Creation of a web application for smart park system and parking prediction study for system integration

In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.

Integration of a mobile autonomous robot in a surveillance multi-agent system

This dissertation aims to guarantee the integration of a mobile autonomous robot equipped with many sensors in a multi-agent distributed and georeferenced surveillance system. The integration of a mobile autonomous robot in this system leads to new features that will be available to clients of surveillance system may use. These features may be of two types: using the robot as an agent that will act in the environment or by using the robot as a mobile set of sensors. As an agent in the system, the robot can move to certain locations when alerts are received, in order to acknowledge the underlying events or take to action in order to assist in resolving this event. As a sensor platform in the system, it is possible to access information that is read from the sensors of the robot and access complementary measurements to the ones taken by other sensors in the multi-agent system. To integrate this mobile robot in an effective way it is necessary to extend the current multi-agent system architecture to make the connection between the two systems and to integrate the functionalities provided by the robot into the multi-agent system.

Functional MRI of stimulus interference on auditory processing in normal listeners and tinnitus patients

We are constantly immersed in stimuli. Upon reaching our senses, stimuli are processed within various brain systems along various pathways into the brain, and eventually turned into a percept. However, there are percepts that do not result from responses to external source stimuli. A particular case of this situation is the auditory percept known as tinnitus. Tinnitus can be seen as a task-irrelevant auditory percept, commonly reported to interfere with normal daily tasks. This is known from reports made by tinnitus sufferers that refer to their phantom percept as distracting, and that it diverts their focus from the task-relevant stimuli.(...)

Brazilian equity risk premium analysis: A macroeconomic approach

Double Degree Masters in Economics Program from Insper and NOVA School of Business and Economics

DYNAMOD – A dynamic agent based modelling framework for digital businesses

Digital Businesses have become a major driver for economic growth and have seen an explosion of new startups. At the same time, it also includes mature enterprises that have become global giants in a relatively short period of time. Digital Businesses have unique characteristics that make the running and management of a Digital Business much different from traditional offline businesses. Digital businesses respond to online users who are highly interconnected and networked. This enables a rapid flow of word of mouth, at a pace far greater than ever envisioned when dealing with traditional products and services. The relatively low cost of incremental user addition has led to a variety of innovation in pricing of digital products, including various forms of free and freemium pricing models. This thesis explores the unique characteristics and complexities of Digital Businesses and its implications on the design of Digital Business Models and Revenue Models. The thesis proposes an Agent Based Modeling Framework that can be used to develop Simulation Models that simulate the complex dynamics of Digital Businesses and the user interactions between users of a digital product. Such Simulation models can be used for a variety of purposes such as simple forecasting, analysing the impact of market disturbances, analysing the impact of changes in pricing models and optimising the pricing for maximum revenue generation or a balance between growth in usage and revenue generation. These models can be developed for a mature enterprise with a large historical record of user growth rate as well as for early stage enterprises without much historical data. Through three case studies, the thesis demonstrates the applicability of the Framework and its potential applications.

Using an LED as a sensor and visible light communication device in a smart illumination system

The need for more efficient illumination systems has led to the proliferation of Solid-State Lighting (SSL) systems, which offer optimized power consumption. SSL systems are comprised of LED devices which are intrinsically fast devices and permit very fast light modulation. This, along with the congestion of the radio frequency spectrum has paved the path for the emergence of Visible Light Communication (VLC) systems. VLC uses free space to convey information by using light modulation. Notwithstanding, as VLC systems proliferate and cost competitiveness ensues, there are two important aspects to be considered. State-of-the-art VLC implementations use power demanding PAs, and thus it is important to investigate if regular, existent Switched-Mode Power Supply (SMPS) circuits can be adapted for VLC use. A 28 W buck regulator was implemented using a off-the-shelf LED Driver integrated circuit, using both series and parallel dimming techniques. Results show that optical clock frequencies up to 500 kHz are achievable without any major modification besides adequate component sizing. The use of an LED as a sensor was investigated, in a short-range, low-data-rate perspective. Results show successful communication in an LED-to-LED configuration, with enhanced range when using LED strings as sensors. Besides, LEDs present spectral selective sensitivity, which makes them good contenders for a multi-colour LED-to-LED system, such as in the use of RGB displays and lamps. Ultimately, the present work shows evidence that LEDs can be used as a dual-purpose device, enabling not only illumination, but also bi-directional data communication.

Smart machines in day-to-day financial management:

Starting from Novabase’s challenge to launch in the UK Millennials a personal financial advisor mobile application, this work project aims to build a planning model to frame a business side of a launch strategy for mobile application in similar market and category. This study culminates on the design of SPOSTAC planning model. The created framework is intended to effectively and efficiently plan a launch strategy, being structured based on seven sequential elements: Situation, Product, Objectives, Strategy, Tactics, Action, and Control.

An agent-based simulator to estimate domestic energy use

Throughout recent years, there has been an increase in the population size, as well as a fast economic growth, which has led to an increase of the energy demand that comes mainly from fossil fuels. In order to reduce the ecological footprint, governments have implemented sustainable measures and it is expected that by 2035 the energy produced from renewable energy sources, such as wind and solar would be responsible for one-third of the energy produced globally. However, since the energy produced from renewable sources is governed by the availability of the respective primary energy source there is often a mismatch between production and demand, which could be solved by adding flexibility on the demand side through demand response (DR). DR programs influence the end-user electricity usage by changing its cost along the time. Under this scenario the user needs to estimate the energy demand and on-site production in advance to plan its energy demand according to the energy price. This work focuses on the development of an agent-based electrical simulator, capable of: (a) estimating the energy demand and on-site generation with a 1-min time resolution for a 24-h period, (b) calculating the energy price for a given scenario, (c) making suggestions on how to maximize the usage of renewable energy produced on-site and to lower the electricity costs by rescheduling the use of certain appliances. The results show that this simulator allows reducing the energy bill by 11% and almost doubling the use of renewable energy produced on-site.

The use of technology in Portuguese hospitals- The case of MRI

We study the determinants of MRI use across Portuguese NHS hospitals for patients belonging to specific DRGs. Using data on individual hospital admissions, we estimate a probit model including individual-, hospital-, time- and region-specific variables in order to explain the probability of a patient being sent for MRI. Results convey a tightening effect on the hospital’s budget constraint in the end of each year. Hospitals seem to account for regional characteristics when defining adoption patterns. Individual-specific variables are good predictors of MRI use. Measures taken by the Government only impact the short run. Finally, the gains from an MRI scan, as far as the probability of death is concerned, occur mainly for less severe patients.

EDP inovcity: Electricity feedback with smart meters through TV

In this work project I propose an innovative service – Electricity Feedback with Smart Meters through TV – to be considered as an additional test in the residential electricity use feedback trials currently being conducted in EDP’s InovCity project. My proposal is based on relevant past and current research studies, both Portuguese and international, which explain and support the proposed operationalization and characteristics of this new service. Furthermore, a careful analysis about the segmentation framing, the best market entry strategy and the consequences of adopting a joint venture with cable TV operators, is also provided. Finally, I present a SWOT analysis and highlight critical issues affecting the effectiveness of feedback which require further research.

Essays on bounded rationality: Individual decision and strategic interaction

Economics is a social science which, therefore, focuses on people and on the decisions they make, be it in an individual context, or in group situations. It studies human choices, in face of needs to be fulfilled, and a limited amount of resources to fulfill them. For a long time, there was a convergence between the normative and positive views of human behavior, in that the ideal and predicted decisions of agents in economic models were entangled in one single concept. That is, it was assumed that the best that could be done in each situation was exactly the choice that would prevail. Or, at least, that the facts that economics needed to explain could be understood in the light of models in which individual agents act as if they are able to make ideal decisions. However, in the last decades, the complexity of the environment in which economic decisions are made and the limits on the ability of agents to deal with it have been recognized, and incorporated into models of decision making in what came to be known as the bounded rationality paradigm. This was triggered by the incapacity of the unboundedly rationality paradigm to explain observed phenomena and behavior. This thesis contributes to the literature in three different ways. Chapter 1 is a survey on bounded rationality, which gathers and organizes the contributions to the field since Simon (1955) first recognized the necessity to account for the limits on human rationality. The focus of the survey is on theoretical work rather than the experimental literature which presents evidence of actual behavior that differs from what classic rationality predicts. The general framework is as follows. Given a set of exogenous variables, the economic agent needs to choose an element from the choice set that is avail- able to him, in order to optimize the expected value of an objective function (assuming his preferences are representable by such a function). If this problem is too complex for the agent to deal with, one or more of its elements is simplified. Each bounded rationality theory is categorized according to the most relevant element it simplifes. Chapter 2 proposes a novel theory of bounded rationality. Much in the same fashion as Conlisk (1980) and Gabaix (2014), we assume that thinking is costly in the sense that agents have to pay a cost for performing mental operations. In our model, if they choose not to think, such cost is avoided, but they are left with a single alternative, labeled the default choice. We exemplify the idea with a very simple model of consumer choice and identify the concept of isofin curves, i.e., sets of default choices which generate the same utility net of thinking cost. Then, we apply the idea to a linear symmetric Cournot duopoly, in which the default choice can be interpreted as the most natural quantity to be produced in the market. We find that, as the thinking cost increases, the number of firms thinking in equilibrium decreases. More interestingly, for intermediate levels of thinking cost, an equilibrium in which one of the firms chooses the default quantity and the other best responds to it exists, generating asymmetric choices in a symmetric model. Our model is able to explain well-known regularities identified in the Cournot experimental literature, such as the adoption of different strategies by players (Huck et al. , 1999), the inter temporal rigidity of choices (Bosch-Dom enech & Vriend, 2003) and the dispersion of quantities in the context of di cult decision making (Bosch-Dom enech & Vriend, 2003). Chapter 3 applies a model of bounded rationality in a game-theoretic set- ting to the well-known turnout paradox in large elections, pivotal probabilities vanish very quickly and no one should vote, in sharp contrast with the ob- served high levels of turnout. Inspired by the concept of rhizomatic thinking, introduced by Bravo-Furtado & Côrte-Real (2009a), we assume that each per- son is self-delusional in the sense that, when making a decision, she believes that a fraction of the people who support the same party decides alike, even if no communication is established between them. This kind of belief simplifies the decision of the agent, as it reduces the number of players he believes to be playing against { it is thus a bounded rationality approach. Studying a two-party first-past-the-post election with a continuum of self-delusional agents, we show that the turnout rate is positive in all the possible equilibria, and that it can be as high as 100%. The game displays multiple equilibria, at least one of which entails a victory of the bigger party. The smaller one may also win, provided its relative size is not too small; more self-delusional voters in the minority party decreases this threshold size. Our model is able to explain some empirical facts, such as the possibility that a close election leads to low turnout (Geys, 2006), a lower margin of victory when turnout is higher (Geys, 2006) and high turnout rates favoring the minority (Bernhagen & Marsh, 1997).

Control in distribution networks with demand side management

The way in which electricity networks operate is going through a period of significant change. Renewable generation technologies are having a growing presence and increasing penetrations of generation that are being connected at distribution level. Unfortunately, a renewable energy source is most of the time intermittent and needs to be forecasted. Current trends in Smart grids foresee the accommodation of a variety of distributed generation sources including intermittent renewable sources. It is also expected that smart grids will include demand management resources, widespread communications and control technologies required to use demand response are needed to help the maintenance in supply-demand balance in electricity systems. Consequently, smart household appliances with controllable loads will be likely a common presence in our homes. Thus, new control techniques are requested to manage the loads and achieve all the potential energy present in intermittent energy sources. This thesis is focused on the development of a demand side management control method in a distributed network, aiming the creation of greater flexibility in demand and better ease the integration of renewable technologies. In particular, this work presents a novel multi-agent model-based predictive control method to manage distributed energy systems from the demand side, in presence of limited energy sources with fluctuating output and with energy storage in house-hold or car batteries. Specifically, here is presented a solution for thermal comfort which manages a limited shared energy resource via a demand side management perspective, using an integrated approach which also involves a power price auction and an appliance loads allocation scheme. The control is applied individually to a set of Thermal Control Areas, demand units, where the objective is to minimize the energy usage and not exceed the limited and shared energy resource, while simultaneously indoor temperatures are maintained within a comfort frame. Thermal Control Areas are overall thermodynamically connected in the distributed environment and also coupled by energy related constraints. The energy split is performed based on a fixed sequential order established from a previous completed auction wherein the bids are made by each Thermal Control Area, acting as demand side management agents, based on the daily energy price. The developed solutions are explained with algorithms and are applied to different scenarios, being the results explanatory of the benefits of the proposed approaches.

An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.

Chitosan-based magnetic nanoparticles for osteosarcoma theranostic

Cancer is a well-known disease with a significant impact in society not only due to its incidence, more evident in more developed countries, but also due to the expenses related to medical treat-ments. Cancer research is considered an increasingly logical science with great potential for the development of new treatment options. Advances in nanomedicine have resulted in rapid devel-opment of nanomaterials with considerable potential in cancer diagnostics and treatment. The combination of diagnosis and treatment in a single nano-platform is named theranostic. In this PhD thesis a theranostic system for osteosarcoma was proposed, composed by a magnetic core, a polymeric coating, and a chemotherapeutic drug. The presence of a specific targeting agent, in this case a monoclonal antibody, provides high specificity to the proposed theranostic system. For the core of the proposed theranostic system, stable aqueous suspensions of superparamagnetic iron oxide nanoparticles with an average diameter of 9 nm were produced. Chitosan-based poly-meric nanoparticles with a hydrodynamic diameter around 150 nm were successfully produced. Incorporation of iron oxide nanoparticles into the polymeric ones increased their hydrodynamic diameter to at least 250 nm. A monoclonal antibody specific for a transmembranar protein (car-bonic anhydrase IX) present in solid tumors was developed by hybridoma technology. Functional hybridomas producing the desired monoclonal antibodies were obtained. The proposed theranostic system functionality was evaluated in separated parts of its components. Uncoated and coated iron oxide nanoparticles with chitosan-based polymers generated heat under the application of an external alternating magnetic field. Uncoated iron oxide nanoparticles sta-bilized with oleic acid were able to enhance contrast in magnetic resonance imaging. Drug deliv-ery studies were conducted in chitosan-based polymeric nanoparticles without and with the in-corporation of iron oxide nanoparticles, demonstrating to be an effective drug delivery platform for doxorubicin. The theranostic system proposed in this PhD thesis is very promising for cancer theranostic, demonstrating to be applicable in solid tumors such as osteosarcoma.