Fees: (Include participation in the conference and publication in the Proceedings plus 2 Coffee-breaks per day, Welcome Cocktail and Dinner)

      Early Registration: 480 EUR (until October 22, 2024)
      Late Registration: 530 EUR (after October 22, 2024)
      On-Site Registration: 620 EUR
      Additional Articles in the Proceedings (more than 1): 150 EUR

  Papers' withdrawals are not allowed after November 1, 2024.

The ELECS 2024 is a face-to-face (in person) conference.
Review Process:
All submitted papers will undergo a peer review process coordinated by the General Chairmen and one Associate Editor. Authors are notified of acceptance when the Conference receives the comments and the recommendation of at least 3 qualified reviewers. Reviewers cannot come from the same country with the authors and cannot have previous collaboration with the authors of the papers.

So, the Conference sends each paper to 3-5 independent reviewers, experts in the area of the paper.
So, each paper will be evaluated, at least, by three independent experts according to the following Criteria

1) Relevance to the Conference Topics
2) Scientific - Technical Originality, Potential Impact and Interest for the audience
3) Scientific/Technical Content and Advances beyond The State-Of-The-Art
4) Quality of the Presentation, clarity of the Content
5) Comments for the authors

The reviewers are going to indicate their familiarity with the paper's subject, evaluate the paper along the aforementioned criteria. Finally, the Editor-in-Chief or a Member of the Editorial Board will decide whether a paper will be accepted or not. Our Score System will classify the papers as follows:
* Publish as it is
* Consider after Minor Changes
* Consider after Major Changes
* Reject
If the Editor recommends "Publish as it is", then the manuscript will undergo a final check by the conference's editorial office in order to ensure that the manuscript and its review process adhere to the conference's guidelines and policies. Once this is done, the authors will be notified of the manuscript's acceptance, and the manuscript will appear in the Articles in Press section of the conference's website.
If the Editor recommends "Consider after Minor Changes," the authors are notified to prepare and submit a final copy of their manuscript with the required minor changes suggested by the reviewers. The Editor reviews the revised manuscript after the minor changes have been made by the authors. Once the Editor is satisfied with the final manuscript, the manuscript can be accepted.
If the Editor recommends "Consider after Major Changes," the recommendation is communicated to the authors. The authors are expected to revise their manuscripts in accordance with the changes recommended by the reviewers and to submit their revised manuscript in a timely manner. Once the revised manuscript is submitted, the Editor can then make an editorial recommendation which can be "Publish Unaltered", "Consider after Minor Changes", "Reject."
If the Editor recommends rejecting the manuscript, the rejection is immediate. Also, if the majority of the reviewers recommend rejecting the manuscript, the rejection is immediate.

Review Criteria:
Is this paper appropriate for the conference?
Does the paper present original and novel research results in Computational and Applied Mathematics & Computer Science ?
Is the paper significant and convincing for the Computational and Applied Mathematics & Computer Science ?
Does the title adequately represent the content of the paper?
Does the paper bribng novel research results on numerical, computational, applied mathematics along with modern simulation and modelling techniques, computational methods Computer Science?
Is the referencing appropriate?
Is the presentation high quality?
Do the methods, data, and analysis support the conclusions?
Is the paper clearly and concisely written?
Are the interpretations and conclusions supported by the evidence presented?
Are all parts of the text, references, graphics and tables necessary for the new results and main points to be understood?
Are the conclusions and potential impacts of the paper clear?
Are the graphics and tables clear and their captions self-explanatory?

Special Sessions

1) Title: Integrated Micro-System in Medicine
Organizer-Chairman: Professor Georges Nassar
Institute of Electronic, Microelectronic & Nanotechnology, INSA (HdF), UPHF, 59300 Valenciennes, France

Today, healthcare technologies are reshaping our life and providing a more advanced, targeted and efficient service. Like some sectors that have had to evolve due to the emergence of new technologies, healthcare providers must adapt to the technological trends in their sector to be able to best guide the patient towards an optimized therapy. Indeed, smart technologies are being added to the healthcare sector at a rapid pace, bringing hope for improved treatment and effective care. This is particularly important for healthcare establishments looking for solutions to better manage admission flows and adapt care effectively. As a result, the transfer and ‘real-time’ coupled analysis of multiple physiological data becomes a necessity in order to ensure continuous information monitoring with the aim of improving performance both in diagnosis and in the choice of therapy.

- Bio-MEMS
- Network connected Sensors
- Embedded System
- Biotechnologies
- Bio-Connected Architecture
- Autonomous Diagnosis Design
- Intelligence Analysis
- Telemedical Modeling Unit
- Decision Support Programming System

2) Title: Distance Learning In The Digitalization And Artificial Intelligence Era
Assistant Professor, Department of Production Engineering and Safety. Faculty of Management, CZESTOCHOWA UNIVERSITY OF TECHNOLOGY, POLAND

E-mail: Joanna.rosak-szyrocka@wz.pcz.pl

In recent years, there has been a substantial shift in how e-learning is approached. Due to the extensive usage of e-learning, many teachers have thus far addressed the implementation of the didactic process using this method. As a result, educators have been obliged to quickly switch to educating students using platforms like Moodle. The epidemic has altered schooling forever. It was an effort on the part of both students and instructors. Teachers who are digitally aware and well qualified are needed in the epidemic crisis. Inquire about the Web 3.0 transformation project, which refers to intelligent apps employing natural language processing, machine-based learning, and reasoning. The Web has changed since the early days of the Web 3.0 transformation project. Therefore, educators should improve their knowledge and abilities in order to make the best use possible of technical equipment, E-learning tools, educational apps, and other online platforms for educational applications. Although virtual universities have been around for about ten years, there hasn't been much research done to show how much this knowledge differs from traditional knowledge acquisition in terms of quality, pedagogical methods used, and other issues. There has also been little research done on how students and teachers view teaching in terms of time, work organization, didactic needs, and personal character predispositions. Universities are being forced to change their curricula and methods of teaching as we approach the Industry 4.0 industrial revolution in order to prepare students for careers as engineers who can function in a virtual and almost totally automated world. Unquestionably, remote learning is a cutting-edge teaching technique that seamlessly integrates with the strategies used to train employees for Industry 4.0. The rapid growth of mobile digital information and communication technologies at the age of 30 indicates that a shift in how people see e-education is inevitable. Largely portable Computer devices (laptops, palmtops, and tablets), especially contemporary ones, have risen in popularity as multimedia gadgets in the media world, where modern people and businesses function. Smartphones and wireless Internet access will be commonplace in Industry 4.0, allowing human resources to be included in training programs that employ computer-stored materials and online activities. Due to this, it is crucial to start research and train future Industry 4.0 employees via distance learning. In line with the advancement of information and communication technology, e-learning has dramatically changed. Opportunities that conventional training does not provide are offered by e-learning. Mobility, flexibility, and interaction are three of this style of education most significant benefits. After the invention of the Web, e-Learning really took off, and it is continually evolving to meet new difficulties. All educational levels use this kind of instruction. The learning process, as well as that of university instructors and students, may greatly benefit from e-Learning. The aim of this special session is to discuss how education has changed, especially in times of pandemic, digitalization, AI times and what challenges universities face in ensuring the highest possible level of education. The aim of the session will also be to find out how teachers and students evaluate distance learning, what their expectations are, and what  elements require improvement. It will also be discussed whether e-learning is our future and what the main problems are with introducing such a form of education at Universities in the industry 5.0, digitalization and artificial intelligence (AI) eras.

- Distance learning
- Industry 4.0
- Industry 5.0
- Digitalization era
- E-learning in the face of demographic trends
- Web 3.0 in e-learning
- Digitalization at a university
- E-learning as a desirable form of education
- Artificial intelligence
- ChatbotFuture competences
- Smart Universities

3) Title: AI-enabled information systems
Organizer-Chairman: Dr. Mariya Evtimova
Université Paris 1 Panthéon- Sorbonne, Paris, FRANCE
E-mail: mevtimovagardair@gmail.com

The Information Systems and Technologies research using AI is invited to submit proposals for the organization of AIEIS “AI- enabled information systems” is a special session in the Electrical Engineering & Computer Science (ELECS) conference that will be held in Bern, Switzerland. December 21-23, 2024. AIEIS is a global forum for researchers and practitioners to present and discuss the most recent innovations, trends, results, experiences and concerns in the AI that is present to Information Systems and Technologies.

- Machine learning algorithms
- Questions & Answering systems
- Knowledge Reasoning
- Semantic systems
- Metadata description and metadata systems
- Ontologies and knowledge graph applications
- Data mining systems
- Natural Language Processing algorithms
- Recommender systems
- Knowledge discovery
- Intelligent Systems
- Artificial Neural Networks
- Fuzzy and probability systems
- Big Data systems
- Information processing
- Information extraction
- Data- sharing and fairness in AI
- Human-computer interaction systems
- intelligent support systems in human science
- intelligent support systems in education
- intelligent business systems

4) Title: Advanced Computational and Artificial Intelligence Methods in Smart Forestry
Organisers-Chairs: Dr. Robertas Damasevicius
Faculty of Applied Mathematics, Silesian University of Technology, Gliwice, Poland
Email: robertas.damasevicius@polsl.pl

Prof. Dr. Gintautas Mozgeris
Agriculture Academy, Faculty of Forest Sciences and Ecology, Department of Forest Sciences, Vytautas Magnus University, Akademija, Lithuania.
Email: gintautas.mozgeris@vdu.lt

Dr. Rytis Maskeliunas
Department of Multimedia Technologies, Kaunas University of Technology, 51311 Kaunas, Lithuania
Email: rytis.maskeliunas@ktu.lt

To provide a platform for researchers, practitioners, and policymakers to discuss, share, and promote the latest advancements in computational techniques and AI applications tailored for forestry. This special issue aims to shed light on the intersection of AI, data science, and the intricate dynamics of forest ecosystems, paving the way for more informed forest management, conservation, and industry practices. This conference special issue seeks to combine the collective expertise of multiple disciplines, ensuring a comprehensive perspective on the potential of AI and advanced computational techniques in revolutionizing forestry for the betterment of both humanity and the planet.

- Remote Sensing and AI: Utilization of machine learning techniques for interpreting satellite imagery, LiDAR data, and drone footage in forest monitoring and assessment.
- Predictive Modeling: Employing deep learning and other AI models to forecast forest growth, disease outbreaks, pest infestations, and the effects of climate change.
- Automated Wildlife Tracking: Leveraging AI in the identification and monitoring of wildlife populations within forested areas, using sensors, audio recordings, and cameras.
- Forest Fire Detection and Prediction: Utilizing machine learning algorithms for early detection of forest fires, prediction of fire spread, and strategizing containment.
- Sustainable Forest Management: AI-assisted tools for monitoring tree growth, calculating sustainable harvest rates, and ensuring reforestation success.
- Bioacoustic Monitoring: Using neural networks and other AI methods to interpret and catalog forest sounds, aiding in biodiversity assessments and ecosystem health monitoring.
- Timber Traceability and Supply Chain Monitoring: Implementing blockchain and AI for ensuring sustainable and transparent forestry practices.
- Smart IoT Devices in Forestry: Deployment and data interpretation from smart sensors, RFID tags, and other IoT devices for real-time forest monitoring.
- Forest Health and Disease Analysis: AI-driven diagnostic tools for detecting pathogens, diseases, and other stressors in forest ecosystems.
- AI-Driven Conservation Efforts: Strategies and applications for using AI to boost conservation efforts, including protection of endangered species and habitats.
- Virtual and Augmented Reality in Forestry Education: Innovative ways to leverage AI in producing immersive educational experiences for forestry students and professionals.
- Forest Biomimicry and AI: Learning from forest structures and processes to enhance AI algorithms and architectures.
- Data Integration and Interoperability: Challenges and solutions in merging heterogeneous datasets for comprehensive forest analyses.

5) Title: Emerging Technologies in Social Commerce
Organiser-Chairman: Prof. Dr. Achmad Nizar Hidayanto
Professor of Information Systems, Universitas Indonesia, Faculty of Computer Science, Kota Depok, Jawa Barat 16425, Indonesia
E-mail: nizar@cs.ui.ac.id

Aim: In an era where social media platforms have transformed the way businesses interact with their customers, understanding and connecting with your audience is more critical than ever before. The conference session, "Knowing Your Customer in The Age of Social Commerce," delves deep into the dynamic world of social commerce and explores strategies to unlock the power of customer insights. In today's interconnected digital landscape, consumers are not only making purchases online but also actively engaging with brands and products through social media. This special session seeks to foster a deep understanding of customer behavior, preferences, and interactions in the age of social media and e-commerce, and how they influence customers’ purchase intentions and decision-making processes.

- Navigating the Social Commerce Revolution
- Customer Profiling and Behavioral Analysis
- Personalization and Customer Experience
- Data Privacy and Ethical Considerations
- Case Studies and Success Stories
- Future Trends and Innovations
- Networking and Collaboration
- Exploration of Customer Motivations
- Impact on Purchase Intentions
- Best Practices and Strategies for understanding customer engagement

6) Title: Circuit Design, Calibration, Advances and Applications of Sensor and Data Converters
Organiser-Chairman: Prof. Dr. Hua Fan
Professor of School of Integrated Circuit Science and Engineering (Exemplary School of Microelectronics), University of Electronic Science and Technology of China, Chengdu, China
E-mail: fanhua7531@163.com

Aim: Wearable electronics are devices that can be worn or mated with human skin to pay close attention to activities of individual continuously without interrupting or limiting the motions of people and will play vital functions in future prevention-oriented healthcare monitoring systems. Most wearable sensing technologies that exist have focused on power efficiency, cost and portability. Future proactive health technologies, on the other hand, must be accurate and high-resolution if the general population is going to adopt them. In the other words, when sensor nodes are used in the body area networks for data collection, linearity and resolution are usually of much more vital importance than the power, because the amplitude of these signals is quite small. This session aims to bring together researchers, academicians and practitioners for discussion and exchange of ideas on the latest developments in high-resolution circuit design of the sensor as well as data converters, which always play an important role in the sensor microsystem.

- Navigating the Social Commerce Revolution
- Customer Profiling and Behavioral Analysis
- Personalization and Customer Experience
- Data Privacy and Ethical Considerations
- Case Studies and Success Stories
- Future Trends and Innovations
- Networking and Collaboration
- Exploration of Customer Motivations
- Impact on Purchase Intentions
- Best Practices and Strategies for understanding customer engagement

Conference Place

About Bern

How to get around in the City

Switzerland: Travel and Vacation

Conference Venue:
A1 Hotel Grauholz AG
Autobahn A1
CH-3063 Ittigen, Bern
Tel.: +41 (0)31 915 12 12
Fax.: +41 (0)31 915 12 13
Website: https://www.a1grauholz.ch

Upload your paper from here https://universitypress.org.uk/form/eecs-form/upload-form

Contact us by email:
Primary Email of Secretariat
Secondary Email of the Committee

or by Phone: 00359 88501 0581 , 00359 88 5623 888