Image processing methodology for assessment of drilling induced damage in CFRP

Dissertação para obtenção do Grau de Mestre em Engenharia Mecânica

Human activity data discovery based on accelerometry

Dissertation to Obtain Master Degree in Biomedical Engineering

Design and development of a microfluidic platform for use with colorimetric gold nanoprobe assays

Due to the importance and wide applications of the DNA analysis, there is a need to make genetic analysis more available and more affordable. As such, the aim of this PhD thesis is to optimize a colorimetric DNA biosensor based on gold nanoprobes developed in CEMOP by reducing its price and the needed volume of solution without compromising the device sensitivity and reliability, towards the point of care use. Firstly, the price of the biosensor was decreased by replacing the silicon photodetector by a low cost, solution processed TiO2 photodetector. To further reduce the photodetector price, a novel fabrication method was developed: a cost-effective inkjet printing technology that enabled to increase TiO2 surface area. Secondly, the DNA biosensor was optimized by means of microfluidics that offer advantages of miniaturization, much lower sample/reagents consumption, enhanced system performance and functionality by integrating different components. In the developed microfluidic platform, the optical path length was extended by detecting along the channel and the light was transmitted by optical fibres enabling to guide the light very close to the analysed solution. Microfluidic chip of high aspect ratio (~13), smooth and nearly vertical sidewalls was fabricated in PDMS using a SU-8 mould for patterning. The platform coupled to the gold nanoprobe assay enabled detection of Mycobacterium tuberculosis using 3 8l on DNA solution, i.e. 20 times less than in the previous state-of-the-art. Subsequently, the bio-microfluidic platform was optimized in terms of cost, electrical signal processing and sensitivity to colour variation, yielding 160% improvement of colorimetric AuNPs analysis. Planar microlenses were incorporated to converge light into the sample and then to the output fibre core increasing 6 times the signal-to-losses ratio. The optimized platform enabled detection of single nucleotide polymorphism related with obesity risk (FTO) using target DNA concentration below the limit of detection of the conventionally used microplate reader (i.e. 15 ng/μl) with 10 times lower solution volume (3 μl). The combination of the unique optical properties of gold nanoprobes with microfluidic platform resulted in sensitive and accurate sensor for single nucleotide polymorphism detection operating using small volumes of solutions and without the need for substrate functionalization or sophisticated instrumentation. Simultaneously, to enable on chip reagents mixing, a PDMS micromixer was developed and optimized for the highest efficiency, low pressure drop and short mixing length. The optimized device shows 80% of mixing efficiency at Re = 0.1 in 2.5 mm long mixer with the pressure drop of 6 Pa, satisfying requirements for the application in the microfluidic platform for DNA analysis.

High ffficiency transmission techniques for broadband wireless systems

Future broadband wireless systems are expected to cope with severely time dispersive channels, due to multi-path signal propagation between the transmitter and the receiver while having high power and spectral efficiency. Thus, advanced Frequency Domain Equalization techniques are required. The implementation complexity in mobile terminals should be as low as possible to achieve highest possible efficiency. Therefore, most of the signal processing requirements will be shifted to the base station and we will employ signals compatible with an efficient, grossly nonlinear power amplification. For this reason, we will consider offset modulation signals with quasi-constant envelope and develop receivers that will obtain good BER performance. However, these signals require a bandwidth significantly above the Nyquist rate, which can be reduced by an overlap of different frequency channels.

Wearable monitoring system for assistance dogs

Despite the recent progresses in robotics, autonomous robots still have too many limitations to reliably help people with disabilities. On the other hand, animals, and especially dogs, have already demonstrated great skills in assisting people in many daily situations. However, dogs also have their own set of limitations. For example, they need to rest periodically, to be healthy (physically and psychologically), and it is difficult to control them remotely. This project aims to “augment” the Assistance dog, by developing a system that compensates some of the dog weaknesses through a robotic device mounted on the dog harness. This specific study, involved in the COCHISE project, focuses on the development of a system for the monitoring of dogs activity and physiological parameters.

Fabrication and characterization of transparent conductive oxide surface sensors for electrocorticography – TrECoG

Understanding how the brain works has been one of the greatest goals of mankind. This desire fuels the scientific community to pursue novel techniques able to acquire the complex information produced by the brain at any given moment. The Electrocorticography (ECoG) is one of those techniques. By placing conductive electrodes over the dura, or directly over the cortex, and measuring the electric potential variation, one can acquire information regarding the activation of those areas. In this work, transparent ECoGs, (TrECoGs) are fabricated through thin film deposition of the Transparent Conductive Oxides (TCOs) Indium-Zinc-Oxide (IZO) and Gallium-Zinc-Oxide (GZO). Five distinct devices have been fabricated via shadow masking and photolithography. The data acquired and presented in this work validates the TrECoGs fabricated as efficient devices for recording brain activity. The best results were obtained for the GZO- based TrECoG, which presented an average impedance of 36 kΩ at 1 kHz for 500 μm diameter electrodes, a transmittance close to 90% for the visible spectrum and a clear capability to detect brain signal variations. The IZO based devices also presented high transmittance levels (90%), but with higher impedances, which ranged from 40 kΩ to 100 kΩ.

Frequency-domain receiver design for doubly-selective channels

This work is devoted to the broadband wireless transmission techniques, which are serious candidates to be implemented in future broadband wireless and cellular systems, aiming at providing high and reliable data transmission and concomitantly high mobility. In order to cope with doubly-selective channels, receiver structures based on OFDM and SC-FDE block transmission techniques, are proposed, which allow cost-effective implementations, using FFT-based signal processing. The first subject to be addressed is the impact of the number of multipath components, and the diversity order, on the asymptotic performance of OFDM and SC-FDE, in uncoded and for different channel coding schemes. The obtained results show that the number of relevant separable multipath components is a key element that influences the performance of OFDM and SC-FDE schemes. Then, the improved estimation and detection performance of OFDM-based broadcasting systems, is introduced employing SFN (Single Frequency Network) operation. An initial coarse channel is obtained with resort to low-power training sequences estimation, and an iterative receiver with joint detection and channel estimation is presented. The achieved results have shown very good performance, close to that with perfect channel estimation. The next topic is related to SFN systems, devoting special attention to time-distortion effects inherent to these networks. Typically, the SFN broadcast wireless systems employ OFDM schemes to cope with severely time-dispersive channels. However, frequency errors, due to CFO, compromises the orthogonality between subcarriers. As an alternative approach, the possibility of using SC-FDE schemes (characterized by reduced envelope fluctuations and higher robustness to carrier frequency errors) is evaluated, and a technique, employing joint CFO estimation and compensation over the severe time-distortion effects, is proposed. Finally, broadband mobile wireless systems, in which the relative motion between the transmitter and receiver induces Doppler shift which is different or each propagation path, is considered, depending on the angle of incidence of that path in relation to the direction of travel. This represents a severe impairment in wireless digital communications systems, since that multipath propagation combined with the Doppler effects, lead to drastic and unpredictable fluctuations of the envelope of the received signal, severely affecting the detection performance. The channel variations due this effect are very difficult to estimate and compensate. In this work we propose a set of SC-FDE iterative receivers implementing efficient estimation and tracking techniques. The performance results show that the proposed receivers have very good performance, even in the presence of significant Doppler spread between the different groups of multipath components.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.