Semantic social network analysis

Mestrado em Engenharia Informática

On the use of IEEE 802.15.4/Zigbee for time-sensitive wireless sensor network applications

Mestrado em Engenharia Electrotécnica e de Computadores

Sistema de detecção de intrusão em redes informáticas

Mestrado em Engenharia Electrotécnica e de Computadores

Celiac disease detection using a transglutaminase electrochemical immunosensor fabricated on nanohybrid screen-printed carbon electrodes

Celiac disease is a gluten-induced autoimmune enteropathy characterized by the presence of tissue tranglutaminase (tTG) autoantibodies. A disposable electrochemical immunosensor (EI) for the detection of IgA and IgG type anti-tTG autoantibodies in real patient’s samples is presented. Screen-printed carbon electrodes (SPCE) nanostructurized with carbon nanotubes and gold nanoparticles were used as the transducer surface. This transducer exhibits the excellent characteristics of carbon–metal nanoparticle hybrid conjugation and led to the amplification of the immunological interaction. The immunosensing strategy consisted of the immobilization of tTG on the nanostructured electrode surface followed by the electrochemical detection of the autoantibodies present in the samples using an alkaline phosphatase (AP) labelled anti-human IgA or IgG antibody. The analytical signal was based on the anodic redissolution of enzymatically generated silver by cyclic voltammetry. The results obtained were corroborated with a commercial ELISA kit indicating that the electrochemical immunosensor is a trustful analytical screening tool.

Towards an Academic Social Network for Bologna Process

The Bologna Process aimed to build a European Higher Education Area promoting student's mobility. The adoption of Bologna Declaration directives requires a self management distributed approach to deal with student's mobility, allowing frequent updates in institutions rules or legislation. This paper suggests a computational system architecture, which follows a social network design. A set of structured annotations is proposed in order to organize the user's information. For instance, when the user is a student its annotations are organized into an academic record. The academic record data is used to discover interests, namely mobility interests, among students that belongs the academic network. These ideas have been applied into a demonstrator that includes a mobility simulator to compare and show the student's academic evolution.

Molecular imprinted nanoelectrodes for ultra sensitive detection of ovarian cancer marker

The relentless discovery of cancer biomarkers demands improved methods for their detection. In this work, we developed protein imprinted polymer on three-dimensional gold nanoelectrode ensemble (GNEE) to detect epithelial ovarian cancer antigen-125 (CA 125), a protein biomarker associated with ovarian cancer. CA 125 is the standard tumor marker used to follow women during or after treatment for epithelial ovarian cancer. The template protein CA 125 was initially incorporated into the thin-film coating and, upon extraction of protein from the accessible surfaces on the thin film, imprints for CA 125 were formed. The fabrication and analysis of the CA 125 imprinted GNEE was done by using cyclic voltammetry (CV), differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS) techniques. The surfaces of the very thin, protein imprinted sites on GNEE are utilized for immunospecific capture of CA 125 molecules, and the mass of bound on the electrode surface can be detected as a reduction in the faradic current from the redox marker. Under optimal conditions, the developed sensor showed good increments at the studied concentration range of 0.5–400 U mL−1. The lowest detection limit was found to be 0.5 U mL−1. Spiked human blood serum and unknown real serum samples were analyzed. The presence of non-specific proteins in the serum did not significantly affect the sensitivity of our assay. Molecular imprinting using synthetic polymers and nanomaterials provides an alternative approach to the trace detection of biomarker proteins.

Ultrasensitive detection of ovarian cancer marker using immunoliposomes and gold nanoelectrodes

Mucin-16 (MUC16) is the established ovarian cancer marker used to follow the disease during or after treatment for epithelial ovarian cancer. The emerging science of cancer markers also demands for the new sensitive detection methods. In this work, we have developed an electrochemical immunosensor for antigen MUC16 using gold nanoelectrode ensemble (GNEE) and ferrocene carboxylic acid encapsulated liposomes tethered with monoclonal anti-Mucin-16 antibodies ( MUC16). GNEEs were fabricated by electroless deposition of the gold within the pores of polycarbonate track-etched membranes. Afterwards, MUC16 were immobilized on preformed self-assembled monolayer of cysteamine on the GNEE via cross-linking with EDC-Sulfo-NHS. A sandwich immunoassay was performed on MUC16 functionalized GNEE with MUC16 and immunoliposomes. The differential pulse voltammetry was employed to quantify the faradic redox response of ferrocene carboxylic acid released from immunoliposomes. The dose–response curve for MUC16 concentration was found between the range of 0.001–300 U mL−1. The lowest detection limit was found to be 5 × 10−4 U mL−1 (S/N = 3). We evaluated the performance of this developed immunosensor with commercial ELISA assay by comparing results obtained from spiked serum samples and real blood serum samples from volunteers.

Electrochemical immunosensor for multiplexed detection of food-borne pathogens using nanocrystal bioconjugates and MWCNT screen-printed electrode

Bacterial food poisoning is an ever-present threat that can be prevented with proper care and handling of food products. A disposable electrochemical immunosensor for the simultaneous measurements of common food pathogenic bacteria namely Escherichia coli O157:H7 (E. coli), campylobacter and salmonella were developed. The immunosensor was fabricated by immobilizing the mixture of anti-E. coli, anticampylobacter and anti-salmonella antibodies with a ratio of 1:1:1 on the surface of the multiwall carbon nanotube-polyallylamine modified screen printed electrode (MWCNT-PAH/SPE). Bacteria suspension became attached to the immobilized antibodies when the immunosensor was incubated in liquid samples. The sandwich immunoassay was performed with three antibodies conjugated with specific nanocrystal ( -E. coli-CdS, -campylobacter-PbS and -salmonella-CuS) which has releasable metal ions for electrochemical measurements. The square wave anodic stripping voltammetry (SWASV) was employed to measure released metal ions from bound antibody nanocrystal conjugates. The calibration curves for three selected bacteria were found in the range of 1 × 103 – 5 × 105 cells mL−1 with the limit of detection (LOD) 400 cells mL−1 for salmonella, 400 cells mL−1 for campylobacter and 800 cells mL−1 for E. coli. The precision and sensitivity of this method show the feasibility of multiplexed determination of bacteria in milk samples.

Academic social network in EHES

This paper presents the foundations of an Academic Social Network (ASN) focusing the Bologna Declaration and the Bologna Process (BP) mobility issues using ontological support. An ASN will permit students to share commons academic interests, preferences and mobility paths in the European Higher Education Space (EHES). The description of the conceptual support is ontology based allowing knowledge sharing and reuse. An approach is presented by merging Academic Ontology to Support the Bologna Mobility Process with Friend of a Friend ontology. The resulting ontology supports the student mobility profile in the ASN. The strategies to make available, in the network, knowledge about mobility issues, are presented including knowledge discovery and simulation approaches to cover student's mobility scenarios for BP.

Analysis and simulation of a-Si Ha-SiC HPINIP structures for color image detection

It is presented in this paper a study on the photo-electronic properties of multi layer a-Si: H/a-SiC: H p-i-n-i-p structures. This study is aimed to give an insight into the internal electrical characteristics of such a structure in thermal equilibrium, under applied Was and under different illumination condition. Taking advantage of this insight it is possible to establish a relation among-the electrical behavior of the structure the structure geometry (i.e. thickness of the light absorbing intrinsic layers and of the internal n-layer) and the composition of the layers (i.e. optical bandgap controlled through percentage of carbon dilution in the a-Si1-xCx: H layers). Showing an optical gain for low incident light power controllable by means of externally applied bias or structure composition, these structures are quite attractive for photo-sensing device applications, like color sensors and large area color image detector. An analysis based on numerical ASCA simulations is presented for describing the behavior of different configurations of the device and compared with experimental measurements (spectral response and current-voltage characteristic). (c) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automatic vehicle detection and classification

This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.

An ultrasound based computer-aided diagnosis tool for steatosis detection

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.

Global and local detection of liver steatosis from ultrasound

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. Steatosis is usually a diffuse liver disease, since it is globally affected. However, steatosis can also be focal affecting only some foci difficult to discriminate. In both cases, steatosis is detected by laboratorial analysis and visual inspection of ultrasound images of the hepatic parenchyma. Liver biopsy is the most accurate diagnostic method but its invasive nature suggest the use of other non-invasive methods, while visual inspection of the ultrasound images is subjective and prone to error. In this paper a new Computer Aided Diagnosis (CAD) system for steatosis classification and analysis is presented, where the Bayes Factor, obatined from objective intensity and textural features extracted from US images of the liver, is computed in a local or global basis. The main goal is to provide the physician with an application to make it faster and accurate the diagnosis and quantification of steatosis, namely in a screening approach. The results showed an overall accuracy of 93.54% with a sensibility of 95.83% and 85.71% for normal and steatosis class, respectively. The proposed CAD system seemed suitable as a graphical display for steatosis classification and comparison with some of the most recent works in the literature is also presented.

Outermost european regions of the atlantic area network

This paper is part of the results from the project "Implementation Strategies and Development of an Open and Distance Education System for the University of the Azores" funded by the European Social Fund. http://hdl.handle.net/10400.3/2327

Descoberta de conhecimento em Logs de tentativas de intrusão. Um estudo de caso em Instituições de Ensino Superior

Perante a evolução constante da Internet, a sua utilização é quase obrigatória. Através da web, é possível conferir extractos bancários, fazer compras em países longínquos, pagar serviços sem sair de casa, entre muitos outros. Há inúmeras alternativas de utilização desta rede. Ao se tornar tão útil e próxima das pessoas, estas começaram também a ganhar mais conhecimentos informáticos. Na Internet, estão também publicados vários guias para intrusão ilícita em sistemas, assim como manuais para outras práticas criminosas. Este tipo de informação, aliado à crescente capacidade informática do utilizador, teve como resultado uma alteração nos paradigmas de segurança informática actual. Actualmente, em segurança informática a preocupação com o hardware é menor, sendo o principal objectivo a salvaguarda dos dados e continuidade dos serviços. Isto deve-se fundamentalmente à dependência das organizações nos seus dados digitais e, cada vez mais, dos serviços que disponibilizam online. Dada a mudança dos perigos e do que se pretende proteger, também os mecanismos de segurança devem ser alterados. Torna-se necessário conhecer o atacante, podendo prever o que o motiva e o que pretende atacar. Neste contexto, propôs-se a implementação de sistemas de registo de tentativas de acesso ilícitas em cinco instituições de ensino superior e posterior análise da informação recolhida com auxílio de técnicas de data mining (mineração de dados). Esta solução é pouco utilizada com este intuito em investigação, pelo que foi necessário procurar analogias com outras áreas de aplicação para recolher documentação relevante para a sua implementação. A solução resultante revelou-se eficaz, tendo levado ao desenvolvimento de uma aplicação de fusão de logs das aplicações Honeyd e Snort (responsável também pelo seu tratamento, preparação e disponibilização num ficheiro Comma Separated Values (CSV), acrescentando conhecimento sobre o que se pode obter estatisticamente e revelando características úteis e previamente desconhecidas dos atacantes. Este conhecimento pode ser utilizado por um administrador de sistemas para melhorar o desempenho dos seus mecanismos de segurança, tais como firewalls e Intrusion Detection Systems (IDS).