987 resultados para Source profiles


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Hendra virus (HeV) causes highly lethal disease in horses and humans in the eastern Australian states of Queensland (QLD) and New South Wales (NSW), with multiple equine cases now reported on an annual basis. Infection and excretion dynamics in pteropid bats (flying-foxes), the recognised natural reservoir, are incompletely understood. We sought to identify key spatial and temporal factors associated with excretion in flying-foxes over a 2300 km latitudinal gradient from northern QLD to southern NSW which encompassed all known equine case locations. The aim was to strengthen knowledge of Hendra virus ecology in flying-foxes to improve spillover risk prediction and exposure risk mitigation strategies, and thus better protect horses and humans. Monthly pooled urine samples were collected from under roosting flying-foxes over a three-year period and screened for HeV RNA by quantitative RT-PCR. A generalised linear model was employed to investigate spatiotemporal associations with HeV detection in 13,968 samples from 27 roosts. There was a non-linear relationship between mean HeV excretion prevalence and five latitudinal regions, with excretion moderate in northern and central QLD, highest in southern QLD/northern NSW, moderate in central NSW, and negligible in southern NSW. Highest HeV positivity occurred where black or spectacled flying-foxes were present; nil or very low positivity rates occurred in exclusive grey-headed flying-fox roosts. Similarly, little red flying-foxes are evidently not a significant source of virus, as their periodic extreme increase in numbers at some roosts was not associated with any concurrent increase in HeV detection. There was a consistent, strong winter seasonality to excretion in the southern QLD/northern NSW and central NSW regions. This new information allows risk management strategies to be refined and targeted, mindful of the potential for spatial risk profiles to shift over time with changes in flying-fox species distribution.

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Online content services can greatly benefit from personalisation features that enable delivery of content that is suited to each user's specific interests. This thesis presents a system that applies text analysis and user modeling techniques in an online news service for the purpose of personalisation and user interest analysis. The system creates a detailed thematic profile for each content item and observes user's actions towards content items to learn user's preferences. A handcrafted taxonomy of concepts, or ontology, is used in profile formation to extract relevant concepts from the text. User preference learning is automatic and there is no need for explicit preference settings or ratings from the user. Learned user profiles are segmented into interest groups using clustering techniques with the objective of providing a source of information for the service provider. Some theoretical background for chosen techniques is presented while the main focus is in finding practical solutions to some of the current information needs, which are not optimally served with traditional techniques.

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Free and open source software development is an alternative to traditional software engineering as an approach to the development of complex software systems. It is a way of developing software based on geographically distributed teams of volunteers without apparent central plan or traditional mechanisms of coordination. The purpose of this thesis is to summarize the current knowledge about free and open source software development and explore the ways on which further understanding on it could be gained. The results of research on the field as well as the research methods are introduced and discussed. Also adapting software process metrics to the context of free and open source software development is illustrated and the possibilities to utilize them as tools to validate other research are discussed.

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Abstract is not vailable.

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The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

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A mathematical model for doped-oxide-source diffusion is proposed. In this model the concept of segregation of impurity at the silicon-silicon dioxide is used and also a constant of “rate limitation” is introduced through a chemical reaction at the interface.

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The solution for a line source of oscillatory strength kept at the origin in a wall bounding a semi-infinite viscous imcompressible stratified fluid is presented in an integral form. The behaviour of the flow at far field and near field is studied by an asymptotic expansion procedure. The streamlines for different parameters are drawn and discussed. The real characteristic straight lines present in the inviscid problem are modified by the viscosity and the solutions obtained are valid even at the resonance frequency.

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Aerosol particles can cause detrimental environmental and health effects. The particles and their precursor gases are emitted from various anthropogenic and natural sources. It is important to know the origin and properties of aerosols to efficiently reduce their harmful effects. The diameter of aerosol particles (Dp) varies between ~0.001 and ~100 μm. Fine particles (PM2.5: Dp < 2.5 μm) are especially interesting because they are the most harmful and can be transported over long distances. The aim of this thesis is to study the impact on air quality by pollution episodes of long-range transported aerosols affecting the composition of the boundary-layer atmosphere in remote and relatively unpolluted regions of the world. The sources and physicochemical properties of aerosols were investigated in detail, based on various measurements (1) in southern Finland during selected long-range transport (LRT) pollution episodes and unpolluted periods and (2) over the Atlantic Ocean between Europe and Antarctica during a voyage. Furthermore, the frequency of LRT pollution episodes of fine particles in southern Finland was investigated over a period of 8 years, using long-term air quality monitoring data. In southern Finland, the annual mean PM2.5 mass concentrations were low but LRT caused high peaks of daily mean concentrations every year. At an urban background site in Helsinki, the updated WHO guideline value (24-h PM2.5 mean 25 μg/m3) was exceeded during 1-7 LRT episodes each year during 1999-2006. The daily mean concentrations varied between 25 and 49 μg/m3 during the episodes, which was 3-6 times higher than the mean concentration in the long term. The in-depth studies of selected LRT episodes in southern Finland revealed that biomass burning in agricultural fields and wildfires, occurring mainly in Eastern Europe, deteriorated air quality on a continental scale. The strongest LRT episodes of fine particles resulted from open biomass-burning fires but the emissions from other anthropogenic sources in Eastern Europe also caused significant LRT episodes. Particle mass and number concentrations increased strongly in the accumulation mode (Dp ~ 0.09-1 μm) during the LRT episodes. However, the concentrations of smaller particles (Dp < 0.09 μm) remained low or even decreased due to the uptake of vapours and molecular clusters by LRT particles. The chemical analysis of individual particles showed that the proportions of several anthropogenic particle types increased (e.g. tar balls, metal oxides/hydroxides, spherical silicate fly ash particles and various calcium-rich particles) in southern Finland during an LRT episode, when aerosols originated from the polluted regions of Eastern Europe and some open biomass-burning smoke was also brought in by LRT. During unpolluted periods when air masses arrived from the north, the proportions of marine aerosols increased. In unpolluted rural regions of southern Finland, both accumulation mode particles and small-sized (Dp ~ 1-3 μm) coarse mode particles originated mostly from LRT. However, the composition of particles was totally different in these size fractions. In both size fractions, strong internal mixing of chemical components was typical for LRT particles. Thus, the aging of particles has significant impacts on their chemical, hygroscopic and optical properties, which can largely alter the environmental and health effects of LRT aerosols. Over the Atlantic Ocean, the individual particle composition of small-sized (Dp ~ 1-3 μm) coarse mode particles was affected by continental aerosol plumes to distances of at least 100-1000 km from the coast (e.g. pollutants from industrialized Europe, desert dust from the Sahara and biomass-burning aerosols near the Gulf of Guinea). The rate of chloride depletion from sea-salt particles was high near the coasts of Europe and Africa when air masses arrived from polluted continental regions. Thus, the LRT of continental aerosols had significant impacts on the composition of the marine boundary-layer atmosphere and seawater. In conclusion, integration of the results obtained using different measurement techniques captured the large spatial and temporal variability of aerosols as observed at terrestrial and marine sites, and assisted in establishing the causal link between land-bound emissions, LRT and air quality.

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During the past ten years, large-scale transcript analysis using microarrays has become a powerful tool to identify and predict functions for new genes. It allows simultaneous monitoring of the expression of thousands of genes and has become a routinely used tool in laboratories worldwide. Microarray analysis will, together with other functional genomics tools, take us closer to understanding the functions of all genes in genomes of living organisms. Flower development is a genetically regulated process which has mostly been studied in the traditional model species Arabidopsis thaliana, Antirrhinum majus and Petunia hybrida. The molecular mechanisms behind flower development in them are partly applicable in other plant systems. However, not all biological phenomena can be approached with just a few model systems. In order to understand and apply the knowledge to ecologically and economically important plants, other species also need to be studied. Sequencing of 17 000 ESTs from nine different cDNA libraries of the ornamental plant Gerbera hybrida made it possible to construct a cDNA microarray with 9000 probes. The probes of the microarray represent all different ESTs in the database. From the gerbera ESTs 20% were unique to gerbera while 373 were specific to the Asteraceae family of flowering plants. Gerbera has composite inflorescences with three different types of flowers that vary from each other morphologically. The marginal ray flowers are large, often pigmented and female, while the central disc flowers are smaller and more radially symmetrical perfect flowers. Intermediate trans flowers are similar to ray flowers but smaller in size. This feature together with the molecular tools applied to gerbera, make gerbera a unique system in comparison to the common model plants with only a single kind of flowers in their inflorescence. In the first part of this thesis, conditions for gerbera microarray analysis were optimised including experimental design, sample preparation and hybridization, as well as data analysis and verification. Moreover, in the first study, the flower and flower organ-specific genes were identified. After the reliability and reproducibility of the method were confirmed, the microarrays were utilized to investigate transcriptional differences between ray and disc flowers. This study revealed novel information about the morphological development as well as the transcriptional regulation of early stages of development in various flower types of gerbera. The most interesting finding was differential expression of MADS-box genes, suggesting the existence of flower type-specific regulatory complexes in the specification of different types of flowers. The gerbera microarray was further used to profile changes in expression during petal development. Gerbera ray flower petals are large, which makes them an ideal model to study organogenesis. Six different stages were compared and specifically analysed. Expression profiles of genes related to cell structure and growth implied that during stage two, cells divide, a process which is marked by expression of histones, cyclins and tubulins. Stage 4 was found to be a transition stage between cell division and expansion and by stage 6 cells had stopped division and instead underwent expansion. Interestingly, at the last analysed stage, stage 9, when cells did not grow any more, the highest number of upregulated genes was detected. The gerbera microarray is a fully-functioning tool for large-scale studies of flower development and correlation with real-time RT-PCR results show that it is also highly sensitive and reliable. Gene expression data presented here will be a source for gene expression mining or marker gene discovery in the future studies that will be performed in the Gerbera Laboratory. The publicly available data will also serve the plant research community world-wide.

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Recommender systems assist users in finding what they want. The challenging issue is how to efficiently acquire user preferences or user information needs for building personalized recommender systems. This research explores the acquisition of user preferences using data taxonomy information to enhance personalized recommendations for alleviating cold-start problem. A concept hierarchy model is proposed, which provides a two-dimensional hierarchy for acquiring user preferences. The language model is also extended for the proposed hierarchy in order to generate an effective recommender algorithm. Both Amazon.com book and music datasets are used to evaluate the proposed approach, and the experimental results show that the proposed approach is promising.

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Behavioral profiles have been proposed as a behavioral abstraction of dynamic systems, specifically in the context of business process modeling. A behavioral profile can be seen as a complete graph over a set of task labels, where each edge is annotated with one relation from a given set of binary behavioral relations. Since their introduction, behavioral profiles were argued to provide a convenient way for comparing pairs of process models with respect to their behavior or computing behavioral similarity between process models. Still, as of today, there is little understanding of the expressive power of behavioral profiles. Via counter-examples, several authors have shown that behavioral profiles over various sets of behavioral relations cannot distinguish certain systems up to trace equivalence, even for restricted classes of systems represented as safe workflow nets. This paper studies the expressive power of behavioral profiles from two angles. Firstly, the paper investigates the expressive power of behavioral profiles and systems captured as acyclic workflow nets. It is shown that for unlabeled acyclic workflow net systems, behavioral profiles over a simple set of behavioral relations are expressive up to configuration equivalence. When systems are labeled, this result does not hold for any of several previously proposed sets of behavioral relations. Secondly, the paper compares the expressive power of behavioral profiles and regular languages. It is shown that for any set of behavioral relations, behavioral profiles are strictly less expressive than regular languages, entailing that behavioral profiles cannot be used to decide trace equivalence of finite automata and thus Petri nets.

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Corporate executives require relevant and intelligent business information in real-time to take strategic decisions. They require the freedom to access this information anywhere and anytime. There is a need to extend this functionality beyond the office and on the fingertips of the decision makers. Mobile Business Intelligence Tool (MBIT) aims to provide these features in a flexible and cost-efficient manner. This paper describes the detailed architecture of MBIT to overcome the limitations of existing mobile business intelligence tools. Further, a detailed implementation framework is presented to realize the design. This research highlights the benefits of using service oriented architecture to design flexible and platform independent mobile business applications. © 2009 IEEE.

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Impervious surfaces in an urban catchment are the primary stormwater pollutant contributing areas. Appropriate treatment of stormwater runoff from these impervious surfaces is essential to safeguard the urban water environment. While urban roads have received significant research attention in this regard, roofs have not been well investigated. Key pollutant processes such as build-up on roads and roofs can be different due to the different surface characteristics. This entails different treatment strategies being needed for road and roofs. The research study characterized roof pollutants build-up by differentiating with road surfaces. It was noted that pollutants are more highly concentrated on particles and particularly finer particles in the case of roof surfaces, compared to road surfaces. Additionally, pollutants built-up on roof surfaces tend to be relatively more variable from one day to another in terms of pollutant loads. These results highlight the significance of roofs as a stormwater pollutant source and the important need for a specific stormwater treatment strategy rather than the application of a combined approach for treating stormwater runoff from both, roads and roofs.

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A geodesic-based approach using Lamb waves is proposed to locate the acoustic emission (AE) source and damage in an isotropic metallic structure. In the case of the AE (passive) technique, the elastic waves take the shortest path from the source to the sensor array distributed in the structure. The geodesics are computed on the meshed surface of the structure using graph theory based on Dijkstra's algorithm. By propagating the waves in reverse virtually from these sensors along the geodesic path and by locating the first intersection point of these waves, one can get the AE source location. The same approach is extended for detection of damage in a structure. The wave response matrix of the given sensor configuration for the healthy and the damaged structure is obtained experimentally. The healthy and damage response matrix is compared and their difference gives the information about the reflection of waves from the damage. These waves are backpropagated from the sensors and the above method is used to locate the damage by finding the point where intersection of geodesics occurs. In this work, the geodesic approach is shown to be suitable to obtain a practicable source location solution in a more general set-up on any arbitrary surface containing finite discontinuities. Experiments were conducted on aluminum specimens of simple and complex geometry to validate this new method.