles: Comprehensive syntheses of emerging trends and state-of-the-art technologies.
• Short Communications: Rapid-turnaround papers highlighting breakthroughs or significant preliminary findings.
• Case Studies: Real-world implementations and field evaluations of engineering systems.
• Technical Notes: Innovations in tools, software packages, or specialized algorithms.
• Concept Papers: High-level frameworks, new methodologies, or theoretical paradigms.
• Conference Proceedings: Selected, peer-reviewed collections from premier international workshops and symposia.
• Book Reviews: Critical evaluations of newly published literature in relevant technical fields.