Finite-element Analysis Of 3 Situations Of Trauma In The Human Edentulous Mandible.

Maxillofacial trauma resulting from falls in elderly patients is a major social and health care concern. Most of these traumatic events involve mandibular fractures. The aim of this study was to analyze stress distributions from traumatic loads applied on the symphyseal, parasymphyseal, and mandibular body regions in the elderly edentulous mandible using finite-element analysis (FEA). Computerized tomographic analysis of an edentulous macerated human mandible of a patient approximately 65 years old was performed. The bone structure was converted into a 3-dimensional stereolithographic model, which was used to construct the computer-aided design (CAD) geometry for FEA. The mechanical properties of cortical and cancellous bone were characterized as isotropic and elastic structures, respectively, in the CAD model. The condyles were constrained to prevent free movement in the x-, y-, and z-axes during simulation. This enabled the simulation to include the presence of masticatory muscles during trauma. Three different simulations were performed. Loads of 700 N were applied perpendicular to the surface of the cortical bone in the symphyseal, parasymphyseal, and mandibular body regions. The simulation results were evaluated according to equivalent von Mises stress distributions. Traumatic load at the symphyseal region generated low stress levels in the mental region and high stress levels in the mandibular neck. Traumatic load at the parasymphyseal region concentrated the resulting stress close to the mental foramen. Traumatic load in the mandibular body generated extensive stress in the mandibular body, angle, and ramus. FEA enabled precise mapping of the stress distribution in a human elderly edentulous mandible (neck and mandibular angle) in response to 3 different traumatic load conditions. This knowledge can help guide emergency responders as they evaluate patients after a traumatic event.

Ciratefi: An RST-invariant template matching with extension to color images

Template matching is a technique widely used for finding patterns in digital images. A good template matching should be able to detect template instances that have undergone geometric transformations. In this paper, we proposed a grayscale template matching algorithm named Ciratefi, invariant to rotation, scale, translation, brightness and contrast and its extension to color images. We introduce CSSIM (color structural similarity) for comparing the similarity of two color image patches and use it in our algorithm. We also describe a scheme to determine automatically the appropriate parameters of our algorithm and use pyramidal structure to improve the scale invariance. We conducted several experiments to compare grayscale and color Ciratefis with SIFT, C-color-SIFT and EasyMatch algorithms in many different situations. The results attest that grayscale and color Ciratefis are more accurate than the compared algorithms and that color-Ciratefi outperforms grayscale Ciratefi most of the time. However, Ciratefi is slower than the other algorithms.

Thermal/mechanical simulation and laboratory fatigue testing of an alternative yttria tetragonal zirconia polycrystal core-veneer all-ceramic layered crown design

This study evaluated the stress levels at the core layer and the veneer layer of zirconia crowns (comprising an alternative core design vs. a standard core design) under mechanical/thermal simulation, and subjected simulated models to laboratory mouth-motion fatigue. The dimensions of a mandibular first molar were imported into computer-aided design (CAD) software and a tooth preparation was modeled. A crown was designed using the space between the original tooth and the prepared tooth. The alternative core presented an additional lingual shoulder that lowered the veneer bulk of the cusps. Finite element analyses evaluated the residual maximum principal stresses fields at the core and veneer of both designs under loading and when cooled from 900 degrees C to 25 degrees C. Crowns were fabricated and mouth-motion fatigued, generating master Weibull curves and reliability data. Thermal modeling showed low residual stress fields throughout the bulk of the cusps for both groups. Mechanical simulation depicted a shift in stress levels to the core of the alternative design compared with the standard design. Significantly higher reliability was found for the alternative core. Regardless of the alternative configuration, thermal and mechanical computer simulations showed stress in the alternative core design comparable and higher to that of the standard configuration, respectively. Such a mechanical scenario probably led to the higher reliability of the alternative design under fatigue.

Intelligent supervisory control system for home devices using a cyber physical approach

Although we have many electric devices at home, there are just few systems to evaluate, monitor and control them. Sometimes users go out and leave their electric devices turned on what can cause energy wasting and dangerous situations. Therefore most of the users may want to know the using states of their electrical appliances through their mobile devices in a pervasive way. In this paper, we propose an Intelligent Supervisory Control System to evaluate, monitor and control the use of electric devices in home, from outside. Because of the transferring data to evaluate, monitor and control user's location and state of home (ex. nobody at home) may be opened to attacks leading to dangerous situations. In our model we include a location privacy module and encryption module to provide security to user location and data. Intelligent Supervising Control System gives to the user the ability to manage electricity loads by means of a multi-agent system involving evaluation, monitoring, control and energy resource agents.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

Ensemble: an e-learning framework

E-Learning frameworks are conceptual tools to organize networks of elearning services. Most frameworks cover areas that go beyond the scope of e-learning, from course to financial management, and neglects the typical activities in everyday life of teachers and students at schools such as the creation, delivery, resolution and evaluation of assignments. This paper presents the Ensemble framework - an e-learning framework exclusively focused on the teaching-learning process through the coordination of pedagogical services. The framework presents an abstract data, integration and evaluation model based on content and communications specifications. These specifications must base the implementation of networks in specialized domains with complex evaluations. In this paper we specialize the framework for two domains with complex evaluation: computer programming and computer-aided design (CAD). For each domain we highlight two Ensemble hotspots: data and evaluations procedures. In the former we formally describe the exercise and present possible extensions. In the latter, we describe the automatic evaluation procedures.

Strategic bidding in electricity markets: an agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Adaptive learning in agents behaviour: A framework for electricity markets simulation

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Aquaponics System - An EPS@ISEP 2014 Spring Project

The goal of this project, one of the proposals of the EPS@ISEP 2014 Spring, was to develop an Aquaponics System. Over recent years Aquaponics systems have received increased attention due to its possibilities in helping reduce strain on resources within 1st and 3rd world countries. Aquaponics is the combination of Hydroponics and Aquaculture and mimics a natural environment in order to successfully apply and enhance the understanding of natural cycles within an indoor process. By using this knowledge of natural cycles it was possible to create a system with the capabilities similar to that of a natural environment with the benefits of electronic adaptions to enhance the overall efficiency of the system. The multinational team involved in its development was composed of five students, from five countries and fields of study. This paper covers their solution, involving overall design, the technology involved and the benefits it could bring to the current market. The team was able to achieve the final rendered Computer Aided Design (CAD) drawings, successfully performed all the electronic testing, and designed a solution under budget. Furthermore, the solution presented was deeply studied from the sustainability viewpoint and the team also developed a product specific marketing plan. Finally, the students involved in this project obtained new knowledge and skills.

Developing an aquaponics system to learn sustainability and social compromise skills

The goal of this project, one of the proposals of the EPS@ISEP Spring 2014, was to develop an Aquaponics System. Over recent years Aquaponics systems have received increased attention since they contribute to reduce the strain on resources within 1st and 3rd world countries. Aquaponics is the combination of Hydroponics and Aquaculture, mimicking a natural environment in order to successfully apply and enhance the understanding of natural cycles within an indoor process. Using this knowledge of natural cycles, it was possible to create a system with capabilities similar to that of a natural environment with the support of electronics, enhancing the overall efficiency of the system. The multinational team involved in the development of this system was composed of five students from five countries and fields of study. This paper describes their solution, including the overall design, the technology involved and the benefits it can bring to the current market. The team was able to design and render the Computer Aided Design (CAD) drawings of the prototype, assemble all components, successfully test the electronics and comply with the budget. Furthermore, the designed solution was supported by a product sustainability study and included a specific marketing plan. Last but not least, the students enrolled in this project obtained new multidisciplinary knowledge and increased their team work and cross-cultural communication skills.

Coalition of distributed generation units to Virtual Power Players - a game theory approach

Smart Grids (SGs) have emerged as the new paradigm for power system operation and management, being designed to include large amounts of distributed energy resources. This new paradigm requires new Energy Resource Management (ERM) methodologies considering different operation strategies and the existence of new management players such as several types of aggregators. This paper proposes a methodology to facilitate the coalition between distributed generation units originating Virtual Power Players (VPP) considering a game theory approach. The proposed approach consists in the analysis of the classifications that were attributed by each VPP to the distributed generation units, as well as in the analysis of the previous established contracts by each player. The proposed classification model is based in fourteen parameters including technical, economical and behavioural ones. Depending of the VPP strategies, size and goals, each parameter has different importance. VPP can also manage other type of energy resources, like storage units, electric vehicles, demand response programs or even parts of the MV and LV distribution network. A case study with twelve VPPs with different characteristics and one hundred and fifty real distributed generation units is included in the paper.

Thermal conditions affecting heat transfer in FDM/FFE: a contribution towards the numerical modelling of the process

The performance of parts produced by Free Form Extrusion (FFE), an increasingly popular additive manufacturing technique, depends mainly on their dimensional accuracy, surface quality and mechanical performance. These attributes are strongly influenced by the evolution of the filament temperature and deformation during deposition and solidification. Consequently, the availability of adequate process modelling software would offer a powerful tool to support efficient process set-up and optimisation. This work examines the contribution to the overall heat transfer of various thermal phenomena developing during the manufacturing sequence, including convection and radiation with the environment, conduction with support and between adjacent filaments, radiation between adjacent filaments and convection with entrapped air. The magnitude of the mechanical deformation is also studied. Once this exercise is completed, it is possible to select the material properties, process variables and thermal phenomena that should be taken in for effective numerical modelling of FFE.

Evolução urbana de Braga na Época Moderna: espaços públicos e períferia

Relatório de estágio de mestrado em Arqueologia

ICTINEUAUV wins the First SAUC-E competition

A pioneer team of students of the University of Girona decided to design and develop an autonomous underwater vehicle (AUV) called ICTINEU-AUV to face the Student Autonomous Underwater Challenge-Europe (SAUC-E). The prototype has evolved from the initial computer aided design (CAD) model to become an operative AUV in the short period of seven months. The open frame and modular design principles together with the compatibility with other robots previously developed at the lab have provided the main design philosophy. Hence, at the robot's core, two networked computers give access to a wide set of sensors and actuators. The Gentoo/Linux distribution was chosen as the onboard operating system. A software architecture based on a set of distributed objects with soft real time capabilities was developed and a hybrid control architecture including mission control, a behavioural layer and a robust map-based localization algorithm made ICTINEU-AUV the winning entry