Environment-Aware Regression for Indoor Localization based on WiFi Fingerprinting

Mendoza-Silva, G., Costa, A. C., Torres-Sospedra, J., Painho, M., & Huerta, J. (2022). Environment-Aware Regression for Indoor Localization based on WiFi Fingerprinting. IEEE Sensors Journal, 22(6), 4978 - 4988. https://doi.org/10.1109/JSEN.2021.3073878Data enrichment through interpolation or regression is a common approach to deal with sample collection for Indoor Localization with WiFi fingerprinting. This paper provides guidelines on where to collect WiFi samples, and proposes a new model for received signal strength regression. The new model creates vectors that describe the presence of obstacles between an access point and the collected samples. The vectors, the distance between the access point and the positions of the samples, and the collected, are used to train a Support Vector Regression. The experiments included some relevant analyses and showed that the proposed model improves received signal strength regression in terms of regression residuals and positioning accuracy.authorsversionpublishe

Sensor fusion of IMU and BLE using a well-condition triangle approach for BLE positioning

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesGPS has been a de-facto standard for outdoor positioning. For indoor positioning different systems exist. But there is no general solution to fit all situations. A popular choice among service provider is BLE-based IPS. BLE-has low cost, low power consumption, and tit is are compatible with newer smartphones. These factors make it suitable for mass market applications with an estimated market of 10 billion USD by 2020. Although, BLEbased IPS have advantages over its counterparts, it has not solved the position accuracy problem yet. More research is needed to meet the position accuracy required for indoor LBS. In this thesis, two ways for accuracy improvement were tested i) a new algorithm for BLE-based IPS was proposed and ii) fusion of BLE position estimates with IMU position estimates was implemented. The first way exploits a concept from control survey called well-conditioned triangle. Theoretically, a well-conditioned triangle is an equilateral triangle but for in practice, triangles whose angles are greater than 30° and less than 120° are considered well-conditioned. Triangles which do not satisfy well-condition are illconditioned. An estimated position has the least error if the geometry from which it is estimated satisfy well-condition. Ill-conditioned triangle should not be used for position estimation. The proposed algorithm checked for well-condition among the closest detected beacons and output estimates only when the beacons geometry satisfied well-condition. The proposed algorithm was compared with weighted centroid (WC) algorithm. Proposed algorithm did not improve on the accuracy but the variance in error was highly reduced. The second way tested was fusion of BLE and IMU using Kálmán filter. Fusion generally gives better results but a noteworthy result from fusion was that the position estimates during turns were accurate. When used separately, both BLE and IMU estimates showed errors in turns. Fusion with IMU improved the accuracy. More research is required to improve accuracy of BLE-based IPS. Reproducibility self-assessment (https://osf.io/j97zp/): 2, 2, 2, 1, 2 (input data, prepossessing, methods, computational environment, results)

Self-healing radio maps of wireless networks for indoor positioning

Programa Doutoral em Telecomunicações MAP-tele das Universidades do Minho, Aveiro e PortoA Indústria 4.0 está a impulsionar a mudança para novas formas de produção e otimização em tempo real nos espaços industriais que beneficiam das capacidades da Internet of Things (IoT) nomeadamente, a localização de veículos para monitorização e optimização de processos. Normalmente os espaços industriais possuem uma infraestrutura Wi-Fi que pode ser usada para localizar pessoas, bens ou veículos, sendo uma oportunidade para aumentar a produtividade. Os mapas de rádio são importantes para os sistemas de posicionamento baseados em Wi-Fi, porque representam o ambiente de rádio e são usados para estimar uma posição. Os mapas de rádio são constituídos por amostras Wi-Fi recolhidas em posições conhecidas e degradam-se ao longo do tempo devido a vários fatores, por exemplo, efeitos de propagação, adição/remoção de APs, entre outros. O processo de construção do mapa de rádio costuma ser exigente em termos de tempo e recursos humanos, constituindo um desafio considerável. Os veículos, que operam em ambientes industriais podem ser explorados para auxiliar na construção de mapas de rádio, desde que seja possível localizá-los e rastreá-los. O objetivo principal desta tese é desenvolver um sistema de posicionamento para veículos industriais com mapas de rádio auto-regenerativos (capaz de manter os mapas de rádio atualizados). Os veículos são localizados através da fusão sensorial de Wi-Fi com sensores de movimento, que permitem anotar novas amostras Wi-Fi para o mapa de rádio auto-regenerativo. São propostas duas abordagens de fusão sensorial, baseadas em Loose Coupling e Tight Coupling, para a localização dos veículos. A abordagem Tight Coupling inclui uma métrica de confiança para determinar quando é que as amostras de Wi-Fi devem ser anotadas. Deste modo, esta solução não requer calibração nem esforço humano para a construção e manutenção do mapa de rádio. Os resultados obtidos em experiências sugerem que esta solução tem potencial para a IoT e a Indústria 4.0, especialmente em serviços de localização, mas também na monitorização, suporte à navegação autónoma, e interconectividade.Industry 4.0 is driving change for new forms of production and real-time optimization in factories, which benefit from the Industrial Internet of Things (IoT) capabilities to locate industrial vehicles for monitoring, improving safety, and operations. Most industrial environments have a Wi-Fi infrastructure that can be exploited to locate people, assets, or vehicles, providing an opportunity for enhancing productivity and interconnectivity. Radio maps are important for Wi-Fi-based Indoor Position Systems (IPSs) since they represent the radio environment and are used to estimate a position. Radio maps comprise a set of Wi- Fi samples collected at known positions, and degrade over time due to several aspects, e.g., propagation effects, addition/removal of Access Points (APs), among others, hence they should be periodically updated to maintain the IPS performance. The process to build and maintain radio maps is usually time-consuming and demanding in terms of human resources, thus being challenging to perform. Vehicles, commonly present in industrial environments, can be explored to help build and maintain radio maps, as long as it is possible to locate and track them. The main objective of this thesis is to develop an IPS for industrial vehicles with self-healing radio maps (capable of keeping radio maps up to date). Vehicles are tracked using sensor fusion of Wi-Fi with motion sensors, which allows to annotate new Wi-Fi samples to build the self-healing radio maps. Two sensor fusion approaches based on Loose Coupling and Tight Coupling are proposed to track vehicles. The Tight Coupling approach includes a reliability metric to determine when Wi-Fi samples should be annotated. As a result, this solution does not depend on any calibration or human effort to build and maintain the radio map. Results obtained in real-world experiments suggest that this solution has potential for IoT and Industry 4.0, especially in location services, but also in monitoring and analytics, supporting autonomous navigation, and interconnectivity between devices.MAP-Tele Doctoral Programme scientific committee and the FCT (Fundação para a Ciência e Tecnologia) for the PhD grant (PD/BD/137401/2018

Post-genomic structural analysis of single amino acid polymorphisms

Inherited genetic variation is critical in defining disease susceptibility. PDs, or pathogenic deviations, are mutations reported to be disease-causing, while SNPs, or single nucleotide polymorphisms, are understood to have a negligible effect on phenotype. With recent developments in biotechnology—most relevant being increased reliability and speed of sequencing—a wealth of information regarding SNPs and PDs has been acquired. Quite apart from the analytical challenge of analysing this information with a view to identifying novel therapies and targets for disease, the challenge of simply storing, mapping and processing these data is significant in itself. This thesis describes the development of a large-scale, automated pipeline that provides hypotheses as to what the structural effects of these genomic variations might be. This includes the development of nine new analyses. Eight of these new methods are structural, identifying mutations that disrupt various aspects of protein structure, including the interface, binding sites, folding mechanics and stability. The final new analysis is a novel method of identifying highly conserved residues from sequence. Here, the distribution of conservation scores from a multiple sequence alignment (MSA) is analysed to generate an MSA-specific threshold for high conservation. In order to construct MSAs for the sequence analysis, a novel method for identifying functionally equivalent proteins has been developed. Further, PDs and SNPs are characterised with respect to these structural analyses, and with respect to basic sequence and structural features. The findings support trends elsewhere in the literature: PDs are more often found in the core of proteins and at highly conserved sites; they most often affect the stability of protein structures; and they more often are between very different amino acids. In addition to the implications for disease therapies, these findings are informative in the more general context of protein structure

An experimental rock mechanics investigation into shear discontinuities and their influence in the hydrocarbon resevoir environment

Abstract unavailable please refer to PD

Influence of sea-ice structure on minke whale and other krill-predator distribution

This thesis investigated the extent to which sea-ice structure and complexity could be measured to identify suitable feeding habitat for krill-eating predators such as the Antarctic minke whale (Balaenoptera bonaerensis). The results of this study suggest that the distribution and movement of minke whales is limited by the structure of the sea ice and that the sea ice influences minke whales\u27 habitat use more than their overall distribution. Similar relationships were found for other krill predators such as Adelie penguins and crabeater seals

The climatic significance of tropical forest edges and their representation in global climate models

An emerging theme in global climate modelling is whether land covers created in the clearance of tropical humid forests influence water exchange between remnant forest patches and the atmosphere, and, if so, how this affects regional and global water exchange. Fieldwork presented in this thesis ascertains whether the amount of water transferred to the atmosphere from a humid tropical forest situated in Sabah, Northern Borneo, Malaysia, differs between its edge and interior due to the influence of surrounding clearings through horizontal heat transfer. Using satellite imagery to measure the shape and size of tropical forests, field measurements of water transfer were extrapolated to continental and global levels to infer how differences in water exchange with the atmosphere between forest edges and interiors may influence regional and global forest-atmosphere water exchange. Mean sap flow in trees within 50 meters of a forest-clearing boundary was found to be 73% greater than that in trees further into the forest; an observation supported by the decreased canopy temperature also recorded there. Evaporation from the forest canopy constituted a high fraction of annual rainfall (33%), but showed no edge effect similar to that of sap flow. Edge plots, however, expressed evapotranspiration rates 22% lower than forest interiors (657-890 mm yr-1), owing to the lower number and size of trees there. One edge plot, however, exhibited evapotranspiration 49.5% greater than that of forest interiors. Gradients of air temperature, vapour pressure deficit and wind speed from the adjacent clearing to the forest interior indicated that warm, dry air moving from the clearing to the forest was the most credible cause of increased sap flow of trees near the forest edge. This hypothesis was supported by a strong correlation between the amount of vapour in the air moving from the clearing and tree water use. It was estimated that the influence of differences in water transfer to the atmosphere between the edges and interiors of tropical forest would not alter global water transfer to the atmosphere by more than 0.25-4%, or by 4-7% in the most fragmented tropical continent, Africa. However, it remains unclear whether the inclusion of tropical forest edge effects within climate models is necessary, as the pioneering nature of this thesis, and of existing studies reviewed within it, means that solid conclusions will be dependent upon future work. This thesis concludes with suggestions for future research that will most effectively consolidate the provisional conclusions and recommendations herein

Quantifying the pro- and antimutagenic roles of DNA damage and repair

Genome integrity is essential to the survival of any living organism. The genome is constantly challenged by a multitude of endogenous and exogenous mutagenic factors such as environmental exposures or replication errors. Therefore, evolution has supplied cells with a number of repair mechanisms to protect their genetic information; however, excessive exposures or defects in the repair machinery can lead to the accumulation of deleterious mutations which may cause a range of diseases including cancer. Different mutational processes often leave behind characteristic patterns of mutations, so-called mutational signatures. Mutational signature analysis of tumours has gained a lot of attention recently, because it may reveal carcinogenic exposures and also therapeutic vulnerabilities. So far, over 50 mutational signatures have been identified using pattern recognition in large cancer cohorts, reflecting the action of a range of known mutagenic processes, such as UV light, tobacco smoke or mismatch repair deficiency, but for many mutational signatures an underlying generative process is still unknown. The search for the causes behind a given mutational signature is further complicated by the fact that every alteration in the DNA results from failed or incorrect repair of a DNA lesion, hence there are two factors which jointly shape the mutational spectrum of any mutagenic process. In this thesis, I quantify the variability of mutational signatures in model organisms and in human cancer and explore the diversity of DNA damage-repair interactions. Using data from a large mutagenesis screen in C. elegans, including over 50 DNA repair deficient genetic backgrounds, 12 genotoxins and nearly 200 combinations thereof, I characterise the mutational spectra and genomic features of a range of DNA repair deficiencies, and describe the mutational signatures of genotoxins across multiple genetic backgrounds. Importantly, the mutagenic contributions of genetic and mutagenic factors can vary dev pending on the DNA repair components available: over 35% of genotoxin-knockout combinations demonstrated a measurable effect on the mutation rate compared to expected values, and about 10% also presented a new mutational spectrum. Analysis of mutational signatures in cancer exomes demonstrates the relevance of C. elegans results to cancer investigation. Mismatch repair deficiency patterns extracted from C. elegans are comparable to those in gastrointestinal tumours, and help to dissect convoluted mutational processes. The antagonism between DNA damage and repair drives variability in cancer genomes as well: the observed interaction effects were low in magnitude, but evolutionary considerations suggest that cancer risk may be substantially elevated even by small increases in mutagenicity. In summary, this thesis presents the first comprehensive analysis of mutagenic DNA damage-repair interactions using experimental and cancer data. The results show that mutations result from the opposing pro- and anti-mutagenic forces of DNA damage and repair, which shape mutational signatures in highly variable ways. This variation has to be acknowledged and integrated into mutational signature analysis to ensure reliable interpretation and applicability in clinical oncology. Lastly, the cross-species comparison shows that the fundamental laws of mutagenesis are acting similarly across eukaryotic organisms reminding that many mutational processes fuelling tumorigenesis are not exclusive to cancer, but also drive variation and the evolution of species.My PhD studies were funded by the EMBL International PhD Programme