Automating fault tolerance in high-performance computational biological jobs using multi-agent approaches

Background: Large-scale biological jobs on high-performance computing systems require manual intervention if one or more computing cores on which they execute fail. This places not only a cost on the maintenance of the job, but also a cost on the time taken for reinstating the job and the risk of losing data and execution accomplished by the job before it failed. Approaches which can proactively detect computing core failures and take action to relocate the computing core's job onto reliable cores can make a significant step towards automating fault tolerance. Method: This paper describes an experimental investigation into the use of multi-agent approaches for fault tolerance. Two approaches are studied, the first at the job level and the second at the core level. The approaches are investigated for single core failure scenarios that can occur in the execution of parallel reduction algorithms on computer clusters. A third approach is proposed that incorporates multi-agent technology both at the job and core level. Experiments are pursued in the context of genome searching, a popular computational biology application. Result: The key conclusion is that the approaches proposed are feasible for automating fault tolerance in high-performance computing systems with minimal human intervention. In a typical experiment in which the fault tolerance is studied, centralised and decentralised checkpointing approaches on an average add 90% to the actual time for executing the job. On the other hand, in the same experiment the multi-agent approaches add only 10% to the overall execution time

Context-dependent Combination of Sensor Information in Dempster-Shafer Theory for BDI

There has been much interest in the belief–desire–intention (BDI) agent-based model for developing scalable intelligent systems, e.g. using the AgentSpeak framework. However, reasoning from sensor information in these large-scale systems remains a significant challenge. For example, agents may be faced with information from heterogeneous sources which is uncertain and incomplete, while the sources themselves may be unreliable or conflicting. In order to derive meaningful conclusions, it is important that such information be correctly modelled and combined. In this paper, we choose to model uncertain sensor information in Dempster–Shafer (DS) theory. Unfortunately, as in other uncertainty theories, simple combination strategies in DS theory are often too restrictive (losing valuable information) or too permissive (resulting in ignorance). For this reason, we investigate how a context-dependent strategy originally defined for possibility theory can be adapted to DS theory. In particular, we use the notion of largely partially maximal consistent subsets (LPMCSes) to characterise the context for when to use Dempster’s original rule of combination and for when to resort to an alternative. To guide this process, we identify existing measures of similarity and conflict for finding LPMCSes along with quality of information heuristics to ensure that LPMCSes are formed around high-quality information. We then propose an intelligent sensor model for integrating this information into the AgentSpeak framework which is responsible for applying evidence propagation to construct compatible information, for performing context-dependent combination and for deriving beliefs for revising an agent’s belief base. Finally, we present a power grid scenario inspired by a real-world case study to demonstrate our work.

DEVELOPING AN INTELLIGENT DIGITAL MOCK UP TO INTEGRATE DESIGN AND MANUFACTURING DISCIPLINES

This paper presents an approach to develop an intelligent digital mock-up (DMU) through integration of design and manufacturing disciplines to enable a better understanding of assembly related issues during design evolution. The intelligent DMU will contain tolerance information related to manufacturing capabilities so it can be used as a source for assembly simulations of realistic models to support the manufacturing decision making process within the design domain related to tolerance build ups. A literature review of the contributing research areas is presented, from which identification of the need for an intelligent DMU has been developed. The proposed methodology including the applications of cellular modelling and potential features of the intelligent DMU are presented and explained. Finally a conclusion examines the work to date and the future work to achieve an intelligent DMU.

Bioassays against pinewood nematode: assessment of a suitable dilution agent and screening for bioactive essential oils

Acetone was investigated and found to be an appropriate alternative to Triton X-100 as a solvent of essential oils in bioassays aimed to investigate their effects on pinewood nematode (Bursaphelenchus xylophilus) mortality. Therefore it was used as dilution agent to screen the effectiveness of fifty two essential oils against this pest. Thirteen essential oils were highly effective, resulting in more than 90% pinewood nematode mortality at 2 mg/mL, with six of them resulting in 100% mortality. LC100 values ranged between 0.50 mg/mL and 0.83 mg/mL for the essential oils of Origanum vulgare and Satureja montana, respectively. Essential oils were submitted to gas chromatography and gas chromatography-mass spectrometry analysis and their chemical composition established. Data from essential oils with 100% mortality at 2 mg/mL and other essential oils previously found to have LC100 ≤ 2 mg/mL was combined, their chemical profiles investigated by correspondences analysis plus automatic classification.

SWORD: an intelligent vibratory wearable device to improve rehabilitation in stroke patients

Anualmente ocorrem cerca de 16 milhões AVCs em todo o mundo. Cerca de metade dos sobreviventes irá apresentar défice motor que necessitará de reabilitação na janela dos 3 aos 6 meses depois do AVC. Nos países desenvolvidos, é estimado que os custos com AVCs representem cerca de 0.27% do Produto Interno Bruto de cada País. Esta situação implica um enorme peso social e financeiro. Paradoxalmente a esta situação, é aceite na comunidade médica a necessidade de serviços de reabilitação motora mais intensivos e centrados no doente. Na revisão do estado da arte, demonstra-se o arquétipo que relaciona metodologias terapêuticas mais intensivas com uma mais proficiente reabilitação motora do doente. Revelam-se também as falhas nas soluções tecnológicas existentes que apresentam uma elevada complexidade e custo associado de aquisição e manutenção. Desta forma, a pergunta que suporta o trabalho de doutoramento seguido inquire a possibilidade de criar um novo dispositivo de simples utilização e de baixo custo, capaz de apoiar uma recuperação motora mais eficiente de um doente após AVC, aliando intensidade com determinação da correcção dos movimentos realizados relativamente aos prescritos. Propondo o uso do estímulo vibratório como uma ferramenta proprioceptiva de intervenção terapêutica a usar no novo dispositivo, demonstra-se a tolerabilidade a este tipo de estímulos através do teste duma primeira versão do sistema apenas com a componente de estimulação num primeiro grupo de 5 doentes. Esta fase validará o subsequente desenvolvimento do sistema SWORD. Projectando o sistema SWORD como uma ferramenta complementar que integra as componentes de avaliação motora e intervenção proprioceptiva por estimulação, é descrito o desenvolvimento da componente de quantificação de movimento que o integra. São apresentadas as diversas soluções estudadas e o algoritmo que representa a implementação final baseada na fusão sensorial das medidas provenientes de três sensores: acelerómetro, giroscópio e magnetómetro. O teste ao sistema SWORD, quando comparado com o método de reabilitação tradicional, mostrou um ganho considerável de intensidade e qualidade na execução motora para 4 dos 5 doentes testados num segundo grupo experimental. É mostrada a versatilidade do sistema SWORD através do desenvolvimento do módulo de Tele-Reabilitação que complementa a componente de quantificação de movimento com uma interface gráfica de feedback e uma ferramenta de análise remota da evolução motora do doente. Finalmente, a partir da componente de quantificação de movimento, foi ainda desenvolvida uma versão para avaliação motora automatizada, implementada a partir da escala WMFT, que visa retirar o factor subjectivo da avaliação humana presente nas escalas de avaliação motora usadas em Neurologia. Esta versão do sistema foi testada num terceiro grupo experimental de cinco doentes.

Patient classification for intelligent wheelchair adaptation

A importância e preocupação dedicadas à autonomia e independência das pessoas idosas e dos pacientes que sofrem de algum tipo de deficiência tem vindo a aumentar significativamente ao longo das últimas décadas. As cadeiras de rodas inteligentes (CRI) são tecnologias que podem ajudar este tipo de população a aumentar a sua autonomia, sendo atualmente uma área de investigação bastante ativa. Contudo, a adaptação das CRIs a pacientes específicos e a realização de experiências com utilizadores reais são assuntos de estudo ainda muito pouco aprofundados. A cadeira de rodas inteligente, desenvolvida no âmbito do Projeto IntellWheels, é controlada a alto nível utilizando uma interface multimodal flexível, recorrendo a comandos de voz, expressões faciais, movimentos de cabeça e através de joystick. Este trabalho teve como finalidade a adaptação automática da CRI atendendo às características dos potenciais utilizadores. Foi desenvolvida uma metodologia capaz de criar um modelo do utilizador. A investigação foi baseada num sistema de recolha de dados que permite obter e armazenar dados de voz, expressões faciais, movimentos de cabeça e do corpo dos pacientes. A utilização da CRI pode ser efetuada em diferentes situações em ambiente real e simulado e um jogo sério foi desenvolvido permitindo especificar um conjunto de tarefas a ser realizado pelos utilizadores. Os dados foram analisados recorrendo a métodos de extração de conhecimento, de modo a obter o modelo dos utilizadores. Usando os resultados obtidos pelo sistema de classificação, foi criada uma metodologia que permite selecionar a melhor interface e linguagem de comando da cadeira para cada utilizador. A avaliação para validação da abordagem foi realizada no âmbito do Projeto FCT/RIPD/ADA/109636/2009 - "IntellWheels - Intelligent Wheelchair with Flexible Multimodal Interface". As experiências envolveram um vasto conjunto de indivíduos que sofrem de diversos níveis de deficiência, em estreita colaboração com a Escola Superior de Tecnologia de Saúde do Porto e a Associação do Porto de Paralisia Cerebral. Os dados recolhidos através das experiências de navegação na CRI foram acompanhados por questionários preenchidos pelos utilizadores. Estes dados foram analisados estatisticamente, a fim de provar a eficácia e usabilidade na adequação da interface da CRI ao utilizador. Os resultados mostraram, em ambiente simulado, um valor de usabilidade do sistema de 67, baseado na opinião de uma amostra de pacientes que apresentam os graus IV e V (os mais severos) de Paralisia Cerebral. Foi também demonstrado estatisticamente que a interface atribuída automaticamente pela ferramenta tem uma avaliação superior à sugerida pelos técnicos de Terapia Ocupacional, mostrando a possibilidade de atribuir automaticamente uma linguagem de comando adaptada a cada utilizador. Experiências realizadas com distintos modos de controlo revelaram a preferência dos utilizadores por um controlo compartilhado com um nível de ajuda associado ao nível de constrangimento do paciente. Em conclusão, este trabalho demonstra que é possível adaptar automaticamente uma CRI ao utilizador com claros benefícios a nível de usabilidade e segurança.

Methylamine as true template and TEAOH as purifying agent: unexpected roles of current organic additives in the hydrothermal synthesis of microporous aluminophosphates

Methylamine (MA), TEA+ and water were shown to play a concerted role during the synthesis of two new aluminophosphates IST-1 and IST-2. Both structures start to nucleate after the dramatic change of the gel composition due to preliminary interactions between TEA+ cations.

Intelligent predictive control for thermal comfort and energy savings in public buildings

This talk addresses the problem of controlling a heating ventilating and air conditioning system with the purpose of achieving a desired thermal comfort level and energy savings. The formulation uses the thermal comfort, assessed using the predicted mean vote (PMV) index, as a restriction and minimises the energy spent to comply with it. This results in the maintenance of thermal comfort and on the minimisation of energy, which in most operating conditions are conflicting goals requiring some sort of optimisation method to find appropriate solutions over time. In this work a discrete model based predictive control methodology is applied to the problem. It consists of three major components: the predictive models, implemented by radial basis function neural networks identifed by means of a multi-objective genetic algorithm [1]; the cost function that will be optimised to minimise energy consumption and provide adequate thermal comfort; and finally the optimisation method, in this case a discrete branch and bound approach. Each component will be described, with a special emphasis on a fast and accurate computation of the PMV indices [2]. Experimental results obtained within different rooms in a building of the University of Algarve will be presented, both in summer [3] and winter [4] conditions, demonstrating the feasibility and performance of the approach. Energy savings resulting from the application of the method are estimated to be greater than 50%.

Special section on intelligent control systems and signal processing

The IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003) was organized under the auspices of the recently founded IFAC Technical Committee on Cognition and Control, and it was the first IFAC event specifically devoted to this theme. Recognizing the importance of soft-computing techniques for fields covered by other IFAC Technical Committees, ICONS 2003 was a multi-track Conference, co-sponsored by four additional Technical Committees: Computers for Control, Optimal Control, Control in Agriculture, and Modelling, Identification and Signal Processing. The Portuguese Society for Automatic Control (APCA) hosted ICONS 2003, which was held at the University of Algarve, Faro, Portugal.

Intelligent control and signal processing

SYSID is organized every three years. This will be the first SYSID symposium in the 3rd millenium and the second SYSID symposium to take place in The Netherlands. The symposium covers all major aspects of system identification, experimental modelling, signal processing and adaptive control from theoretical and methodological developments to practical applications in a wide range of application areas. The aim of the meeting is to promote the research activities and the cooperation between researchers in these areas. To enhance the applications and industrial perspective of the symposium, participation from industrial authors is particularly encouraged. This will be the first Council meeting after the World Congress in Barcelona last year. The year that has passed has been very active indeed. Following the restructuring of the Technical Board which was endorsed in Barcelona, the 39 Technical Committees within the Technical Board have taken up their work and, after a year, we may say that work is proceeding very smoothly and a lot of activities are going on which will be reported on in greater detail after the meeting of the Technical Board in Rotterdam. The scopes of all these 39 Technical Committees have been revised and were published in Issue 1, 2003 of the IFAC Newsletter, which was published on the web. Shortly a document for download with all the scopes will be available on the web.

On-line operation of an intelligent seismic detector

This study describes the on-line operation of a seismic detection system to act at the level of a seismic station providing similar role to that of a STA /LTA ratio-based detection algorithms. The intelligent detector is a Support Vector Machine (SVM), trained with data consisting of 2903 patterns extracted from records of the PVAQ station, one of the seismographic network's stations of the Institute of Meteorology of Portugal (IM). Records' spectral variations in time and characteristics were reflected in the SVM input patterns, as a set of values of power spectral density at selected frequencies. To ensure that all patterns of the sample data were within the range of variation of the training set, we used an algorithm to separate the universe of data by hyper-convex polyhedrons, determining in this manner a set of patterns that have a mandatory part of the training set. Additionally, an active learning strategy was conducted, by iteratively incorporating poorly classified cases in the training set. After having been trained, the proposed system was experimented in continuous operation for unseen (out of sample) data, and the SVM detector obtained 97.7% and 98.7% of sensitivity and selectivity, respectively. The same type of ANN presented 88.4 % and 99.4% of sensitivity and selectivity when applied to data of a different seismic station of IM. © 2013 Springer-Verlag Berlin Heidelberg.

Interrelationship between two variants of the Circulifer tenellus complex and Spiroplasma citri: the causal agent of stubborn disease

Tese de Doutoramento, Ciências Naturais, Unidade de Ciências e Tecnologias Agrárias, Universidade do Algarve, 1992

Intelligent modelling of temperature propagation induced by therapeutic ultrasound

Dissertação de Mestrado, Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

Design and Qualitative/Quantitative Analysis of Multi-Agent Spatial Simulation Library

Thesis (Master's)--University of Washington, 2012