Prof. Leopoldo Angrisani (IEEE Fellow)
University of Napoli Federico II, Italy
Speech Title: Soft Growing Sensors: a
context-aware evolution of Cyber-Physical Measurement Systems
Abstract: The fourth industrial revolution has brought a plethora of technological advancements that are transforming not only manufacturing processes but also the lives of individuals. At the core of this technological innovation is the concept of Cyber-Physical System (CPS), which combines communication and information technologies with physical processes and machinery to create highly automated and interconnected production environments.
In this framework, Measurement and Monitoring Systems (MMS) have traditionally been viewed as subordinate elements that provide a source of information for CPS without actively participating in any higher-level actions, such as decision making. However, in recent years, the suitable adoption of the 4.0 enabling technologies has resulted in a paradigm shift in this perspective. CPS and MMS are now considered as intrinsically coexisting entities, leading to the development of Cyber-Physical Measurement Systems (CPMS). They holistically integrate sensing, actuation, computation, and communication to enable highly accurate and responsive measurement and control. CPMS are capable of providing granular and detailed measurements of various phenomena, ranging from industrial machinery behavior to smart city's people and goods movement.
On these bases, in this talk, I will introduce a relevant practical evolution of CPMS, namely Soft-Growing Sensors, also stemming from a special measurement focus on soft robotics and its interaction with 4.0 technologies. By extending its body through a pneumatically-enabled eversion mechanism, inspired by the growth patterns of plants and vines, a soft-growing sensor can access and navigate constrained environments and seamlessly learn from them. This unique feature, in addition to the sensing of the environment, can assure contextual and self-awareness capabilities also through artificial intelligence solutions. These attributes are essential for making self-adapting, proactive, and reliable decisions during task execution. Consequently, this paves the way for achieving more precise measurements and reducing the uncertainty arising from challenging environmental conditions.
Leopoldo Angrisani is Full Professor of Electrical and Electronic Measurements with the Department of Information Technology and Electrical Engineering of the University of Naples Federico II, Italy. He is also Chair of the Board of the Ph.D. Program ICTH - Information and Communication Technology for Health - and General Manager/Director of CeSMA – Center of Advanced Measurement and Technology Services - of University of Naples Federico II.
His research activity is currently focused on Internet of Things and cyber-physical measurement systems; green soft-growing sensors; measurement sustainability; measurement uncertainty; measurements for Industry 4.0; communication systems and networks test and measurement.
He was and is currently involved in many industrial research projects, in cooperation with small, medium and great enterprises, for which he played and is currently playing the role of scientific coordinator. He is currently the Coordinator of the Technical/Scientific Committee of MedITech – one of the eight Italian Competence Centers on I4.0 enabling technologies.
He is Fellow Member of the IEEE Instrumentation and Measurement and Communications Societies, Chair of the IEEE Instrumentation & Measurement Society Italy Chapter, Honorary Chairman of the first (M&N 2019) and second (M&N 2022) edition of the IEEE International Symposium on Measurements & Networking, General Chairman of the second edition (MetroInd4.0&IoT 2019) of the IEEE International Workshop on Metrology for Industry 4.0 and IoT, and General Chairman of the first edition (IEEE MeAVeAS 2023) of the IEEE International Workshop on Measurements and Applications in Veterinary and Animal Sciences. He is vice-chair of the Italian Association “GMEE-Electrical and Electronic Measurements Group”, and corresponding member of the Accademia Pontaniana in Naples, the oldest Italian academy, with almost 600 years of history, which has always brought together renowned Neapolitan scholars.
In 2009, he was awarded the IET Communications Premium for the paper entitled “Performance measurement of IEEE 802.11b-based networks affected by narrowband interference through cross-layer measurements” (published in IET Communications, vol. 2, No. 1, January 2008).
The IEEE Instrumentation & Measurement Society Italy Chapter, which he has been chairing since 2015, was awarded in 2016 the prestigious recognition “I&M Society Best Chapter Award” by the IEEE Instrumentation & Measurement Society, in 2017 the prestigious recognition “Most Improved Membership Chapter for 2016” by the IEEE Italy Section, in 2018 the prestigious recognition “Most Innovative Chapter 2018” by the IEEE Italy Section, and in 2021 the prestigious recognition "Chapter of the Year 2021" by the IEEE Region 8 (Europe, Middle Est, Africa).
In 2021, he was awarded the prestigious recognition “2021 IEEE Instrumentation and Measurement Society Technical Award” with the following citation “For contributions in the advancement of innovative methods and techniques for communication systems test and measurement”.
Prof. Hesham H. Ali
University of Nebraska Omaha, USA
Speech Title: Exciting Recent Results
in Big Data Analytics using Complex Networks and Population Analysis
Abstract: We live in data-rich societies. The availability of all types of data in many application domains continues to grow, and data collection mechanisms continue to expand in number and sophistication. In such scenario, researchers who try to mine knowledge from the available data continue to play the catchup game and struggle to get the most out of the raw data. It may be argued that extracting useful, and in some cases critical, knowledge from the available raw data can be considered as the single most outstanding research problem of our generation. Developing innovative data integration and mining techniques along with clever computational methods to implement them will be critical in addressing such problem and taking advantage of the many associated opportunities. This talk demonstrates how graph modeling and population analysis can be used to model heterogenous data and solve complex problems in various applications. Exciting recent results from three case studies are presented to validate this claim and show how using graphs/networks can be applied to address major challenges in numerous scientific domains. The talk will include case studies related to critical applications domains in biomedical informatics and healthcare, wireless sensors and wearable devices, and safety of engineering infrastructures.
Hesham H. Ali is a Professor of Computer Science and the director of the University of Nebraska Omaha (UNO) Bioinformatics Core Facility. He served as the Lee and Wilma Seemann Distinguished Dean of the College of Information Science and Technology at UNO between 2006 and 2021. He has published numerous articles in various IT areas including scheduling, distributed systems, data analytics, wireless networks, and Bioinformatics. He has also published two books in scheduling and graph algorithms, and several book chapters in Bioinformatics. He has been serving as the PI or Co-PI of several projects funded by NSF, NIH and Nebraska Research Initiative in the areas of data analytics, wireless networks and Bioinformatics. He has also been leading a Research Group that focuses on developing innovative computational approaches to model complex biomedical systems and analyze big bioinformatics data. The research group is currently developing several next generation big data analytics tools for analyzing large heterogeneous biological and health data associated with various biomedical research areas, particularly projects associated with infectious diseases, microbiome studies, early childhood development and aging research. He has also been leading two projects for developing secure and energy-aware wireless infrastructure to address tracking and monitoring problems in medical environments, particularly to study mobility profiling for advancing healthy aging research and personalized healthcare.
Prof. Sergei Gorlatch
University of Muenster, Germany
Speech Title: Future Applications Based on Mobile Cloud and
Abstract: We consider an emerging class of challenging software applications called Real-Time Online Interactive Applications (ROIA). ROIA are networked applications connecting a potentially very high number of users who interact with the application and with each other in real time, i.e., a response to a user’s action happens virtually immediately. Typical representatives of ROIA are multiplayer online computer games, advanced simulation-based e-learning and serious gaming. All these applications are characterized by high performance and QoS requirements, such as: short response times to user inputs (about 0.1-1.5 s); frequent state updates (up to 100 Hz); large and frequently changing numbers of users in a single application instance (up to tens of thousands simultaneous users). This talk will address two challenging aspects of software for future Internet-based ROIA applications: a) using Mobile Cloud Computing for allowing high application performance when a ROIA application is accessed from multiple mobile devices, and b) managing dynamic QoS requirements of ROIA applications by employing the emerging technology of Software-Defined Networking (SDN).
Sergei Gorlatch is Full Professor of Computer Science at the University of Muenster (Germany) since 2003. Earlier he was Associate Professor at the Technical University of Berlin, Assistant Professor at the University of Passau, and Humboldt Research Fellow at the Technical University of Munich, all in Germany. Prof. Gorlatch has more than 200 peer-reviewed publications in renowned international books, journals and conferences. He was principal investigator in several international research and development projects in the field of software for parallel, distributed, Grid and Cloud systems and networking, funded by the European Commission and by German national bodies.