Pedro Pereira

In this paper, three metaheuristics are investigated to optimize RF Integrated Inductors; namely Differential Evolution (DE) from the field of evolutionary computation, Gravitational Search Algorithm (GSA) based on the law of gravity and mass interactions and Particle Swarm Optimization (PSO) inspired by swarm behaviors in nature. A particular interest is given to the optimization of RF Integrated Inductors. Performances in terms of optimum quality and computing time of the metaheuristics are checked via three test functions and one application that consist of optimizing performances of characterize integrated inductors based on the double$π$-model.

Although tourism is a major engine of economic growth, it also creates a burden hard to manage, and has a great impact on the conservation of the heritage. The HERIT-DATA project aims to reduce the impact of human activities, related to tourism, on cultural heritage, with a special focus on two kind of cultural destinations that can benefit from and be affected by mass tourism: Old towns and places of specific cultural heritage or archaeological interest for visitors, including UNESCO World Heritage Sites. In that framework, HERIT-DATA plans to develop of a sustainable and responsible tourism management towards cultural heritage in MED regions, in particular by taking advantage of technology and innovation in management tools (Smart Cities), as well as other policy and social measures.

Nowadays technologies relate to so many aspects in our daily life that makes society eager for more and more ways of using it. To keep up with this new technological world, all economic sectors, from industry to services, are trying to adapt their products into this new reality. Presently, cultural heritage is already a field where the application of technology allows a static site to be converted into an intelligent environment, with detailed information about a specific monument or historical place, becoming more interesting, not only for local habitants, but also for tourists. This paper describes an application that allows tourists, managers and historical sites' habitants to experience a completely new way of discovering those places, offering a visit with detailed real-time information taking into account their personal interests. Tourists will have at their disposal a full set of optimized routes, combining their interests with their visiting time.

Tourism is an industry that has been growing rapidly in the last few years and it is expected that it will continue to grow. Due to the evolution of technology, mobile applications are being increasingly used in all kinds of industries, being one of them tourism. Presently there are already a few mobile applications used to increase the experience of the user when visiting a place, but these mobile applications lack some important features. This paper describes the development of a mobile application with integrated routing algorithms used to increase the experience of the tourists when visiting the city of Avila, Spain. The tourist will have at their disposal real time information about all the monuments available for visit, a full set of predefined circuits with different visit times and degrees of difficulty and also the possibility to create an optimized or personalized circuit combining the user preferences such as visiting time and number of monuments to visit.

In this paper we deal with analog active filter design using discrete components taking into consideration tolerance effects. Sensitivity analysis is performed to determine the most influential components in the considered circuit, thus relative higher precision is offered to those parameters. Further, an in-loop optimization technique is considered, thus actual IC models are handled. An application example is presented. HSpice simulation results, supported by Monte Carlo analysis, are given to highlight efficiency of the proposed selection technique.

In this paper, an innovative approach for monitoring home electric power quality indicators is presented. Using an electric power analysis device (for this work purpose it will be a smart-meter) and a personal computer it is proved that it is possible to monitor and register electric power quality anomalies, such as long interruptions, voltage dips/swells and frequency oscillations. Through an application developed in Java, a user can view real-time electric parameters, check for electric power quality anomalies and assess load diagram of previous days. Experimental results regarding the application performance are also presented with the respective conclusions.

Swarm intelligence techniques are among the most talented and successful approaches that gained a lot of popularity over the past two decades. They are inspired by animal behavior (such as ants, termites and bees) and insect conduct (by swarm, herd, flock and shoal phenomena) in order to develop these techniques in terms of mimicking their problem/solution abilities. These techniques provide good approximate solutions in a reasonable time for solving hard and complex problems in many engineering fields. This book is intended for researchers, engineers and graduate students with interests in swarm intelligence algorithms and their applications. It discusses and describes the various swarm intelligence techniques as useful tools for solving practical problems, such as urban traffic optimization, electrical engineering problems and the design of integrated analog circuits.

In this paper an interoperability solution is proposed, aiming to go from (building) construction models to energy simulation. Moreover, the energy simulation results will feed the KPI’s analysis of a designed building. The proposed solution will be used to translate different data formats allowing the communication between different systems in an automated environment. The solution presented in this paper exploits the concept of Plug’n’Interoperate (PnI), that is supported by the principle of self-configuration as to automate, as much as possible, the configuration and participation of systems into a shared interoperability environment. In order to validate this approach two different scenarios were taken into account, translating from a CAD (Computer- Aided Design) model data format to an energy simulation data format.

The key step of the analog active filter design is the optimal selection of component values due to manufactured series (E12, E24, E48, E96 and E192). In this paper, four simulation-based metaheuristics are applied to optimize four active filters using commercials available ICs as building blocks. The emphasis of this work is applying Richardson extrapolation-based sensitivity analysis in the optimization process of analog active filters. Indeed, Richardson extrapolation technique facilitates the calculation of the partial derivatives for the sensitivity using the simulation-based evaluation, without an explicit mathematical expression. Viability and benefits of the sensitivity analysis are highlighted. Monte Carlo analysis is performed in order to investigate robustness of the proposed sensitivity analysis of the active filters in case of component value variations due to specified tolerances of manufactured series.

The complex data exchange between architectural design and building energy simulation constitutes the main challenge in the use of energy performance analyses in the early design stage. The enhancement of BIM model data with additional specific energy-related information and the subsequent mapping to the input of an energy analysis or simulation tool is yet an open issue. This paper examines three approaches for the data transfer from 3D CAD applications to building performance simulations using BIM as central data repository and points out their current and envisaged use in practice. The first approach addresses design scenarios. It focuses on the supporting tools needed to achieve interoperability given a 74 wide-spread commercial BIM model (Autodesk Revit) and a dedicated pre-processing tool (DesignBuilder) for EnergyPlus. The second approach is similar but addresses retrofitting scenarios. In both workflows gbXML is used as the transformation format. In the third approach a standard BIM model, IFC is used as basis for the transfer process for any relevant lifecycle phase.

Abstract This paper deals with multiobjective analog circuit optimization taking into consideration performance sensitivity vis-a-vis parameters' variations. It mainly considers improving computation time of the inloop optimization approaches by including sensitivity considerations in the Pareto front generation process, not as a constraint, but by involving it within the used metaheuristic evolution process. Different approaches are proposed and compared. NSGA-II metaheuristic is considered. The proposed sensitivity aware approaches are showcased via two analog circuits, namely, a second generation \{CMOS\} current conveyor and a \{CMOS\} voltage follower. We show that the proposed ideas considerably alleviate the long computation time of the process and improve the quality of the generated front, as well.

This work deals with the multi-objective optimization of analog circuits by generating the Pareto front where elements are low sensitive to parameters' variations. NSGA-II is used for obtaining the non-dominated solutions. Richardson extrapolation technique is used for the in-loop optimization approach for computing partial derivatives and, thus, the solutions' sensitivity. NSGA-II Pareto fronts' intrinsic ranking is exploited for the generation of the new ‘low-sensitive’ Pareto front. The case of the optimal sizing of a CMOS voltage follower is considered to exemplify the proposed approach.

Power Quality is a generic term focusing on several issues, going from reliability to the quality of service provided by the energy supplier. It addresses limiting aspects such as harmonic distortion, flicker, sags, swells and transients... It is important for the students to understand the differences between the large amounts of events that fit into poor power quality category. Moreover it is important for them to analyze real time non-laboratory events. To provide this experience to the students this paper presents a remote m-learning experimental system where several types of poor power quality events can be tested. The developed system is based on a power quality analysis distributed network and can be remotely accessed from a remote computer or smart phones.

The integration of high temperature superconductors (HTS) in electrical machines potentially allows reduction in devices dimensions or performance improvement for the same active volume, when compared with their conventional ones. The use of polycrystalline HTS samples allows big bulk samples. An axial disc motor with HTS material or conventional aluminium in the rotor and conventional armature has been designed and developed. This paper describes simulations and laboratory experiments performed at liquid nitrogen temperature (77 K) in order to analyze the motor's behaviour and its electromechanical characteristics and to define an electric equivalent circuit that allows describing its operation. In order to evaluate the superconducting quality of the bulks and flux pinning phenomena, Hall probe mapping system was performed in order to define the field profiles at 77 K for different polar configurations. The analysis of the obtained results allows confirm the flux pinning phenomena, being the entire rotor magnetized and conclude that the motor with the HTS rotor behaves as a conventional hysteresis motor even though with a different nature, while the motor with aluminium rotor behaves as a conventional induction motor. In asynchronous regime, the HTS motor exhibits a constant torque, higher than the conventional aluminium one. For both cases, the developed torque is proportional to the poles pairs.

Sand pile and Bean models have already been applied to describe single grain HTS bulks. An extension to that approach was used to model multiseed bulks, needed for several practical applications as electric motors or flywheels with superconducting bearings. The use of genetic algorithms was then proposed to determine intra- and intergrain current densities, and application to two and three seeds samples using trapped flux experimental measurements was exemplified. However, this model assumed some simplifications, as equal properties in grain boundaries between neighboring grains. In this paper an extension to this methodology is proposed and evaluated by analyzing measurements performed in plans at different distances from surfaces of samples with three seeds. Discussion of its influence on a practical application is also explored.

The study and assessment of Power Quality issues is nowadays a very important subject, particularly regarding Cyber-physical and Industrial Agents based systems, which are extremely sensitive to Power Quality disturbances. Giving students or engineers practical experience in this field requires a large investment from teaching institutions. This paper presents a laboratory device that emulates Power Quality disturbances in order to provide the required experimental expertize in the subject. It addresses limiting aspects such as harmonic distortion, flicker, sags, swells and transients. The developed system presents a good opportunity for technicians, even without deep knowledge on the field of power quality, to learn basic principles and be able to identify Power Quality events. Since the system is based on real data, represents a valuable approach giving trainees practical knowledge on the field.

Voltage-Controlled Oscillators (VCOs) are widely used in wireless transceivers. Due to the stringent specifications regarding phase-noise, LC-VCOs are usually adopted. The need for maximizing phase-noise as well as minimizing the power consumption makes imperious the adoption of optimization-based design methodologies. For the optimization of the LC-VCO characteristics, special attention must be paid to the integrated inductor design, since its quality factor may have a strong influence in the LC-VCO phase-noise. Furthermore, designers must ensure that the higher limit of VCO operating frequency is sufficiently below the inductor resonant frequency. In this chapter, a study on the influence of the quality factor of the inductors on the LC-VCO overall behavior is presented. Then, optimization of integrated inductors by exploring the inductor geometric layout is presented. Finally, results obtained for the design of an LC-VCO in 130nm Technology using a previously optimized inductor are presented.

Abstract This paper proposes a hybrid methodology for the evaluation of integrated inductors sensitivity against technological/geometrical parameters variation. The obtained results are used in an optimization-based design environment for integrated inductors, as a way of guaranteeing that obtained solutions are robust against parameter variation. For the inductor characterization, a lumped element model is used, where each element value is evaluated through physics based equations. The sensitivity of the inductor characterization to parameter variations is evaluated at two levels. At the physical level, the sensitivity of the model element values to technological/geometrical parameters variations is computed through an equation-based strategy. Then, the sensitivity of the inductor characterization to the model parameter variations is obtained through a simulation-based approach, where the Richardson extrapolation technique is used for the calculation of the partial derivatives. Several examples considering the evaluation of sensitivity of both inductance and quality factor of two inductors in \{UMC130\} technology are presented. Obtained results are compared against Monte-Carlo simulations.

This paper presents a remote laboratory linked with mobile devices for real data analysis on the field of power quality. A global system was developed from the power quality analyzer into the human machine interface devoted to the m-learning system. This m-learning system is intended to be used in a long life learning perspective. The developed remote laboratory is a good opportunity for people, even without deep knowledge on the field, to learn power quality principles in an applied way. Since the system is based on real data, is a good approach to give trainees practical knowledge on the field.

The need for implementing low cost, fully integrated RF wireless transceivers has motivated the widespread use CMOS technology. However, in the particular case for voltage-controlled oscillators (VCO) where ever more stringent specifications in terms of phase-noise must be attained, the design of the on-chip LC tank is a challenging task, where fully advantage of the actual technologies characteristics must be pushed to nearly its limits. To overcome phase-noise limitations arising from the low quality factor of integrated inductors, optimization design methodologies are usually used. In this paper a model-based optimization approach is proposed. In this work the characterization of the oscillator behaviour is guaranteed by a set of analytical models describing each circuit element performance. A set of working examples for UMC130 technology, aiming the minimization of both VCO phase noise and power consumption, is addressed. The results presented, illustrate the potential of a GA optimization procedure design methodology yielding accurate and timely efficient oscillator designs. The validity of the results is checked against HSPICE/RF simulations.

The sand pile model, in conjunction with Bean model, is often applied to describe single grain bulk superconductors. However, in several applications such as electric motors, multiseeded bulks are needed, due to the need to increase sample dimensions. In this paper, an extension of the sand pile model is presented in order to manage this type of materials. Multiseeded HTS bulk superconductors, produced, e.g., by the top-seeded melt growth process, are characterized by intra- and intergrain currents, and these are reflected in the model. However, identifying these currents from flux density measurements is not straightforward, when considering more than one grain. In fact, the number of currents increases with the number of grains, and these have to be identified from the measured field surface. A method to identify these currents based on genetic algorithms is validated with artificial data and then used in real measurements.

The goal of this paper is to present a comparison among three known metaheuristics: Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Simulated Annealing (SA). For the comparison, the design of an LC - Voltage Controlled Oscillator (LC-VCO) is considered, where the minimization of both VCO phase noise and power consumption is envisaged. The objective of this comparison is to find the algorithm yielding the best solution. The validity of the solution obtained with each metaheuristic algorithm is checked against HSPICE/RF simulation results. Robustness checks for each algorithm are presented at the end of this paper.

The progressive scaling of CMOS technology towards nanometre sizes has made the implementation of highly integrated systems for the wireless communication systems possible. Additionally, higher speed, lower power consumption and area reduction has been reached. Due to the high-density integration needs, as well as to low cost fabrication, RF applications, such as the LC-voltage controlled oscillator (LC-VCO), are usually implemented in CMOS technology. The complexity of designing LC-VCOs has lead to the development of several design methodologies. This chapter introduces an optimization based methodology for the design of LC-VCOs, where its efficiency is granted by the use of analytical models to characterize the active and passive elements’ behaviour.

The continuing size reduction of electronic devices imposes design challenges to optimize the performances of modern electronic systems, such as: wireless services, telecom and mobile computing. Fortunately, those design challenges can be overcome thanks to the development of Electronic Design Automation (EDA) tools. In the analog, mixed signal and radio-frequency (AMS/RF) domains, circuit optimization tools have demonstrated their usefulness in addressing design problems taking into account downscaling technological aspects. Recent advances in EDA have shown that the simulation-based sizing technique is a very interesting solution to the ‘complex’ modelling task in the circuit design optimization problem. In this paper we propose a multi-objective simulation-based optimization tool. A CMOS LC-VCO circuit is presented to show the viability of this tool. The tool is used to generate the Pareto front linking two conflicting objectives, namely the VCO Phase Noise and Power Consumption. The accuracy of the results is checked against HSPICE/RF simulations.

The advancement of CMOS technology led to the integration of more complex functions. In the particular of wireless transceivers, integrated LC tanks are becoming popular both for VCOs and integrated filters [1]. For RF applications the main challenge is still the design of integrated inductors with the maximum quality factor. For that purpose, tapered, i.e., variable width inductors have been proposed in the literature. In this paper, analytical expressions for the determination the pi-model parameters, for the characterization of variable width integrated inductors are proposed. The expressions rely exclusively on geometrical and technological parameters, thus granting the rapid adaptation of the model to different technologies. The results obtained with the model are compared against simulation with ASITIC, showing errors below 10%. The model is then integrated into an optimization procedure where inductors with a quality factor improvement in the order of 20-30% are obtained, when compared with fixed width inductors.