Intelligent system for interaction with virtual characters based on volumetric sensors

Dissertação de Mestrado, Engenharia Elétrica e Eletrónica, Instituto Superior de Engenharia, Universidade do Algarve, 2015

Implementation of an intelligent sensor for measurement and prediction of solar radiation and atmospheric temperature

Dissertação de mestrado, Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2011

Avaliação in vitro da adaptação marginal e interna de coroas de cerâmica e resina composta fabricadas com o sistema CAD/CAM utilizando duas câmeras intraorais de moldagem digital

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Ciências da Saúde, Programa de Pós-Graduação em Ciências da Saúde, 2015.

Design gráfico da pluma de contaminação por compostos orgânicos voláteiss utilizando software CAD na investigação de passivo ambiental em um posto revendedor de combustíveis em Natal/RN

Among the potentially polluting economic activities that compromise the quality of groundwater are the gas stations. The city of Natal has about 120 gas stations, of which only has an environmental license for operation. Discontinuities in the offices were notified by the Public Ministry of Rio Grande do Norte to carry out the environmental adaptations, among which is the investigation of environmental liabilities. The preliminary and confirmatory stages of this investigation consisted in the evaluation of soil gas surveys with two confirmatory chemical analysis of BTEX, PAH and TPH. To get a good evaluation and interpretation of results obtained in the field, it became necessary three-dimensional representation of them. We used a CAD software to graph the equipment installed in a retail service station fuel in Natal, as well as the plumes of contamination by volatile organic compounds. The tool was concluded that contamination is not located in the current system of underground storage of fuel development, but reflects the historical past in which tanks were removed not tight gasoline and diesel

Interfaz AIS para aplicaciones en CAD/CAM/CG

Los modeladores geométricos más comunes en el mercado ofrecen, además de sus servicios de modelado, una API (Application Programming Interface) que permite la construcción de aplicaciones o software cliente -- Estas aplicaciones aprovechan los servicios básicos del modelador para proveer tareas específicas -- Sin embargo las diferencias entre API´s de distintos modeladores imposibilita el intercambio del software cliente entre ellos -- Application Interface Specification -AIS- es una API genérica para ser usada por aplicaciones cliente de los modeladores geométricos -- Este artículo reporta la implementación de AIS sobre AutoCAD® y MicroStation® y discute aspectos importantes de dicha implementación -- Además presenta una aplicación cliente neutra que habla lenguaje AIS y por lo tanto se ejecuta transparentemente sobre los dos modeladores -- AIS se presenta como una alternativa económica para escribir aplicaciones de CAD/CAM/CG -- Futuros desarrollos incluyen la implementación de AIS para labores gráficas y/o de base de datos

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

Hybrid Power System Intelligent Operation and Protection Involving Distributed Architectures and Pulsed Loads

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system’s dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness.^ Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.^ Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems.^ To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].^

Hybrid power system intelligent operation and protection involving plug-in electric vehicles

Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. ^ The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. ^ The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.^

Do intelligent heating controls out-smart ordinary users?

Nearly a third of UK gas and electricity is used in homes, of which 80% is for space heating and hot water provision. Rising consumer bills, concerns about climate change and the surge in personal digital technology use has provoked the development of intelligent domestic heating controls. Whilst the need for having suitable control of the home heating system is essential for reducing domestic energy use, these heating controls rely on appropriate user interaction to achieve a saving and it is unclear whether these ‘smart’ heating controls enhance the use of domestic heating or reduce energy demand. This paper describes qualitative research undertaken with a small sample of UK householders to understand how people use new heating controls installed in their homes and what the requirements are for improved smart heating control design. The paper identifies, against Nielsen’s usability heuristics, the divergence between the householder’s use, understanding and expectations of the heating system and the actual design of the system. Digital and smart heating control systems should be designed to maximise usability so that they can be effectively used for efficient heating control by all users. The research highlights the need for development of new systems to readdress the needs of users and redefine the system requirements.

Intelligent outcome measures in liaison psychiatry:essential even if not desirable. Commentary on... a multidimensional Framework for Routine Outcome Measurement in Liaison Psychiatry (FROM-LP)

Service development is guided by outcome measures that inform service commissioners and providers. Those in liaison psychiatry should be encouraged to develop a positive approach that integrates the collection of outcome measures into everyday clinical practice. The Framework for Routine Outcome Measurement in Liaison Psychiatry (FROM-LP) is a very useful tool to measure service quality and clinical effectiveness, using a combination of clinician-rated and patient-rated outcome measures and patient-rated experience measures. However, it does not include measures of cost-effectiveness or training activities. The FROM-LP is a significant step towards developing nationally unified outcome measures.

FY2010 Annual Report Research, Intelligent Transportation Systems, and Technology Transfer Activities, October 18, 2011

Transportation research makes a difference for Iowans and the nation. Implementation of cost effective research projects contributes to a transportation network that is safer, more efficient, and longer lasting. Working in cooperation with our partners from universities, industry, other states, and FHWA, as well as participation in the Transportation Research Board (TRB), provides benefits for every facet of the DOT. This allows us to serve our communities and the traveling public more effectively. Pooled fund projects allow leveraging of funds for higher returns on investments. In 2010, Iowa led fifteen active pooled fund studies, participated in twenty-two others, and was wrapping-up, reconciling, and closing out an additional 6 Iowa Led pooled fund studies. In addition, non-pooled fund SPR projects included approximately 20 continued, 9 new, and over a dozen reoccurring initiatives such as the technical transfer/training program. Additional research is managed and conducted by the Office of Traffic and Safety and other departments in the Iowa DOT.

Revêtement intelligent à base des silices mésoporeuses fonctionnalisées pour le relargage stimulé d’agents antimicrobiens

Les biofilms bactériens sont composés d’organismes unicellulaires vivants au sein d’une matrice protectrice, formée de macromolécules naturelles. Des biofilms non désirés peuvent avoir un certain nombre de conséquences néfastes, par exemple la diminution du transfert de chaleur dans les échangeurs de chaleurs, l’obstruction de membranes poreuses, la contamination des surfaces coques de navires, etc. Par ailleurs, les bactéries pathogènes qui prolifèrent dans un biofilm posent également un danger pour la santé s’ils croissent sur des surfaces médicales synthétiques comme des implants biomédicaux, cathéters ou des lentilles de vue. De plus, la croissance sur le tissu naturel par certaines souches des bactéries peut être fatale, comme Pseudomonas aeruginosa dans les poumons. Cependant, la présence de biofilms reste difficile à traiter, car les bactéries sont protégées par une matrice extracellulaire. Pour tenter de remédier à ces problèmes, nous proposons de développer une surface antisalissure (antifouling) qui libère sur demande des agents antimicrobiens. La proximité et la disposition du système de relargage placé sous le biofilm, assureront une utilisation plus efficace des molécules antimicrobiennes et minimiseront les effets secondaires de ces dernières. Pour ce faire, nous envisageons l’utilisation d’une couche de particules de silice mésoporeuses comme agents de livraison d’agents antimicrobiens. Les nanoparticules de silice mésoporeuses (MSNs) ont démontré un fort potentiel pour la livraison ciblée d’agents thérapeutiques et bioactifs. Leur utilisation en nano médecine découle de leurs propriétés de porosité intéressantes, de la taille et de la forme ajustable de ces particules, de la chimie de leur surface et leur biocompatibilité. Ces propriétés offrent une flexibilité pour diverses applications. De plus, il est possible de les charger avec différentes molécules ou biomolécules (de tailles variées, allant de l’ibuprofène à l’ARN) et d’exercer un contrôle précis des paramètres d’adsorption et des cinétiques de relargage (désorption). Mots Clés : biofilms, nanoparticules de silice mésoporeuses, microfluidique, surface antisalissure.

Gestion de contexte dans un habitat intelligent à base d’ontologie : modélisation, implantation et validation

Le laboratoire DOMUS développe des applications sensibles au contexte dans une perspective d’intelligence ambiante. L’architecture utilisée présentement pour gérer le contexte a atteint ses limites en termes de capacité d’évoluer, d’intégration de nouvelles sources de données et de nouveaux capteurs et actionneurs, de capacité de partage entre les applications et de capacité de raisonnement. Ce projet de recherche a pour objectif de développer un nouveau modèle, un gestionnaire de contexte et de proposer une architecture pour les applications d’assistance installées dans un habitat intelligent. Le modèle doit répondre aux exigences suivantes : commun, abstrait, évolutif, décentralisé, performant et une accessibilité uniforme. Le gestionnaire du contexte doit permettre de gérer les événements et offrir des capacités de raisonnement sur les données et le contexte. La nouvelle architecture doit simplifier le développement d’applications d’assistance et la gestion du contexte. Les applications doivent pouvoir se mettre à jour si le modèle de données évolue dans le temps sans nécessiter de modification dans le code source. Le nouveau modèle de données repose sur une ontologie définie avec le langage OWL 2 DL. L’architecture pour les applications d’assistance utilise le cadre d’applications Apache Jena pour la gestion des requêtes SPARQL et un dépôt RDF pour le stockage des données. Une bibliothèque Java a été développée pour gérer la correspondance entre le modèle de données et le modèle Java. Le serveur d’événements est basé sur le projet OpenIoT et utilise un dépôt RDF. Il fournit une API pour la gestion des capteurs / événements et des actionneurs / actions. Les choix d’implémentation et l’utilisation d’une ontologie comme modèle de données et des technologies du Web sémantique (OWL, SPARQL et dépôt RDF) pour les applications d’assistance dans un habitat intelligent ont été validés par des tests intensifs et l’adaptation d’applications déjà existantes au laboratoire. L’utilisation d’une ontologie a pour avantage une intégration des déductions et du raisonnement directement dans le modèle de données et non au niveau du code des applications.

Curva de retenção de água no solo e capacidade de água disponível (CAD) em seis vinhedos da Campanha Gaúcha.

2015