Road network and GPS tracking with data processing and quality assessment

GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application. This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost. The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.

Assessing the physical environment of older people’s residential care facilities: development of the Swedish version of the Sheffield Care Environment Assessment Matrix (S-SCEAM)

Background There is emerging evidence that the physical environment is important for health, quality of life and care, but there is a lack of valid instruments to assess health care environments. The Sheffield Care Environment Assessment Matrix (SCEAM), developed in the United Kingdom, provides a comprehensive assessment of the physical environment of residential care facilities for older people. This paper reports on the translation and adaptation of SCEAM for use in Swedish residential care facilities for older people, including information on its validity and reliability. Methods SCEAM was translated into Swedish and back-translated into English, and assessed for its relevance by experts using content validity index (CVI) together with qualitative data. After modification, the validity assessments were repeated and followed by test-retest and inter-rater reliability tests in six units within a Swedish residential care facility that varied in terms of their environmental characteristics. Results Translation and back translation identified linguistic and semantic related issues. The results of the first content validity analysis showed that more than one third of the items had item-CVI (I-CVI) values less than the critical value of 0.78.  After modifying the instrument, the second content validation analysis resulted in I-CVI scores above 0.78, the suggested criteria for excellent content validity. Test-retest reliability showed high stability (96% and 95% for two independent raters respectively), and inter-rater reliability demonstrated high levels of agreement (95% and 94% on two separate rating occasions). Kappa values were very good for test-retest (κ= 0.903 and 0.869) and inter-rater reliability (κ= 0.851 and 0.832). Conclusions Adapting an instrument to a domestic context is a complex and time-consuming process, requiring an understanding of the culture where the instrument was developed and where it is to be used. A team, including the instrument’s developers, translators, and researchers is necessary to ensure a valid translation and adaption. This study showed preliminary validity and reliability evidence for the Swedish version (S-SCEAM) when used in a Swedish context. Further, we believe that the S-SCEAM has improved compared to the original instrument and suggest that it can be used as a foundation for future developments of the SCEAM model.

NDVI With Artificial Neural Networks For SRTM Elevation Model Improvement – Hydrological Model Application

Digital elevation model (DEM) plays a substantial role in hydrological study, from understanding the catchment characteristics, setting up a hydrological model to mapping the flood risk in the region. Depending on the nature of study and its objectives, high resolution and reliable DEM is often desired to set up a sound hydrological model. However, such source of good DEM is not always available and it is generally high-priced. Obtained through radar based remote sensing, Shuttle Radar Topography Mission (SRTM) is a publicly available DEM with resolution of 92m outside US. It is a great source of DEM where no surveyed DEM is available. However, apart from the coarse resolution, SRTM suffers from inaccuracy especially on area with dense vegetation coverage due to the limitation of radar signals not penetrating through canopy. This will lead to the improper setup of the model as well as the erroneous mapping of flood risk. This paper attempts on improving SRTM dataset, using Normalised Difference Vegetation Index (NDVI), derived from Visible Red and Near Infra-Red band obtained from Landsat with resolution of 30m, and Artificial Neural Networks (ANN). The assessment of the improvement and the applicability of this method in hydrology would be highlighted and discussed.

Uncertainties In Future Projections Of Extreme Rainfall: The Role Of Climate Model, Emission Scenario And Randomness

Climate change has resulted in substantial variations in annual extreme rainfall quantiles in different durations and return periods. Predicting the future changes in extreme rainfall quantiles is essential for various water resources design, assessment, and decision making purposes. Current Predictions of future rainfall extremes, however, exhibit large uncertainties. According to extreme value theory, rainfall extremes are rather random variables, with changing distributions around different return periods; therefore there are uncertainties even under current climate conditions. Regarding future condition, our large-scale knowledge is obtained using global climate models, forced with certain emission scenarios. There are widely known deficiencies with climate models, particularly with respect to precipitation projections. There is also recognition of the limitations of emission scenarios in representing the future global change. Apart from these large-scale uncertainties, the downscaling methods also add uncertainty into estimates of future extreme rainfall when they convert the larger-scale projections into local scale. The aim of this research is to address these uncertainties in future projections of extreme rainfall of different durations and return periods. We plugged 3 emission scenarios with 2 global climate models and used LARS-WG, a well-known weather generator, to stochastically downscale daily climate models’ projections for the city of Saskatoon, Canada, by 2100. The downscaled projections were further disaggregated into hourly resolution using our new stochastic and non-parametric rainfall disaggregator. The extreme rainfall quantiles can be consequently identified for different durations (1-hour, 2-hour, 4-hour, 6-hour, 12-hour, 18-hour and 24-hour) and return periods (2-year, 10-year, 25-year, 50-year, 100-year) using Generalized Extreme Value (GEV) distribution. By providing multiple realizations of future rainfall, we attempt to measure the extent of total predictive uncertainty, which is contributed by climate models, emission scenarios, and downscaling/disaggregation procedures. The results show different proportions of these contributors in different durations and return periods.

Newly Automated System For Integrated Assessment Of The Conditions Of Underwater Gas Pipelines

An underwater gas pipeline is the portion of the pipeline that crosses a river beneath its bottom. Underwater gas pipelines are subject to increasing dangers as time goes by. An accident at an underwater gas pipeline can lead to technological and environmental disaster on the scale of an entire region. Therefore, timely troubleshooting of all underwater gas pipelines in order to prevent any potential accidents will remain a pressing task for the industry. The most important aspect of resolving this challenge is the quality of the automated system in question. Now the industry doesn't have any automated system that fully meets the needs of the experts working in the field maintaining underwater gas pipelines. Principle Aim of this Research: This work aims to develop a new system of automated monitoring which would simplify the process of evaluating the technical condition and decision making on planning and preventive maintenance and repair work on the underwater gas pipeline. Objectives: Creation a shared model for a new, automated system via IDEF3; Development of a new database system which would store all information about underwater gas pipelines; Development a new application that works with database servers, and provides an explanation of the results obtained from the server; Calculation of the values MTBF for specified pipelines based on quantitative data obtained from tests of this system. Conclusion: The new, automated system PodvodGazExpert has been developed for timely and qualitative determination of the physical conditions of underwater gas pipeline; The basis of the mathematical analysis of this new, automated system uses principal component analysis method; The process of determining the physical condition of an underwater gas pipeline with this new, automated system increases the MTBF by a factor of 8.18 above the existing system used today in the industry.

Delaware Reservoirs’ Drought Risk Assessment: A Paleo View

The Delaware River provides half of New York City's drinking water, is a habitat for wild trout, American shad and the federally endangered dwarf wedge mussel. It has suffered four 100‐year floods in the last seven years. A drought during the 1960s stands as a warning of the potential vulnerability of the New York City area to severe water shortages if a similar drought were to recur. The water releases from three New York City dams on the Delaware River's headwaters impact not only the reliability of the city’s water supply, but also the potential impact of floods, and the quality of the aquatic habitat in the upper river. The goal of this work is to influence the Delaware River water release policies (FFMP/OST) to further benefit river habitat and fisheries without increasing New York City's drought risk, or the flood risk to down basin residents. The Delaware water release policies are constrained by the dictates of two US Supreme Court Decrees (1931 and 1954) and the need for unanimity among four states: New York, New Jersey, Pennsylvania, and Delaware ‐‐ and New York City. Coordination of their activities and the operation under the existing decrees is provided by the Delaware River Basin Commission (DRBC). Questions such as the probability of the system approaching drought state based on the current FFMP plan and the severity of the 1960s drought are addressed using long record paleo‐reconstructions of flows. For this study, we developed reconstructed total annual flows (water year) for 3 reservoir inflows using regional tree rings going back upto 1754 (a total of 246 years). The reconstructed flows are used with a simple reservoir model to quantify droughts. We observe that the 1960s drought is by far the worst drought based on 246 years of simulations (since 1754).

Consumption smoothing in Latin America: an empirical assessment of present value models

The study aims to assess the empirical adherence of the permanent income theory and the consumption smoothing view in Latin America. Two present value models are considered, one describing household behavior and the other open economy macroeconomics. Following the methodology developed in Campbell and Schiller (1987), Bivariate Vector Autoregressions are estimated for the saving ratio and the real growth rate of income concerning the household behavior model and for the current account and the change in national cash ‡ow regarding the open economy model. The countries in the sample are considered separately in the estimation process (individual system estimation) as well as jointly (joint system estimation). Ordinary Least Squares (OLS) and Seemingly Unrelated Regressions (SURE) estimates of the coe¢cients are generated. Wald Tests are then conducted to verify if the VAR coe¢cient estimates are in conformity with those predicted by the theory. While the empirical results are sensitive to the estimation method and discount factors used, there is only weak evidence in favor of the permanent income theory and consumption smoothing view in the group of countries analyzed.

A BDI-based approach for the assessment of driver's decision-making in commuter scenarios

The rapid growth of urban areas has a significant impact on traffic and transportation systems. New management policies and planning strategies are clearly necessary to cope with the more than ever limited capacity of existing road networks. The concept of Intelligent Transportation System (ITS) arises in this scenario; rather than attempting to increase road capacity by means of physical modifications to the infrastructure, the premise of ITS relies on the use of advanced communication and computer technologies to handle today’s traffic and transportation facilities. Influencing users’ behaviour patterns is a challenge that has stimulated much research in the ITS field, where human factors start gaining great importance to modelling, simulating, and assessing such an innovative approach. This work is aimed at using Multi-agent Systems (MAS) to represent the traffic and transportation systems in the light of the new performance measures brought about by ITS technologies. Agent features have good potentialities to represent those components of a system that are geographically and functionally distributed, such as most components in traffic and transportation. A BDI (beliefs, desires, and intentions) architecture is presented as an alternative to traditional models used to represent the driver behaviour within microscopic simulation allowing for an explicit representation of users’ mental states. Basic concepts of ITS and MAS are presented, as well as some application examples related to the subject. This has motivated the extension of an existing microscopic simulation framework to incorporate MAS features to enhance the representation of drivers. This way demand is generated from a population of agents as the result of their decisions on route and departure time, on a daily basis. The extended simulation model that now supports the interaction of BDI driver agents was effectively implemented, and different experiments were performed to test this approach in commuter scenarios. MAS provides a process-driven approach that fosters the easy construction of modular, robust, and scalable models, characteristics that lack in former result-driven approaches. Its abstraction premises allow for a closer association between the model and its practical implementation. Uncertainty and variability are addressed in a straightforward manner, as an easier representation of humanlike behaviours within the driver structure is provided by cognitive architectures, such as the BDI approach used in this work. This way MAS extends microscopic simulation of traffic to better address the complexity inherent in ITS technologies.

Should we be afraid of managed care?: a theoretical assessment

Managed caIe capitation contracts provide monetary incentives for doctoIs to save medical costs while standard health insurance contracts do noto The papeI proposes an alternative model for insurance markets which is used to analyze managed caIe contracts. In our model, households would like to buy insurance for the possible need of a service. The distinctive aspect of our model is that providers of service have privileged information on the most appropriate procedure to be followed. In the managed care application of the model, doctors are the providers of the service and through a diagnosis have better information of the patient's health condition. Equilibrium in our model is always constrained eflicient. A partial capitation contract arises when both the cost and net benefits of treatment are high enough. We show that a capitation contract provides incentives for doctors: i) to care about the likelihood households will obtain the good state of nature (altruistic behamor); and ii) to save medical costs (managed care behamor). Doctors, in this case, choose less medically eflicient treatments as they would choose under a standard health insurance contract. Besides this, household' welfare is increased in comparison to the standard contract. This increased welfare translates into a revealed preference for the capitation contract.

Assessment of value creation in private equity: the acquisition of Burger King by 3G Capital

This thesis elaborates the creation of value in private equity and in particular analyzes value creation in 3G Capital’s acquisition of Burger King. In this sense, a specific model is applied that composes value creation into several drivers, in order to answer the question of how value creation can be addressed in private equity investments. Although previous research by Achleitner et al. (2010) introduced a specific model that addresses value creation in private equity, the respective model was neither applied to an individual company, nor linked to indirect drivers that explain the dynamics and rationales for the creation of value. In turn this paper applies the quantitative model to an ongoing private equity investment and thereby provides different extensions to turn the model into a better forecasting model for ongoing investments, instead of only analyzing a deal that has already been divested from an ex post perspective. The chosen research approach is a case study about the Burger King buyout that first includes an extensive review about the current status of academic literature, second a quantitative calculation and qualitative interpretation of different direct value drivers, third a qualitative breakdown of indirect drivers, and lastly a recapitulating discussion about value creation and value drivers. Presenting a very successful private equity investment and elaborately demonstrating the dynamics and mechanisms that drive value creation in this case, provides important implications for other private equity firms as well as public firms in order to develop their proprietary approach towards value creation.

The impact of social security reform on occupational and retirement behavior : a quantitative assessment for Brazil

Population ageing is a problem that countries will have to cope with within a few years. How would changes in the social security system affect individual behaviour? We develop a multi-sectoral life-cycle model with both retirement and occupational choices to evaluate what are the macroeconomic impacts of social security reforms. We calibrate the model to match 2011 Brazilian economy and perform a counterfactual exercise of the long-run impacts of a recently adopted reform. In 2013, the Brazilian government approximated the two segregated social security schemes, imposing a ceiling on public pensions. In the benchmark equilibrium, our modelling economy is able to reproduce the early retirement claiming, the agents' stationary distribution among sectors, as well as the social security deficit and the public job application decision. In the counterfactual exercise, we find a significant reduction of 55\% in the social security deficit, an increase of 1.94\% in capital-to-output ratio, with both output and capital growing, a delay in retirement claims of public workers and a modification in the structure of agents applying to the public sector job.

Assessment of estrogenic, mutagenic and antimutagenic activity of nemorosone

Currently, a wide range of research involving natural products is focused on the discovery of new drugs in many different therapeutic areas. A great number of the synthetic compounds on the market were derived from natural products, especially plants. Nemorosone is the major constituent of the floral resin of Clusia rosea Jacq., Clusiaceae, and in Cuban propolis. In vitro studies have shown cytotoxic activity in this substance against various tumor cell lines, including those resistant to various cytotoxic drugs, whereas it has low cytotoxicity to non-tumoral cells. Therefore, in order to characterize the biological activity of nemorosone, a substance with potential antitumor activity, and in view of preclinical testing of the toxicity of drug candidate compounds, the main aim of this study was to determine the mutagenic and antimutagenic activity of nemorosone by the Ames test, using the strains TA97a, TA98, TA100 and TA102 of Salmonella typhimurium. Secondly, to characterize the estrogenic activity in an experimental recombinant yeast model (Recombinant Yeast Assay) mutagenic activity was observed at in any of the concentrations in any of the test strains. To evaluate the antimutagenic potential, direct and indirect mutagenic agents were used: 4 nitro-o-phenylenediamine (NPD), mitomycin C (MMC) and aflatoxin B1 (AFL). Nemorosone showed moderate antimutagenic activity (inhibition level 31%), in strain TA100 in the presence of AFL, and strong antimutagenic activity in TA102 against MMC (inhibition level 53%). Estrogenic activity was observed, with an EEq of 0.41±0.16 nM at various tested concentrations.

Evaluation of the elevated T-maze as an animal model of anxiety in the mouse

The elevated T-maze has been developed as an animal model of anxiety to generate both conditioned and unconditioned fears in the same rat. This study explores a version of the elevated T-maze fit for mice. Inhibitory (passive) avoidance-conditioned fear-is measured by recording the latency to leave the enclosed arm during three consecutive trials. One-way escape-unconditioned fear-is measured by recording the time to withdraw from open arms. The results showed that mice do not appear to acquire inhibitory avoidance in the standard T-maze, since their latencies to leave enclosed arm did not increase along trials. Nevertheless, the open arms seemed to be aversive for mice, because the latency to leave the enclosed arm after the first trial was lower in a T-maze with the three enclosed arms than in the standard elevated T-maze, In agreement, the exposure of mice to an elevated T-maze without shield, that reduces the perception of openness, increased significantly the latencies to leave the enclosed arm, However, the absence of the shield also increased the time taken to leave the open arms when compared to that recorded in standard T-maze. Systematic observation of behavioral items in the enclosed arm has shown that risk assessment behavior decreases along trials while freezing increases. In the open arms, freezing did not appear to influence the high latency to leave this compartment, since mice spend only about 8% of their time exhibiting this behavior, These results suggest that mice acquire inhibitory avoidance of the open arms by decreasing and increasing time in risk assessment and freezing, respectively, along three consecutive trials, However, one-way escape could not be characterized. Therefore, there are important differences between mice (present results) and rats (previously reported results) in the performance of behavioral tasks in the elevated T-maze. (C) 1999 Elsevier B.V.

Does bench model fidelity interfere in the acquisition of suture skills by novice medical students?

OBJETIVO: Embora vários modelos de bancada inanimados tenham sido descritos para o treinamento de habilidades de sutura, até o momento, não existe um método ideal para esse ensino e aprendizagem durante a formação médica. O objetivo foi avaliar se a fidelidade dos modelos de bancada interfere na aquisição de habilidades de sutura em estudantes de medicina iniciantes na prática cirúrgica. MÉTODOS: 36 estudantes de medicina sem exposição prévia a habilidades cirúrgicas foram randomizados em três grupos (n = 12): treinamento de suturas baseado em materiais didáticos (controle); treinamento de suturas em modelo de baixa-fidelidade (modelo de bancada de etileno vinil acetato); ou treinamento de suturas em modelo de alta-fidelidade (modelo de bancada de pele de pata de porco). Foram aplicados pré e pós-testes (realização de pontos simples e pontos subdérmicos invertidos em língua de boi). Três ferramentas (Global Rating Scale com avaliação cega, tamanho do efeito e autopercepção da confiança baseada em uma escala de Likert) foram utilizadas para mensurar todas as performances de sutura. RESULTADOS: A análise após o treinamento demonstrou que os estudantes que treinaram nos modelos tiveram um melhor (p < 0.0000) desempenho na avaliação pela Global Rating Scale, quando comparados com o controle, independente da fidelidade do modelo. A magnitude do efeito (treinamento) foi considerada grande (> 0.80) em todas as mensurações. Após o treinamento os alunos sentiram-se mais confiantes (p < 0.0000) para executarem os dois tipos de suturas. CONCLUSÃO: A aquisição de habilidades de suturas no modelo de baixa fidelidade foi semelhante à prática no modelo de alta fidelidade, sendo que a melhora no desempenho dos participantes que treinaram nesses dois modelos foi superior à aprendizagem baseada em materiais didáticos.

Cancer risk assessment of ethyl carbamate in alcoholic beverages from Brazil with special consideration to the spirits cachaca and tiquira

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)