Face Recognition in the Scrambled Domain via Salience-Aware Ensembles of Many Kernels

With the rapid development of internet-of-things (IoT), face scrambling has been proposed for privacy protection during IoT-targeted image/video distribution. Consequently in these IoT applications, biometric verification needs to be carried out in the scrambled domain, presenting significant challenges in face recognition. Since face models become chaotic signals after scrambling/encryption, a typical solution is to utilize traditional data-driven face recognition algorithms. While chaotic pattern recognition is still a challenging task, in this paper we propose a new ensemble approach – Many-Kernel Random Discriminant Analysis (MK-RDA) to discover discriminative patterns from chaotic signals. We also incorporate a salience-aware strategy into the proposed ensemble method to handle chaotic facial patterns in the scrambled domain, where random selections of features are made on semantic components via salience modelling. In our experiments, the proposed MK-RDA was tested rigorously on three human face datasets: the ORL face dataset, the PIE face dataset and the PUBFIG wild face dataset. The experimental results successfully demonstrate that the proposed scheme can effectively handle chaotic signals and significantly improve the recognition accuracy, making our method a promising candidate for secure biometric verification in emerging IoT applications.

Analysis of multirate behavior in electronic systems

Esta tese insere-se na área da simulação de circuitos de RF e microondas, e visa o estudo de ferramentas computacionais inovadoras que consigam simular, de forma eficiente, circuitos não lineares e muito heterogéneos, contendo uma estrutura combinada de blocos analógicos de RF e de banda base e blocos digitais, a operar em múltiplas escalas de tempo. Os métodos numéricos propostos nesta tese baseiam-se em estratégias multi-dimensionais, as quais usam múltiplas variáveis temporais definidas em domínios de tempo deformados e não deformados, para lidar, de forma eficaz, com as disparidades existentes entre as diversas escalas de tempo. De modo a poder tirar proveito dos diferentes ritmos de evolução temporal existentes entre correntes e tensões com variação muito rápida (variáveis de estado activas) e correntes e tensões com variação lenta (variáveis de estado latentes), são utilizadas algumas técnicas numéricas avançadas para operar dentro dos espaços multi-dimensionais, como, por exemplo, os algoritmos multi-ritmo de Runge-Kutta, ou o método das linhas. São também apresentadas algumas estratégias de partição dos circuitos, as quais permitem dividir um circuito em sub-circuitos de uma forma completamente automática, em função dos ritmos de evolução das suas variáveis de estado. Para problemas acentuadamente não lineares, são propostos vários métodos inovadores de simulação a operar estritamente no domínio do tempo. Para problemas com não linearidades moderadas é proposto um novo método híbrido frequência-tempo, baseado numa combinação entre a integração passo a passo unidimensional e o método seguidor de envolvente com balanço harmónico. O desempenho dos métodos é testado na simulação de alguns exemplos ilustrativos, com resultados bastante promissores. Uma análise comparativa entre os métodos agora propostos e os métodos actualmente existentes para simulação RF, revela ganhos consideráveis em termos de rapidez de computação.

Structural analysis of glycans and development of microarrays from Helcobacter pylori cell surface glycome

Helicobacter pylori is a bacterial pathogen that affects more than half of the world’s population with gastro-intestinal diseases and is associated with gastric cancer. The cell surface of H. pylori is decorated with lipopolysaccharides (LPSs) composed of three distinct regions: a variable polysaccharide moiety (O-chain), a structurally conserved core oligosaccharide, and a lipid A region that anchors the LPS to the cell membrane. The O-chain of H. pylori LPS, exhibits unique oligosaccharide structures, such as Lewis (Le) antigens, similar to those present in the gastric mucosa and are involved in interactions with the host. Glucan, heptoglycan, and riban domains are present in the outer core region of some H. pylori LPSs. Amylose-like glycans and mannans are also constituents of some H. pylori strains, possibly co-expressed with LPSs. The complexity of H. pylori LPSs has hampered the establishment of accurate structure-function relationships in interactions with the host, and the design of carbohydrate-based therapeutics, such as vaccines. Carbohydrate microarrays are recent powerful and sensitive tools for studying carbohydrate antigens and, since their emergence, are providing insights into the function of carbohydrates and their involvement in pathogen-host interactions. The major goals of this thesis were the structural analysis of LPSs from H. pylori strains isolated from gastric biopsies of symptomatic Portuguese patients and the construction of a novel pathogen carbohydrate microarray of these LPSs (H. pylori LPS microarray) for interaction studies with proteins. LPSs were extracted from the cell surface of five H. pylori clinical isolates and one NCTC strain (26695) by phenol/water method, fractionated by size exclusion chromatography and analysed by gas chromatography coupled to mass spectrometry. The oligosaccharides released after mild acid treatment of the LPS were analysed by electrospray mass spectrometry. In addition to the conserved core oligosaccharide moieties, structural analyses revealed the presence of type-2 Lex and Ley antigens and N-acetyllactosamine (LacNAc) sequences, typically found in H. pylori strains. Also, the presence of O-6 linked glucose residues, particularly in LPSs from strains 2191 and NCTC 26695, pointed out to the expression of a 6-glucan. Other structural domains, namely ribans, composed of O-2 linked ribofuranose residues were observed in the LPS of most of H. pylori clinical isolates. For the LPS from strain 14382, large amounts of O-3 linked galactose units, pointing to the occurrence of a galactan, a domain recently identified in the LPS of another H. pylori strain. A particular feature to the LPSs from strains 2191 and CI-117 was the detection of large amounts of O-4 linked N-acetylglucosamine (GlcNAc) residues, suggesting the presence of chitin-like glycans, which to our knowledge have not been described for H. pylori strains. For the construction of the H. pylori LPS microarray, the structurally analysed LPSs, as well as LPS-derived oligosaccharide fractions, prepared as neoglycolipid (NGL) probes were noncovalently immobilized onto nitrocellulosecoated glass slides. These were printed together with NGLs of selected sequence defined oligosaccharides, bacterial LPSs and polysaccharides. The H. pylori LPS microarray was probed for recognition with carbohydratebinding proteins (CBPs) of known specificity. These included Le and blood group-related monoclonal antibodies (mAbs), plant lectins, a carbohydratebinding module (CBM) and the mammalian immune receptors DC-SIGN and Dectin-1. The analysis of these CBPs provided new information that complemented the structural analyses and was valuable in the quality control of the constructed microarray. Microarray analysis revealed the occurrence of type-2 Lex and Ley, but not type-1 Lea or Leb antigens, supporting the results obtained in the structural analysis. Furthermore, the H. pylori LPSs were recognised by DC-SIGN, a mammalian lectin known to interact with this bacterium through fucosylated Le epitopes expressed in its LPSs. The -fucose-specific lectin UEA-I, showed restricted binding to probes containing type-2 blood group H sequence and to the LPSs from strains CI-117 and 14382. The presence of H-type-2, as well Htype- 1 in the LPSs from these strains, was confirmed using specific mAbs. Although H-type-1 determinant has been reported for H. pylori LPSs, this is the first report of the presence of H-type-2 determinant. Microarray analysis also revealed that plant lectins known to bind 4-linked GlcNAc chitin oligosaccharide sequences bound H. pylori LPSs. STL, which exhibited restricted and strong binding to 4GlcNAc tri- and pentasaccharides, differentially recognised the LPS from the strain CI-117. The chitin sequences recognised in the LPS could be internal, as no binding was detected to this LPS with WGA, known to be specific for nonreducing terminal of 4GlcNAc sequence. Analyses of the H. pylori LPSs by SDS-PAGE and Western blot with STL provided further evidence for the presence of these novel domains in the O-chain region of this LPS. H. pylori LPS microarray was also applied to analysis of two human sera. The first was from a case infected with H. pylori (H. pylori+ CI-5) and the second was from a non-infected control.The analysis revealed a higher IgG-reactivity towards H. pylori LPSs in the H. pylori+ serum, than the control serum. A specific IgG response was observed to the LPS isolated from the CI-5 strain, which caused the infection. The present thesis has contributed to extension of current knowledge on chemical structures of LPS from H. pylori clinical isolates. Furthermore, the H. pylori LPS microarray constructed enabled the study of interactions with host proteins and showed promise as a tool in serological studies of H. pyloriinfected individuals. Thus, it is anticipated that the use of these complementary approaches may contribute to a better understanding of the molecular complexity of the LPSs and their role in pathogenesis.

Molecular structure and functional analysis of runx3 in zebrafish

Tese de doutoramento, Ciências Biomédicas, Universidade do Algarve, Departamento de Ciências Biomédicas e Medicina, 2014

2011 mortgage log analysis report

The mortgage log report is a requirement of the South Carolina Mortgage Lending Act. The composite information contained herein is derived from the more than 31,000 entries logged by mortgage lenders and mortgage brokers for the 2011 calendar year.

Optical and mechanical analysis on a biological cell in optical tweezers

La réponse mécanique d’une cellule à une force externe permet d’inférer sa structure et fonction. Les pinces optiques s’avèrent une approche particulièrement attrayante pour la manipulation et caractérisation biophysique sophistiquée des cellules de façon non invasive. Cette thèse explore l’utilisation de trois types de pinces optiques couramment utilisées : 1) statiques (static), 2) à exposition partagée (time-sharing) et 3) oscillantes (oscillating). L’utilisation d’un code basé sur la méthode des éléments finis en trois dimensions (3DFEM) nous permet de modéliser ces trois types de piégeage optique afin d’extraire les propriétés mécaniques cellulaires à partir des expériences. La combinaison des pinces optiques avec la mécanique des cellules requiert des compétences interdisciplinaires. Une revue des approches expérimentales sur le piégeage optique et les tests unicellulaires est présentée. Les bases théoriques liant l’interaction entre la force radiative optique et la réponse mécanique de la cellule aussi. Pour la première fois, une simulation adaptée (3DFEM) incluant la diffusion lumineuse et la distribution du stress radiatif permet de prédire la déformation d’une cellule biconcave –analogue aux globules rouges—dans un piège statique double (static dual-trap). À l’équilibre, on observe que la déformation finale est donnée par l’espacement entre les deux faisceaux lasers: la cellule peut être étirée ou même comprimée. L’exposition partagée (time-sharing) est la technique qui permet de maintenir plusieurs sites de piégeage simultanément à partir du même faisceau laser. Notre analyse quantitative montre que, même oscillantes, la force optique et la déformation sont omniprésentes dans la cellule : la déformation viscoélastique et la dissipation de l’énergie sont analysées. Une autre cellule-type, la tige cubique, est étudiée : cela nous permet d’élucider de nouvelles propriétés sur la symétrie de la réponse mécanique. Enfin, l’analyse de la déformation résolue en temps dans un piége statique ou à exposition partagée montre que la déformation dépend simultanément de la viscoélasticité, la force externe et sa forme tridimensionnelle. La technique à force oscillante (oscillating tweezers) montre toutefois un décalage temporel, entre la force et la déformation, indépendant de la forme 3D; cette approche donnerait directement accès au tenseur viscoélastique complexe de la cellule.

Analysis and compensation of RF impairments for next generation multimode GNSS receivers

Global navigation satellite system (GNSS) receivers require solutions that are compact, cheap and low-power, in order to enable their widespread proliferation into consumer products. Furthermore, interoperability of GNSS with non-navigation systems, especially communication systems will gain importance in providing the value added services in a variety of sectors, providing seamless quality of service for users. An important step into the market for Galileo is the timely availability of these hybrid multi-mode terminals for consumer applications. However, receiver architectures that are amenable to high-levels of integration will inevitably suffer from RF impairments hindering their easy widespread use in commercial products. This paper studies and presents analytical evaluations of the performance degradation due to the RF impairments and develops algorithms that can compensate for them in the DSP domain at the base band with complexity-reduced hardware overheads, hence, paving the way for low-power, highly integrated multi-mode GNSS receivers.

Electrochemical immunosensor for the analysis of the breast cancer biomarker HER2 ECD

Human epidermal growth factor receptor 2 (HER2) is a breast cancer biomarker that plays a major role in promoting breast cancer cell proliferation and malignant growth. The extracellular domain (ECD) of HER2 can be shed into the blood stream and its concentration is measurable in the serum fraction of blood. In this work an electrochemical immunosensor for the analysis of HER2 ECD in human serum samples was developed. To achieve this goal a screen-printed carbon electrode, modified with gold nanoparticles, was used as transducer surface. A sandwich immunoassay, using two monoclonal antibodies, was employed and the detection of the antibody–antigen interaction was performed through the analysis of an enzymatic reaction product by linear sweep voltammetry. Using the optimized experimental conditions the calibration curve (ip vs. log[HER2 ECD]) was established between 15 and 100 ng/mL and a limit of detection (LOD) of 4.4 ng/mL was achieved. These results indicate that the developed immunosensor could be a promising tool in breast cancer diagnostics, patient follow-up and monitoring of metastatic breast cancer since it allows quantification in a useful concentration range and has an LOD below the established cut-off value (15 ng/mL).

Analysis of Forest Fires by means of Pseudo Phase Plane and Multidimensional Scaling Methods

Forest fires dynamics is often characterized by the absence of a characteristic length-scale, long range correlations in space and time, and long memory, which are features also associated with fractional order systems. In this paper a public domain forest fires catalogue, containing information of events for Portugal, covering the period from 1980 up to 2012, is tackled. The events are modelled as time series of Dirac impulses with amplitude proportional to the burnt area. The time series are viewed as the system output and are interpreted as a manifestation of the system dynamics. In the first phase we use the pseudo phase plane (PPP) technique to describe forest fires dynamics. In the second phase we use multidimensional scaling (MDS) visualization tools. The PPP allows the representation of forest fires dynamics in two-dimensional space, by taking time series representative of the phenomena. The MDS approach generates maps where objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to better understand forest fires behaviour.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Dynamical Analysis and Visualization of Tornadoes Time Series

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

An Extension of Estimation of Domain of Attraction for Fractional Order Linear System Subject to Saturation Control

This paper employs the Lyapunov direct method for the stability analysis of fractional order linear systems subject to input saturation. A new stability condition based on saturation function is adopted for estimating the domain of attraction via ellipsoid approach. To further improve this estimation, the auxiliary feedback is also supported by the concept of stability region. The advantages of the proposed method are twofold: (1) it is straightforward to handle the problem both in analysis and design because of using Lyapunov method, (2) the estimation leads to less conservative results. A numerical example illustrates the feasibility of the proposed method.

Co-Authorship of scientists in the energy field: an exploratory study of the ETDE World Energy Database (ETDEWEB) using Social Network Analysis

Paper presented at the 5th European Conference Economics and Management of Energy in Industry, Vilamoura, Algarve. Apr. 14-17, 2009, 11p. URL: http:// www.cenertec.pt/ecemei/

Learning domain-specific sentiment lexicons with applications to recommender systems

Search is now going beyond looking for factual information, and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present dissertation addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. For this research objective we propose to capture sentiment words that are derived from online users’ reviews. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. To this aim we present a fully generative method that automatically learns a domain-specific lexicon and is fully independent of external sources. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. Therefore, we present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm. Furthermore, entities’ reputation is intrinsically associated with sentiment words that have a positive or negative relation with those entities. Hence, is provided a study that observes the viability of using a domain-specific lexicon to compute entities reputation. Finally, a recommendation system algorithm is improved with the use of sentiment-based ratings and entities reputation.