Topics thesis focuses on the feed mixing wagons, specifically on the impact of individual components of mixed feed rations with feed mixer wagons without pickup cutters accuracy loads. The result of this work is your own assessment of the qualitative characteristics of individual components of mixed feed rations, but their influence on the possible inaccuracy of the weighing equipment of these vehicles and thus on the actual composition of the diet and the resulting measures to prevent the occurrence of these inaccuracies when preparing feed.

Aim of this work is to study the impact of inaccuracy in execution of required task (inaccuracy in subject’s behavioral response to experimental stimulation) by person who undergoes fMRI examination. The work is solved in several stages. First, theoretical analysis of inaccuracy in fMRI experiment was performed, and simulations with synthetic data were created. Several variables in general linear model and t-statistics were followed. We found that estimated effect size depends linearly on covariance between the corresponding columns of X and D matrices or their linear combination. The component of residual variance caused by inaccuracy is negligible at real-life noise levels. In such case, moreover, the dependence of t-statistics on inaccuracy becomes linear. Next, our theoretical results (dependencies/characteristics of variables) were verified using real data. All results were confirmed. Last, I focused on possible practical use of the uncovered characteristics and dependencies. Optimization of experimental design with respect to inaccuracy, correction of inaccurate results and reliability of inaccurate results are introduced and discussed. Especially, the calculation of maps of maximal tolerable inaccuracy can be useful to find robust or weak (tending to be not detected or to be significantly different from accurate value) activation in real fMRI experiments.

This doctoral thesis widely analyses the process of investment decision-making. In its individual parts, it researches models used for planning, analysing and evaluation of investments projects, but also models used for final decision about realization of the investment. Investing activity is present in world economic cycle in all it’s phases. Capital sources used for financing if the investment projects are scarce and must be handled with care. For this reason, there are many supportive methodologies and models employed in managing of the investments as well as instruments developed to miti-gate the potential project risks. However, even utilization of these instruments and models can’t guarantee the expected results. There are uncertainties, errors and in-accuracies in the process that can thwart investment decisions. The aim of the thesis is to analyse the investment decision-making process (from the initial idea to the realization of the investment project) and to identify the main un-certainties – factors influencing the success / error rate of models for investment project planning as well as the decision on their realization. The main outcome of the thesis is an overview of these factors and recommenda-tions on how to work with these factors and make the process as effective as possi-ble. Another output is an analysis and recommendations for the use of financing sources and mix of the instruments that should be used to mitigate the potential impact of risks that are connected to all investment projects.