983 resultados para Conventional matching networks


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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.

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With the recent advances in technology and miniaturization of devices such as GPS or IMU, Unmanned Aerial Vehicles became a feasible platform for a Remote Sensing applications. The use of UAVs compared to the conventional aerial platforms provides a set of advantages such as higher spatial resolution of the derived products. UAV - based imagery obtained by a user grade cameras introduces a set of problems which have to be solved, e. g. rotational or angular differences or unknown or insufficiently precise IO and EO camera parameters. In this work, UAV - based imagery of RGB and CIR type was processed using two different workflows based on PhotoScan and VisualSfM software solutions resulting in the DSM and orthophoto products. Feature detection and matching parameters influence on the result quality as well as a processing time was examined and the optimal parameter setup was presented. Products of the both workflows were compared in terms of a quality and a spatial accuracy. Both workflows were compared by presenting the processing times and quality of the results. Finally, the obtained products were used in order to demonstrate vegetation classification. Contribution of the IHS transformations was examined with respect to the classification accuracy.

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This work models the competitive behaviour of individuals who maximize their own utility managing their network of connections with other individuals. Utility is taken as a synonym of reputation in this model. Each agent has to decide between two variables: the quality of connections and the number of connections. Hence, the reputation of an individual is a function of the number and the quality of connections within the network. On the other hand, individuals incur in a cost when they improve their network of contacts. The initial value of the quality and number of connections of each individual is distributed according to an initial (given) distribution. The competition occurs over continuous time and among a continuum of agents. A mean field game approach is adopted to solve the model, leading to an optimal trajectory for the number and quality of connections for each individual.

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Introduction Trypanosoma cruzi, a flagellated protozoan, is the etiologic agent of Chagas disease, and it is estimated that approximately 5 million people in Brazil are infected with this parasite. This work aimed to compare the current diagnostic methods for Chagas disease, including conventional serological (IFAT and ELISA) and molecular techniques (PCR), to introduce PCR as an auxiliary technique. Methods A total of 106 chagasic patients were evaluated: 88 from endemic areas of Parana, 6 from São Paulo, 3 from Minas Gerais, 3 from Rio Grande do Sul, 1 from Bahia and 5 from the Santa Catarina T. cruzi outbreak. The samples were analyzed by conventional serological methods (IFAT, ELISA), hemoculture and PCR to confirm Chagas disease. Results When IFAT was used to determine antibody levels, the sensitivity was 81.7% for patients with the cardiac form of the disease and 100% for the other clinical forms. In contrast, ELISA showed 84% sensitivity and 100% specificity. The use of serological and molecular techniques and their implications for the diagnosis of Chagas disease in non-endemics area are discussed. Conclusions PCR constitutes an excellent support methodology for the laboratory diagnosis of Chagas disease due to its high sensitivity and specificity.

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Introduction Collaboration is one of the defining features of contemporary scientific research, and it is particularly important with regard to neglected diseases that primarily affect developing countries. Methods The present study has identified publications on leishmaniasis in the Medline database from 1945 to 2010, analyzing them according to bibliometric indicators and statistics from social network analysis. Examining aspects such as scientific production, diachronic evolution, and collaboration and configuration of the research groups in the field, we have considered the different types of Leishmania studied and the institutional affiliation and nationality of the authors. Results Seven-hundred and thirty-five authors participate in 154 prominent research clusters or groups. Although the most predominant and consolidated collaborations are characterized by members from the same country studying the same type of Leishmania, there are also notable links between authors from different countries or who study different clinical strains of the disease. Brazil took the lead in this research, with numerous Brazilian researchers heading different clusters in the center of the collaboration network. Investigators from the USA, India, and European countries, such as France, Spain, the United Kingdom, and Italy, also stand out within the network. Conclusions Research should be fostered in countries such as Bangladesh, Nepal, Sudan, and Ethiopia, where there is a high prevalence of different forms of the disease but limited research development with reference authors integrated into the collaboration networks.

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In-Band Full-DupleX (IB-FDX) is defined as the ability for nodes to transmit and receive signals simultaneously on the same channel. Conventional digital wireless networks do not implement it, since a node’s own transmission signal causes interference to the signal it is trying to receive. However, recent studies attempt to overcome this obstacle, since it can potentially double the spectral efficiency of current wireless networks. Different mechanisms exist today that are able to reduce a significant part of the Self- Interference (SI), although specially tuned Medium Access Control (MAC) protocols are required to optimize its use. One of IB-FDX’s biggest problems is that the nodes’ interference range is extended, meaning the unusable space for other transmissions and receptions is broader. This dissertation proposes using MultiPacket Reception (MPR) to address this issue and adapts an already existing Single-Carrier with Frequency-Domain Equalization (SC-FDE) receiver to IB-FDX. The performance analysis suggests that MPR and IB-FDX have a strong synergy and are able to achieve higher data rates, when used together. Using analytical models, the optimal transmission patterns and transmission power were identified, which maximize the channel capacity with the minimal energy consumption. This was used to define a new MAC protocol, named Full-duplex Multipacket reception Medium Access Control (FM-MAC). FM-MAC was designed for a single-hop cellular infrastructure, where the Access Point (AP) and the terminals implement both IB-FDX and MPR. It divides the coverage range of the AP into a closer Full-DupleX (FDX) zone and a farther Half-DupleX (HDX) zone and adds a tunable fairness mechanism to avoid terminal starvation. Simulation results show that this protocol provides efficient support for both HDX and FDX terminals, maximizing its capacity when more FDX terminals are used.

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This research addresses the problem of creating interactive experiences to encourage people to explore spaces. Besides the obvious spaces to visit, such as museums or art galleries, spaces that people visit can be, for example, a supermarket or a restaurant. As technology evolves, people become more demanding in the way they use it and expect better forms of interaction with the space that surrounds them. Interaction with the space allows information to be transmitted to the visitors in a friendly way, leading visitors to explore it and gain knowledge. Systems to provide better experiences while exploring spaces demand hardware and software that is not in the reach of every space owner either because of the cost or inconvenience of the installation, that can damage artefacts or the space environment. We propose a system adaptable to the spaces, that uses a video camera network and a wi-fi network present at the space (or that can be installed) to provide means to support interactive experiences using the visitor’s mobile device. The system is composed of an infrastructure (called vuSpot), a language grammar used to describe interactions at a space (called XploreDescription), a visual tool used to design interactive experiences (called XploreBuilder) and a tool used to create interactive experiences (called urSpace). By using XploreBuilder, a tool built of top of vuSpot, a user with little or no experience in programming can define a space and design interactive experiences. This tool generates a description of the space and of the interactions at that space (that complies with the XploreDescription grammar). These descriptions can be given to urSpace, another tool built of top of vuSpot, that creates the interactive experience application. With this system we explore new forms of interaction and use mobile devices and pico projectors to deliver additional information to the users leading to the creation of interactive experiences. The several components are presented as well as the results of the respective user tests, which were positive. The design and implementation becomes cheaper, faster, more flexible and, since it does not depend on the knowledge of a programming language, accessible for the general public.

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Urinary symptoms occur in 19% of human T-cell lymphotropic virus type 1 (HTLV-1)-infected patients who do not fulfill criteria for HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) and in almost 100% of HAM/TSP patients. Few studies have evaluated therapies for overactive bladder (OAB) caused by HTLV-1 infection. This case report describes the effect of onabotulinum toxin A on the urinary manifestations of three patients with HAM/TSP and OAB symptoms. The patients were intravesically administered 200 units of Botox®. Their incontinence episodes improved, and their OAB symptoms scores (OABSS) reduced significantly. These data indicate that Botox® should be a treatment option for OAB associated with HTLV-1 infection.

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Tese de Doutoramento em Psicologia na área de especialização de Psicologia das Organizações apresentada ao ISPA - Instituto Universitário

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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.

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Existing wireless networks are characterized by a fixed spectrum assignment policy. However, the scarcity of available spectrum and its inefficient usage demands for a new communication paradigm to exploit the existing spectrum opportunistically. Future Cognitive Radio (CR) devices should be able to sense unoccupied spectrum and will allow the deployment of real opportunistic networks. Still, traditional Physical (PHY) and Medium Access Control (MAC) protocols are not suitable for this new type of networks because they are optimized to operate over fixed assigned frequency bands. Therefore, novel PHY-MAC cross-layer protocols should be developed to cope with the specific features of opportunistic networks. This thesis is mainly focused on the design and evaluation of MAC protocols for Decentralized Cognitive Radio Networks (DCRNs). It starts with a characterization of the spectrum sensing framework based on the Energy-Based Sensing (EBS) technique considering multiple scenarios. Then, guided by the sensing results obtained by the aforementioned technique, we present two novel decentralized CR MAC schemes: the first one designed to operate in single-channel scenarios and the second one to be used in multichannel scenarios. Analytical models for the network goodput, packet service time and individual transmission probability are derived and used to compute the performance of both protocols. Simulation results assess the accuracy of the analytical models as well as the benefits of the proposed CR MAC schemes.

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This thesis proposes a methodology for modelling business interoperability in a context of cooperative industrial networks. The purpose is to develop a methodology that enables the design of cooperative industrial network platforms that are able to deliver business interoperability and the analysis of its impact on the performance of these platforms. To achieve the proposed objective, two modelling tools have been employed: the Axiomatic Design Theory for the design of interoperable platforms; and Agent-Based Simulation for the analysis of the impact of business interoperability. The sequence of the application of the two modelling tools depends on the scenario under analysis, i.e. whether the cooperative industrial network platform exists or not. If the cooperative industrial network platform does not exist, the methodology suggests first the application of the Axiomatic Design Theory to design different configurations of interoperable cooperative industrial network platforms, and then the use of Agent-Based Simulation to analyse or predict the business interoperability and operational performance of the designed configurations. Otherwise, one should start by analysing the performance of the existing platform and based on the achieved results, decide whether it is necessary to redesign it or not. If the redesign is needed, simulation is once again used to predict the performance of the redesigned platform. To explain how those two modelling tools can be applied in practice, a theoretical modelling framework, a theoretical Axiomatic Design model and a theoretical Agent-Based Simulation model are proposed. To demonstrate the applicability of the proposed methodology and/or to validate the proposed theoretical models, a case study regarding a Portuguese Reverse Logistics cooperative network (Valorpneu network) and a case study regarding a Portuguese construction project (Dam Baixo Sabor network) are presented. The findings of the application of the proposed methodology to these two case studies suggest that indeed the Axiomatic Design Theory can effectively contribute in the design of interoperable cooperative industrial network platforms and that Agent-Based Simulation provides an effective set of tools for analysing the impact of business interoperability on the performance of those platforms. However, these conclusions cannot be generalised as only two case studies have been carried out. In terms of relevance to theory, this is the first time that the network effect is addressed in the analysis of the impact of business interoperability on the performance of networked companies and also the first time that a holistic approach is proposed to design interoperable cooperative industrial network platforms. Regarding the practical implications, the proposed methodology is intended to provide industrial managers a management tool that can guide them easily, and in practical and systematic way, in the design of configurations of interoperable cooperative industrial network platforms and/or in the analysis of the impact of business interoperability on the performance of their companies and the networks where their companies operate.

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Social ties are potentially an important determinant of migrants’ intention to return to their home country, and yet this topic has not been addressed in the existing economics literature on international migration. This study examines the absolute and relative importance of migrant social networks both at destination and at origin. We base our research on experimental data from Batista and Narciso (2013)1. By defining networks according to different characteristics of their members and migrant return intentions with respect to three different time horizons, we are able to dissect the network effect into its components. After controlling for unobserved heterogeneity and reverse causality biases we find that network at home seems to be the most important determinant of the migrant’s intention to return home within five and ten years.

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OBJECTIVE: The aims of this study were to evaluate the safety and efficacy of laparoscopic abdominoperineal resection compared to conventional approach for surgical treatment of patients with distal rectal cancer presenting with incomplete response after chemoradiation. METHOD: Twenty eight patients with distal rectal adenocarcinoma were randomized to undergo surgical treatment by laparoscopic abdominoperineal resection or conventional approach and evaluated prospectively. Thirteen underwent laparoscopic abdominoperineal resection and 15 conventional approach. RESULTS: There was no significant difference (p<0,05) between the two studied groups regarding: gender, age, body mass index, patients with previous abdominal surgeries, intra and post operative complications, need for blood transfusion, hospital stay after surgery, length of resected segment and pathological staging. Mean operation time was 228 minutes for the laparoscopic abdominoperineal resection versus 284 minutes for the conventional approach (p=0.04). Mean anesthesia duration was shorter (p=0.03) for laparoscopic abdominoperineal resection when compared to conventional approach : 304 and 362 minutes, respectively. There was no need for conversion to open approach in this series. After a mean follow-up of 47.2 months and with the exclusion of two patients in the conventional abdominoperineal resection who presented with unsuspected synchronic metastasis during surgery, local recurrence was observed in two patients in the conventional group and in none in the laparoscopic group. CONCLUSIONS: We conclude that laparoscopic abdominoperineal resection is feasible, similar to conventional approach concerning surgery duration, intra operative morbidity, blood requirements and post operative morbidity. Larger number of cases and an extended follow-up are required to adequate evaluation of oncological results for patients undergoing laparoscopic abdominoperineal resection after chemoradiation for radical treatment of distal rectal cancer.