Intelligence Algorithms for Increasing Navigation Systems Accuracy

Application of neural network algorithm for increasing the accuracy of navigation systems are showing. Various navigation systems, where a couple of sensors are used in the same device in different positions and the disturbances act equally on both sensors, the trained neural network can be advantageous for increasing the accuracy of system. The neural algorithm had used for determination the interconnection between the sensors errors in two channels to avoid the unobservation of navigation system. Representation of thermal error of two- component navigation sensors by time model, which coefficients depend only on parameters of the device, its orientations relative to disturbance vector allows to predict thermal errors change, measuring the current temperature and having identified preliminary parameters of the model for the set position. These properties of thermal model are used for training the neural network and compensation the errors of navigation system in non- stationary thermal fields.

Cauchy Problem for Differential Equation with Caputo Derivative

The paper is devoted to the study of the Cauchy problem for a nonlinear differential equation of complex order with the Caputo fractional derivative. The equivalence of this problem and a nonlinear Volterra integral equation in the space of continuously differentiable functions is established. On the basis of this result, the existence and uniqueness of the solution of the considered Cauchy problem is proved. The approximate-iterative method by Dzjadyk is used to obtain the approximate solution of this problem. Two numerical examples are given.

Advanced methodologies in dynamic traffic assignment modeling of managed lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. ^ Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. ^ Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. ^ With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.^

Mindfulness and Spirituality as determinants of Existential Loneliness in the Dutch

Existential loneliness is a concept that is largely ignored in the psychological research tradition, although from a philosophical perspective it is deeply connected to inherent human longings of connection and meaning. This research investigated the relationship between existential loneliness and two variables that are theoretically closely related to the concepts of connection and meaning, namely mindfulness (connection to oneself and others) and spiritual well-being (connection to a larger whole). This was done in a sample of n = 180 individuals (61.7% female; mean age 41.72, SD = 12.16) of the Dutch population. A multiple regression analysis was conducted. It can be concluded that there is a negative relationship between mindfulness and existential loneliness, as well as between spiritual well-being and existential loneliness. This means that people with a higher level of mindfulness and/or a higher level of spiritual well-being experience a lower level of existential loneliness. At the same time, people with a lower level of mindfulness and/or spiritual well-being experience a lower level of existential loneliness. There are some limitations to this study, for example the use of a non-random sampling method, a limited sample group, a scale that has not been widely tested, and a potential bias towards the higher educated. However, these limitations are inherent to exploratory research and does not diminish the main strength of this thesis, namely that it has provided more insight into an important and prevalent societal phenomenon, that had not been extensively researched previously, that has so far only been addressed in more philosophical instead of scientific debates, and linked almost exclusively to negative concepts, such as terminal illness. This research provides a first understanding of two positive determinants of existential loneliness, which could potentially be used to help make sense of this inherently humane condition, as well as to actively cope with the potential (adverse) effects of it.

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Obtención de un modelo estadístico para proporcionar QoS en enlaces inalámbricos ópticos submarinos

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Referenciação de crianças com problemas de comunicação e linguagem a partir dos cuidados de saúde primários

Os problemas de comunicação e linguagem (PCL) podem limitar a atividade e participação de um indivíduo ao longo da sua vida. Todavia, a intervenção precoce tem-se provado bastante eficaz nestes casos. Os médicos de família (MF) encontram-se numa posição privilegiada para deteção e referenciação destes problemas em idades precoces. Porém, há evidências de que a sua participação neste processo tem sido reduzida, nomeadamente no que respeita à referenciação para serviços de Intervenção Precoce. Assim, esta investigação pretende compreender qual o papel que os MF consideram ter relativamente a este processo e quais os fatores que podem influenciar a referenciação de crianças com suspeita de PCL. Este estudo teve como base um desenho de investigação descritivo, transversal e observacional. Recorreu-se a um método de amostragem por redes para a distribuição de um questionário On-line. O instrumento foi construído pela autora e é de caráter maioritariamente quantitativo, embora integre uma questão qualitativa de resposta semiaberta. Dos questionários enviados foram devolvidos 55. A resposta semiaberta foi preenchida por 16 dos 55 MF. Os resultados demonstram que a maioria dos MF valoriza bastante ou muito a sua participação na deteção de PCL e considera importante detetar precocemente estes problemas. Para além disso, valorizam bastante ou muito a colaboração em equipa e do terapeuta da fala. A grande parte sente-se influenciada pela preocupação dos pais, pela satisfação com os serviços e com os resultados da Escala de Avaliação de Desenvolvimento de Mary Sheridan Modificada para a referenciação de crianças com PCL. Para além disso, identificam barreiras relacionadas com recursos humanos, serviços, conhecimentos relacionados com o processo de referenciação, burocracia, lentidão do processo e com a atitude dos pais. Considera-se que este estudo pode constituir um ponto de partida para futuras investigações, para a adequação de estratégias institucionais e implementação de práticas que aproximem profissionais e serviços, de forma a melhorar o processo de referenciação de crianças com PCL a partir dos cuidados de saúde primários.

Entropy feature extraction of EEG signals for automatic person identification

The use of human brain electroencephalography (EEG) signals for automatic person identi cation has been investigated for a decade. It has been found that the performance of an EEG-based person identication system highly depends on what feature to be extracted from multi-channel EEG signals. Linear methods such as Power Spectral Density and Autoregressive Model have been used to extract EEG features. However these methods assumed that EEG signals are stationary. In fact, EEG signals are complex, non-linear, non-stationary, and random in nature. In addition, other factors such as brain condition or human characteristics may have impacts on the performance, however these factors have not been investigated and evaluated in previous studies. It has been found in the literature that entropy is used to measure the randomness of non-linear time series data. Entropy is also used to measure the level of chaos of braincomputer interface systems. Therefore, this thesis proposes to study the role of entropy in non-linear analysis of EEG signals to discover new features for EEG-based person identi- cation. Five dierent entropy methods including Shannon Entropy, Approximate Entropy, Sample Entropy, Spectral Entropy, and Conditional Entropy have been proposed to extract entropy features that are used to evaluate the performance of EEG-based person identication systems and the impacts of epilepsy, alcohol, age and gender characteristics on these systems. Experiments were performed on the Australian EEG and Alcoholism datasets. Experimental results have shown that, in most cases, the proposed entropy features yield very fast person identication, yet with compatible accuracy because the feature dimension is low. In real life security operation, timely response is critical. The experimental results have also shown that epilepsy, alcohol, age and gender characteristics have impacts on the EEG-based person identication systems.

Bioanalytical applications of microfluidic devices

The first part of the thesis describes a new patterning technique--microfluidic contact printing--that combines several of the desirable aspects of microcontact printing and microfluidic patterning and addresses some of their important limitations through the integration of a track-etched polycarbonate (PCTE) membrane. Using this technique, biomolecules (e.g., peptides, polysaccharides, and proteins) were printed in high fidelity on a receptor modified polyacrylamide hydrogel substrate. The patterns obtained can be controlled through modifications of channel design and secondary programming via selective membrane wetting. The protocols support the printing of multiple reagents without registration steps and fast recycle times. The second part describes a non-enzymatic, isothermal method to discriminate single nucleotide polymorphisms (SNPs). SNP discrimination using alkaline dehybridization has long been neglected because the pH range in which thermodynamic discrimination can be done is quite narrow. We found, however, that SNPs can be discriminated by the kinetic differences exhibited in the dehybridization of PM and MM DNA duplexes in an alkaline solution using fluorescence microscopy. We combined this method with multifunctional encoded hydrogel particle array (fabricated by stop-flow lithography) to achieve fast kinetics and high versatility. This approach may serve as an effective alternative to temperature-based method for analyzing unamplified genomic DNA in point-of-care diagnostic.

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Propostas de gestão participativa para o desenvolvimento sustentável dos recursos naturais e biodiversidade de Santa Maria

Os Açores reúnem nove ilhas com singularidades peculiares em termos paisagísticos, arquitetónicos e riqueza dos seus recursos naturais. Este panorama levanta contudo grandes desafios de sustentabilidade, de entre eles a reorientação de estratégias, atendendo à especificidade da região (segundo os objetivos à escala nacional em sede da Estratégia Nacional Desenvolvimento Sustentável (ENDS)). No caso da Ilha de Santa Maria (SMA), pequena ilha em que as estratégias tendem a ser ignoradas, a participação da população e dos dirigentes locais é minorada por interesses económicos desvinculados do desenvolvimento sustentável (DS). Para inverter esta situação é necessário conhecer para preservar, proteger para conservar, planificar e orientar os comportamentos e atitudes visando a sustentabilidade dos recursos naturais (RN) da ilha. Aplicando uma metodologia que conjugou os métodos quantitativos e qualitativos, com uma componente prática, utilizando um método de amostragem não casual dirigida, não probabilística com um método de amostragem por clusters, agrupado em grupos (workshop, séniores e jovens), pretendeu-se descrever os conhecimentos, as práticas e as perceções sobre a gestão dos RN’s, DS e instrumentos de gestão territorial (IGT’s). Os resultados mostram que os conhecimentos, práticas e perceções dos diferentes grupos são insuficientes no que respeita ao conhecimento dos conceitos e dimensões do DS (independentemente das idades ou habilitações literárias), verificando-se contudo melhorias, por vezes significativas, após as ações de sensibilização e educação. É imperativo continuar o esforço de valorização dos RN’s, envolvendo a população nas estratégias de conservação, objetivando uma proposta orientadora e participada numa visão para sustentabilidade da Ilha (SMA). Recomenda-se uma proposta de modelo de Estratégia DS dos recursos naturais e biodiversidade para SMA e diversas propostas de ações para colocar em prática essa estratégia como desenvolvimentos futuros.

A modified DEA model to estimate the importance of objectives with an application to agricultural economics

This paper demonstrates a connection between data envelopment analysis (DEA) and a non-interactive elicitation method to estimate the weights of objectives for decision-makers in a multiple attribute approach. This connection gives rise to a modified DEA model that allows us to estimate not only efficiency measures but also preference weights by radially projecting each unit onto a linear combination of the elements of the payoff matrix (which is obtained by standard multicriteria methods). For users of multiple attribute decision analysis the basic contribution of this paper is a new interpretation in terms of efficiency of the non-interactive methodology employed to estimate weights in a multicriteria approach. We also propose a modified procedure to calculate an efficient payoff matrix and a procedure to estimate weights through a radial projection rather than a distance minimization. For DEA users, we provide a modified DEA procedure to calculate preference weights and efficiency measures that does not depend on any observations in the dataset. This methodology has been applied to an agricultural case study in Spain.

Long-term relationship between energy consumption and GDP in Latin America: an empirical assessment using panel data

The main objetive of this research is to evaluate the long term relationship between energy consumption and GDP for some Latin American countries in the period 1980-2009 -- The estimation has been done through the non-stationary panel approach, using the production function in order to control other sources of GDP variation, such as capital and labor -- In addition to this, a panel unit root tests are used in order to identify the non-stationarity of these variables, followed by the application of panel cointegration test proposed by Pedroni (2004) to avoid a spurious regression (Entorf, 1997; Kao, 1999)

Endoscopic optical coherence tomography : design and application

This thesis presents an investigation on endoscopic optical coherence tomography (OCT). As a noninvasive imaging modality, OCT emerges as an increasingly important diagnostic tool for many clinical applications. Despite of many of its merits, such as high resolution and depth resolvability, a major limitation is the relatively shallow penetration depth in tissue (about 2∼3 mm). This is mainly due to tissue scattering and absorption. To overcome this limitation, people have been developing many different endoscopic OCT systems. By utilizing a minimally invasive endoscope, the OCT probing beam can be brought to the close vicinity of the tissue of interest and bypass the scattering of intervening tissues so that it can collect the reflected light signal from desired depth and provide a clear image representing the physiological structure of the region, which can not be disclosed by traditional OCT. In this thesis, three endoscope designs have been studied. While they rely on vastly different principles, they all converge to solve this long-standing problem.

A hand-held endoscope with manual scanning is first explored. When a user is holding a hand- held endoscope to examine samples, the movement of the device provides a natural scanning. We proposed and implemented an optical tracking system to estimate and record the trajectory of the device. By registering the OCT axial scan with the spatial information obtained from the tracking system, one can use this system to simply ‘paint’ a desired volume and get any arbitrary scanning pattern by manually waving the endoscope over the region of interest. The accuracy of the tracking system was measured to be about 10 microns, which is comparable to the lateral resolution of most OCT system. Targeted phantom sample and biological samples were manually scanned and the reconstructed images verified the method.

Next, we investigated a mechanical way to steer the beam in an OCT endoscope, which is termed as Paired-angle-rotation scanning (PARS). This concept was proposed by my colleague and we further developed this technology by enhancing the longevity of the device, reducing the diameter of the probe, and shrinking down the form factor of the hand-piece. Several families of probes have been designed and fabricated with various optical performances. They have been applied to different applications, including the collector channel examination for glaucoma stent implantation, and vitreous remnant detection during live animal vitrectomy.

Lastly a novel non-moving scanning method has been devised. This approach is based on the EO effect of a KTN crystal. With Ohmic contact of the electrodes, the KTN crystal can exhibit a special mode of EO effect, termed as space-charge-controlled electro-optic effect, where the carrier electron will be injected into the material via the Ohmic contact. By applying a high voltage across the material, a linear phase profile can be built under this mode, which in turn deflects the light beam passing through. We constructed a relay telescope to adapt the KTN deflector into a bench top OCT scanning system. One of major technical challenges for this system is the strong chromatic dispersion of KTN crystal within the wavelength band of OCT system. We investigated its impact on the acquired OCT images and proposed a new approach to estimate and compensate the actual dispersion. Comparing with traditional methods, the new method is more computational efficient and accurate. Some biological samples were scanned by this KTN based system. The acquired images justified the feasibility of the usage of this system into a endoscopy setting. My research above all aims to provide solutions to implement an OCT endoscope. As technology evolves from manual, to mechanical, and to electrical approaches, different solutions are presented. Since all have their own advantages and disadvantages, one has to determine the actual requirements and select the best fit for a specific application.

Some misspecfication problems in long-memory time series models

Doctor of Philosophy in Mathematics