Manuel FM Barros

Polytechnic Institute of Tomar · Smart Cities Research Center

The Smart monitoring of constructed wetlands to improve efficiency and water quality (SmarterCW) project aims to monitor biological wastewater treatment processes by gathering continuous data from remote water and environmental sensors. The acquired data can be processed and analyzed through data science tools to understand better the complex and c...

Networks are an important mechanism for systemic change towards sustainability in higher education institutions. In Portugal there is no formal law or regulation at governmental level pressuring for this change. Also, there was a need for action and a lack of collaboration between the Portuguese higher education community to allow an advanced susta...

O trabalho desenvolvido consistiu no projeto de solução prática para um sistema de monitorização da qualidade de águas superficiais em tempo real, usando umaplataforma de robótica e serviços em nuvem e as mais recentes tecnologias de comunicação e de informação. Os dados obtidos permitem aos agentes de decisãoentender, interpretar e usar, de forma...

In recent years, there has been increasing awareness of the preservation, protection and sustainable use of natural resources. Water resources, being one of the most important, face major threats due to contamination by pollutants of various types and origins. Maintaining the quality of water resources requires more robust, reliable and more freque...

In this chapter, a multi-objective design methodology for automatic an-alog integrated circuits (IC) synthesis, which enhances the robustness of the solu-tion by varying technological and environmental parameters, is presented. The au-tomatic analog IC sizing tool GENOM-POF was implemented and used to demonstrate the methodology, and to verify the...

In this paper an innovative fuzzy-genetic approach is proposed to address the problem of analog circuit sizing. The proposed approach introduces a fuzzy mutation operator which models expert design knowledge and this way not only avoids local minima but also reduces the search dynamically the space. The proposed approach is compared against a state...

This paper presents a new design automation tool, based on a modified genetic algorithm kernel, in order to improve efficiency on the analog IC design cycle. The proposed approach combines a robust optimization with corner analysis, machine learning techniques and distributed processing capability able to deal with multi-objective and constrained o...

The microelectronics market trends present an ever-increasing level of complexity with special emphasis on the production of complex mixed-signal systems-on-chip. Strict economic and design pressures have driven the development of new methods for automating the analog design process. However, and despite some significant research efforts, the essen...

This chapter starts with an overview on computation techniques aiming to solve nonlinear optimization problems with emphasis on evolutionary optimization algorithms and discusses their relevance to analog design problem. The main virtues and weaknesses, as well as, the design issues of evolutionary algorithms are discussed with a description of the...

In the previous chapters there was a description of the optimization methodology and the supporting tool that simplifies the design tasks of analog integrated circuits. The developed design optimization tool, GENOM, based on evolutionary computation techniques and incorporating heuristic knowledge on the automatic control mechanism was combined eff...

This chapter presents the State-of-the-Art (SOA) in analog circuit design automation. First, the analog design flow is reviewed and the fundamental trends in design automation are discussed. Then, the existing approaches to circuit sizing are presented, outlining in each case their advantages and limitations. Next, a detailed discussion over the ex...

This chapter describes the implementation of an innovative design automation tool, GENOM which explores the potentials of evolutionary computation techniques and state-of-the-art modeling techniques presented in the previous chapters. The main design options of the proposed approach will be here described and justified. First, an overview of the de...

In order to improve the relatively slow convergence of GA, in the presence of large search spaces, and reduce the high consuming time of evaluation functions in analog circuit design applications, this chapter will discuss the use of learning algorithms. These algorithms explore the successive generation of solutions, learn the tendency of the best...

This chapter presents the motivation to the research work in the area of analog integrated circuit (IC) design automation, i.e., outlines the market and technological evolution, characterizes the analog IC design, discusses the available CAD solutions and, finally, describes goals for the this work.

This last chapter presents the work conclusions and discusses the future work issues.

This paper addresses the analog integrated circuit design automation by proposing an innovative circuit-level optimization kernel. The proposed approach, first, models analog design knowledge using soft computing techniques, than, enhances a stochastic optimization kernel by embedding the design knowledge model. The proposed approach uses common IC...

In this paper a new design automation approach to the problem of sizing analog ICs is described. The proposed approach employs a dynamic learning scheme, based on Support Vector Machines (SVMs), which together with an evolutionary strategy is used to create feasibility models to efficiently prune the design search space during the optimization proc...

An efficient use of macromodeling techniques is pointed out as an effective approach to improve the convergence and speed of the optimization process. The methodology presented in this paper is based on a learning scheme using Support Vector Machines(SVMs) that together with and an evolutionary strategy is used to create efficient models to estimat...

This paper presents a circuit/system level synthesis and optimization approach based on a learning scheme using support vectors machines (SVMs) and evolutionary strategies applied to the design of analog and mixed-signal ICs. This approach combines the best qualities of these two techniques, a robust classification and regression method and a power...

This paper presents a new design automation environment to support analog IC design. The proposed approach introduces an increased level of flexibility and reusability when compared to traditional approaches. The flexibility is achieved by both allowing the designer to define its own hierarchical design organization and, simultaneously, the design...

This paper presents a new design automation methodology for analog IC design. The proposed approach introduces an increased level of flexibility and reusability when compared to traditional approaches. The flexibility is achieved by allowing the designer to define both his/her own hierarchical design organization and, simultaneously, the design flo...

This paper presents a new evolutionary optimization kernel applied to the automatic synthesis of high performance analog and mixed-signal ICs. This enhanced evolutionary approach is based on a modified genetic algorithm with self adaptive parameters tailored to efficiently control the optimization process. Particularly, the benefits introduced by s...

This paper presents a circuit/system-level optimization E-Design environment based on an enhanced modified genetic algorithm kernel. The presented approach improves the standard genetic algorithm implementation by including automatic search space decomposition, premature convergence prevention procedures and distributed processing features. In orde...