Automatic classification of scientific records using the German Subject Heading Authority File (SWD)

The following paper deals with an automatic text classification method which does not require training documents. For this method the German Subject Heading Authority File (SWD), provided by the linked data service of the German National Library is used. Recently the SWD was enriched with notations of the Dewey Decimal Classification (DDC). In consequence it became possible to utilize the subject headings as textual representations for the notations of the DDC. Basically, we we derive the classification of a text from the classification of the words in the text given by the thesaurus. The method was tested by classifying 3826 OAI-Records from 7 different repositories. Mean reciprocal rank and recall were chosen as evaluation measure. Direct comparison to a machine learning method has shown that this method is definitely competitive. Thus we can conclude that the enriched version of the SWD provides high quality information with a broad coverage for classification of German scientific articles.

New approaches for the diagnosis of human papillomavirus infection:relevance for clinical practice and cancer prevention

Tese de doutoramento, Biologia (Microbiologia), Universidade de Lisboa, Faculdade de Ciências, 2014

Automatic extraction of definitions

Tese de doutoramento, Informática (Engenharia Informática), Universidade de Lisboa, Faculdade de Ciências, 2014

Enhancing extractive summarization with automatic post-processing

Tese de doutoramento, Informática (Ciência da Computação), Universidade de Lisboa, Faculdade de Ciências, 2015

Automatic deployment of interoperable legacy code services

The Grid Execution Management for Legacy Code Architecture (GEMLCA) enables exposing legacy applications as Grid services without re-engineering the code, or even requiring access to the source files. The integration of current GT3 and GT4 based GEMLCA implementations with the P-GRADE Grid portal allows the creation, execution and visualisation of complex Grid workflows composed of legacy and nonlegacy components. However, the deployment of legacy codes and mapping their execution to Grid resources is currently done manually. This paper outlines how GEMLCA can be extended with automatic service deployment, brokering, and information system support. A conceptual architecture for an Automatic Deployment Service (ADS) and for an x-Service Interoperability Layer (XSILA) are introduced explaining how these mechanisms support desired features in future releases of GEMLCA.

Pilot study of the utility and acceptability of tampon sampling for the diagnosis of Neisseria gonorrhoeae and Chlamydia trachomatis infections by duplex realtime polymerase chain reaction in United Kingdom sex workers

We aimed to evaluate the acceptability of self-collected tampon samples for the screening of female sex workers for sexually transmitted infections. We recruited 65 sex workers, and 63 agreed to provide tampon samples. The tampon samples were processed by realtime polymerase chain reaction (PCR) targeting Neisseria gonorrhoeae and Chlamydia trachomatis. Urethral and endocervical swabs were also obtained from 61 of 63 participants and tested using culture (N. gonorrhoeae) and the BD ProbeTec strand displacement amplification (SDA) (C. trachomatis) assay. Tampon sampling was preferred by 95% of the women and all favoured being tested away from genitourinary medicine clinics; the most common reasons cited were avoidance of embarrassment (40%) and convenience (30%). Besides near-universal acceptability of tampon sampling, the tampon sampling-PCR approach described in this study appeared to have enhanced sensitivity compared with conventional testing, suggesting the possibility of a residual hidden burden of N. gonorrhoeae and/or C. trachomatis genital infections in UK female sex workers.

Automatic Video Analysis for Fisheries Survey Systems

Thesis (Ph.D.)--University of Washington, 2015

Automatic recognition of seafloor features in sub-bottom profiles using eigenimages

Senior thesis written for Oceanography 445

Automated P.falciparum detection system for post-treatment malaria diagnosis using modified annular ring ratio method

The gametocytes of the malaria parasite Plasmodium falciparum are highly resistant to antimalarial drugs. Its presence in the blood can be detected even after a successful malaria treatment. This paper explains a modified Annular Ring Ratio method which successfully locates and differentiates gametocytes of P. falciparum species in thin blood film images. The method can be used as an efficient tool for gametocyte detection for post-treatment malaria diagnosis. It also identifies the presence of any White Blood Cells (WBCs) in the image, and discards other artifacts and non infected cells. It utilizes the information based on structure, color and geometry of the cells and does not require any segmentation or non-illumination correction techniques that are commonly used for cell detection.

Introducing EbolaCheck: potential for point-of-need infectious disease diagnosis

The 2013–2015 Ebolavirus disease humanitarian crisis has spurred the development of laboratory-free, point-of-care nucleic acid testing solutions. EbolaCheck is an international consortium of public health, academic and biotechnology industry stakeholders aiming to deliver clinical molecular diagnostic standard-of-care testing suitable for the West African milieu within 12 months. In this article, the current status of the EbolaCheck platform is discussed in the context of the current regulatory framework. Presented here are future goals to achieve differential diagnosis of hemorrhagic fever disease from <5-μl of whole blood samples or mucosal biofluids, in a single tube process, under 40 min and with minimal operator training requirements.

DITRANS - a multi-agent system for integrated diagnosis of power transformers

This paper describes the development and the implementation of a multi-agent system for integrated diagnosis of power transformers. The system is divided in layers which contain a number of agents performing different functions. The social ability and cooperation between the agents lead to the final diagnosis and to other relevant conclusions through integrating various monitoring technologies, diagnostic methods and data sources, such as the dissolved gas analysis.

Adaptive tool for automatic data collection of real electricity markets

The study of electricity markets operation has been gaining an increasing importance in last years, as result of the new challenges that the electricity markets restructuring produced. This restructuring increased the competitiveness of the market, but with it its complexity. The growing complexity and unpredictability of the market’s evolution consequently increases the decision making difficulty. Therefore, the intervenient entities are forced to rethink their behaviour and market strategies. Currently, lots of information concerning electricity markets is available. These data, concerning innumerous regards of electricity markets operation, is accessible free of charge, and it is essential for understanding and suitably modelling electricity markets. This paper proposes a tool which is able to handle, store and dynamically update data. The development of the proposed tool is expected to be of great importance to improve the comprehension of electricity markets and the interactions among the involved entities.

Training control centers' operators in incident diagnosis and power restoration using intelligent tutoring systems

The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults like blackouts. In this paper, we present an Intelligent Tutoring approach for training Portuguese Control Center operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, having into account context awareness and the unobtrusive integration in the working environment. Several Artificial Intelligence techniques were criteriously used and combined together to obtain an effective Intelligent Tutoring environment, namely Multiagent Systems, Neural Networks, Constraint-based Modeling, Intelligent Planning, Knowledge Representation, Expert Systems, User Modeling, and Intelligent User Interfaces.