DEI TALKS | “Let’s discuss about Models and Languages for embedded systems in Industry 4.0” by Prof. Julio Medina

“This talk proposes to have a conversation about the trends in conceptual modelling languages used for the design and analysis of real-time and embedded systems in the context of the ever changing industrial environments but never changing business demands”.

Let’s discuss about Models and Languages for embedded systems in Industry 4.0” will be presented February 1, at 11:00, room I-105, moderated by Prof. Gil Gonçalves (DEI).

Short Bio:
“Julio Medina is Associate Professor at Universidad de Cantabria, Spain. His main research areas include the modeling of real-time distributed systems for schedulability analysis and dependability, standards and languages for the representation of such models, and their usage for modular and component-based development software engineering strategies. He contributes to the OMG in the standardization of languages like SysML, MARTE, UCM, UTP, among others.”

Talk a Bit is back for its 12th edition

*Talk a Bit is back on stage at the FEUP Auditorium next Saturday, February 3.

The theme of this 12th edition, “Today’s Choices, Tomorrow’s World“, will highlight the profound impact of contemporary technological decisions on the future.

The programme will feature insightful talks and discussions on Artificial Intelligence (AI) and its role in health, smart cities and sustainable industries. Several experts will share with the public their knowledge on the latest technological advances and their future implications, promoting an environment conducive to learning and socializing opportunities.

Hugo Neves (MOG), Filipe Portela (IOTECH), Luís Valente (ILOF) and Tiago Reis (DIGESTAID) have all been confirmed as guest speakers in a programme (being updated) that can be seen here.

Registration is free but mandatory and must be submitted here.

*Talk a Bit is a technology conference organized by the students of the Master’s Degree in Informatics and Computing Engineering at the Faculty of Engineering of the University of Porto.

PhD Defense in Informatics Engineering : ”Highly reconfigurable smart component system”

Candidate
Luís Carlos de Sousa Moreira Neto

Date, Time and Place 
January 31, 14:15, Sala de Atos FEUP

President of the Jury
Carlos Miguel Ferraz Baquero-Moreno, PhD, Full Professor, Department of Informatics Engineering, Faculdade de Engenharia, Universidade do Porto.

Members
Julio Luis Medina Pasaje, PhD, Associate Professor, Departamento de Ingeniería Informática y Electrónica, Facultad de Ciencias, Universidad de Cantabria, Espanha;
António Eduardo Vitória do Espírito Santo, PhD, Assistant Professor, Department of Mechanical Engineering, Faculdade de Engenharia, Universidade da Beira Interior;
Pedro Nuno Ferreira da Rosa da Cruz Diniz, PhD, Full Professor, Department of Informatics Engineering, Faculdade de Engenharia, Universidade do Porto;
Luis Miguel Pinho de Almeida, Associate Professor with Habilitation, Department of Electrical and Computer Engineering, Faculdade de Engenharia, Universidade do Porto;
Gil Manuel Magalhães de Andrade Gonçalves, PhD, Assistant Professor, Department of Informatics Engineering, Faculdade de Engenharia, Universidade do Porto (Supervisor).

Abstract:
“Across all sectors of our society, efficiency is an increasingly paramount concern for a sustainable world. While the significance of efficiency spans all levels, it is at a large scale where the impacts of efficient practices are most prominently noticed. Industrial activities are an example of how efficiency traduces in visible results. It doesn’t require extensive reasoning to recognize that everyday increasingly affordable goods we consume are a direct outcome of these efficiency demands. The market is demanding new services and business models that center the end user in the product design. In the near future, consumers will be able to customize a product on-line, place a production order, and see it delivered, all in the same day. This remarkable possibility arises from of a combination of efficiency and flexibility within the production processes. Several names have been used to describe the same fundamental paradigm in both academic and industrial contexts: Factories of the Future, Smart Manufacturing and Industry 4.0, all remounting to the same technological advent. This concept has far-reaching implications, extending its influence across multiple technological domains, presenting a wealth of research opportunities and driving the need for innovative technologies. This thesis delves into two technological domains related with this new paradigm and tackles one key problem in either domain. Within the Cyber-Physical Production Systems (CPPS) domain, it addresses the problem of establishing a unified network of industrial assets where software and its connections to other assets are clearly discernible and recognized. On the Reconfigurable Manufacturing Systems (RMS) domain, it addresses the fast pace at which the production lines will have to reconfigure, in particular, how software will have to reconfigure in parallel with the production lines and the ease with which new software can be developed and deployed to meet emerging challenges. A solution to both problems emerges from the field of Component-Based Software Engineering (CBSE), where this thesis drew inspiration to develop an innovative Smart Component with enhanced software reconfiguration and deployment capabilities. The proposed system exploits using Linux, a general-purpose operating system, as the component runtime environment (RTE). A combination of shared memory for efficient component communication and parallel and reconfigurable computing properties for enhanced throughput allows the proposed system to meet established application performance standards while maintaining a high degree of flexibility and reusability. The Smart Component’s flexibility is demonstrated through the implementation of two component models. The IEC 61499 component model, designed to model event-driven distributed applications for industrial system monitoring and control, and the Smart Object Self-Description (SOSD), developed by the author to describe software components, their interconnections, and their associations with industrial assets. The IEC 61499 implementation was directly compared to existing RTEs, outperforming them in real-world use cases and equaling the performance of one RTE in a literature benchmark. Additional benchmarks to assess the Smart Component’s reconfiguration performance and simplified software component development method were proposed in this thesis. The effectiveness of the SOSD implementation was validated through its application in a real-world use case, furnishing other CPPS nodes with context regarding the origin of the collected data and the software components responsible for its processing. By using Linux as the RTE, a software layer traditionally dedicated to manage components was deemed unnecessary, due to the system’s ability to execute applications conforming to relevant performance standards, while showing superior software flexibility, and even outperforming existing RTEs which employ the traditional approach. Many runtime environments for software components exist, but few allow the deployment of components built in more than one programming language, and none – to the best of the author’s knowledge – allow the development of components in any language – provided that language is at least able to read and write to files. The simplicity of developing regular software program for Linux and converting it into a software component is a promising feature that should benefit the development of industrial control and monitoring applications by bringing along the benefits of multiple high-level programming languages.”

DEI TALKS | “Analyzing and Modeling Intelligent Systems Users’ Behavior in Digital Society” by Prof. Humberto Marques-Neto

“Information systems are ever-increasingly intelligent and present in the daily lives of people and companies, facilitating and modifying the performance of various activities. In addition to handling each system’s intrinsic data, data from its users’ interactions can contribute to identifying, modeling, and analyzing people’s behavior patterns. The data analysis from the usage of web systems and mobile applications and, in particular, from online social networks such as Twitter, Facebook, WhatsApp, Instagram, and TikTok (obviously respecting the privacy of users) can contribute to the understanding of some dynamics and specific behaviors of human beings.

In this talk, I will present how our research group has done the characterization, analysis, and modeling of the behavior of users of intelligent information systems, more specifically, users of online social networks and information systems that make information available in open data portals, to induce the development of new software that use machine learning and artificial intelligent algorithms. The information systems user behavior, together with patterns of social interaction and human mobility in urban centers, in addition to subsidizing decisions and policies of government agencies and institutions responsible for urban planning, could foster and even target software developers interested in creating innovative software with the potential to improve people’s lives in a digital and connected society.”

Analyzing and Modeling Intelligent Systems Users’ Behavior in Digital Society” will be presented January 25, at 14:00, room B006, moderated by Prof. Gil Gonçalves (DEI).

Short Bio:
Prof. Humberto T. Marques-Neto is a researcher and a professor in the Department of Computer Science at the Pontifical Catholic University of Minas Gerais (PUC Minas) in Belo Horizonte – Brazil. He holds a degree in Computer Science from the PUC Minas, a Master’s in Information Science, and a Ph.D. in Computer Science, both from the Federal University of Minas Gerais – UFMG. In the last few years, he has published some papers on the characterization and modeling of large-scale distributed system user behavior, online social network analysis and modeling, computing systems for mobile devices, and software engineering. He also coordinates (at PUC Minas) the Center of Technological Innovation and PUCTec, a Hub for Innovation and Business with about 30 startups. Since last August, he has been spending a one-year sabbatical as a Visiting Fellow in the Department of Computer Science of the University of Pisa.”

PhD Defense in Informatics (MAP-i): ”Artificial Intelligence Methods for Automated Difficulty and Power Balance in Games”

Candidate
Simão Paulo Rato Alves Reis

Date, Time and Place
January 11, 14:00, Sala de Atos FEUP

President of the Jury
Carlos Miguel Ferraz Baquero-Moreno, PhD, Full Professor, Department of Informatics Engineering, Faculdade de Engenharia, University of Porto

Members
João Alberto Fabro, PhD, Associate Professor, Departamento Acadêmico de Informática, Universidade Tecnológica Federal do Paraná, Brasil;
Rui Filipe Fernandes Prada, PhD, Associate  Professor, Instituto Superior Técnico, Universidade de Lisboa;
Pétia Georgieva Georgieva, PhD, Associate Professor with Habilitation, Department of Electronics, Telecommunications and Informatics, Universidade de Aveiro (representative of the MAP-i Scientific Committee);
Luís Paulo Gonçalves dos Reis, PhD, Associate Professor with Habilitation, Department of Informatics Engineering, Faculdade de Engenharia, Universidade do Porto (Supervisor);
Henrique Daniel de Avelar Lopes Cardoso, PhD, Associate Professor, Department of Informatics Engineering, Faculdade de Engenharia, Universidade do Porto.

The thesis was co-supervised by Doutor Nuno Lau, Associate Professor at the University of Aveiro.

Abstract:
“This thesis studies the balance problem in game development, notably in two-player games. Specifically, we aim to study the viability of Artificial Intelligence (AI) as an assisting tool to fix game properties. We split our research into two paths: Power Balance, where the aim is to adjust game strategies, so they become effective as winning tools; Difficulty Balance, where the objective is to adjust game attributes on the fly so that weaker players or players at a disadvantage can compete with stronger players or players in advantage. Both domains require tuning the game, but they mainly differ in the timing and in their aim, one deals with the imbalance in game design, while the other deals with inequality in player skills. For Power Balance, our methodology was to define a full meta-game balance ecosystem based on the Pokémon video game franchise and develop an AI competition where the multiple associated tasks (battling, team prediction and assembly, and meta-game balance) are present and can be tested in a common ground. To balance the meta-game, we follow an adversarial model where team builders aim to narrow the use of optimal Pokémon while balancer agents aim to incentive the maximum of Pokémon as possible to be selected by team builders. This results in agents being able to play, build effective teams, and being able to tune the Pokémon roster over time. We discuss how our models can be extended to other video game domains. For Difficulty Balance, we propose a Multiplayer Dynamic Difficulty Adjustment framework where a Game Master (GM) agent is trained and embedded into a game, depending on the game state it will deploy handicap mechanisms. The training regime follows a specific pipeline. To generalize advantage situations, parameterized perturbations on the actions of a reference player are used to emulate several degrees of playing skill, and the advantage for each player is used to draw curves which are evaluated as a reward for the GM. This results in the GM being able to optimize game design criteria and create opportunities for the player behind to recover. We show there are suited AI tools for each task, and it is reasonable to think of power balance and difficulty as separate problems, where both can be automatically assisted and eased. Both further augment our overall comprehension of the automated game balance field.”