Consumer confidence and economic growth: case studies of Jamaica and Trinidad and Tobago

Includes bibliography

Implementação de um sistema para geração e avaliação de movimentos em pacientes hemiplégicos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

L3-arpsec - módulo seguro para controle e proteção do protocolo de resolução de endereços em redes definidas por software

Pós-graduação em Engenharia Elétrica - FEIS

Processos de auto-regulação no curso de vida: controle primário e controle secundário

Este artigo discute conceitos relevantes à perspectiva do curso de vida, porém pouco difundidos no Brasil: controle primário e controle secundário. O primeiro se refere aos esforços que o indivíduo empreende para adaptar o ambiente às suas necessidades; o segundo, para se adaptar ao ambiente. Apresenta-se a formulação original dos conceitos como modelo de dois processos de controle, em oposição a modelos de processo único, como o do desamparo aprendido. Em seguida, discute-se revisão conceitual que trouxe modificação e ampliação para estes construtos, concebendo-os em um modelo bidimensional que articula controle primário e secundário com os conceitos de seleção e compensação. Nesse processo, apresentam-se contribuições no intuito de estimular a reflexão e expandir a discussão teórico-conceitual que envolve estes construtos.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.

Integrated care in patients with schizophrenia: results of trials published between 2011 and 2013 focusing on effectiveness and efficiency

Purpose of review: Overview on integrated care trials focusing on effectiveness and efficiency published from 2011 to 2013. Recent findings: Eight randomized controlled trials (RCTs) and 21 non-RCT studies were published from 2011 to 2013. Studies differed in several methodological aspects such as study population, psychotherapeutic approaches used, outcome parameters, follow-up times, fidelities, and implementation of the integrated care model and the nation-specific healthcare context with different control conditions. This makes it difficult to draw firm conclusions. Most studies demonstrated relevant improvements regarding symptoms (P = 0.001) and functioning (P = 0.01), quality of life (P = 0.01), adherence (P <0.05) and patient's satisfaction (P = 0.01), and reduction of caregiver's stress (P < 0.05). Mean total costs were favoring or at least equalizing costs but with positive effects found on subjective health favoring integrated care models. Summary: There is an increasing interest in the effectiveness and efficiency of integrated care models in patients with mental disorders, specifically in those with severe and persistent mental illness. To increase generalizability, future trials should exactly describe rationales and content of integrated care model and control conditions.

Engineering an Ontology for Autonomous Systems - The OASys Ontology

This paper describes the development of an ontology for autonomous systems, as the initial stage of a research programe on autonomous systems’ engineering within a model-based control approach. The ontology aims at providing a unified conceptual framework for the autonomous systems’ stakeholders, from developers to software engineers. The modular ontology contains both generic and domain-specific concepts for autonomous systems description and engineering. The ontology serves as the basis in a methodology to obtain the autonomous system’s conceptual models. The objective is to obtain and to use these models as main input for the autonomous system’s model-based control system.

Desenvolvimento de um controlador preditivo estocástico para processos da indústria química.

O sucesso de estratégias de controle preditivo baseado em modelo (MPC, na sigla em inglês) tanto em ambiente industrial quanto acadêmico tem sido marcante. No entanto, ainda há diversas questões em aberto na área, especialmente quando a hipótese simplificadora de modelo perfeito é abandonada. A consideração explícita de incertezas levou a importantes progressos na área de controle robusto, mas esta ainda apresenta alguns problemas: a alta demanda computacional e o excesso de conservadorismo são questões que podem ter prejudicado a aplicação de estratégias de controle robusto na prática. A abordagem de controle preditivo estocástico (SMPC, na sigla em inglês) busca a redução do conservadorismo através da incorporação de informação estatística dos ruídos. Como processos na indústria química sempre estão sujeito a distúrbios, seja devido a diferenças entre planta e modelo ou a distúrbios não medidos, está técnica surge como uma interessante alternativa para o futuro. O principal objetivo desta tese é o desenvolvimento de algoritmos de SMPC que levem em conta algumas das especificidades de tais processos, as quais não foram adequadamente tratadas na literatura até o presente. A contribuição mais importante é a inclusão de ação integral no controlador através de uma descrição do modelo em termos de velocidade. Além disso, restrições obrigatórias (hard) nas entradas associadas a limites físicos ou de segurança e restrições probabilísticas nos estados normalmente advindas de especificações de produtos também são consideradas na formulação. Duas abordagens foram seguidas neste trabalho, a primeira é mais direta enquanto a segunda fornece garantias de estabilidade em malha fechada, contudo aumenta o conservadorismo. Outro ponto interessante desenvolvido nesta tese é o controle por zonas de sistemas sujeitos a distúrbios. Essa forma de controle é comum na indústria devido à falta de graus de liberdade, sendo a abordagem proposta a primeira contribuição da literatura a unir controle por zonas e SMPC. Diversas simulações de todos os controladores propostos e comparações com modelos da literatura são exibidas para demonstrar o potencial de aplicação das técnicas desenvolvidas.

A contribution on modeling methodologies for multibody systems.

Multibody System Dynamics has been responsible for revolutionizing Mechanical Engineering Design by using mathematical models to simulate and optimize the dynamic behavior of a wide range of mechanical systems. These mathematical models not only can provide valuable informations about a system that could otherwise be obtained only by experiments with prototypes, but also have been responsible for the development of many model-based control systems. This work represents a contribution for dynamic modeling of multibody mechanical systems by developing a novel recursive modular methodology that unifies the main contributions of several Classical Mechanics formalisms. The reason for proposing such a methodology is to motivate the implementation of computational routines for modeling complex multibody mechanical systems without being dependent on closed source software and, consequently, to contribute for the teaching of Multibody System Dynamics in undergraduate and graduate levels. All the theoretical developments are based on and motivated by a critical literature review, leading to a general matrix form of the dynamic equations of motion of a multibody mechanical system (that can be expressed in terms of any set of variables adopted for the description of motions performed by the system, even if such a set includes redundant variables) and to a general recursive methodology for obtaining mathematical models of complex systems given a set of equations describing the dynamics of each of its uncoupled subsystems and another set describing the constraints among these subsystems in the assembled system. This work also includes some discussions on the description of motion (using any possible set of motion variables and admitting any kind of constraint that can be expressed by an invariant), and on the conditions for solving forward and inverse dynamics problems given a mathematical model of a multibody system. Finally, some examples of computational packages based on the novel methodology, along with some case studies, are presented, highlighting the contributions that can be achieved by using the proposed methodology.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

Aplicações baseadas em geolocalizações para gestão de instalações desportivas: exemplo de utilização da API da GOOGLE Maps no concelho de Guimarães

O contexto tecnológico em que vivemos é uma realidade. E a tendência é para ser assim também no futuro. Cada vez mais. É o caso das representações de locais e entidades em mapas digitais na web. Na visão de Crocker (2014), esta tendência é ainda mais acentuada, no âmbito das aplicações móveis, como mostram as mais diversas location-based applications. No setor do desporto e da respetiva gestão nem sempre foi fácil desenvolver aplicações, recorrendo a este tipo de representações espaciais. A tecnologia não era fácil e o know-how não era adequadamente qualificado. Mas, as empresas fornecedoras de tecnologia geoespacial simplificaram o desenvolvimento de aplicações web nesta área, através da utilização de application programming interfaces (API). Como refere Svennerberg (2010), estas API’s servem de interface entre um serviço proporcionado por uma empresa, caso da Google Maps (2013) e uma aplicação web ou móvel que utiliza esses serviços. Foi com este objetivo que desenvolvemos uma aplicação web, utilizando as metodologias próprias neste domínio, como a framework de Zachman (2009), tal como foi originalmente adaptada por Whitten e Bentley (2005), onde um dos módulos é precisamente a representação de espaços desportivos, recorrendo à utilização dos serviços da Google Maps. Para além disso, toda a aplicação é suportada numa abordagem Model-View-Control (MVC). Para conseguir representar as instalações desportivas num mapa, criámos uma base de dados MySQL, com dados de longitude e latitude, de cada instalação desportiva. Através de JavaScript criou-se o mapa propriamente dito, indicando o tipo (mapa de estradas, satélite ou street view) e as respetivas opções (nível de zoom, alinhamento, controlo de interface e posicionamente, entre muitas outras opções). O passo seguinte consistiu em passar os dados para o frontend da aplicação web. Para isso, recorreu-se à integração do PHP com as livrarias externas de código JavaSrcipt, criadas especificamente para o efeito (caso da MarkerManager). A implementação destas funcionalidades permite georeferenciar todos os tipos e géneros de espaços desportivos de um concelho, região ou País. Obteve-se ainda know-how, background e massa crítica, para o desenvolvimento de novas funcionalidades. A sua utilização em dispositivos móveis é outra das possibilidades atualmente já em desenvolvimento.

A Study of Shallow Groundwater Migration through Anthropogenic Fill along a Seawall

This report provides the findings and opinions of a historical document review, hydraulic balance calculation, and proposed additional study for a property that was historically used as a bulk petroleum storage and distribution facility. The property lies along the base, west, of a heavily vegetated bluff with a tidally influenced body of water west-adjacent to the property. The western portion of the property is bounded by a seawall spanning approximately 3,200 linear feet trending north-south. The seawall’s construction details are not known, save for a 225-foot section of driven sheet pile wall located within the northern portion of the property’s seawall. Due to the presence of petroleum hydrocarbons in soil and groundwater at the property, a cleanup action for the property will likely be overseen by the state regulatory agency. The property is currently undergoing remedial investigation in an effort to identify the lateral and vertical extent in which contaminants at the property have come to be located, also known as the “site” as defined by the Model Toxics Control Act (MTCA). The majority of the property bounded within the seawall area has been characterized; however, the shoreline sediments located immediately west-adjacent of the seawall have not been properly delineated. Identifying the bounds of the site to the west within sediment is pivotal for the purposes of the remedial investigation. Since the west-adjacent shoreline is so extensive, conducting a complete sediment sampling event along the entire shoreline would be cost-prohibitive due to analytical costs and logistical issues at the property. Because of the extensive nature of the shoreline, it would greatly benefit the client and project to focus sampling efforts at areas of greater risk for contaminants along the shoreline by identifying potential preferential pathways for contaminants to migrate off of the property and into adjacent shoreline sediments. The review of historical studies of the property yielded some useful information; however much of the findings included within the historical studies were lacking original raw data, therefore limiting the information obtained. The calculated hydraulic balance for the property yielded a relatively large surplus of recharge to groundwater after precipitation events, reinforcing the concept that contaminant have potentially historically, and currently, been migrating into the adjacent shoreline through preferential pathways along the seawall. Due to the limitation within the historical studies for the property as well as the groundwater recharge identified in the hydraulic balance, an additional study was proposed in an effort to provide additional aquifer characteristics along the seawall, and the ability to observe flow propagation at and proximate to the seawall in two-dimensions through time without the need to piece separate studies together. This proposed study includes a single simultaneous tidal study which comprises select monitoring points along the seawall. This report has identified the need for additional data that can be collected through available avenues for the property based upon the client’s desires and project needs. Ultimately, the proposed additional study is suggested based upon its relatively low capital investment, and ability meet the requirements relevant to the specific project needs and scope. Assuming preferential pathways are identified through the additional study proposed within this report, a representative and cost-effective sediment sampling plan can then be put in place in an effort to define the site.

Ethanol prevents NMDA receptor reduction by maternal separation in neonatal rat hippocampus

We measured the effects of ethanol on glutamate receptor levels in the hippocampus of neonatal Wistar rats using a vapor chamber model. Two control groups were used; a normal suckle group and a maternal separation group. Levels of NMDA receptors were not significantly altered in ethanol-treated animals compared to the normal suckle control group, as shown by [H-3]MK-801 binding and Western blot analysis. However, MK-801 binding and NR1 subunit immunoreactivity were greatly reduced in the hippocampus of separation control animals. Neither ethanol treatment nor maternal separation altered levels of GluR1 or GluR2(4). These results have serious implications for the importance of maternal contact for normal brain development.

Neural Network Based Approach for Developing the Enterprise Strategy

Modern enterprises work in highly dynamic environment. Thus, the developing of company strategy is of crucial importance. It determines the surviving of the enterprise and its evolution. Adapting the desired management goal in accordance with the environment changes is a complex problem. In the present paper, an approach for solving this problem is suggested. It is based on predictive control philosophy. The enterprise is modelled as a cybernetic system and the future plant response is predicted by a neural network model. The predictions are passed to an optimization routine, which attempts to minimize the quadratic performance criterion.

Otimização do sistema de supervisão e controle de uma planta de tratamento de resíduos utilizando plasma

A major and growing problems faced by modern society is the high production of waste and related effects they produce, such as environmental degradation and pollution of various ecosystems, with direct effects on quality of life. The thermal treatment technologies have been widely used in the treatment of these wastes and thermal plasma is gaining importance in processing blanketing. This work is focused on developing an optimized system of supervision and control applied to a processing plant and petrochemical waste effluents using thermal plasma. The system is basically composed of a inductive plasma torch reactors washing system / exhaust gases and RF power used to generate plasma. The process of supervision and control of the plant is of paramount importance in the development of the ultimate goal. For this reason, various subsidies were created in the search for greater efficiency in the process, generating events, graphics / distribution and storage of data for each subsystem of the plant, process execution, control and 3D visualization of each subsystem of the plant between others. A communication platform between the virtual 3D plant architecture and a real control structure (hardware) was created. The goal is to use the concepts of mixed reality and develop strategies for different types of controls that allow manipulating 3D plant without restrictions and schedules, optimize the actual process. Studies have shown that one of the best ways to implement the control of generation inductively coupled plasma techniques is to use intelligent control, both for their efficiency in the results is low for its implementation, without requiring a specific model. The control strategy using Fuzzy Logic (Fuzzy-PI) was developed and implemented, and the results showed satisfactory condition on response time and viability