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En milieu agricole, on observe depuis plusieurs décennies une régression des prairies ainsi qu’uneévolution de leur mode de gestion liées à l’intensification de l’agriculture. Face aux enjeux que ces changementsimpliquent tant sur le plan environnemental qu’économique, l’estimation de la place des prairies dans les systèmes de production et la détermination des pratiques agricoles qui leur sont associées sont stratégiques. Avec l’arrivée de nouveaux capteurs de télédétection à Haute Résolution Spatiale (HRS) caractérisés par une résolution temporelle élevée, il est désormais possible d’envisager l’étude des couverts prairiaux à une échelle fine et à partir d’observations régulières dans le temps. L’objectif de cette thèse est d’identifier les couverts prairiaux à l’échelle des territoires agricoles et de déterminer leurs modes de gestion à partir de paramètres dérivés de séries temporelles d’images de télédétection à HRS. Pour cela, plusieurs séries intra–annuelles d’images à haute résolution spatiale optiques et radars ont été constituées afin de recenser les prairies et d’identifier trois de leurs modes de gestion : le pâturage, la fauche et l’exploitation mixte, sur un bassin versant dont le système d’exploitation dominant est l’élevage laitier. Les résultats obtenus à partir du traitement et de l’analyse des séries temporelles optiques ont permis de montrer qu’il est possible d’estimer avec une bonne précision la biomasse des prairies, de les identifier et de les caractériser. Ils mettent aussi en évidence le fait que les images radars améliorent l’identification des prairies sans pouvoir discriminer leurs modes de gestion, l’utilisation combinée des deux types d’images augmentant encore le taux d’identification des prairies. Par ailleurs, les résultats montrent que les méthodes de classification s’appuyant sur des critères de comparaison adaptés aux séries temporelles (distances élastiques) produisent des résultats nettement plus satisfaisants pour discriminer les modes de gestion des prairies que les méthodes de classification standards. / In agricultural areas, we observed a decrease of grasslands and change in their management in the last half–century, which are commonly associated with agriculture intensification. These changes have affected environmental and economic systems. In this context, the evaluation of grassland status and grassland management in farming systems is a key–issue for sustainable agriculture. With the arrival of new Earth observation sensors with high spatial and temporal resolutions, it is now possible to study grasslands at fine scale using regular observations over time. The objective of this thesis is to identify grasslands and their management practices using parameters derived from time–series of high spatial resolution (HSR) remote sensing data. For that purpose, several intra–annual time series of HSR optical and Synthetic Aperture Radar (SAR) satellite images were acquired in order to identify grasslands and three of their management practices: grazing, mowing and mixed management, on a catchment area mainly oriented towards cattle production. Results obtained from the processing and analysis of the optical time series have shown that it is possible to estimate with good accuracy grassland biomass, to identify and to characterize them. They also highlighted that radar images improve grassland identification without being able to distinguish management practices, the combined use of the two types of images further increasing grassland identification. Furthermore, results showed that the classification methods based on comparison criteria adapted to time series (warping criteria) increase significantly results for discriminating grassland management practices compared to standard classification methods

Timber drying is one of the most important processes whenmanufacturing sawn timber products. The drying processinfluences deformations, surface checking, discoloration andhence, the product quality and the manufacturing costs.Research in this field is of great importance for the woodindustry since the industrial drying process always needs to beimproved as market demands increases and new wood products aredeveloped. The aim of the present thesis was to investigate themoisture transport behaviour in wood based on measurementsduring drying from fresh condition down to end use moisturecontent. The behaviour near the surface interface has beenspecifically investigated since it is of great importance forthe theoretical description of the drying process. Furthermore,studies based on measurements in the wood surface layer duringdrying are not easy to find in the literature. The reason forthat is probably that it is very difficult to make accuratemoisture measurements with high spatial or temporal resolutionwithout disturbing the drying process. Measurements of moisture content profiles in Scots pineheartwood and sapwood during drying have been performed byusing three different methods. The first was a destructivemethod where the wood samples are sliced with a knife intoseveral smaller pieces. The moisture content in each piece wasdetermined with the dry weight method. The second method usedis non-destructive and it utilises a medical CT-scanner thathas been adapted for drying experiments. The samples are driedin-situ the scanner through the whole experiment. TheCT-scanner measures density and the moisture content arecalculated according to existing methods developed by otherscientists. The third method was also non-destructive and itutilises a Magnetic Resonance Imaging, MRI, technique. Withthis technique the amount of water in the wood sample ismeasured directly even though it has to be calibrated tomoisture content. The surface emission factor, S, or surface resistance, 1/S,has been studied by performing sorption experiments with MDF ina narrow moisture content range. The experiment was evaluatedusing a simple diffusion model that includes a surface emissionfactor S. The experimental result was compared with resultscalculated using well established boundary layer theories. Measurements of moisture content profiles in the wood bulkshowed an expected Fickian behaviour at moisture contents belowthe fibre saturation point. Above the fibre saturation pointalmost flat moisture profiles were observed. This behaviour wasnot expected and it is not possible to simulate this behaviourwith the existing drying models since they usually assume thatthere is a gradient in the moisture profile over the wholemoisture content range. From the moisture profiles thediffusion coefficients were determined over a moisture contentranging from 8 to 30%. The values for heartwood and sapwood areapproximately equal in radial and tangential direction tograin. Furthermore, the diffusion values in longitudinaldirection are much higher as expected. The sorption experiments with MDF gave a greater surfaceresistance compared with the calculation that was based onboundary layer theory. The ratio was three or higher. Thisimplied that there was a greater resistance in the surfacelayer. In addition, this was not well described in theliterature even though a few recent published studiesexist. High resolution measurements in the surface layer of woodshowed behaviour similar to that observed in the bulk wood. Theresults showed the very early development of a dry zone closeto the surface interface. In that zone or shell the moisturecontent was below the FSP even though the bulk moisture contentwas far above the FSP. At the end of the experiments themoisture content in the surface layer (0–300 µm)nearly reached the equilibrium moisture content even though thebulk moisture content still was much higher. Keywords:Computer tomography, Diffusion, Magneticresonance, Moisture measurements, Moisture profiles, Surfaceemission, Wood drying / <p>NR 20140805</p>

The cosmic ray neutron method was developed for intermediate-scale soil moisture detection, but may potentially be used for other hydrological applications. The neutron signal of different hydrogen pools is poorly understood and separating them is difficult based on neutron measurements alone. Including neutron transport modeling may accommodate this shortcoming. However, measured and modeled neutrons are not directly comparable. Neither the scale nor energy ranges are equivalent, and the exact neutron energy sensitivity of the detectors is unknown. Here a methodology to enable comparability of the measured and modeled neutrons is presented. The usual cosmic ray soil moisture detector measures moderated neutrons by means of a proportional counter surrounded by plastic, making it sensitive to epithermal neutrons. However, that configuration allows for some thermal neutrons to be measured. The thermal contribution can be removed by surrounding the plastic with a layer of cadmium, which absorbs neutrons with energies below 0.5 eV. Likewise, cadmium shielding of a bare detector allows for estimating the epithermal contribution. First, the cadmium difference method is used to determine the fraction of thermal and epithermal neutrons measured by the bare and plastic-shielded detectors, respectively. The cadmium difference method results in linear correction models for measurements by the two detectors, and has the greatest impact on the neutron intensity measured by the moderated detector at the ground surface. Next, conversion factors are obtained relating measured and modeled neutron intensities. Finally, the methodology is tested by modeling the neutron profiles at an agricultural field site and satisfactory agreement to measurements is found.

A oferta de produtos,informação e serviços a partir de perfis de usuários tem tornado os sistemas de recomendação cada vez mais presentes na Web, aumentando a facilidade de escolha e de permanência dos usuários nestes sistemas. Entretanto, existem otimizações a serem feitas principalmente com relação à modelagem do perfil do usuário. Geralmente, suas preferências são modeladas de modo superficial, devido à escassez das informações coletadas,como notas ou comentários, ou devido a informações indutivas que estão suscetíveis a erros. Esta dissertação propõe uma ferramenta de recomendação baseado em interações multimodais, capaz de combinar informações de usuários processadas individualmente por algoritmos de recomendação tradicionais. Nesta ferramenta desenvolveram-se quatro técnicas de combinação afim fornecer aos sistemas de recomendação, subsídios para melhoria na qualidade das predições em diversos domínios. / Providing products, information and services from user profiles has made the recommendation systems to be increasingly present, increasing the ease of selection and retention of users in Webservices. However, there are optimizations to be made in these systems mainly with respect to modeling the user profile. Generally, the preferences are modeled superficially, due to the scarcity of information collected, as notes or comments, or because of inductive information that is susceptible to errors. This work proposes are commendation tool based on multimodal interactions that combines users\' interactions, wich are processed individually by traditional recommendation algorithms. In this tool developed four combination of techniques in order to provide recommendation systems subsidies to improve the quality of predictions.

Honeypots have been implemented in network security for years now, from the simplesystems where they could only mimic one vulnerable service and gather information aboutan intruder they have morphed in to advanced and complicated environments.Unfortunately, hackers have not left that untouched, and constantly try to detect honeypotsbefore being caught. This ongoing battle can be damaging to unexperienced internet users,who have no idea about securing devices in their small home-based network environment.The purpose of this research is to perform a technical study using IoT devices placed in a homeenvironment in a specially separated segment, and capture traffic between them and externalagents. This data is then analysed and used to build risk profiles of tested IoT devices aimingto provide security recommendations.The results indicate creating risk profiles for IoT devices could be used to gather more preciseinformation about external attacks and provide instant answer to what type of attacks couldbe generated against a selected IoT device. More development would be required to improvethis process, this includes redesign of the network and an automatic software-based toolcapable of generating risk profiles.

With large populations living in tropical regions of the world with volcanic substrates, understanding basalt weathering processes is vital. The Hawaiian Islands are an excellent natural analogue to study chemical weathering rates due to a uniform bedrock (basalt), large variations in rainfall, and varying ages across the islands. Laterite weathering profiles (LWP) develop over time through chemical weathering, where LWP thickness is influenced by many factors, including precipitation and time. Using the rapid, non-invasive horizontal-to-vertical spectral ratio (HVSR) method, LWP thicknesses can be estimated to constrain chemical weathering rates. Studying the laterite weathering profiles developed from basaltic bedrock of varying ages on Oahu (~2 Ma), Molokai (~1 Ma) and Kohala, Hawaii (~0.3 Ma) reveals three profiles in varying developmental stages. Over 200 HVSR soundings were collected on Oahu, Molokai, and Kohala. Shear wave velocity values of LWPs were determined by MASW (multichannel analysis of surface waves), and LWP thicknesses verified from geologic logs and outcrop. Oahu has thick LWPs compared to the other islands and shows a trend of increasing thickness with increasing precipitation across the island. The Molokai LWP follows a trend similar to Oahu, with a noticeable difference of thicknesses (20-40 m) at similar precipitation thresholds. Molokai presented a unique case, where the shear-wave velocity (Vs) boundaries between laterite and basalt were gradational for ~43% of HVSR datapoints, resulting in featureless frequency spectra that could not reliably model laterite-basalt boundary depths. The gradational nature of the LWP of Molokai is attributed to the young age of the island, and primary permeability properties of the thick, post-shield alkalic lavas. Molokai has an aerially average weathering rate of 0.02 to 0.04 m/ka. Kohala HVSR data show a newly developed LWP with varying LWP thickness within the same precipitation isohyet. LWPs on Kohala show a unique trend where LWP is thickest along the coast and is wedge shaped thinning out towards higher elevations. Each island differs in age and has its own unique LWP trends, with older islands tending to have deeper, more developed LWPs at similar precipitation ranges.

Background: In drug discovery morphological profiles can be used to identify and establish a drug's biological activity or mechanism of action. Quantitative structure-activity relationship (QSAR) is an approach that uses the chemical structures to predict properties e.g., biological activity. Support Vector Machine (SVM) is a machine learning algorithm that can be used for classification. Confidence measures as conformal predictions can be implemented on top of machine learning algorithms. There are several methods that can be applied to improve a model’s predictive performance. Aim: The aim in this project is to evaluate if ligand-based modelling can be improved by combining features from chemical structures, target predictions and morphological profiles. Method: The project was divided into three experiments. In experiment 1 five bioassay datasets were used. In experiment 2 and 3 a cell painting dataset was used that contained morphological profiles from three different classes of kinase inhibitors, and the classes were used as endpoints. Support vector machine, liblinear models were built in all three experiments. A significant level of 0.2 was set to calculate the efficiency. The mean observed fuzziness and efficiency were used as measurements to evaluate the model performance. Results: Similar trends were observed for all datasets in experiment 1. Signatures+CDK13+TP which is the most complex model obtained the lowest mean observed fuzziness in four out of five times. With a confidence level of 0.8, TP+Signatures obtained the highest efficiency. Signatures+Morphological Profiles+TP obtained the lowest mean observed fuzziness in experiment 2 and 3. Signatures obtained the highest correct single label predictions with a confidence of 80%. Discussion: Less correct single label predictions were observed for the active class in comparison to the inactive class. This could have been due to them being harder to predict. The morphological profiles did not contribute with an improvement to the models predictive performance compared to Signatures. This could be due to the lack of information obtained from the dataset. Conclusion: A combination of features from chemical structures and target predictions improved ligand-based modelling compared to models only built on one of the features. The combination of features from chemical structures and morphological profiles did not improve the ligand-based models, compared to the model only built on chemical structures. By adding features from target predictions to a model built with features from chemical structures and morphological profiles a decrease in mean observed fuzziness was obtained.

Subclinical atherosclerosis is an important area of research to evaluate stroke risk and predict localization of plaque. The current methods for detecting atherosclerosis risk are insufficient because it is based on The Framingham Risk Score and carotid intima media thickness, therefore an engineering detection model based on quantifiable data is needed. Laminar and turbulent flow, dictated by Reynolds number and relative roughness, was modeled through the carotid artery bifurcation to compare shear stress and shear rate. Computer-aided design and fluid flow software were used to model hemodynamics through the carotid artery. Data from the model was derived from governing equations programmed in COMSOL for both laminar and turbulent flow. A carotid artery model is accurate enough to describe how relative roughness, flow profiles, and shear rate can be a good prediction of subclinical atherosclerosis.

The aim of the diploma thesis is design and assessment of steel structure of greenhouse in botanical garden in Ostrava. The building is designed as a hexagon with a diameter 50 m, the highest point of the construction is 32,907 m. Whole structure will be made of hollow round tubes of different profiles. The support system consist of columns and truss girders. The bracing of the structure is in three levels. Main construction material is steel S355 J0+AR. The covering of the roofs and walls is made of glass panels ISOTHERM.