Extending Science Gateway Frameworks to Support Big Data Applications in the Cloud

Cloud computing offers massive scalability and elasticity required by many scien-tific and commercial applications. Combining the computational and data handling capabilities of clouds with parallel processing also has the potential to tackle Big Data problems efficiently. Science gateway frameworks and workflow systems enable application developers to implement complex applications and make these available for end-users via simple graphical user interfaces. The integration of such frameworks with Big Data processing tools on the cloud opens new oppor-tunities for application developers. This paper investigates how workflow sys-tems and science gateways can be extended with Big Data processing capabilities. A generic approach based on infrastructure aware workflows is suggested and a proof of concept is implemented based on the WS-PGRADE/gUSE science gateway framework and its integration with the Hadoop parallel data processing solution based on the MapReduce paradigm in the cloud. The provided analysis demonstrates that the methods described to integrate Big Data processing with workflows and science gateways work well in different cloud infrastructures and application scenarios, and can be used to create massively parallel applications for scientific analysis of Big Data.

Compositional data analysis of Holocene sediments from the West Bengal Sundarbans, India: Geochemical proxies for grain-size variability in a delta environment

This paper is part of a special issue of Applied Geochemistry focusing on reliable applications of compositional multivariate statistical methods. This study outlines the application of compositional data analysis (CoDa) to calibration of geochemical data and multivariate statistical modelling of geochemistry and grain-size data from a set of Holocene sedimentary cores from the Ganges-Brahmaputra (G-B) delta. Over the last two decades, understanding near-continuous records of sedimentary sequences has required the use of core-scanning X-ray fluorescence (XRF) spectrometry, for both terrestrial and marine sedimentary sequences. Initial XRF data are generally unusable in ‘raw-format’, requiring data processing in order to remove instrument bias, as well as informed sequence interpretation. The applicability of these conventional calibration equations to core-scanning XRF data are further limited by the constraints posed by unknown measurement geometry and specimen homogeneity, as well as matrix effects. Log-ratio based calibration schemes have been developed and applied to clastic sedimentary sequences focusing mainly on energy dispersive-XRF (ED-XRF) core-scanning. This study has applied high resolution core-scanning XRF to Holocene sedimentary sequences from the tidal-dominated Indian Sundarbans, (Ganges-Brahmaputra delta plain). The Log-Ratio Calibration Equation (LRCE) was applied to a sub-set of core-scan and conventional ED-XRF data to quantify elemental composition. This provides a robust calibration scheme using reduced major axis regression of log-ratio transformed geochemical data. Through partial least squares (PLS) modelling of geochemical and grain-size data, it is possible to derive robust proxy information for the Sundarbans depositional environment. The application of these techniques to Holocene sedimentary data offers an improved methodological framework for unravelling Holocene sedimentation patterns.

New Method Based on the UNIFAC–VISCO Model for the Estimation of Ionic Liquids Viscosity Using the Experimental Data Recommended by Mathematical Gnostics

The viscosity of ionic liquids (ILs) has been modeled as a function of temperature and at atmospheric pressure using a new method based on the UNIFAC–VISCO method. This model extends the calculations previously reported by our group (see Zhao et al. J. Chem. Eng. Data 2016, 61, 2160–2169) which used 154 experimental viscosity data points of 25 ionic liquids for regression of a set of binary interaction parameters and ion Vogel–Fulcher–Tammann (VFT) parameters. Discrepancies in the experimental data of the same IL affect the quality of the correlation and thus the development of the predictive method. In this work, mathematical gnostics was used to analyze the experimental data from different sources and recommend one set of reliable data for each IL. These recommended data (totally 819 data points) for 70 ILs were correlated using this model to obtain an extended set of binary interaction parameters and ion VFT parameters, with a regression accuracy of 1.4%. In addition, 966 experimental viscosity data points for 11 binary mixtures of ILs were collected from literature to establish this model. All the binary data consist of 128 training data points used for the optimization of binary interaction parameters and 838 test data points used for the comparison of the pure evaluated values. The relative average absolute deviation (RAAD) for training and test is 2.9% and 3.9%, respectively.

SAPO campus: aprendizagem, ensino e pessoas em rede

As escolas portuguesas do ensino não superior estão dotadas com infraestruturas e equipamentos que permitem trazer o mundo para dentro da sala de aula, tornando o processo de ensino e de aprendizagem mais rico e motivador para os alunos. A adoção institucional de uma plataforma que segue os princípios da web social, o SAPO Campus (SC), definida pela abertura, partilha, integração, inovação e personalização, pode ser catalisadora de processos de mudança e inovação. O presente estudo teve como finalidade acompanhar o processo de adoção do SC em cinco escolas, bem como analisar o impacto no processo de ensino e de aprendizagem e a forma como os alunos e professores se relacionam com esta tecnologia. As escolas envolvidas foram divididas em dois grupos: o primeiro grupo, constituído por três escolas onde o acompanhamento teve uma natureza mais interventiva e presente, enquanto que no segundo grupo, composto por duas escolas, foram apenas observadas as dinâmicas que se desenvolveram no processo de adoção e utilização do SC. No presente estudo, que se assume como um estudo longitudinal de multicasos, foram aplicadas técnicas de tratamento de dados como a estatística descritiva, a análise de conteúdo e a Social Network Analysis (SNA), com o objetivo de, através de uma triangulação permanente, proceder a uma análise dos impactos observados pela utilização do SC. Estes impactos podem ser situados em três níveis diferentes: relativos à instituição, aos professores e aos alunos. Ao nível da adoção institucional de uma tecnologia, verificou-se que essa adoção passa uma mensagem a toda a organização e que, no caso do SC, apela à participação coletiva num ambiente aberto onde as hierarquias se dissipam. Verificou-se ainda que deve implicar o envolvimento dos alunos em atividades significativas e a adoção de estratégias dinâmicas, preferencialmente integradas num projeto mobilizador. A adoção do SC foi ainda catalisadora de dinâmicas que provocaram mudanças nos padrões de consumo e de produção de conteúdos bem como de uma atitude diferente perante o papel da web social no processo de ensino e aprendizagem. As conclusões apontam ainda no sentido da identificação de um conjunto de fatores, observados no estudo, que tiveram impacto no processo de adoção como o papel das lideranças, a importância da formação de professores, a cultura das escolas, a integração num projeto pedagógico e, a um nível mais primário, as questões do acesso à tecnologia. Algumas comunidades construídas à volta do SAPO Campus, envolvendo professores, alunos e a comunidade, evoluíram no sentido da autossustentação, num percurso de reflexão sobre as práticas pedagógicas e partilha de experiências.

Valoração do efluente da indústria processadora de pescado por incorporação de nutrientes em aphanothece microscopica nägeli

Nesta tese procurou-se demonstrar a valoração do efluente do processamento de pescado por incorporação dos nutrientes em Aphanothece microscopica Nägeli a diferentes temperaturas. Para tanto o trabalho é composto de cinco artigos que objetivaram avaliar sob o ponto de vista do tratamento do efluente pela cianobactéria Aphanothece e a separação e avaliação da biomassa gerada. O primeiro artigo intitula-se “Influência da temperatura na remoção de nutrientes do efluente da indústria de pescado por Aphanothece microscopica Nägeli”, e teve por objetivo avaliar a influência da temperatura (10, 20 e 30ºC) em um sistema de tratamento pela cianobactéria Aphanothece na remoção de matéria orgânica, nitrogênio e fósforo do efluente oriundo do processamento de pescado. A análise dos resultados mostrou que a temperatura influenciou significativamente na remoção de DQO, NTK, N-NH4 + e P-PO4 -3 . Para os experimentos a 20 e 30ºC todos os limites estabelecidos para os parâmetros avaliados foram atingidos. O segundo artigo intitulado “Efeito de coagulantes no efluente da indústria da pesca visando à separação de biomassa quando tratado por cianobactéria” avaliou o efeito da concentração e pH de dois tipos de coagulantes, cloreto férrico (FeCl3) e sulfato de alumínio (Al2(SO4)3), na separação da biomassa da cianobactéria Aphanothece microscopica Nägeli cultivada em efluente da indústria da pesca, assim como a remoção de matéria orgânica e nutrientes do efluente. Os resultados indicaram que o coagulante FeCl3 foi mais eficaz na remoção de todos os parâmetros testados. No que concerne à separação da biomassa, com um número de seis lavagens foi removido cerca de 97,6% da concentração de FeCl3 adicionado inicialmente. O terceiro artigo com o título “Caracterização da biomassa de Aphanothece microscopica Nägeli gerada no efluente da indústria da pesca em diferentes temperaturas de cultivo” avaliou a composição química da biomassa da cianobactéria Aphanothece microscopica Nägeli quando desenvolvida em meio de cultivo padrão BG11 e no efluente do processamento de pescado. O quarto artigo teve como título “Influência do meio de cultivo e temperatura em compostos nitrogenados na cianobactéria Aphanothece microscopica Nägeli” objetivou avaliar o teor de compostos nitrogenados presentes na biomassa da cianobactéria Aphanothece microscopica Nägeli quando cultivada em meio padrão e no efluente da indústria da pesca nas diferentes fases de crescimento. Para o estudo da composição química e nitrogenados no efluente foram realizados experimentos nas temperaturas de 10, 20 e 30ºC. As concentrações de proteína, cinzas e pigmentos aumentaram com o aumento da temperatura. Por outro lado, foi observada uma redução do teor de lipídios e carboidratos com o aumento da temperatura. O íon amônio juntamente com os ácidos nucléicos representa uma importante fração do nitrogênio não protéico presente na biomassa da cianobactéria Aphanothece. Ficou demonstrada a influência do meio de cultivo na concentração de nitrogênio, bem como a determinação de proteína pelo método de Kjeldahl superestima a concentração protéica em cianobactérias. O quinto artigo intitulado “Produção de proteína unicelular a partir do efluente do processamento do pescado: modelagem preditiva e simulação” avaliou a produção de proteína unicelular através do cultivo da cianobactéria Aphanothece microscopica Nägeli no efluente da indústria da pesca. Os dados cinéticos de crescimento celular foram ajustados a quatro modelos matemáticos (Logístico, Gompertz, Gompertz Modificado e Baranyi). Os resultados demonstraram que o modelo Logístico foi considerado o mais adequado para descrever a formação de biomassa. A análise preditiva mostrou a possibilidade da obtenção de 1,66, 18,96 e 57,36 kg.m-3.d-1 de biomassa por volume do reator em 1000 h de processo contínuo, para as temperaturas de 10, 20 e 30ºC, respectivamente.

Modelo para formação dinâmica de rede de fornecedores em empresas estendidas

Supply chains have become an important focus for competitive advantage. The performance of a company increasingly depends on its ability to maintain effective and efficient relationships with its suppliers and customers. The extended enterprise (i.e. composed of several partners) needs to be dynamically formed in order to be agile and adaptable. According to the Digital Manufacturing paradigm, companies have to be able to quickly share and disseminate information regarding planning, designing and manufacturing of products. Additionally, they must be responsive to all technical and business determinants, as well as be assessed and certified for guaranteed performance. The current research intends to present a solution for the dynamic composition of the extended enterprise, formed to take advantage of market opportunities quickly and efficiently. A construction model was developed. This construction model consists of: information model, protocol model and process model. The information model has been defined based on the concepts of Supply Chain Operations Reference model (SCOR®). In this model is defined information for negotiating the participation of candidate companies in the dynamic establishment of a network for responding to a given demand for developing and manufacturing products, in seven steps as follows: request for information; request for qualification; alignment of strategy; request for proposal; request for quotation; compatibility of process; and compatibility of system. The protocol model has been elaborated and inspired in the OSI, this model provides a framework for linking customers and suppliers, indicates a sequence to be followed, in order to selecte companies to become suppliers. The process model has been implemented by means of process modeling according to the BPMN standard and, in turn, implemented as a web-based application that runs the process through its several steps, which uses forms to gather data. An application example in the context of the oil and gas industry is used for demonstrating the solution concept.

Gestural communication of music structure during solo classical piano performance

The production and perception of music is a multimodal activity involving auditory, visual and conceptual processing, integrating these with prior knowledge and environmental experience. Musicians utilise expressive physical nuances to highlight salient features of the score. The question arises within the literature as to whether performers’ non-technical, non-sound-producing movements may be communicatively meaningful and convey important structural information to audience members and co-performers. In the light of previous performance research (Vines et al., 2006, Wanderley, 2002, Davidson, 1993), and considering findings within co-speech gestural research and auditory and audio-visual neuroscience, this thesis examines the nature of those movements not directly necessary for the production of sound, and their particular influence on audience perception. Within the current research 3D performance analysis is conducted using the Vicon 12- camera system and Nexus data-processing software. Performance gestures are identified as repeated patterns of motion relating to music structure, which not only express phrasing and structural hierarchy but are consistently and accurately interpreted as such by a perceiving audience. Gestural characteristics are analysed across performers and performance style using two Chopin preludes selected for their diverse yet comparable structures (Opus 28:7 and 6). Effects on perceptual judgements of presentation modes (visual-only, auditory-only, audiovisual, full- and point-light) and viewing conditions are explored. This thesis argues that while performance style is highly idiosyncratic, piano performers reliably generate structural gestures through repeated patterns of upper-body movement. The shapes and locations of phrasing motions are identified particular to the sample of performers investigated. Findings demonstrate that despite the personalised nature of the gestures, performers use increased velocity of movements to emphasise musical structure and that observers accurately and consistently locate phrasing junctures where these patterns and variation in motion magnitude, shape and velocity occur. By viewing performance motions in polar (spherical) rather than cartesian coordinate space it is possible to get mathematically closer to the movement generated by each of the nine performers, revealing distinct patterns of motion relating to phrasing structures, regardless of intended performance style. These patterns are highly individualised both to each performer and performed piece. Instantaneous velocity analysis indicates a right-directed bias of performance motion variation at salient structural features within individual performances. Perceptual analyses demonstrate that audience members are able to accurately and effectively detect phrasing structure from performance motion alone. This ability persists even for degraded point-light performances, where all extraneous environmental information has been removed. The relative contributions of audio, visual and audiovisual judgements demonstrate that the visual component of a performance does positively impact on the over- all accuracy of phrasing judgements, indicating that receivers are most effective in their recognition of structural segmentations when they can both see and hear a performance. Observers appear to make use of a rapid online judgement heuristics, adjusting response processes quickly to adapt and perform accurately across multiple modes of presentation and performance style. In line with existent theories within the literature, it is proposed that this processing ability may be related to cognitive and perceptual interpretation of syntax within gestural communication during social interaction and speech. Findings of this research may have future impact on performance pedagogy, computational analysis and performance research, as well as potentially influencing future investigations of the cognitive aspects of musical and gestural understanding.

Ambiente para aquisição e processamento de sinal eletromiográfico de superfície

In this work, a platform to the conditioning, digitizing, visualization and recording of the EMG signals was developed. After the acquisition, the analysis can be done by signal processing techniques. The platform consists of two modules witch acquire electromyography (EMG) signals by surface electrodes, limit the interest frequency band, filter the power grid interference and digitalize the signals by the analogue-to- digital converter of the modules microcontroller. Thereby, the data are sent to the computer by the USB interface by the HID specification, displayed in real-time in graphical form and stored in files. As processing resources was implemented the operations of signal absolute value, the determination of effective value (RMS), Fourier analysis, digital filter (IIR) and the adaptive filter. Platform initial tests were performed with signal of lower and upper limbs with the aim to compare the EMG signal laterality. The open platform is intended to educational activities and academic research, allowing the addition of other processing methods that the researcher want to evaluate or other required analysis.

Processing Bio-Argo nitrate concentration at the DAC Level

The only method used to date to measure dissolved nitrate concentration (NITRATE) with sensors mounted on profiling floats is based on the absorption of light at ultraviolet wavelengths by nitrate ion (Johnson and Coletti, 2002; Johnson et al., 2010; 2013; D’Ortenzio et al., 2012). Nitrate has a modest UV absorption band with a peak near 210 nm, which overlaps with the stronger absorption band of bromide, which has a peak near 200 nm. In addition, there is a much weaker absorption due to dissolved organic matter and light scattering by particles (Ogura and Hanya, 1966). The UV spectrum thus consists of three components, bromide, nitrate and a background due to organics and particles. The background also includes thermal effects on the instrument and slow drift. All of these latter effects (organics, particles, thermal effects and drift) tend to be smooth spectra that combine to form an absorption spectrum that is linear in wavelength over relatively short wavelength spans. If the light absorption spectrum is measured in the wavelength range around 217 to 240 nm (the exact range is a bit of a decision by the operator), then the nitrate concentration can be determined. Two different instruments based on the same optical principles are in use for this purpose. The In Situ Ultraviolet Spectrophotometer (ISUS) built at MBARI or at Satlantic has been mounted inside the pressure hull of a Teledyne/Webb Research APEX and NKE Provor profiling floats and the optics penetrate through the upper end cap into the water. The Satlantic Submersible Ultraviolet Nitrate Analyzer (SUNA) is placed on the outside of APEX, Provor, and Navis profiling floats in its own pressure housing and is connected to the float through an underwater cable that provides power and communications. Power, communications between the float controller and the sensor, and data processing requirements are essentially the same for both ISUS and SUNA. There are several possible algorithms that can be used for the deconvolution of nitrate concentration from the observed UV absorption spectrum (Johnson and Coletti, 2002; Arai et al., 2008; Sakamoto et al., 2009; Zielinski et al., 2011). In addition, the default algorithm that is available in Satlantic sensors is a proprietary approach, but this is not generally used on profiling floats. There are some tradeoffs in every approach. To date almost all nitrate sensors on profiling floats have used the Temperature Compensated Salinity Subtracted (TCSS) algorithm developed by Sakamoto et al. (2009), and this document focuses on that method. It is likely that there will be further algorithm development and it is necessary that the data systems clearly identify the algorithm that is used. It is also desirable that the data system allow for recalculation of prior data sets using new algorithms. To accomplish this, the float must report not just the computed nitrate, but the observed light intensity. Then, the rule to obtain only one NITRATE parameter is, if the spectrum is present then, the NITRATE should be recalculated from the spectrum while the computation of nitrate concentration can also generate useful diagnostics of data quality.

CATARINA 2012-Leg 1 - CTD-O2 Data report

The CATARINA Leg1 cruise was carried out from June 22 to July 24 2012 on board the B/O Sarmiento de Gamboa, under the scientific supervision of Aida Rios (CSIC-IIM). It included the occurrence of the OVIDE hydrological section that was performed in June 2002, 2004, 2006, 2008 and 2010, as part of the CLIVAR program (name A25) ), and under the supervision of Herlé Mercier (CNRSLPO). This section begins near Lisbon (Portugal), runs through the West European Basin and the Iceland Basin, crosses the Reykjanes Ridge (300 miles north of Charlie-Gibbs Fracture Zone, and ends at Cape Hoppe (southeast tip of Greenland). The objective of this repeated hydrological section is to monitor the variability of water mass properties and main current transports in the basin, complementing the international observation array relevant for climate studies. In addition, the Labrador Sea was partly sampled (stations 101-108) between Greenland and Newfoundland, but heavy weather conditions prevented the achievement of the section south of 53°40’N. The quality of CTD data is essential to reach the first objective of the CATARINA project, i.e. to quantify the Meridional Overturning Circulation and water mass ventilation changes and their effect on the changes in the anthropogenic carbon ocean uptake and storage capacity. The CATARINA project was mainly funded by the Spanish Ministry of Sciences and Innovation and co-funded by the Fondo Europeo de Desarrollo Regional. The hydrological OVIDE section includes 95 surface-bottom stations from coast to coast, collecting profiles of temperature, salinity, oxygen and currents, spaced by 2 to 25 Nm depending on the steepness of the topography. The position of the stations closely follows that of OVIDE 2002. In addition, 8 stations were carried out in the Labrador Sea. From the 24 bottles closed at various depth at each stations, samples of sea water are used for salinity and oxygen calibration, and for measurements of biogeochemical components that are not reported here. The data were acquired with a Seabird CTD (SBE911+) and an SBE43 for the dissolved oxygen, belonging to the Spanish UTM group. The software SBE data processing was used after decoding and cleaning the raw data. Then, the LPO matlab toolbox was used to calibrate and bin the data as it was done for the previous OVIDE cruises, using on the one hand pre and post-cruise calibration results for the pressure and temperature sensors (done at Ifremer) and on the other hand the water samples of the 24 bottles of the rosette at each station for the salinity and dissolved oxygen data. A final accuracy of 0.002°C, 0.002 psu and 0.04 ml/l (2.3 umol/kg) was obtained on final profiles of temperature, salinity and dissolved oxygen, compatible with international requirements issued from the WOCE program.

Pesticide bioconcentration modelling for fruit trees.

The model presented allows simulating the pesticide concentration in fruit trees and estimating the pesticide bioconcentration factor in fruits of woody species. The model allows estimating the pesticide uptake by plants through the water transpiration stream and also the time in which maximum pesticide concentration occur in the fruits. The equation proposed presents the relationships between bioconcentration factor (BCF) and the following variables: plant water transpiration volume (Q), pesticide transpiration stream concentration factor (TSCF), pesticide stem-water partition coefficient (KWood,w), stem dry biomass (M) and pesticide dissipation rate in the soil-plant system (kEGS). The modeling started and was developed from a previous model ?Fruit Tree Model? (FTM), reported by Trapp and collaborators in 2003, to which was added the hypothesis that the pesticide degradation in the soil follows a first order kinetic equation. The model fitness was evaluated through the sensitivity analysis of the pesticide BCF values in fruits with respect to the model entry data variability.

Design de equipamento médico

Dissertação de Mestrado para obtenção do grau de Mestre em Design de Produto, apresentada na Universidade de Lisboa - Faculdade de Arquitectura.

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.

Spatial and Functional Organization of Pig Trade in Different European Production Systems: Implications for Disease Prevention and Control

Understanding the complexity of live pig trade organization is a key factor to predict and control major infectious diseases, such as classical swine fever (CSF) or African swine fever (ASF). Whereas the organization of pig trade has been described in several European countries with indoor commercial production systems, little information is available on this organization in other systems, such as outdoor or small-scale systems. The objective of this study was to describe and compare the spatial and functional organization of live pig trade in different European countries and different production systems. Data on premise characteristics and pig movements between premises were collected during 2011 from Bulgaria, France, Italy, and Spain, which swine industry is representative of most of the production systems in Europe (i.e., commercial vs. small-scale and outdoor vs. indoor). Trade communities were identified in each country using the Walktrap algorithm. Several descriptive and network metrics were generated at country and community levels. Pig trade organization showed heterogeneous spatial and functional organization. Trade communities mostly composed of indoor commercial premises were identified in western France, northern Italy, northern Spain, and north-western Bulgaria. They covered large distances, overlapped in space, demonstrated both scale-free and small-world properties, with a role of trade operators and multipliers as key premises. Trade communities involving outdoor commercial premises were identified in western Spain, south-western and central France. They were more spatially clustered, demonstrated scale-free properties, with multipliers as key premises. Small-scale communities involved the majority of premises in Bulgaria and in central and Southern Italy. They were spatially clustered and had scale-free properties, with key premises usually being commercial production premises. These results indicate that a disease might spread very differently according to the production system and that key premises could be targeted to more cost-effectively control diseases. This study provides useful epidemiological information and parameters that could be used to design risk-based surveillance strategies or to more accurately model the risk of introduction or spread of devastating swine diseases, such as ASF, CSF, or foot-and-mouth disease.

Novel Machine-Learning Based IC Testing Strategy

The final goal of the thesis should be a real-world application in the production test data environment. This includes the pre-processing of the data, building models and visualizing the results. To do this, different machine learning models, outlier prediction oriented, should be investigated using a real dataset. Finally, the different outlier prediction algorithms should be compared, and their performance discussed.