Bioelectronic Applications of RF and Microwaves
Prof. Giovanni Crupi, University of Messina, Italy
Prof. Vincenzo Stornelli, University of L’Aquila, Italy
Bioelectronics is an interdisciplinary field that integrates electronics and life sciences for the benefit of mankind. The origin of the bioelectronics can be dated back to the experiments of the Italian anatomist and physician Luigi Galvani in the second half of the 18th century. Throughout the years, bioelectronics has greatly evolved and nowadays is experiencing a tremendous growth, driven by an explosive proliferation of bioelectronic applications, among which the implantable cardiac pacemaker can be cited as the classical example. In this dynamic and exciting scenario, the continuous progress in RF and microwave engineering plays a key role in enabling the everlasting growth of bioelectronic applications. This is because the amazing features of the high-frequency technologies allow opening new frontiers in the development of the bioelectronics. The objective of this special session is, therefore, to provide a platform to present and discuss recent advancements in the characterization, modeling, and design of RF and microwave devices, circuits, and systems oriented to bioelectronic applications, going from diagnostic to therapeutic purposes.
Call for papers
Advanced Sensor Technologies in Biomedical Applications and Healthcare
Prof. Zlatica Marinković, University of Niš, Serbia
Prof. Nicola Donato, University of Messina, Italy
In recent years, sensors have seen a growing interest and a high development in terms of variety of application fields and associated services, due to their employment either as single devices or as sensor arrays in conjunction with embedded systems. In this context, several sensors and sensor based systems typologies can be employed with the aim to fulfill the new requirements coming from biomedical and health care are applications. With the aim of contributing to this research field, this special session is intended to be a platform for meeting and discussing about the state-of-the-art, the new challenges and new technologies concerning these sensors and the related functioning mechanisms. Particular attention will be paid to resonant sensors and their use up to microwave ranges. However, papers regarding the use of sensors in complex systems aimed at health monitoring and non-invasive diagnostics will also be warmly welcome.
Call for papers
IoT Applications, State-of-the-Art and Beyond
Prof. Dejan Drajic, University of Belgrade, Serbia
We live in a world of constant development and changes where innovative technologies like IoT, sensing technologies and wireless sensors networks, 5G and beyond, UAV, machine learning, advanced data analytics will fundamentally redefine the world as we know. All these new technologies, have an important role in creating IoT solutions that reduce costs, improve the quality of services delivered to inhabitants and overall quality of life of people, thus, making world safer and more efficient place for living. Areas where IoT applications and solutions can have significant impact are numerous, like smart cities (energy efficiency, citizens’ services, environment monitoring, smart waste, smart traffic), agriculture (food production optimization and high quality food production), industry/manufacturing, transportation/mobility, retail, supply chain, buildings, healthcare, maritime monitoring, etc. On the other hand, these technologies need vast amounts of data to function properly and these data need to be gathered, stored, protected, analyzed and used to create value for social, business, environment, and many other aspects of living.
This special session aims to join the efforts of researchers, experts, technology providers and technology users to discuss and present the latest research findings on development and demonstration of applications based on sensors, sensor networks, emerging sensors and IoT technologies.
Call for papers:
Stochastic Electromagnetic Fields
Prof. Johannes Russer, Technical University of Munich, Germany
Prof. Yury Kuznetsov, Moscow Aviation Institute, Russian Federation
Stochastic electromagnetic fields play an important role in wireless communications, electromagnetic interference and electromagnetic metrology. Accurate characterization and modeling techniques for stochastic electromagnetic fields are essential to evaluate electromagnetic compatibility and system integrity in electronic product design. Correlation analysis of EM fields and pertaining signals is also crucial in electromagnetic imaging and radar sensing. Uncertainties in geometrical properties or variation of the dielectric properties of environmental structures or devices under test themselves determine solutions of the electromagnetic field. This session is dedicated to analytical and numerical techniques which address statistical variations in either the field quantities themselves or in the geometry of the environmental electromagnetic structures. Modeling and analysis techniques for electromagnetic field problems are considered pertaining to topical areas such as:
• Stochastic electromagnetic fields
• Modeling of parameter uncertainties
• Stationary and/or cyclostationary noisy fields
Methods based on correlation analysis and statistical properties of the field, the field sources or the boundary conditions are of interest. This includes analysis techniques for electromagnetic field modeling in electromagnetic interference and compatibility assessment, in wireless communication, and sensing and imaging problems. Techniques for scenarios with consideration of classical electromagnetic fields as well as for quantized electromagnetic fields are of interest.
Call for papers:
Special CEEPUS Session: Modeling, simulation, computer-aided design and management for advanced communication systems
Prof. Vera Marković, University of Niš, Serbia
Prof. Galia Marinova , Technical University – Sofia, Bulgaria
The goal of the special session is to bring together researchers from the domain of modeling, simulation, computer-aided design and management for advanced communication systems. The topics of the session are, but not limited to the following:
– Modelling, simulation and optimization of communication systems
– Artificial intelligence and IoT
– Software and hardware solutions for cybersecurity
– Business models for high tech companies in ICT
– International standardization of wireless technologies safety
Deadline for paper submission: 15.06.2021
TUTORIAL: Machine-learning Techniques to Enhance High-Frequency Electroporation Treatments
Luciano Tarricone, IEEE Fellow, University of Salento, Lecce, Italy,
Microwave (MW) technologies are increasingly employed in biomedicine and healthcare. Applications such as MW ablation, MW sensors for real-time monitoring of physiological parameters and lab-on-a-chip devices, are just some examples in a wide variety of possibilities. Recently, high-frequency irreversible electroporation (H-FIRE) has been attracting more and more attention, due to its important applications in oncology. It uses pulsed electrical stimulating fields (PEFs) to induce a controlled but irreversible process of permeabilization of cell membranes, thus triggering a substantial alteration in the physiological equilibria of cells, ultimately leading to their death.
Despite its undoubted potential and the growing number of studies on this topic, several challenges still hinder a broader adoption of H-FIRE therapy. The considerable variety and complexity of the experimental settings and the limited extent of the investigations conducted so far in this field, leave an unfilled gap of knowledge that separates the achievable results from actual large-scale clinical applications. A typical H-FIRE protocol, indeed, has to be defined in terms of targeted subject (e.g., type of subject, tissue, organ, pathologies, conditions), application devices (e.g., number, shape, and placement of electrodes), pulse parameters (e.g., waveform, sequence, on-time, frequency, voltage, number of repetitions) and evaluation conditions (e.g., ablation extent, unwanted thermal damage, assessment procedure, success rate, remission rate), while even the most extensive studies in this field only explore specific subsets of those parameters.
The problem is of an impressive complexity, even though the scientific literature is rich, and the available knowledge and experience quite important. In other words, we have an important knowledge basis, not always fully exploited, and a complex problem with many variables to be optimized.
In order to tackle these challenges, ML techniques can be used to improve the effectiveness of H-FIRE experimental settings. Properly tuned, ML solutions can represent a viable preliminary evaluation for clinicians and researchers willing to narrow their trials to only the most promising experimental settings. More specifically, our aim is to benefit from the large pool of already performed H-FIRE experiments and to use it as a reliable knowledge base for evaluating and/or optimizing new H-FIRE experiments. Such an evaluation is made possible by training the adopted ML solution with the data and results of the experiments in the knowledge base. Several benefits can be achieved in this way: first, clinical trials can be reserved for only the most promising experimental configurations. Second, protocol customization can be reached by tuning ML optimization parameters, without requiring too many preliminary tests. Third, an overall increase in H-FIRE efficacy can be targeted. To our knowledge, no other research works addressing the H-FIRE domain from this perspective are available in the current scientific literature.