A case study in identifying acceptable bitrates for human face recognition tasks

Face recognition from images or video footage requires a certain level of recorded image quality. This paper derives acceptable bitrates (relating to levels of compression and consequently quality) of footage with human faces, using an industry implementation of the standard H.264/MPEG-4 AVC and the Closed-Circuit Television (CCTV) recording systems on London buses. The London buses application is utilized as a case study for setting up a methodology and implementing suitable data analysis for face recognition from recorded footage, which has been degraded by compression. The majority of CCTV recorders on buses use a proprietary format based on the H.264/MPEG-4 AVC video coding standard, exploiting both spatial and temporal redundancy. Low bitrates are favored in the CCTV industry for saving storage and transmission bandwidth, but they compromise the image usefulness of the recorded imagery. In this context, usefulness is determined by the presence of enough facial information remaining in the compressed image to allow a specialist to recognize a person. The investigation includes four steps: (1) Development of a video dataset representative of typical CCTV bus scenarios. (2) Selection and grouping of video scenes based on local (facial) and global (entire scene) content properties. (3) Psychophysical investigations to identify the key scenes, which are most affected by compression, using an industry implementation of H.264/MPEG-4 AVC. (4) Testing of CCTV recording systems on buses with the key scenes and further psychophysical investigations. The results showed a dependency upon scene content properties. Very dark scenes and scenes with high levels of spatial–temporal busyness were the most challenging to compress, requiring higher bitrates to maintain useful information.

Starting antidepressant use: a qualitative synthesis of UK and Australian data

Objective To explore people's experiences of starting antidepressant treatment. Design Qualitative interpretive approach combining thematic analysis with constant comparison. Relevant coding reports from the original studies (generated using NVivo) relating to initial experiences of antidepressants were explored in further detail, focusing on the ways in which participants discussed their experiences of taking or being prescribed an antidepressant for the first time. Participants 108 men and women aged 22–84 who had taken antidepressants for depression. Setting Respondents recruited throughout the UK during 2003–2004 and 2008 and 2012–2013 and in Australia during 2010–2011. Results People expressed a wide range of feelings about initiating antidepressant use. People's attitudes towards starting antidepressant use were shaped by stereotypes and stigmas related to perceived drug dependency and potentially extreme side effects. Anxieties were expressed about starting use, and about how long the antidepressant might begin to take effect, how much it might help or hinder them, and about what to expect in the initial weeks. People worried about the possibility of experiencing adverse effects and implications for their senses of self. Where people felt they had not been given sufficient time during their consultation information or support to take the medicines, the uncertainty could be particularly unsettling and impact on their ongoing views on and use of antidepressants as a viable treatment option. Conclusions Our paper is the first to explore in-depth patient existential concerns about start of antidepressant use using multicountry data. People need additional support when they make decisions about starting antidepressants. Health professionals can use our findings to better understand and explore with patients’ their concerns before their patients start antidepressants. These insights are key to supporting patients, many of whom feel intimidated by the prospect of taking antidepressants, especially during the uncertain first few weeks of treatment.

Cross-National Differences in Managerial Discretion: Insights from the Middle East

Our study examines the effect of cultural practices on CEO discretion across six Middle Eastern countries. Using a panel of senior management consultants, we extend the national-level framework of managerial discretion and find that an encompassing array of cultural practices play a crucial role in shaping the degree of discretion provided to CEOs’ of public firms headquartered in these countries. We empirically demonstrate that power distance, future and performance orientation along with gender egalitarianism and assertiveness have positive relationships with managerial discretion. However, institutional collectivism, uncertainty avoidance and humane orientation negatively affect the degree of discretion provided to CEOs. As such, our results indicate that executives are able to take idiosyncratic and bold actions to the extent to which the cultural environment allows them to do so. As such, we contribute to the strategic leadership literature by finding new national-level antecedents of managerial discretion that haven’t been considered in earlier studies and confirm the context dependency of the discretion construct.

Electric vehicles in urban areas: test cases using a scenario simulator

Electric vehicles introduction will affect cities environment and urban mobility policies. Network system operators will have to consider the electric vehicles in planning and operation activities due to electric vehicles’ dependency on the electricity grid. The present paper presents test cases using an Electric Vehicle Scenario Simulator (EVeSSi) being developed by the authors. The test cases include two scenarios considering a 33 bus network with up to 2000 electric vehicles in the urban area. The scenarios consider a penetration of 10% of electric vehicles (200 of 2000), 30% (600) and 100% (2000). The first scenario will evaluate network impacts and the second scenario will evaluate CO2 emissions and fuel consumption.

Natural gas system operation: lagrangean optimization techniques

To comply with natural gas demand growth patterns and Europe´s import dependency, the gas industry needs to organize an efficient upstream infrastructure. The best location of Gas Supply Units – GSUs and the alternative transportation mode – by phisical or virtual pipelines, are the key of a successful industry. In this work we study the optimal location of GSUs, as well as determining the most efficient allocation from gas loads to sources, selecting the best transportation mode, observing specific technical restrictions and minimizing system total costs. For the location of GSUs on system we use the P-median problem, for assigning gas demands nodes to source facilities we use the classical transportation problem. The developed model is an optimisation-based approach, based on a Lagrangean heuristic, using Lagrangean relaxation for P-median problems – Simple Lagrangean Heuristic. The solution of this heuristic can be improved by adding a local search procedure - the Lagrangean Reallocation Heuristic. These two heuristics, Simple Lagrangean and Lagrangean Reallocation, were tested on a realistic network - the primary Iberian natural gas network, organized with 65 nodes, connected by physical and virtual pipelines. Computational results are presented for both approaches, showing the location gas sources and allocation loads arrangement, system total costs and gas transportation mode.

Implementação de WDM com 4 canais no espetro do visível

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Reabilitação energética de um edifício de índole cultural: Centro Cultural de Belém

Dissertação de Natureza Científica para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Edificações

Estudo económico das energias renováveis: o caso português

Dissertação de Mestrado apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Empreendedorismo e Internacionalização, sob orientação de Maria Clara Dias Pinto Ribeiro

Impacto económico, energético e ambiental da produção renovável na Ilha Terceira

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Is the electric vehicle a solution for the wind power integration in the portuguese power system?

The integration of Plug-in electric vehicles in the transportation sector has a great potential to reduce oil dependency, the GHG emissions and to contribute for the integration of renewable sources into the electricity generation mix. Portugal has a high share of wind energy, and curtailment may occur, especially during the off-peak hours with high levels of hydro generation. In this context, the electric vehicles, seen as a distributed storage system, can help to reduce the potential wind curtailments and, therefore, increase the integration of wind power into the power system. In order to assess the energy and environmental benefits of this integration, a methodology based on a unit commitment and economic dispatch is adapted and implemented. From this methodology, the thermal generation costs, the CO2 emissions and the potential wind generation curtailment are computed. Simulation results show that a 10% penetration of electric vehicles in the Portuguese fleet would increase electrical load by 3% and reduce wind curtailment by only 26%. This results from the fact that the additional generation required to supply the electric vehicles is mostly thermal. The computed CO2 emissions of the EV are 92 g CO2/kWh which become closer to those of some new ICE engines.

Análise do efeito de implementação de armazenamento térmico em banco de gelo e armazenamento elétrico em baterias Sódio-Enxofre (NaS) sobre o custo de exploração de edifícios de serviços

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

Kalman tracking linear predictor for vowel intelligibility enhancement on european portuguese HMM based speech synthesis

The recent developments on Hidden Markov Models (HMM) based speech synthesis showed that this is a promising technology fully capable of competing with other established techniques. However some issues still lack a solution. Several authors report an over-smoothing phenomenon on both time and frequencies which decreases naturalness and sometimes intelligibility. In this work we present a new vowel intelligibility enhancement algorithm that uses a discrete Kalman filter (DKF) for tracking frame based parameters. The inter-frame correlations are modelled by an autoregressive structure which provides an underlying time frame dependency and can improve time-frequency resolution. The system’s performance has been evaluated using objective and subjective tests and the proposed methodology has led to improved results.

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

As empresas e a sua internacionalização

Dissertação de Mestrado apresentada ao Instituto Superior de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Assessoria de Administração, sob orientação da Professora Doutora Raquel Susana da Costa Pereira