A youth vision of the city: The socio-spatial lives and exclusion of street girls in Bogota, Colombia

This dissertation documents the everyday lives and spaces of a population of youth typically constructed as out of place, and the broader urban context in which they are rendered as such. Thirty-three female and transgender street youth participated in the development of this youth-based participatory action research (YPAR) project utilizing geo-ethnographic methods, auto-photography, and archival research throughout a six-phase, eighteen-month research process in Bogotá, Colombia. ^ This dissertation details the participatory writing process that enabled the YPAR research team to destabilize dominant representations of both street girls and urban space and the participatory mapping process that enabled the development of a youth vision of the city through cartographic images. The maps display individual and aggregate spatial data indicating trends within and making comparisons between three subgroups of the research population according to nine spatial variables. These spatial data, coupled with photographic and ethnographic data, substantiate that street girls’ mobilities and activity spaces intersect with and are altered by state-sponsored urban renewal projects and paramilitary-led social cleansing killings, both efforts to clean up Bogotá by purging the city center of deviant populations and places. ^ Advancing an ethical approach to conducting research with excluded populations, this dissertation argues for the enactment of critical field praxis and care ethics within a YPAR framework to incorporate young people as principal research actors rather than merely voices represented in adultist academic discourse. Interjection of considerations of space, gender, and participation into the study of street youth produce new ways of envisioning the city and the role of young people in research. Instead of seeing the city from a panoptic view, Bogotá is revealed through the eyes of street youth who participated in the construction and feminist visualization of a new cartography and counter-map of the city grounded in embodied, situated praxis. This dissertation presents a socially responsible approach to conducting action-research with high-risk youth by documenting how street girls reclaim their right to the city on paper and in practice; through maps of their everyday exclusion in Bogotá followed by activism to fight against it.^

Inter-site and inter-scanner diffusion MRI data harmonization.

We propose a novel method to harmonize diffusion MRI data acquired from multiple sites and scanners, which is imperative for joint analysis of the data to significantly increase sample size and statistical power of neuroimaging studies. Our method incorporates the following main novelties: i) we take into account the scanner-dependent spatial variability of the diffusion signal in different parts of the brain; ii) our method is independent of compartmental modeling of diffusion (e.g., tensor, and intra/extra cellular compartments) and the acquired signal itself is corrected for scanner related differences; and iii) inter-subject variability as measured by the coefficient of variation is maintained at each site. We represent the signal in a basis of spherical harmonics and compute several rotation invariant spherical harmonic features to estimate a region and tissue specific linear mapping between the signal from different sites (and scanners). We validate our method on diffusion data acquired from seven different sites (including two GE, three Philips, and two Siemens scanners) on a group of age-matched healthy subjects. Since the extracted rotation invariant spherical harmonic features depend on the accuracy of the brain parcellation provided by Freesurfer, we propose a feature based refinement of the original parcellation such that it better characterizes the anatomy and provides robust linear mappings to harmonize the dMRI data. We demonstrate the efficacy of our method by statistically comparing diffusion measures such as fractional anisotropy, mean diffusivity and generalized fractional anisotropy across multiple sites before and after data harmonization. We also show results using tract-based spatial statistics before and after harmonization for independent validation of the proposed methodology. Our experimental results demonstrate that, for nearly identical acquisition protocol across sites, scanner-specific differences can be accurately removed using the proposed method.

Retrieval of grassland biophysical parameters using multitemporal optical and radar satellite data

The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.

A method for assessing ecological values to reconcile multiple land use needs

We present a new method for ecologically sustainable land use planning within multiple land use schemes. Our aims were (1) to develop a method that can be used to locate important areas based on their ecological values; (2) to evaluate the quality, quantity, availability, and usability of existing ecological data sets; and (3) to demonstrate the use of the method in Eastern Finland, where there are requirements for the simultaneous development of nature conservation, tourism, and recreation. We compiled all available ecological data sets from the study area, complemented the missing data using habitat suitability modeling, calculated the total ecological score (TES) for each 1 ha grid cell in the study area, and finally, demonstrated the use of TES in assessing the success of nature conservation in covering ecologically valuable areas and locating ecologically sustainable areas for tourism and recreational infrastructure. The method operated quite well at the level required for regional and local scale planning. The quality, quantity, availability, and usability of existing data sets were generally high, and they could be further complemented by modeling. There are still constraints that limit the use of the method in practical land use planning. However, as increasing data become available and open access, and modeling tools improve, the usability and applicability of the method will increase.

Integrating a mobile accessible electronic system into dockside monitoring: How can small-scale fisheries data collection programs transition from paper-based to digital data collection?

Thesis (Master's)--University of Washington, 2016-06

Using interaction data for improving the offline and online evaluation of search engines

This thesis investigates how web search evaluation can be improved using historical interaction data. Modern search engines combine offline and online evaluation approaches in a sequence of steps that a tested change needs to pass through to be accepted as an improvement and subsequently deployed. We refer to such a sequence of steps as an evaluation pipeline. In this thesis, we consider the evaluation pipeline to contain three sequential steps: an offline evaluation step, an online evaluation scheduling step, and an online evaluation step. In this thesis we show that historical user interaction data can aid in improving the accuracy or efficiency of each of the steps of the web search evaluation pipeline. As a result of these improvements, the overall efficiency of the entire evaluation pipeline is increased. Firstly, we investigate how user interaction data can be used to build accurate offline evaluation methods for query auto-completion mechanisms. We propose a family of offline evaluation metrics for query auto-completion that represents the effort the user has to spend in order to submit their query. The parameters of our proposed metrics are trained against a set of user interactions recorded in the search engine’s query logs. From our experimental study, we observe that our proposed metrics are significantly more correlated with an online user satisfaction indicator than the metrics proposed in the existing literature. Hence, fewer changes will pass the offline evaluation step to be rejected after the online evaluation step. As a result, this would allow us to achieve a higher efficiency of the entire evaluation pipeline. Secondly, we state the problem of the optimised scheduling of online experiments. We tackle this problem by considering a greedy scheduler that prioritises the evaluation queue according to the predicted likelihood of success of a particular experiment. This predictor is trained on a set of online experiments, and uses a diverse set of features to represent an online experiment. Our study demonstrates that a higher number of successful experiments per unit of time can be achieved by deploying such a scheduler on the second step of the evaluation pipeline. Consequently, we argue that the efficiency of the evaluation pipeline can be increased. Next, to improve the efficiency of the online evaluation step, we propose the Generalised Team Draft interleaving framework. Generalised Team Draft considers both the interleaving policy (how often a particular combination of results is shown) and click scoring (how important each click is) as parameters in a data-driven optimisation of the interleaving sensitivity. Further, Generalised Team Draft is applicable beyond domains with a list-based representation of results, i.e. in domains with a grid-based representation, such as image search. Our study using datasets of interleaving experiments performed both in document and image search domains demonstrates that Generalised Team Draft achieves the highest sensitivity. A higher sensitivity indicates that the interleaving experiments can be deployed for a shorter period of time or use a smaller sample of users. Importantly, Generalised Team Draft optimises the interleaving parameters w.r.t. historical interaction data recorded in the interleaving experiments. Finally, we propose to apply the sequential testing methods to reduce the mean deployment time for the interleaving experiments. We adapt two sequential tests for the interleaving experimentation. We demonstrate that one can achieve a significant decrease in experiment duration by using such sequential testing methods. The highest efficiency is achieved by the sequential tests that adjust their stopping thresholds using historical interaction data recorded in diagnostic experiments. Our further experimental study demonstrates that cumulative gains in the online experimentation efficiency can be achieved by combining the interleaving sensitivity optimisation approaches, including Generalised Team Draft, and the sequential testing approaches. Overall, the central contributions of this thesis are the proposed approaches to improve the accuracy or efficiency of the steps of the evaluation pipeline: the offline evaluation frameworks for the query auto-completion, an approach for the optimised scheduling of online experiments, a general framework for the efficient online interleaving evaluation, and a sequential testing approach for the online search evaluation. The experiments in this thesis are based on massive real-life datasets obtained from Yandex, a leading commercial search engine. These experiments demonstrate the potential of the proposed approaches to improve the efficiency of the evaluation pipeline.

DESIGN OF EFFICIENT IN-NETWORK DATA PROCESSING AND DISSEMINATION FOR VANETS

By providing vehicle-to-vehicle and vehicle-to-infrastructure wireless communications, vehicular ad hoc networks (VANETs), also known as the “networks on wheels”, can greatly enhance traffic safety, traffic efficiency and driving experience for intelligent transportation system (ITS). However, the unique features of VANETs, such as high mobility and uneven distribution of vehicular nodes, impose critical challenges of high efficiency and reliability for the implementation of VANETs. This dissertation is motivated by the great application potentials of VANETs in the design of efficient in-network data processing and dissemination. Considering the significance of message aggregation, data dissemination and data collection, this dissertation research targets at enhancing the traffic safety and traffic efficiency, as well as developing novel commercial applications, based on VANETs, following four aspects: 1) accurate and efficient message aggregation to detect on-road safety relevant events, 2) reliable data dissemination to reliably notify remote vehicles, 3) efficient and reliable spatial data collection from vehicular sensors, and 4) novel promising applications to exploit the commercial potentials of VANETs. Specifically, to enable cooperative detection of safety relevant events on the roads, the structure-less message aggregation (SLMA) scheme is proposed to improve communication efficiency and message accuracy. The scheme of relative position based message dissemination (RPB-MD) is proposed to reliably and efficiently disseminate messages to all intended vehicles in the zone-of-relevance in varying traffic density. Due to numerous vehicular sensor data available based on VANETs, the scheme of compressive sampling based data collection (CS-DC) is proposed to efficiently collect the spatial relevance data in a large scale, especially in the dense traffic. In addition, with novel and efficient solutions proposed for the application specific issues of data dissemination and data collection, several appealing value-added applications for VANETs are developed to exploit the commercial potentials of VANETs, namely general purpose automatic survey (GPAS), VANET-based ambient ad dissemination (VAAD) and VANET based vehicle performance monitoring and analysis (VehicleView). Thus, by improving the efficiency and reliability in in-network data processing and dissemination, including message aggregation, data dissemination and data collection, together with the development of novel promising applications, this dissertation will help push VANETs further to the stage of massive deployment.

Geospatial Data Indexing Analysis and Visualization via Web Services with Autonomic Resource Management

With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.

The pulsations of the B5IVe star HD 181231 observed with CoRoT and ground-based spectroscopy

Context. HD 181231 is a B5IVe star, which has been observed with the CoRoT satellite during similar to 5 consecutive months and simultaneously from the ground in spectroscopy and spectropolarimetry. Aims. By analysing these data, we aim to detect and characterize as many pulsation frequencies as possible, to search for the presence of beating effects possibly at the origin of the Be phenomenon. Our results will also provide a basis for seismic modelling. Methods. The fundamental parameters of the star are determined from spectral fitting and from the study of the circumstellar emission. The CoRoT photometric data and ground-based spectroscopy are analysed using several Fourier techniques: CLEAN-NG, PASPER, and TISAFT, as well as a time-frequency technique. A search for a magnetic field is performed by applying the LSD technique to the spectropolarimetric data. Results. We find that HD 181231 is a B5IVe star seen with an inclination of similar to 45 degrees. No magnetic field is detected in its photosphere. We detect at least 10 independent significant frequencies of variations among the 54 detected frequencies, interpreted in terms of non-radial pulsation modes and rotation. Two longer-term variations are also detected: one at similar to 14 days resulting from a beating effect between the two main frequencies of short-term variations, the other at similar to 116 days due either to a beating of frequencies or to a zonal pulsation mode. Conclusions. Our analysis of the CoRoT light curve and ground-based spectroscopic data of HD 181231 has led to the determination of the fundamental and pulsational parameters of the star, including beating effects. This will allow a precise seismic modelling of this star.

The merging cluster Abell 1758 revisited: multi-wavelength observations and numerical simulations

Context. Cluster properties can be more distinctly studied in pairs of clusters, where we expect the effects of interactions to be strong. Aims. We here discuss the properties of the double cluster Abell 1758 at a redshift z similar to 0.279. These clusters show strong evidence for merging. Methods. We analyse the optical properties of the North and South cluster of Abell 1758 based on deep imaging obtained with the Canada-France-Hawaii Telescope (CFHT) archive Megaprime/Megacam camera in the g' and r' bands, covering a total region of about 1.05 x 1.16 deg(2), or 16.1 x 17.6 Mpc(2). Our X-ray analysis is based on archive XMM-Newton images. Numerical simulations were performed using an N-body algorithm to treat the dark-matter component, a semi-analytical galaxy-formation model for the evolution of the galaxies and a grid-based hydrodynamic code with a parts per million (PPM) scheme for the dynamics of the intra-cluster medium. We computed galaxy luminosity functions (GLFs) and 2D temperature and metallicity maps of the X-ray gas, which we then compared to the results of our numerical simulations. Results. The GLFs of Abell 1758 North are well fit by Schechter functions in the g' and r' bands, but with a small excess of bright galaxies, particularly in the r' band; their faint-end slopes are similar in both bands. In contrast, the GLFs of Abell 1758 South are not well fit by Schechter functions: excesses of bright galaxies are seen in both bands; the faint-end of the GLF is not very well defined in g'. The GLF computed from our numerical simulations assuming a halo mass-luminosity relation agrees with those derived from the observations. From the X-ray analysis, the most striking features are structures in the metal distribution. We found two elongated regions of high metallicity in Abell 1758 North with two peaks towards the centre. In contrast, Abell 1758 South shows a deficit of metals in its central regions. Comparing observational results to those derived from numerical simulations, we could mimic the most prominent features present in the metallicity map and propose an explanation for the dynamical history of the cluster. We found in particular that in the metal-rich elongated regions of the North cluster, winds had been more efficient than ram-pressure stripping in transporting metal-enriched gas to the outskirts. Conclusions. We confirm the merging structure of the North and South clusters, both at optical and X-ray wavelengths.

Hypoactive sexual desire disorder in a population-based study of Brazilian women: associated factors classified according to their importance

Objective: The etiology of hypoactive sexual desire disorder (HSDD) is known to be multifactorial, involving biological, psychosexual, and context-related factors. The objective of the present study was to analyze the factors associated with female HSDD and to stratify these factors according to their importance. Methods: This was a population-based, hierarchical study conducted in Brazil, based on data from previous research on the Brazilian Sexual Life Study, conducted between November 2002 and February 2003 in various Brazilian cities. The primary study consisted of a self-administered and anonymous questionnaire, addressing sociodemographic parameters, general health, life habits, behavior, and complaints related to sexual function. The association between HSDD and various other factors was assessed. The data were evaluated by hierarchical multiple regression analysis. Results: The prevalence of HSDD in this sample was 9.5%. Associations were found with cardiovascular disease, breast cancer, posttraumatic stress, poorer education level, being older, being married, a lack of information on sexuality in childhood/adolescence, and a limited sexual repertoire. Women who consumed moderate amounts of alcohol were found to be less likely to have HSDD. Conclusions: Analysis of the associated factors classified in order of importance and analysis of the characteristics of the sexual relationships provide additional information to currently available data on the traditional concepts of HSDD.

Asymmetric page split generalized index search trees for formal concept analysis

Formal Concept Analysis is an unsupervised machine learning technique that has successfully been applied to document organisation by considering documents as objects and keywords as attributes. The basic algorithms of Formal Concept Analysis then allow an intelligent information retrieval system to cluster documents according to keyword views. This paper investigates the scalability of this idea. In particular we present the results of applying spatial data structures to large datasets in formal concept analysis. Our experiments are motivated by the application of the Formal Concept Analysis idea of a virtual filesystem [11,17,15]. In particular the libferris [1] Semantic File System. This paper presents customizations to an RD-Tree Generalized Index Search Tree based index structure to better support the application of Formal Concept Analysis to large data sources.

Análise espacial do padrão de introdução e disseminação da dengue nos municípios do Espírito Santo

O número de municípios infestados pelo Aedes aegypti no Estado do Espírito Santo vem aumentando gradativamente, levando a altas taxas de incidência de dengue ao longo dos anos. Apesar das tentativas de combate à doença, esta se tornou uma das maiores preocupações na saúde pública do Estado. Este estudo se propõe a descrever a dinâmica da expansão da doença no Estado a partir da associação entre variáveis ambientais e populacionais, utilizando dados operacionalizados por meio de técnicas de geoprocessamento. O estudo utilizou como fonte de dados a infestação pelo mosquito vetor e o coeficiente de incidência da doença, as distâncias rodoviárias intermunicipais do Estado, a altitude dos municípios e as variáveis geoclimáticas (temperatura e suficiência de água), incorporadas a uma ferramenta operacional, as Unidades Naturais do Espírito Santo (UNES), representadas em um único mapa operacionalizado em Sistema de Informação Geográfica (SIG), obtido a partir do Sistema Integrado de Bases Georreferenciadas do Estado do Espírito Santo. Para análise dos dados, foi realizada a Regressão de Poisson para os dados de incidência de dengue e Regressão Logística para os de infestação pelo vetor. Em seguida, os dados de infestação pelo mosquito e incidência de dengue foram georreferenciados, utilizando como ferramenta operacional o SIG ArcGIS versão 9.2. Observou-se que a pluviosidade é um fator que contribui para o surgimento de mosquito em áreas não infestadas. Altas temperaturas contribuem para um alto coeficiente de incidência de dengue nos municípios capixabas. A variável distância em relação a municípios populosos é um fator de proteção para a incidência da doença. A grande variabilidade encontrada nos dados, que não é explicada pelas variáveis utilizadas no modelo para incidência da doença, reforça a premissa de que a dengue é condicionada pela interação dinâmica entre muitas variáveis que o estudo não abordou. A espacialização dos dados de infestação pelo mosquito e incidência de dengue e as Zonas Naturais do ES permitiu a visualização da influência das variáveis estatisticamente significantes nos modelos utilizados no padrão da introdução e disseminação da doença no Estado.

Smart Electric Vehicle Charging System

In this work is proposed the design of a system to create and handle Electric Vehicles (EV) charging procedures, based on intelligent process. Due to the electrical power distribution network limitation and absence of smart meter devices, Electric Vehicles charging should be performed in a balanced way, taking into account past experience, weather information based on data mining, and simulation approaches. In order to allow information exchange and to help user mobility, it was also created a mobile application to assist the EV driver on these processes. This proposed Smart ElectricVehicle Charging System uses Vehicle-to-Grid (V2G) technology, in order to connect Electric Vehicles and also renewable energy sources to Smart Grids (SG). This system also explores the new paradigm of Electrical Markets (EM), with deregulation of electricity production and use, in order to obtain the best conditions for commercializing electrical energy.

Planeamento espacial marinho das áreas marinhas protegidas: o caso de estudo da ára protegida de gestão de recursos: Caloura - ilhéu de Vila Franca do Campo

Tese de Doutoramento, Ciências do Mar (Ecologia Marinha), 26 de Novembro de 2013, Universidade dos Açores.