Accepted Special Sessions

Conditions

Organizers of Special Sessions are responsible for:

Select a topic of interest to conference delegates.
Obtain papers on this topic, normally at least 5 for an invited special session, but often more. At least 60% of the papers must be by authors who are neither session chairs from their team nor reviewers for the session.
If there are short papers, the final accepted papers will be moved to the general track.
Manage the review process for these papers on due time and deadlines.
Provide suitable reviewers for the reviews of the papers.
Ensure the final versions of the papers are uploaded before the deadline.
Attend the conference and chair the session.
Provide a list of international reviewers (name, affiliation, country) who have already accepted to review the papers.
Disseminate a call for papers for the special session widely.

———————————————————————————————————————-

Special Session 1

Machine Learning and Computer Vision in Industry 4.0 (MLCVI)

Enrique Dominguez – University of Malaga, Spain.
Jose Garcia Rodriguez – University of Alicante, Spain.
Ramon Moreno Jiménez – Grupo Antolin, Spain.

Scope:
In the coming years, the use of machine learning and computer vision in industry will become a trend that affects not only large corporations but also small and medium-sized businesses. Thanks to these technologies, innovation in the industrial sector is giving rise to “smart factories,” which allow them to obtain multiple advantages.
This special session tries to provide a common platform for academics, developers, and industry-related researchers to discuss, share experiences, and explore new technological advances. The objective is to integrate an international scientific community working on industrial applications of machine learning and computer vision for fruitful discussions and ideas on the evolution of these technologies. Topics:

Computational intelligence
Machine learning
Deep learning
Self-organization and self-adaptation
Computer vision
Video and image processing
Biometric features extraction
Pattern recognition
Surveillance systems
Hardware implementations
Smart Manufacturing
Autonomous vehicles/machines
Quality control
Demand prediction
Data visualization

———————————————————————————————————————-

Special Session 2

Time Series Forecasting in Industrial and Environmental Applications (TSF)

José F. Torres – Pablo de Olavide University of Seville, Spain.
Federico Divina – Pablo de Olavide University of Seville, Spain.
Mario Giacobini – University of Torino, Italy.
Julio César Mello Román – Universidad Nacional de Asunción, Facultad Politécnica, Paraguay.
Miguel García Torres – Pablo de Olavide University of Seville, Spain.
Andrés Manuel Chacón Maldonado. Pablo de Olavide University of Seville (Spain).

Scope:
Time series can be found in almost all disciplines nowadays. Thus, time series forecasting is becoming a consolidated discipline that provides meaningful information in a wide variety of application areas, turning their efficient analysis into the utmost relevance for the scientific community. This session pays attention to the extraction of useful knowledge from time series in the context of industrial and environmental applications. Given its relevance in the emergent context of big data, the analysis of very large time series is also encouraged. Topics of interest for the special session, always in the context of industrial and environmental applications, include but are not limited to:

Machine learning applied to time series forecasting.
Deep learning applied to time series forecasting.
New approaches for big data time series forecasting.
Hybrid systems for time series analysis.
Ensemble approaches for time series analysis.

———————————————————————————————————————-

Special Session 3

Efficiency and Explainability in Machine Learning and Soft Computing (EEMLSC)

María del Mar Martínez Ballesteros – University of Seville, Spain.
Manuel Jesús Jiménez Navarro – University of Seville, Spain.
Manuel Carranza García – University of Seville, Spain.
Belén Vega Márquez – University of Seville, Spain.
José María Luna Romera – University of Seville, Spain.
Ángela R. Troncoso García – Pablo de Olavide University, Spain.

Scope:
Explainable Artificial Intelligence (AI) is currently the focus of AI research, enabling humans to understand and trust the decision-making of this technology. Although traditional machine learning models have been considered black boxes, new techniques have been developed to extract knowledge from them locally and globally. However, AI has a significant carbon footprint, which is where Green AI comes in. Green AI uses algorithms that promote inclusivity and environmental friendliness, and the key is to balance the amount of data, time, and iterations necessary to train a model. Considering its ecological impact, it is crucial to consider the energy cost and carbon footprint from the beginning and decide how critical it is to create or improve a model. This session aims to address two main topics. Firstly, new methodologies should be proposed, and existing explainable/interpretable AI techniques should be applied to machine learning and soft computing models. Secondly, to improve the efficiency of Machine Learning and Soft Computing models without compromising their effectiveness. In addition, the special session will cover assorted topics related to industrial and environmental applications, such as but not limited to:

Applications of existing explainable AI methods.
Efficient or explainable methods for black box models.
Preprocessing techniques for efficiency improvement and explainability support.
Novel Global and Local model-agnostic methods.
Novel example-based explanations.
Hardware/software design for energy-efficient models/explanations.
Create human-friendly explanations and tools for non-technical users.
Other relevant topics and applications related to efficiency and explainability in Machine learning and Soft Computing models, such as but not limited to: Blackbox models, Parallel computing, Federal learning, Decision support systems, Social impact, Health, Risk factors, Artificial vision, Natural language processing, Time series, Tabular data.

———————————————————————————————————————-

Special Session 4

Intelligent Models and Frameworks for Smart Agriculture and Green Economy (IMFSAGE)

Jose Barata – UNINOVA, Portugal
Oliviu Matei – HOLISUN, Romania
Petrica Pop – Technical University of Cluj-Napoca, Romania

Scope:
This special session is focused on various sustainable methods in the green economy and new technologies and methodologies for enhancing agricultural production.

High-quality research contributions describing original and unpublished results of conceptual, constructive, empirical, experimental, or theoretical work covering all the aspects of tools and techniques for Smart Agriculture and Green Economy are cordially invited for presentation at the conference. The topics relevant to this special session include but are not limited to:

Artificial Intelligence/Machine Learning
Automation and Mechanization
Big Data, Data Mining, Data Management and Analytics
Cyber-Physical Systems and IoT
Climate-neutral governance
Green economy, sustainability, innovation
Precision agriculture
Precision irrigation
Security and Blockchain
Smart agriculture
Smart campus and digital twins
Smart mobility and infrastructure
Smart sustainable buildings
Supply chain management
Sustainable energy and environment
Sustainable transport
Remote Sensing and Aerial Imaging
Renewable energy
Water management
Waste management

———————————————————————————————————————-

Special Session 5

Quantum Computing (QUANTUM)

David Gutiérrez-Avilés – University of Seville, Spain.
José Francisco Chicano García – University of Málaga, Spain.
Alicia Troncoso – Pablo de Olavide University, Spain.
Francisco Martínez-Álvarez – Pablo de Olavide University, Spain.

Scope:

We are pleased to announce a special session on Quantum Computing as part of the SOCO 2024. The rapid advancement of quantum technologies has sparked significant interest and innovation in the field of quantum computing, promising groundbreaking applications across various domains. This special session aims to bring together researchers, practitioners, and enthusiasts from academia and industry to discuss the latest developments, challenges, and opportunities in quantum computing. We invite researchers and practitioners to submit high-quality papers presenting original research, case studies, and innovative applications related to quantum computing. Topics of interest for this special session include (but are not limited to:

Quantum algorithms and applications
Quantum programming languages and software tools
Quantum simulation and optimization
Hybrid quantum-classical computing
Quantum machine learning and optimization
Quantum networking and communication protocols
Ethical and societal implications of quantum computing

———————————————————————————————————————-

Special Session 6

Soft Computing in Civil Engineering and Environment (SCCEE)

Marijana Hadzima-Nyarko – University of Osijek, Croatia.
Francisco Martínez-Álvarez – Pablo de Olavide University, Seville, Spain
Dorin Radu – Transilvania University of Brașov, Romania
Borko Bulajić – University of Novi Sad, Serbia
Emmanuel Karlo Nyarko – University of Osijek, Croatia

Scope:

We are delighted to announce a special session on Soft Computing in Environmental and Civil Engineering, to be held as part of SOCO 2024, organized under the umbrella of the IM4StEM project (https://im4stem.eu/en/home/). This special session aims to explore the transformative potential of soft computing techniques, including neural networks, fuzzy logic, and genetic algorithms, in addressing the complex challenges faced by the environmental and civil engineering communities.

Environmental and civil engineering are integral disciplines that collaborate to develop sustainable solutions and mitigate the environmental impacts of infrastructure development. With increasing concerns about environmental sustainability, civil engineers are tasked with incorporating environmentally friendly practices into their designs, including the use of energy-efficient technologies and materials and minimizing the environmental footprint of infrastructure projects.

This special session provides a platform for researchers and practitioners to present and discuss the latest advancements, methodologies, and applications of soft computing in environmental and civil engineering. We invite submissions of original research papers, case studies, and innovative applications that contribute to the advancement of soft computing techniques in addressing environmental and civil engineering challenges.

Topics of interest for this special session include (but are not limited to):

Soft computing methods for time series analysis in civil engineering applications.
Environmental monitoring and management using soft computing techniques.
Structural health monitoring and predictive maintenance.
Optimization in construction project planning and management.
Real-time sensor data analysis for construction monitoring.

———————————————————————————————————————-

Special Session 7

Soft Computing Methods in Manufacturing and Management Systems (SCMMMS)

Damian Krenczyk – Silesian University of Technology, Poland
Anna Burduk – Wroclaw University of Science and Technology, Poland
Bożena Skołud – Silesian University of Technology, Poland
Marek Placzek – Silesian University of Technology, Poland

Scope:

Management of manufacturing systems involves the development of detailed solutions related to decision-making and problem-solving processes. There are many important decisions to be taken and high complexity problems to solve (NP-hard), related to e.g. processes organization, planning and control of manufacturing systems. Special attention is paid to inexact solutions for which no known algorithm can obtain an exact solution in polynomial time. Research into new production management methods is also driven by the need to increase the autonomy and flexibility of production systems. The answer to these needs is production focused on cyber-physical systems, which are one of the paradigms of the Industry 4.0 concept. The aim of this session is to present the results of research related to the management of production systems. Taking into account the complexity of problems related to production management, soft computing and intelligent methods may deliver the most adequate answers.

Topics of interest for this special session include (but are not limited to):

Manufacturing Systems Integration
Optimization of Manufacturing Systems
Modeling and Design
Control and Supervision
Industry 4.0
Production Planning and Scheduling
Virtual Organisation
Data Mining and Data Recognition
Production System Organization
Production Management
Discrete Optimization
Line Balancing
Parallel Algorithms
Artificial Intelligence

———————————————————————————————————————-

Special Session 8

Computational Intelligence Applied to Modelling and Control of Engineering Systems (CIAMCES)

J. Enrique Sierra García – University of Burgos, Spain
Matilde Santos Peñas – Complutense University of Madrid, Spain
Fares M’zoughi – University of the Basque Country, Spain
Payam Aboutalebi – University of the Basque Country, Spain
Zennir Youcef, University of 20 August 1955 Skikda, Algeria

Scope:

The hybridization of techniques is very often the only solution to complex modeling and control problems. This approach allows the splitting of the problem goals and the use of different techniques to address each part. In the modeling field, parametric and other classic techniques provide simple and fast models, but their accuracy may not be enough. On the other hand, methods based on artificial intelligence, such as deep-learning-based ones, generate models that better fit the real behavior of the system but can be very demanding in terms of computational requirements. Hybridization of computational intelligence techniques allows exploiting the best of both worlds, providing more accurate models with less computational complexity.

The aim of this special session is to provide a platform for researchers, engineers, and industrial professionals from different fields to share and exchange their innovative ideas, research results, and experiences in the hybridization of techniques applied to the modeling and control of engineering systems. Contributions to this special session are welcome to present and discuss novel methods, algorithms, control techniques, frameworks, architectures, platforms, and applications.

Topics of interest for this special session include, but are not limited to, the following strategies and approaches applied to the hybridization of model and control techniques: :

Modeling and identification by classic techniques combined with soft computing techniques: physics-informed neural networks, linear identification techniques combined with artificial techniques, probabilistic techniques combined with neural networks, etc.
Hybridization of classic and intelligent control techniques: fuzzy control, neuro-control, neuro-fuzzy, intelligent-PID control, etc.
Hybrid learning systems: reinforcement learning, machine learning, and deep learning applications combined with other techniques.
A combination of heuristic techniques and classical optimization techniques