The aim of this diploma thesis is a creation of modal parameter estimation application. Modal properties (natural frequencies, damping factors and mode shapes) are used in many dynamics analysis and their accurate determination is very important therefore the modal parameter estimation is one of the most significant part of the experimental modal analysis. Many methods have been developed for modal parameter estimation, each of them with different assumptions and with different accuracy. In the beginning of this thesis, a theory connected with modal analysis and a theory which is necessary for understanding to presented modal parameter methods are given. Then four different modal parameter estimation methods are presented - Peak Picking, Circle Fit, Least Square method and Eigensystem Realization Algorithm. The application for the modal parameter estimation is the output of this diploma thesis. In addition, the application allows performing all experimental modal analysis such as estimation of frequency response functions, animation of the found mode shapes, different kinds of comparison etc. In the conclusion, three structures are shown on which the application and modal parameter estimation methods were tested.

The aim of this work is to introduce a new type of fuzzy system AnYa. This system, unlike the classical fuzzy systems Takagi-Sugeno and Mamdani, uses a type of antecendent based on real data distribution. As part of the work there will be mentioned system programmed and its functionality will be verified on testing data.

Summary Fresh water availability and distribution have been declining over time due to population increase, climate change and variability, emerging new demands due to economic growth, and changing consumption patterns. Spatial and temporal changes in environmental changes, such as climate and land use/cover (LULC) dynamics have an enormous impact on water availability. Food and energy security, urbanization and industrial growth, as well as climate change (CC) will pose critical challenges on water resources. Climate variability and change may affect both the supply and demand sides of the balance, and thus add to the challenges. Land-cover changes are vastly prominent in the developing countries that are characterized by agriculture-based economies and rapidly increasing human population. The consequent changes in water availability and increase in per capita water demand will adversely affect the food, water and energy security of those countries. Therefore, evaluating the response of the catchment to environmental changes is crucial in the critical part of the basin for sustainable water resource management and development. In particular, assessing the contribution of individual LULC classes to changes in water balance components is vital for effective water and land resource management, and for mitigation of climate change impacts. The dynamic water balance of a catchment is analyzed by hydrological models that consider spatio-temporal catchment characteristics. As a result, hydrological models have become indispensable tools for the study of hydrological processes and the impacts of environmental stressors on the hydrologic system. Physically-based distributed hydrological models are able to explicitly account for the spatial variability of hydrological process, catchment characteristics such as climatic parameters, and land use/cover changes. For improved illustration of physical processes in space and time, the distributed hydrological models need serially complete and homogenized rainfall and temperature data. However, observed rainfall and temperature data are neither serially complete nor homogeneous, particularly in developing countries. Using inhomogeneous climatological data inputs to hydrological models affects the output magnitude of climate and land use/cover change impacts and, hence, climate change adaptation. The Nile River Basin, one of the transboundary river flows through 11 riparian states, serves the livelihoods of millions of people in the basin (nearly 20 per cent of the African population) and covers one-tenth of the land cover of Africa. The basin is characterized by high population growth and high temporal variability in the river flow and rainfall patterns. The Blue Nile river basin, which contributes 62% of the annual main Nile flow, has faced serious land degradation. This has led to increased soil erosion and loss of soil fertility. The most overwhelming challenge that the basin faces is food insecurity caused by subsistence farming and rain-fed agriculture (over 70% of the basin’s population), together with high rainfall variability. Drought and floods are also critical issues in the Blue Nile basin, with the potential for exacerbation by environmental changes. Understanding how LULC and climate changes influence basin hydrology will therefore enable decision makers to introduce policies aimed at reducing the detrimental effects of future environmental changes on water resources. Understanding types and impacts of major environmental stressors in representative and critical regions of the basin is crucial for developing of effective response strategies for sustainable land- and water-resource management in the Eastern Nile Basin in general, and at the Tana and Beles watersheds in particular. In this study, serially completed and homogenized rainfall and temperature dataset are maintained from 1980 to 2013 to fill-in the gap which characterized previous studies on trend analyses. The new hydroclimatic data revealed that the climate the study region has become wetter and warmer. The proportional contribution of main rainy season rainfall to annual total rainfall has increased. This might result in high runoff and ultimately flooding as well as erosion and sedimentation in the source region of the Blue Nile, and siltation in the downstream reservoirs unless soil and water conservation measures are taking place. In the Tana sub-basin, it is found that expansion of cultivation land and decline in woody shrub are the major contributors to the rise in surface run-off and to the decline in the groundwater component from 1986 to 2010. Similarly, decline of woodland and expansion of cultivation land are found to be the major contributors to the increase in surface run-off and water yield. They also contributed to the decrease in groundwater and actual evapotranspiration components in the Beles watershed. Increased run-off and reduced baseflow and actual evapotranspiration would have negative impacts on water resources, especially in relation to erosion and sedimentation in the upper Blue Nile River Basin. As a result, expansion of cultivation land and decline in woody shrub/woodland appear to be major environmental stressors affecting local water resources. GCMs simulated near-future annual total rainfall and average temperature were used to investigate the sensitivity of the catchment to near-future CC. The results showed an increase in streamflow in the annual and the main rainy season, but decrease in the dry period when compared to the baseline period. Catchment response for future LULC scenario showed opposite effect to that of near-future CC. The combined effects of climate change and LULC dynamics can be quite different from the effects resulting from LULC or CC alone. At the outlet of the Tana watershed, streamflow response is amplified under concurrent land cover and climate change scenarios compared to the baseline scenario; but the streamflow has an augmenting response at the outlet of the Beles watershed under future climate change and land use scenarios compared to that of current period. The important inference from these findings is that it could be possible to alleviate intense floods or droughts due to future climate change by planning LULC to achieve particular hydrological effects of land cover in the basin. Continuing expansion of cultivation land and decrease in natural vegetation, coupled with increased rainfall due to climate change, would result in high surface runoff in the main rainy season, which would subsequently increase flooding, erosion and sedimentation in already degraded lands. Sound mitigation measures should therefore be applied to reduce these adverse environmental consequences. On the other hand, the simulated climate and land-use change impacts on the Tana watershed hydrological regime might increase the availability of streamflow to be harnessed by water-storage structures. In conclusion, the present study has developed an innovative approach to identify the major environmental stressors of critical source region of the Blue Nile River in order to effectively managing the water resources and climate risk. Understanding the catchment responses to environmental changes improves sustainability of the water resources management particularly given that the hydropower and the irrigation schemes are recently established for energy and food security.:TABLE OF CONTENTS LIST OF ABBREVIATIONS LIST OF FIGURES LIST OF TABLES 1. General Introduction 2. The study area 3. Gap Filling and Homogenization of Climatological Datasets in the Headwater Region of the Upper Blue Nile Basin, Ethiopia Abstract 3.1. Introduction 3.1.1. Data 3.2. Methodology 3.2.1. Quality control and gap filling 3.2.2. Homogenization 3.3. Results and Discussion 3.3.1. Gap filling 3.3.2. Homogeneity 3.3.3. Verification of the homogenization 3.3.4. Impact of homogenization on the rainfall and temperature series 3.4. Conclusions Acknowledgements 4. Revisiting trend analysis of hydroclimatic data in the Upper Blue Nile basin based on homogenized data Abstract 4.1 Introduction 4.2 Data and Methodology 4. 2.1 Data 4. 2.2 Linear trend 4. 2.3 Trend magnitude 4.3 Results and Discussions 4.3.1. Linear mean climate trends 4.3.1.1. Rainfall 4.3.1.2. Maximum Temperature (Tmax) 4.3.1.3. Minimum Temperature (Tmin) 4.3.1.4. Mean temperature (Tmean) 4.3.1.5. Diurnal temperature range (DTR) 4.3.1.6. Streamflow 4.3.2. Effect of homogenization on Tmax, Tmin, Tmean and DTR linear trends 4.3.3. Linear extreme climate trends 4.3.1. Temperature 4.3.2. Precipitation 4.4 Conclusions Acknowledgements 5. Recent Changes in Land Use/Cover in the Headwater Region of the Upper Blue Nile Basin, Ethiopia 85 Abstract 5.1 Introduction 5.2 Materials and Methods 5.2.1 Data used and image pre-processing 5.2.2 Classification accuracy assessment 5.2.3 Extent and rate of change 5.2.4 Detecting the most systematic transitions (dominant signals of change) 5.4 Results and Discussion 5.4.1 Accuracy assessment 5.4.2 Extent and rate of LULC changes 5.4.3 Rate of land use and land cover change 5.4.4 Detection of most systematic transitions 5.5 Conclusions Acknowledgements 6. Hydrological Responses to Land use/cover Changes in the Tana and Beles Watersheds, the Upper Blue Nile, Ethiopia Abstract 6.1 Introduction 6.2 Method 6.2.1 Hydrological modeling 6.2.2 Partial least squares regression 6.3 Results and Discussion 6.3.1 Calibration and validation of SWAT 6.3.2 Impacts of LULC changes on hydrology at the basin scale 6.3.3 Contribution of changes in individual LULCs to hydrological components 6.4 Conclusions Acknowledgements 7. Combined Impact of Climate and Land Use Changes on Hydrology in the Tana and Beles Sub-Basins, Upper Blue Nile, Ethiopia Abstract 7.1 Introduction 7.2 Methodology 7.2.1 Simulation 7.2.2 Climate change scenarios 7.2.3 LULC change scenarios 7.3 Results and Discussion 7.3.1 Future versus current LULC impact on the basin hydrology 7.3.2 Future versus baseline climate 7.3.3 Impact of combined future climate and LULC changes on hydrology 7.4 Uncertainties and Limitations 7.5 Conclusions Acknowledgements 8. Overall Conclusions, Recommendations and Future Research Directions 8.1. Overall Conclusions 8.2 Recommendations and Directions for further research References

This thesis aims at Multi-Objective Optimization under Uncertainty in structural design. We investigate Polynomial Chaos Expansion (PCE) surrogates which require extensive training sets. We then face two issues: high computational costs of an individual Finite Element simulation and its limited precision. From numerical point of view and in order to limit the computational expense of the PCE construction we particularly focus on sparse PCE schemes. We also develop a custom Latin Hypercube Sampling scheme taking into account the finite precision of the simulation. From the modeling point of view, we propose a multifidelity approach involving a hierarchy of models ranging from full scale simulations through reduced order physics up to response surfaces. Finally, we investigate multiobjective optimization of structures under uncertainty. We extend the PCE model of design objectives by taking into account the design variables. We illustrate our work with examples in sheet metal forming and optimal design of truss structures. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

The Cal Poly Spacecraft Simulator is currently being developed for future testing and verifying theoretical control applications. This paper details the effort to balance the platform and remove undesired external torque from the system using System Identification technique developed by Patrick Healy. Since the relationship between the input and output of the system is linear, the least square method is proposed to identify the mass properties and location of center of mass of the system. The tests use four sine wave generators that are out of phase with different amplitudes as the inputs to excite various structural modes of the system. The outputs, angular rates of the platform, are measured by the newly implemented LN-200 Inertial Measurement Unit that helps reducing the measurement noise. Two test cases of 90o yaw rotations with the identified inertia were performed and validated against the computer simulation model; and the result shows that the test cases trajectories followed closely with the computer simulation model.

The evolution of third-party logistics has sparked much academic interest over the years, with researchers looking at how the industry has grown and the factors that have contributed to it. The primary goal of this thesis is to examine the factors that have driven third-party logistics companies’ growth in Sweden for eighteen years (2002–2020). Growth in this thesis is considered as the growth of net sales. A total of 924 observations of ninety-five active third-party logistics companies operating in the Swedish market are analyzed in this thesis. An Ordinary Least Squares (OLS) linear regression analysis is carried out to examine the growth factors of third-party logistics companies in Sweden, taking into consideration the direct effect of the variables, number of employees, liabilities, operating profit, Earnings Before Interest and Taxes (EBIT), accessibility, technology, reverse logistics, service offer, customer relationship management (CRM), marketing, and distribution systems on the growth of net sales. Results from the OLS model shows that the size of the company, profitability, and the company's level of competence, has a significant positive influence on third-party logistics (3PL) company's growth.

Information seeking and information avoidance are the mechanisms humans natural used for coping with uncertainties and adapting to environmental stressors. Uncertainties are rooted in knowledge gaps. In social sciences, the relationship between knowledge gaps and perceived risk have received little attention. A review of the information science literature suggests that few studies have been devoted to the investigation of the role of this relationship in motivating information-seeking behavior. As an effort to address the lack of theory building in the field of information science, this study attempts to construct a model of information seeking under risk (MISR) by examining the relationships among perceived risk, knowledge gap, fear arousal, risk propensity, personal relevance, and deprivation and interest curiosity as antecedents to motivation to seek information. An experimental approach and a scenario-based survey method are employed to design the study. Partial least square structural equation modeling (PLS-SEM) analysis was conducted to test the relationships in the proposed model. Perceived risk was found to be a highly significant predictor of information seeking in moderately high-risk situations. Similarly, personal relevant has a significant negative effect on perceived risk and its interaction with knowledge gap motivates information seeking.

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<p>  </p> <p>Dicamba (3,6-dichloro-2-methoxybenzoic acid) and 2,4-D (2,4-dichlorophenoxyacetic acid) are two widely used herbicides for broadleaf weed control in soybeans. However, off-target application of dicamba and 2,4-D can cause severe damage to sensitive vegetation and crops. Early detection and assessment of off-target damage caused by these herbicides are necessary to help plant diagnostic labs and state regulatory agencies collect more information of the on-site conditions so to develop solutions to resolve the issue in the future. In 2021, the study was conducted to detect damage to soybean leaves caused by dicamba and 2,4-D by using LeafSpec, an accurate handheld hyperspectral leaf scanner. . High resolution single leaf hyperspectral images of 180 soybean plants in the greenhouse exposed to nine different herbicide treatments were taken 1, 7, 14, 21 and 28 days after herbicide spraying. Pairwise PLS-DA models based on spectral features were able to distinguish leaf damage caused by two different modes of action herbicides, specifically dicamba and 2,4-D, as early as 2 hours after herbicide spraying. In the spatial distribution analysis, texture and morphological features were selected for separating the dosages of herbicide treatments. Compared to the mean spectrum method, new models built upon the spectrum, texture, and morphological features, improved the overall accuracy to over 70% for all evaluation dates. The combined features are able to classify the correct dosage of the right herbicide as early as 7 days after herbicide sprays. Overall, this work has demonstrated the potential of using spectral and spatial features of LeafSpec hyperspectral images for early and accurate detection of dicamba and 2,4-D damage in soybean plants.</p> <p>   </p>

In this project, we are aiming to solve option pricing and hedging problems numerically via Backward Stochastic Differential Equations (BSDEs). We use Markovian BSDEs to formulate nonlinear pricing and hedging problems of both European and American option types. This method of formulation is crucial for pricing financial instruments since it enables consideration of market imperfections and computations in high dimensions. We conduct numerical experiments of the pricing and hedging problems, where there is a higher interest rate for borrowing than lending, using the least squares Monte Carlo and deep neural network methods. Moreover, based on the experiment results, we point out which method to chooseover the other depending on the the problem at hand.