Desenvolvimento de metodologia de análise de indicadores de sustentabilidade como ferramenta para tomada de decisão utilizando lógica fuzzy

Dissertação (Mestrado em Tecnologia Nuclear)

A Fuzzy Decision Strategy for Topic Identification and Dynamic Selection of Language Models

International audience

Sistema inteligente para apoio à decisão na operação de uma malha de escoamento de petróleo

The petroleum production pipeline networks are inherently complex, usually decentralized systems. Strict operational constraints are applied in order to prevent serious problems like environmental disasters or production losses. This paper describes an intelligent system to support decisions in the operation of these networks, proposing a staggering for the pumps of transfer stations that compose them. The intelligent system is formed by blocks which interconnect to process the information and generate the suggestions to the operator. The main block of the system uses fuzzy logic to provide a control based on rules, which incorporate knowledge from experts. Tests performed in the simulation environment provided good results, indicating the applicability of the system in a real oil production environment. The use of the stagger proposed by the system allows a prioritization of the transfer in the network and a flow programming

REAL TIME FUZZY CONTROLLER FOR QUADROTOR STABILITY CONTROL

In this report, we develop an intelligent adaptive neuro-fuzzy controller by using adaptive neuro fuzzy inference system (ANFIS) techniques. We begin by starting with a standard proportional-derivative (PD) controller and use the PD controller data to train the ANFIS system to develop a fuzzy controller. We then propose and validate a method to implement this control strategy on commercial off-the-shelf (COTS) hardware. An analysis is made into the choice of filters for attitude estimation. These choices are limited by the complexity of the filter and the computing ability and memory constraints of the micro-controller. Simplified Kalman filters are found to be good at estimation of attitude given the above constraints. Using model based design techniques, the models are implemented on an embedded system. This enables the deployment of fuzzy controllers on enthusiast-grade controllers. We evaluate the feasibility of the proposed control strategy in a model-in-the-loop simulation. We then propose a rapid prototyping strategy, allowing us to deploy these control algorithms on a system consisting of a combination of an ARM-based microcontroller and two Arduino-based controllers. We then use a combination of the code generation capabilities within MATLAB/Simulink in combination with multiple open-source projects in order to deploy code to an ARM CortexM4 based controller board. We also evaluate this strategy on an ARM-A8 based board, and a much less powerful Arduino based flight controller. We conclude by proving the feasibility of fuzzy controllers on Commercial-off the shelf (COTS) hardware, we also point out the limitations in the current hardware and make suggestions for hardware that we think would be better suited for memory heavy controllers.

Control and Supervision of Wind Energy Conversion Systems

This paper is about a PhD thesis and includes the study and analysis of the performance of an onshore wind energy conversion system. First, mathematical models of a variable speed wind turbine with pitch control are studied, followed by the study of different controller types such as integer-order controllers, fractional-order controllers, fuzzy logic controllers, adaptive controllers and predictive controllers and the study of a supervisor based on finite state machines is also studied. The controllers are included in the lower level of a hierarchical structure composed by two levels whose objective is to control the electric output power around the rated power. The supervisor included at the higher level is based on finite state machines whose objective is to analyze the operational states according to the wind speed. The studied mathematical models are integrated into computer simulations for the wind energy conversion system and the obtained numerical results allow for the performance assessment of the system connected to the electric grid. The wind energy conversion system is composed by a variable speed wind turbine, a mechanical transmission system described by a two mass drive train, a gearbox, a doubly fed induction generator rotor and by a two level converter.

Modelling the effects of bone fragment contact in fracture healing

The fracture healing process is modulated by the mechanical environment created by imposed loads and motion between the bone fragments. Contact between the fragments obviously results in a significantly different stress and strain environment to a uniform fracture gap containing only soft tissue (e.g. haematoma). The assumption of the latter in existing computational models of the healing process will hence exaggerate the inter-fragmentary strain in many clinically-relevant cases. To address this issue, we introduce the concept of a contact zone that represents a variable degree of contact between cortices by the relative proportions of bone and soft tissue present. This is introduced as an initial condition in a two-dimensional iterative finite element model of a healing tibial fracture, in which material properties are defined by the volume fractions of each tissue present. The algorithm governing the formation of cartilage and bone in the fracture callus uses fuzzy logic rules based on strain energy density resulting from axial compression. The model predicts that increasing the degree of initial bone contact reduces the amount of callus formed (periosteal callus thickness 3.1mm without contact, down to 0.5mm with 10% bone in contact zone). This is consistent with the greater effective stiffness in the contact zone and hence, a smaller inter-fragmentary strain. These results demonstrate that the contact zone strategy reasonably simulates the differences in the healing sequence resulting from the closeness of reduction.

Image synthesis based on a model of human vision

Modern computer graphics systems are able to construct renderings of such high quality that viewers are deceived into regarding the images as coming from a photographic source. Large amounts of computing resources are expended in this rendering process, using complex mathematical models of lighting and shading. However, psychophysical experiments have revealed that viewers only regard certain informative regions within a presented image. Furthermore, it has been shown that these visually important regions contain low-level visual feature differences that attract the attention of the viewer. This thesis will present a new approach to image synthesis that exploits these experimental findings by modulating the spatial quality of image regions by their visual importance. Efficiency gains are therefore reaped, without sacrificing much of the perceived quality of the image. Two tasks must be undertaken to achieve this goal. Firstly, the design of an appropriate region-based model of visual importance, and secondly, the modification of progressive rendering techniques to effect an importance-based rendering approach. A rule-based fuzzy logic model is presented that computes, using spatial feature differences, the relative visual importance of regions in an image. This model improves upon previous work by incorporating threshold effects induced by global feature difference distributions and by using texture concentration measures. A modified approach to progressive ray-tracing is also presented. This new approach uses the visual importance model to guide the progressive refinement of an image. In addition, this concept of visual importance has been incorporated into supersampling, texture mapping and computer animation techniques. Experimental results are presented, illustrating the efficiency gains reaped from using this method of progressive rendering. This visual importance-based rendering approach is expected to have applications in the entertainment industry, where image fidelity may be sacrificed for efficiency purposes, as long as the overall visual impression of the scene is maintained. Different aspects of the approach should find many other applications in image compression, image retrieval, progressive data transmission and active robotic vision.

Coordinated road-junction traffic control by dynamic programming

This paper presents a novel approach to road-traffic control for interconnected junctions. With a local fuzzy-logic controller (FLC) installed at each junction, a dynamic-programming (DP) technique is proposed to derive the green time for each phase in a traffic-light cycle. Coordination parameters from the adjacent junctions are also taken into consideration so that organized control is extended beyond a single junction. Instead of pursuing the absolute optimization of traffic delay, this study examines a practical approach to enable the simple implementation of coordination among junctions, while attempting to reduce delays, if possible. The simulation results show that the delay per vehicle can be substantially reduced, particularly when the traffic demand reaches the junction capacity. The implementation of this controller does not require complicated or demanding hardware, and such simplicity makes it a useful tool for offline studies or realtime control purposes.

A new and efficient intelligent collaboration scheme for fashion design

Technology-mediated collaboration process has been extensively studied for over a decade. Most applications with collaboration concepts reported in the literature focus on enhancing efficiency and effectiveness of the decision-making processes in objective and well-structured workflows. However, relatively few previous studies have investigated the applications of collaboration schemes to problems with subjective and unstructured nature. In this paper, we explore a new intelligent collaboration scheme for fashion design which, by nature, relies heavily on human judgment and creativity. Techniques such as multicriteria decision making, fuzzy logic, and artificial neural network (ANN) models are employed. Industrial data sets are used for the analysis. Our experimental results suggest that the proposed scheme exhibits significant improvement over the traditional method in terms of the time–cost effectiveness, and a company interview with design professionals has confirmed its effectiveness and significance.

Current AI in games : a review

As the graphics race subsides and gamers grow weary of predictable and deterministic game characters, game developers must put aside their “old faithful” finite state machines and look to more advanced techniques that give the users the gaming experience they crave. The next industry breakthrough will be with characters that behave realistically and that can learn and adapt, rather than more polygons, higher resolution textures and more frames-per-second. This paper explores the various artificial intelligence techniques that are currently being used by game developers, as well as techniques that are new to the industry. The techniques covered in this paper are finite state machines, scripting, agents, flocking, fuzzy logic and fuzzy state machines decision trees, neural networks, genetic algorithms and extensible AI. This paper introduces each of these technique, explains how they can be applied to games and how commercial games are currently making use of them. Finally, the effectiveness of these techniques and their future role in the industry are evaluated.

A quantum probability perspective on borderline vagueness

The term “vagueness” describes a property of natural concepts, which normally have fuzzy boundaries, admit borderline cases, and are susceptible to Zeno’s sorites paradox. We will discuss the psychology of vagueness, especially experiments investigating the judgment of borderline cases and contradictions. In the theoretical part, we will propose a probabilistic model that describes the quantitative characteristics of the experimental finding and extends Alxatib’s and Pelletier’s (2011) theoretical analysis. The model is based on a Hopfield network for predicting truth values. Powerful as this classical perspective is, we show that it falls short of providing an adequate coverage of the relevant empirical results. In the final part, we will argue that a substan- tial modification of the analysis put forward by Alxatib and Pelletier and its probabilistic pendant is needed. The proposed modification replaces the standard notion of probabilities by quantum probabilities. The crucial phenomenon of borderline contradictions can be explained then as a quantum interference phenomenon.

A semi-supervised graph-based algorithm for detecting outliers in online-social-networks

In this paper, we propose a semi-supervised approach of anomaly detection in Online Social Networks. The social network is modeled as a graph and its features are extracted to detect anomaly. A clustering algorithm is then used to group users based on these features and fuzzy logic is applied to assign degree of anomalous behavior to the users of these clusters. Empirical analysis shows effectiveness of this method.

Effectiveness of eco-driving during queue discharge at urban signalised intersections

This research investigated the effectiveness of using an eco-driving strategy at urban signalised intersections from both the individual driver and the traffic flow perspective. The project included a field driving experiment and a series of traffic simulation investigations. The study found that the prevailing eco-driving strategy has negative impacts on traffic mobility and environmental performance when the traffic is highly congested. An improved eco-driving strategy has been developed to mitigate these negative impacts.

From expert to tasks, expert nursing practice redefined?

Aim The aim of this paper was to explore the concept of expertise in nursing from the perspective of how it relates to current driving forces in health care in which it discusses the potential barriers to acceptance of nursing expertise in a climate in which quantification of value and cost containment run high on agendas. Background Expert nursing practice can be argued to be central to high quality, holistic, individualized patient care. However, changes in government policy which have led to the inception of comprehensive guidelines or protocols of care are in danger of relegating the ‘expert nurse’ to being an icon of the past. Indeed, it could be argued that expert nurses are an expensive commodity within the nursing workforce. Consequently, with this change to the use of clinical guidelines, it calls into question how expert nursing practice will develop within this framework of care. Method The article critically reviews the evidence related to the role of the Expert Nurse in an attempt to identify the key concepts and ideas, and how the inception of care protocols has implications for their role. Conclusion Nursing expertise which focuses on the provision of individualized, holistic care and is based largely on intuitive decision making cannot, should not be reduced to being articulated in positivist terms. However, the dominant power and decision-making focus in health care means that nurses must be confident in articulating the value of a concept which may be outside the scope of knowledge of those with whom they are debating. Relevance to clinical practice The principles of abduction or fuzzy logic may be useful in assisting nurses to explain in terms which others can comprehend, the value of nursing expertise.

Defining the expert ICU nurse

This paper explores the concept of expertise in intensive care nursing practice from the perspective of its relationship to the current driving forces in healthcare. It discusses the potential barriers to acceptance of nursing expertise in a climate in which quantification of value and cost containment run high on agendas. It argues that nursing expertise which focuses on the provision of individualised, holistic care and which is based largely on intuitive decision-making cannot and should not be reduced to being articulated in positivist terms. The principles of abduction or fuzzy logic, derived from computer science, may be useful in assisting nurses to explain in terms, which others can comprehend, the value of nursing expertise.