Detecting phase transitions in community structures using big data analysis of the engineering education research landscape: a European perspective

Comunicação apresentada na 44th SEFI Conference, 12-­15 September 2016, Tampere, Finland

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].^

Understanding the Impact of the Property Tax Appeal Process on Assessment Uniformity: Procedures, Structures, and Outcomes

Property taxes serve as a vital revenue source for local governments. The revenues derived from the property tax function as the primary funding source for a variety of critical local public service systems. Property tax appeal systems serve as quasi-administrative-judicial mechanisms intended to assure the public that property tax assessments are correct, fair, and equitable. Despite these important functions, there is a paucity of empirical research related to property tax appeal systems. This study contributes to property tax literature by identifying who participates in the property tax appeal process and examining their motivations for participation. In addition, the study sought to determine whether patterns of use and success in appeal systems affected the distribution of the tax burden. Data were collected by means of a survey distributed to single-family property owners from two Florida counties. In addition, state and county documents were analyzed to determine appeal patterns and examine the impact on assessment uniformity, over a three-year period. The survey data provided contextual evidence that single-family property owners are not as troubled by property taxes as they are by the conduct of local government officials. The analyses of the decision to appeal indicated that more expensive properties and properties excluded from initial uniformity analyses were more likely to be appealed, while properties with homestead exemptions were less likely to be appealed. The value change analyses indicated that appeals are clustered in certain geographical areas; however, these areas do not always experience a greater percentage of the value changes. Interestingly, professional representation did not increase the probability of obtaining a reduction in value. Other relationships between the variables were discovered, but often with weak predictive ability. Findings from the assessment uniformity analyses were also interesting. The results indicated that the appeals mechanisms in both counties improved assessment uniformity. On average, appealed properties exhibited greater horizontal and vertical inequities, as compared to non-appealed properties, prior to the appeals process. After, the appeal process was completed; the indicators of horizontal and vertical equity were largely improved. However, there were some indications of regressivity in the final year of the study.

Analysis of Non-Stationary Flows Using Eulerian and Lagrangian Frameworks

Recent developments have made researchers to reconsider Lagrangian measurement techniques as an alternative to their Eulerian counterpart when investigating non-stationary flows. This thesis advances the state-of-the-art of Lagrangian measurement techniques by pursuing three different objectives: (i) developing new Lagrangian measurement techniques for difficult-to-measure, in situ flow environments; (ii) developing new post-processing strategies designed for unstructured Lagrangian data, as well as providing guidelines towards their use; and (iii) presenting the advantages that the Lagrangian framework has over their Eulerian counterpart in various non-stationary flow problems. Towards the first objective, a large-scale particle tracking velocimetry apparatus is designed for atmospheric surface layer measurements. Towards the second objective, two techniques, one for identifying Lagrangian Coherent Structures (LCS) and the other for characterizing entrainment directly from unstructured Lagrangian data, are developed. Finally, towards the third objective, the advantages of Lagrangian-based measurements are showcased in two unsteady flow problems: the atmospheric surface layer, and entrainment in a non-stationary turbulent flow. Through developing new experimental and post-processing strategies for Lagrangian data, and through showcasing the advantages of Lagrangian data in various non-stationary flows, the thesis works to help investigators to more easily adopt Lagrangian-based measurement techniques.

An application of two techniques for the analysis of short, multivariate non-stationary time-series of Mauritanian trawl survey data

Min/max autocorrelation factor analysis (MAFA) and dynamic factor analysis (DFA) are complementary techniques for analysing short (> 15-25 y), non-stationary, multivariate data sets. We illustrate the two techniques using catch rate (cpue) time-series (1982-2001) for 17 species caught during trawl surveys off Mauritania, with the NAO index, an upwelling index, sea surface temperature, and an index of fishing effort as explanatory variables. Both techniques gave coherent results, the most important common trend being a decrease in cpue during the latter half of the time-series, and the next important being an increase during the first half. A DFA model with SST and UPW as explanatory variables and two common trends gave good fits to most of the cpue time-series. (c) 2004 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved.

Recovery of reproductive activity and fertility of Saanen goats affected by hydrometra after cloprostenol treatment and estrus induction during the non-breeding season (preliminary data).

2016

Data driven regularization models of non-linear ill-posed inverse problems in imaging

Imaging technologies are widely used in application fields such as natural sciences, engineering, medicine, and life sciences. A broad class of imaging problems reduces to solve ill-posed inverse problems (IPs). Traditional strategies to solve these ill-posed IPs rely on variational regularization methods, which are based on minimization of suitable energies, and make use of knowledge about the image formation model (forward operator) and prior knowledge on the solution, but lack in incorporating knowledge directly from data. On the other hand, the more recent learned approaches can easily learn the intricate statistics of images depending on a large set of data, but do not have a systematic method for incorporating prior knowledge about the image formation model. The main purpose of this thesis is to discuss data-driven image reconstruction methods which combine the benefits of these two different reconstruction strategies for the solution of highly nonlinear ill-posed inverse problems. Mathematical formulation and numerical approaches for image IPs, including linear as well as strongly nonlinear problems are described. More specifically we address the Electrical impedance Tomography (EIT) reconstruction problem by unrolling the regularized Gauss-Newton method and integrating the regularization learned by a data-adaptive neural network. Furthermore we investigate the solution of non-linear ill-posed IPs introducing a deep-PnP framework that integrates the graph convolutional denoiser into the proximal Gauss-Newton method with a practical application to the EIT, a recently introduced promising imaging technique. Efficient algorithms are then applied to the solution of the limited electrods problem in EIT, combining compressive sensing techniques and deep learning strategies. Finally, a transformer-based neural network architecture is adapted to restore the noisy solution of the Computed Tomography problem recovered using the filtered back-projection method.

Design for uncertainty of aerospace structures

The aim of this work is to present a general overview of state-of-the-art related to design for uncertainty with a focus on aerospace structures. In particular, a simulation on a FCCZ lattice cell and on the profile shape of a nozzle will be performed. Optimization under uncertainty is characterized by the need to make decisions without complete knowledge of the problem data. When dealing with a complex problem, non-linearity, or optimization, two main issues are raised: the uncertainty of the feasibility of the solution and the uncertainty of the objective value of the function. In the first part, the Design Of Experiments (DOE) methodologies, Uncertainty Quantification (UQ), and then Uncertainty optimization will be deepened. The second part will show an application of the previous theories on through a commercial software. Nowadays multiobjective optimization on high non-linear problem can be a powerful tool to approach new concept solutions or to develop cutting-edge design. In this thesis an effective improvement have been reached on a rocket nozzle. Future work could include the introduction of multi scale modelling, multiphysics approach and every strategy useful to simulate as much possible real operative condition of the studied design.

Data modelling su database non relazionali: confronto di prestazioni su operazioni CRUD

Gli obiettivi di questi tesi sono lo studio comparativo di alcuni DBMS non relazionali e il confronto di diverse soluzioni di modellazione logica e fisica per database non relazionali. Utilizzando come sistemi di gestione due DBMS Document-based non relazionali, MongoDB e CouchDB, ed un DBMS relazionale, Oracle, sarà effettuata un’analisi di diverse soluzione di modellazione logica dei dati in database documentali e uno studio mirato alla scelta degli attributi sui quali costruire indici. In primo luogo verrà definito un semplice caso di studio su cui effettuare i confronto, basato su due entità in relazione 1:N, sulle quali sarà costruito un opportuno carico di lavoro. Idatabase non relazionali sono schema-less, senza schema fisso, ed esiste una libertà maggiore di modellazione. In questo lavoro di tesi i dati verranno modellati secondo le tecniche del Referencing ed Embedding che consistono rispettivamente nell’inserimento di una chiave (riferimento) oppure di un intero sotto-documento (embedding) all’interno di un documento per poter esprimere il concetto di relazione tra diverse entità. Per studiare l’opportunità di indicizzare un attributo, ciascuna entità sarà poi composta da due triplette uguali di attributi definiti con differenti livelli di selettività, con la differenza che su ciascun attributo della seconda sarà costruito un indice. Il carico di lavoro sarà costituito da query definite in modo da poter testare le diverse modellazioni includendo anche predicati di join che non sono solitamente contemplati in modelli documentali. Per ogni tipo di database verranno eseguite le query e registrati i tempi, in modo da poter confrontare le performance dei diversi DBMS sulla base delle operazioni CRUD.

Touristic water demand: analysis and validation of drinking water consumption data and hotel characterization in Benidorm (Spain)

The work analyses the tourist water demand in Benidorm, a sun-and-sand destination ranked fourth in Spain by number of visitors, where tourism competes with local residents, nature, agriculture and industrial sectors for scarce water resources. In particular, we have studied the correlation between the water consumption of 83 hotels in Benidorm and their characteristics and services which can impact water use. For this purpose, we have examined the water consumption billed, by the water utility company HIDRAQUA in the period January 2010 - October 2022, to the tourist structures in the municipality of Benidorm, and we have explored the hotels’ features, thanks to the collaboration of the tourism and hotels association HOSBEC. To give a better understanding and contextualization of our analysis we first described explained the of the complex water supply system and the efforts that have been made to reduce the threat posed by the peculiar climate conditions of the region. We saw that the water consumption per guest has slightly decreased in the recent years and that the tourist flux has increased: the global pandemic posed a stop to travels for more than one year, but now both the tourist flux and the tourist water consumption are reaching pre-pandemic level. We found that larger hotels, and in particular the ones opened all the year, that probably tend to offer more water-demanding service with respect to the seasonal ones, have higher water consumption per bed. From the analysis of the role of the different hotel characteristics over the water demand patterns, we found that water use increases with the increase in the hotel category and in the ratio between the surface area of the swimming pool and hotel size (number of beds). Other factors impacting the consumption are the presence of an on-site laundry for washing the hotel linen, the garden, and the implementation of environmental policies for water-saving.

Spatial-temporal variability of the benthic communities in Ravenna harbour using Autonomous Reef Monitoring Structures (ARMS) with focus on Non-Indigenous Species (NIS)

A Non-Indigenous Species (NIS) is defined as an organism, introduced outside its natural past or present range of distribution by humans, that successfully survives, reproduces, and establish in the new environment. Harbors and tourist marinas are considered NIS hotspots, as they are departure and arrival points for numerous vessels and because of the presence of free artificial substrates, which facilitate colonization by NIS. To early detect the arrival of new NIS, monitoring benthic communities in ports is essential. Autonomous Reef Monitoring Structures (ARMS) are standardized passive collectors that are used to assess marine benthic communities. Here we use an integrative approach based on multiple 3-month ARMS deployment (from April 2021 to October 2022) to characterize the benthic communities (with a focus on NIS) of two sites: a commercial port (Harbor) and a touristic Marina (Marina) of Ravenna. The colonizing sessile communities were assessed using percentage coverage of the taxa trough image analyses and vagile fauna (> 2 mm) was identified morphologically using a stereomicroscope and light microscope. Overall, 97 taxa were identified and 19 of them were NIS. All NIS were already observed in port environments in the Mediterranean Sea, but for the first time the presence of the polychaete Schistomeringos cf. japonica (Annenkova, 1937) was observed; however molecular analysis is needed to confirm its identity. Harbor and Marina host significantly different benthic communities, with significantly different abundance depending on the sampling period. While the differences between sites are related to their different environmental characteristic and their anthropogenic pressures, differences among times seems related to the different life cycle of the main abundant species. This thesis evidenced that ARMS, together with integrative taxonomic approaches, represent useful tools to early detect NIS and could be used for a long-term monitoring of their presence.

[factors Associated With Satisfaction With Life Among Elderly Caregivers And Non-caregivers].

This article seeks to investigate associations between satisfaction with life and sociodemographic variables, health conditions, functionality, social involvement and social support among elderly caregivers and non-caregivers, as well as between satisfaction and the intensity of stress in the caregiver group. A sample of 338 caregivers was selected according to two items of the Brazilian version of the Elders Life Stress Inventory. A comparison-group of elderly non-caregivers was selected at random, with a similar gender, age and income profile. Data were derived from self-reported questionnaires and scales. Elderly caregivers with low levels of satisfaction and high levels of stress revealed more symptoms of insomnia, fatigue, diseases and worse IADL performance. Those with greater satisfaction and less stress revealed a good level of social support. Insomnia, depression and fatigue were associated with low satisfaction among caregivers, and with fatigue, depression and low social support among non-caregivers. It was considered relevant that instrumental, psychological and informative support can improve the quality of life and the quality of care provided by elderly caregivers, especially if they are affected by unfavorable health and psychosocial conditions and low satisfaction with life.

Centros de treinamento de ginástica rítmica no Brasil : estrutura e programas

Universidade Estadual de Campinas . Faculdade de Educação Física

Analise comparativa das caracteristicas cinematicas da coluna durante a marcha e a corrida

Universidade Estadual de Campinas . Faculdade de Educação Física

Pedagogia do esporte : organização, sistematização, aplicação e avaliação de conteúdos esportivos na educação não formal = Sport pedagogy : organization, systematization and application of sports content in non-formal education

Universidade Estadual de Campinas . Faculdade de Educação Física