Consulta las condiciones de publicación y los listados de títulos de los diferentes Acuerdos vigentes en la UBU para publicar en acceso abierto.
Elsevier
Expert Systems With Applications
Expert Systems With Applications is a refereed international journal whose focus is on exchanging information relating to expert and intelligent systems applied in industry, government, and universities worldwide. The thrust of the journal is to publish papers dealing with the design, development, testing, implementation, and/or management of expert and intelligent systems, and also to provide practical guidelines in the development and management of these systems. The journal will publish papers in expert and intelligent systems technology and application in the areas of, but not limited to: finance, accounting, engineering, marketing, auditing, law, procurement and contracting, project management, risk assessment, information management, information retrieval, crisis management, stock trading, strategic management, network management, telecommunications, space education, intelligent front ends, intelligent database management systems, medicine, chemistry, human resources management, human capital, business, production management, archaeology, economics, energy, and defense. Papers in multi-agent systems, knowledge management, neural networks, knowledge discovery, data and text mining, multimedia mining, and genetic algorithms will also be published in the journal.
International Journal of Human - Computer Studies
The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities.
Research areas relevant to the journal include, but are not limited to:
- Innovative interaction techniques
- Multimodal interaction
- Speech interaction
- Graphic interaction
- Natural language interaction
- Interaction in mobile and embedded systems
- Interface design and evaluation methodologies
- Design and evaluation of innovative interactive systems
- User interface prototyping and management systems
- Ubiquitous computing
- Wearable computers... and
- Human-Computer Interaction theory - e.g. user models, cognitive systems
Springer
International Journal of Intelligent Robotics and Applications
The International Journal of Intelligent Robotics and Applications (IJIRA) fosters the dissemination of new discoveries and novel technologies that advance developments in robotics and their broad applications. This journal provides a publication and communication platform for all robotics topics, from the theoretical fundamentals and technological advances to various applications including manufacturing, space vehicles, biomedical systems and automobiles, data-storage devices, healthcare systems, home appliances, and intelligent highways. IJIRA welcomes contributions from researchers, professionals and industrial practitioners. It publishes original, high-quality and previously unpublished research papers, brief reports, and critical reviews. Specific areas of interest include, but are not limited to:
- Advanced actuators and sensors
- Collective and social robots
- Computing, communication and control
- Design, modeling and prototyping
- Human and robot interaction
- Machine learning and intelligence
- Mobile robots and intelligent autonomous systems
- Multi-sensor fusion and perception
- Planning, navigation and localization
- Robot intelligence, learning and linguistics
- Robotic vision, recognition and reconstruction
- Bio-mechatronics and robotics
- Cloud and Swarm robotics
- Cognitive and neuro robotics
- Exploration and security robotics
- Healthcare, medical and assistive robotics
- Robotics for intelligent manufacturing
- Service, social and entertainment robotics
- Space and underwater robots
- Novel and emerging applications
Digital Society
Digital Society publishes research and policy documentation on fair, responsible, and sustainable design, governance, and regulation of the digital transformation. We are interested in interdisciplinary research on topics such as cybersecurity and digital conflicts; digital sovereignty; e-citizenship, e-democracy, and e-governance; e-commerce; e-health and digital well-being; the environmental impact of digital technologies; ethnographic and anthropological studies about digital cultures; the gig-economy; new forms of mobility; online education and training; the political impact of social platforms; privacy and data protection regulations; and the development of smart cities. Given the rapid pace characterising digital innovation, this list is only indicative.
The journal publishes research articles of different types, often in collections edited by topic specialists, as well as commentaries and brief communications, or review papers critically engaging with best practices and policies relevant to its scope. The journal particularly welcomes rigorous investigations, evaluations, and recommendations concerning the ethical, legal, policy, and social aspects of the impact of digital technologies on society. It supports theoretical analyses, qualitative and quantitative methods, and any intellectual approach, disciplinary tradition, school of thought, and cultural perspective that are respectful of good scholarship standards, sharable empirical evidence, and cogent arguments.
Journal of Reliable Intelligent Environments
“Intelligent Environments (IEs)” is growing fast as a multi-disciplinary field allowing many areas of research to have a real beneficial influence in our society. The basic idea behind these systems is that by enriching an environment with technology (sensors, processors, actuators, information terminals, and other devices interconnected through a network), a system can be built such that based on the real-time information gathered and the historical data accumulated, decisions can be taken to benefit the users of that environment.
Expected benefits of this technology can be: (a) increasing safety (e.g., by monitoring lifestyle patterns or the latest activities and providing assistance when a possibly harmful situation is developing), (b) comfort (e.g., by adjusting temperature automatically), and (c) economy (e.g., controlling the use of lights).
The Journal on Reliable Intelligent Environments focuses on theoretical developments and lessons learnt on the deployment of IEs. The broad areas represented in the journal reflect the fact that reliability of software systems is the result of a number of approaches combined so an overarching principle of our publication will be to be open and flexible to embrace all type of techniques which can increase confidence in Intelligent Environments systems.
Wiley
Computer Applications in Engineering Education
Computer Applications in Engineering Education provides a forum for publishing peer-reviewed timely information on the innovative uses of computers, Internet, and software tools in engineering education. Besides new courses and software tools, the CAE journal covers areas that support the integration of technology-based modules in the engineering curriculum and promotes discussion of the assessment and dissemination issues associated with these new implementation methods.Both contributed and review articles are welcomed for consideration and possible publication in CAE.
The journal publishes research articles in the following areas:
- New software tools and multimedia modules for engineering education
- Development and implementation experiences of Internet and web-based courses
- Artificial Intelligence and Data Analytics for Improving Teaching and Learning Performance
- Use of gamification theory and algorithms in engineering education
- Technology role in globalization of engineering education
- New software tools for virtual and real laboratory development
- Distance learning and use of technology-based tools in classroom teaching
- Visualization, computer graphics, social networking tools, and I/O issues
- K-12 STEM topics and impact on engineering education
- Gender disparity in STEM education and engineering careers
- Effective industry engagement in engineering education
- Use of portable technologies, social media, and participatory digital culture in engineering education
Computational Intelligence
This leading international journal promotes and stimulates research in the field of artificial intelligence (AI). Covering a wide range of issues - from the tools and languages of AI to its philosophical implications - Computational Intelligence provides a vigorous forum for the publication of both experimental and theoretical research, as well as surveys and impact studies. The journal is designed to meet the needs of a wide range of AI workers in academic and industrial research.
Please see the Aims and Scope to learn about the focal topics in Computational Intelligence.
Aims and Scope
FOCAL TOPICS OF COMPUTATIONAL INTELLIGENCE
Discovery science and knowledge mining. Discovery science (also known as discovery-based science) is a scientific methodology which emphasizes analysis of large volumes of experimental data or text data with the goal of finding new patterns or correlations, leading to hypothesis formation and other scientific methodologies. Tools of interest include: Data Mining: looking for associations or relationships in operational or transactional data; Text Mining and Information Extraction: looking for concepts and their associations or relationships in natural language text; Structured, semi-structured and unstructured text mining; Text Summarization: extracting terms and phrases from large text document collections that summarize their content; Web mining: Web structure, content and usage mining; and, Ontology Learning from Text and Data bases.
Web intelligence and semantic web. Web intelligence is concerned with the application of AI to the next generation of web systems, services and resources. These include better search/retrieval algorithms, client side systems (e.g. more effective agents) and server side systems (e.g. effective ways to present material on web pages and throughout web sites, including adaptive websites and personalized interfaces).
The semantic web is an extension to the World Wide Web, in which web content is expressed in a form that is accessible to programs (software agents), following the vision of the web as universal medium for data, information and knowledge exchange.
Agents and multiagent systems. Agents as a computational abstraction have replaced 'objects' in software and have provided the necessary ingredients to move to societies of interacting intelligent entities, based on concepts like agent societies, market economies, e-commerce models and game theory. Such abstractions are dispersed throughout the scientific world, depending largely on applications. Multiagent systems (MAS) are systems in which many autonomous intelligent agents interact with each other. Agents can be either cooperative, pursuing a common goal, or selfish, going after their own interests. Architectures, interaction protocols and languages must be developed for multiagent systems. Topics of interest include: Autonomy-oriented computing; Agent systems methodology and language; Agent-based simulation and modeling; Agent-based applications; Agent-based negotiation and autonomous auction; Advanced Software Engineering supports for Multiagent systems; Trust in Agent Society; and Distributed problem solving.
Machine learning in knowledge-based systems. Knowledge-based systems aim to make expertise available for decision making, and information sharing, when and where needed. The next generation of such systems needs to tap into large domain-specific knowledge, which combine machine learning and structured background knowledge representation, such as ontology, and causal representations and constraint reasoning. Information sharing is concerned with creating collaborative knowledge environments for sharing and disseminating information. Learning is based on real-world data. Key challenges involve the decomposition of practical problems into multiple learnable components, the interaction between the components, and the application of suitable learning algorithms, often in the absence of adequate amounts of labeled training data. Topics of interest include the application of machine learning methods to new practical problems introducing novel algorithms, system frameworks of learnable components or evaluation techniques.
Key application areas of AI. We aim to make the journal the focus of key application areas, where AI is making a significant impact, but lack a coherent publication venue. These include: Business Intelligence, i.e. data mining to support business decision makers; Social Network mining, e.g. modelling aggregate properties and dynamics of social networks, classifying vertices and edges of social networks, identifying clusters of users; Critical Infrastructure Protection, e.g. intrusion/anomaly detection & response, learning knowledge bases of system administration, log file mining); Entertainment and Game Development, i.e. building game engines using AI techniques; Software Engineering, including program understanding, software repositories and reverse engineering; Business, Finance, Commerce and Economics: learning aggregate behaviours (e.g. stock market trends) or modeling individual and group demographics (e.g. web mining); and Knowledge-based and Personalized User Interfaces, to make interaction clearer to the user and more efficient, with better support for the users' goals, and efficient presentation of complex information.
Please note that submissions that are straightforward applications to Machine Learning or other AI techniques to new tasks or new domains will be rejected without review unless they bring novelty in other aspects, such as significance and analysis of the results, explanations of why some methods work better than others in these domains, or other relevant insights.
