976 resultados para Nonlinear Decision Functions
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This paper provides empirical evidence of the impact of life satisfaction on the individual intention to migrate. The impacts of individual characteristics and of country macroeconomic variables on the intention to migrate are analyzed jointly. Differently from other studies, we allow for life satisfaction to serve as a mediator between macroeconomic variables and the intention to migrate. Using the Eurobarometer Survey for 27 Central Eastern European (CEE) and Western European (non-CEE) countries, we find that people have a higher intention to migrate when dissatisfied with life. The socio-economic variables and macroeconomic conditions have an effect on the intention to migrate indirectly through life satisfaction. The impact of life satisfaction on the intention to migrate for middle-aged individuals with past experience of migration, low level of education, and with a low or average income from urban areas is higher in CEE countries than in non-CEE countries.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Dissertation presented to obtain the Ph.D degree in Biology, Computational Biology.
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Dissertation presented to obtain the Ph.D degree in Biology, Neuroscience
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Dissertation presented to obtain the Ph.D degree in Biology.
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Dissertação para obtenção do Grau de Doutor em Alterações Climáticas e Políticas de Desenvolvimento Sustentável
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Forest managers, stakeholders and investors want to be able to evaluate economic, environmental and social benefits in order to improve the outcomes of their decisions and enhance sustainable forest management. This research developed a spatial decision support system that provides: (1) an approach to identify the most beneficial locations for agroforestry projects based on the biophysical properties and evaluate its economic, social and environmental impact; (2) a tool to inform prospective investors and stakeholders of the potential and opportunities for integrated agroforestry management; (3) a simulation environment that enables evaluation via a dashboard with the opportunity to perform interactive sensitivity analysis for key parameters of the project; (4) a 3D interactive geographic visualization of the economic, environmental and social outcomes, which facilitate understanding and eases planning. Although the tool and methodology presented are generic, a case study was performed in East Kalimantan, Indonesia. For the whole study area, it was simulated the most suitable location for three different plantation schemes: monoculture of timber, a specific recipe (cassava, banana and sugar palm) and different recipes per geographic unit. The results indicate that a mixed cropping plantation scheme, with different recipes applied to the most suitable location returns higher economic, environmental and social benefits.
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Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.
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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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Salmonella enterica serovars are Gram-negative facultative intracellular bacterial pathogens that infect a wide variety of animals. Salmonella infections are common in humans, causing usually typhoid fever and gastrointestinal diseases. Salmonella enterica serovar Typhimurium (S. Typhimurium), which is a leading cause of human gastroenteritis, has been extensively used to study the molecular pathogenesis of Salmonella, because of the availability of sophisticated genetic tools, and of suitable animal and tissue culture models mimicking different aspects of Salmonella infections.(...)
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A foremost dispute that persists on the contemporary world’s agenda is change. The on-going social/technological/economic changes create a competitive and challenging environment for companies to endure. To benefit from these changes, world economies partially depend on emerging Small and Medium Enterprises (SMEs) and their adaptability skills, and subsequently the development of an integrated capability to innovate has become the prime strategy for most of SMEs to subsist and grow. However, innovation and change are always somewhat bonded to an inherent risk development, which subsequently brings on the necessity of a revision of risk management approaches in innovative processes, whose importance SMEs tend to disregard. Additionally, little efforts have been made to improve and create empirical models, metrics and tools to assist SMEs managing latent risks in their innovative projects. This work seeks to present and discuss a solution to support SMEs in engaging on systematic risk management practices, which consists on an integrated risk assessment and response support web-based tool - Spotrisk® - designed for SMEs. On the other hand, an inherent subjectivity is linked with risk management and identification processes, due to uncertainty trait of its nature, for each individual perceives situations according to his own idiosyncrasy, which brings complications in normalizing risk profiles and procedures. This essay aims to bring insights concerning the support in decision-making processes under uncertainty, by addressing issues related with the risk behavior character among individuals. To address such issues, subjects of neuroscience or psychology are explored and models to identify such character are proposed, as well as models to improve presented tool. This work attempts to go beyond the restrictive aim of endeavoring on technical improvement dissertation, and in embraces an exploratory conceptualization concerning micro, small and medium businesses’ traits regarding risk characters and project risk assessment tools.
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Based on the report for the unit “Foresight Methods Analysis” of the PhD programme on Technology Assessment at the Universidade Nova de Lisboa, under the supervision of Prof. Dr. António B. Moniz
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This report is the outcome of an internship that took place in Centro de Arbitragem Comercial da Câmara de Comércio e Indústria Portuguesa and its completion is an essential part of the path towards obtaining the Master’s Degree in Faculdade de Direito da Universidade Nova de Lisboa. This report has been structured in two stages – firstly, the presentation of the Centro de Arbitragem Comercial, focusing on its field of expertise, organic structure, principles and advantages. Then, the description of the activities developed within the Secretariat over the several stages of the arbitration procedure – since the reception of the arbitration requirement in institutional proceedings, terms of reference in ad hoc procedures, through the monitoring of the arbitral tribunal sessions (preliminary hearings, submission of evidence and final allegations) and the notification of the arbitration award. The second stage of this report is related to the description of the functions and powers of the President of Centro de Arbitragem Comercial. Firstly, it defines those powers by analyzing the statutes and rules of proceedings of the Centro de Arbitragem, drawing comparisons between the above mention and the rules of proceedings of others arbitral institutional centres, some of them are international references. The report assesses and describes the presidential powers, such as: configuration and composition of the arbitral tribunal (including arbitrator’s replacements, excuses and refusals); deadline extensions; determination of procedural rules and decision-making on any procedural incidents which arise before the constitution of the arbitral tribunal; definition of arbitration costs and fees; joinder of parties and consolidation of proceedings admission; and appointment of an emergency arbitrator. Lastly, this report analyzes some decisions delivered by the President in the respective institutional procedures which took place in the Centre.
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The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.