Aims and Scope

Transactions on Engineering and Computing Sciences aims to advance the theory and practice of engineering and the computing sciences by publishing rigorous, original research and authoritative critical reviews. The journal supports both fundamental enquiry and applied innovation, and welcomes state-of-the-art reports and critical evaluations of applications, techniques and algorithms, as well as theoretical advances. It publishes scholarship of international relevance and places no fixed restriction on the length of papers, provided the length is justified by the content.

Aim

TECS aims to serve as a bridge between fundamental research and practical innovation. It welcomes work spanning the full arc of scholarly enquiry, from mathematical foundations, formal analysis and algorithm design, through modelling, simulation and system implementation, to real-world deployment and empirical evaluation; and it particularly encourages research on emerging fields and concepts that give direction to future research and development in engineering and computing. The journal publishes both applied and basic research, covering all areas of engineering, computer science and artificial intelligence, and imposes no fixed restriction on the length of papers, provided the length is justified by the content and full details are given so that results can be reproduced.

By operating a fully open-access model, TECS ensures that its content is freely and immediately available to researchers, engineers, practitioners, educators and policymakers worldwide, maximising the reach, reproducibility and societal impact of the research it publishes.

Subject coverage

The scope of TECS is deliberately broad and multidisciplinary, encompassing the theory, methods, technologies and applications of the engineering and computing sciences and the interfaces between them. The journal considers contributions that make a clear and substantiated advance to the state of the art, whether through new theory, new techniques, new systems, or new evidence. The principal areas of coverage are set out below; the lists are indicative rather than exhaustive, and cross-disciplinary work that connects two or more of these areas is especially welcome.

Computer science and software engineering

Algorithms and data structures; theory of computation and computational complexity; programming languages, compilers and runtime systems; software engineering, software architecture and design; software testing, verification and validation; formal methods; empirical software engineering; software maintenance and evolution; DevOps and software processes; human–computer interaction and user-experience engineering; and computer graphics and visualisation.

Artificial intelligence and machine learning

Supervised, unsupervised, semi-supervised, self-supervised and reinforcement learning; deep learning architectures, including convolutional, recurrent (LSTM, GRU) and transformer models; representation learning; natural-language processing and large language models; computer vision and image processing; speech and audio processing; knowledge representation and reasoning; planning and multi-agent systems; explainable, trustworthy, fair and responsible AI; generative models; and AI safety, robustness and alignment.

Data science, data mining and knowledge discovery

Data mining and pattern recognition; clustering, classification and anomaly detection; big-data analytics and data-intensive computing; time-series analysis and forecasting (including statistical and machine-learning approaches such as ARIMA and deep sequence models); recommender systems; information retrieval and search; data engineering and data quality; and applied analytics for scientific, industrial, economic and social problems.

Computational intelligence and soft computing

Fuzzy systems, fuzzy logic and fuzzy control; evolutionary computation and genetic algorithms; swarm intelligence; neural and neuro-fuzzy systems; metaheuristics; hybrid intelligent systems; and cognitive computing and cognitive science as they relate to computational modelling.

Intelligent systems, robotics and autonomous systems

Robotics research, perception, planning and control; autonomous vehicles and unmanned systems; human–robot interaction; mechatronics; motion planning and navigation; and intelligent control systems.

Embedded systems, cyber-physical systems and the Internet of Things

Embedded and real-time systems; system-on-chip and hardware/software co-design; cyber-physical systems; the Internet of Things (IoT) and industrial IoT; sensor networks and edge intelligence; and IoT data management, privacy and security.

Networks, distributed systems, cloud and high-performance computing

Computer and communication networks; wireless, mobile and industrial networks; cloud, edge and fog computing; distributed and parallel computing; high-performance and scientific computing; service-oriented and microservice architectures; blockchain and distributed-ledger technologies; and network performance, reliability and management.

Cybersecurity, privacy and trust

Information and network security; cryptography and applied cryptography; privacy-enhancing technologies; secure and dependable systems; intrusion detection and threat intelligence; software and hardware security; digital forensics; and security and privacy for IoT, cloud and AI systems.

Databases, information systems and web computing

Database systems and management; query processing and optimisation; data warehousing; information retrieval; semantic web and knowledge graphs; web and internet computing; and enterprise and management information systems.

Electrical, electronic and communication engineering

Electrical and electronic engineering; circuits and systems; signal and image processing; communication theory and systems; antennas and propagation; power systems, power electronics and renewable-energy integration; instrumentation and measurement; and control engineering.

Mechanical, civil, chemical and industrial engineering

Mechanical engineering, design and manufacturing; thermofluids and energy systems; materials and structural engineering; civil and construction engineering; chemical and process engineering; industrial and systems engineering; manufacturing systems and Industry 4.0; reliability, maintenance and quality engineering; and engineering management and management sciences.

Mathematical modelling, optimisation and computational methods

Mathematical and statistical modelling; numerical methods and scientific computing; optimisation (continuous, discrete, combinatorial and multi-objective); operations research; simulation and system dynamics; and decision-support and computational methods applied to engineering and computing problems.

Applied, interdisciplinary and geospatial computing

Engineering informatics; geographical information systems (GIS) and global navigation satellite systems (GNSS); computational science and engineering; digital twins; and the application of computing and engineering to industry, business, transport and logistics, healthcare, energy, the environment, smart cities and society — including digital transformation, technology management and the socio-technical dimensions of engineering and computing innovation.

Interdisciplinary research

TECS welcomes interdisciplinary work in which an engineering or computing question and contribution are central, including research that connects computing and engineering with the mathematical, physical, environmental, biomedical, economic and social domains in which they are applied. Authors should make clear how their work contributes to the relevant engineering or computing literature.

Research approaches

The journal considers algorithmic and theoretical contributions with rigorous analysis; empirical and experimental studies with reproducible evaluation; system and application design and implementation; modelling, simulation and optimisation; data-driven and machine-learning studies; and systematic or structured reviews and surveys, together with other rigorous approaches appropriate to engineering and computing.

What we look for

A strong submission normally demonstrates a clearly defined research problem or objective; a convincing account of its originality and significance relative to existing work; appropriate engagement with the relevant literature; a sound and transparent method, design or analysis, reported in enough detail to allow evaluation and, where relevant, reproduction; results and claims fully supported by the evidence, including appropriate baselines and evaluation; acknowledgement of limitations; compliance with applicable ethical and integrity requirements; and relevance to the journal’s international readership.

Work that may fall outside scope

A manuscript may be declined before external review where it has no substantial engineering or computing contribution; is a routine or incremental application without novelty or generalisable insight; lacks an identifiable research problem; does not engage adequately with the state of the art; makes claims unsupported by its methods, evaluation or data; falls below basic methodological or reproducibility standards; substantially duplicates prior work; or does not meet the journal’s ethical or submission requirements. Work whose primary contribution lies wholly outside engineering and computing is normally out of scope. Authors uncertain about suitability are welcome to contact the Editorial Office before submitting.