This thesis deals with the possibilities of electronic stock trading of currency pairs. It analyzes the basic conditions and criteria which trader needs to meet to be able to participate on this market. This master’s thesis describes the use of technical indicators and fundamental messages through electronic trading platforms. Further thesis graphically compares the types of trading according to the time horizonts and then concludes suggestions and recommendations.

The diploma thesis deals with control of rotary inverted pendulum - Furuta pendulum. Solution for power electronics, sensors and coupling with PC is described, identification of parameters and nonlinear simulation model in Matlab/Simulink and SimMechanics toolbox is presented. Second type Lagrange equation is used for determination of equations of motion. Controll system based on state-space model of mechanism and LQR algorithm for design of state-space controller is used and switching between swing-up cotroller a stabilizing state-space control is achieved according to actual angular position of pendulum's angle. Input integrator eliminating steady state error was used with success.

The main purpose of this diploma thesis is to design a swing axle of a truck for 4x4 chassis without wheel reduction gears. The study consist of two parts. The first part contains designs of main parts of the axle, mechanism of suspension and steering. The second part contains the gears housing stress analysis using the finite element method. The housing of gears is the arm of the swing axle, which is the main part of the chassis.

The thesis deals with the technologies upgrading the biogas to the quality of the natural gas for the following use in the gas distribution system. The main concern of the thesis is the pressure swing adsorption (PSA), which is nowadays one of the most exploited technologies. For a certain flow and composition of the biogas, completely new PSA technology was designed. Technological schema was created and the main technological devices (adsorbers) were drawn up together with the design documentation for this new technology. The important part of the thesis is also the model of the whole PSA technology in the ChemCAD programme and the evaluation of the operating and investment costs.

This thesis compares forward neural networks with algorithms using game theory on basis of board game Blokus. The theoretical introduction part describes the characteristics of neural networks and work with them. There is also outlined algorithm of game theory. The second part deals about the implementation of players based on the outlined principles  and shortly descriptions GUI of application. In conclusion, the differences between the players  are evaluated on the charts created on the performed tests.

Title: Influence of gait in high heels on posture, and division of pressure on the contact area level of the feet and the floor Objective: The aim of the dissertation was to verify how walking in high-heeled shoes influences the time and pressure parameters of the step cycle and posture during slow and very slow walking in low experienced wearers. Methods: The research study was an empirical, comparative intra-individual study. Pedar-X® measuring inserts (Novel, Munich, Germany) were used to measure the distribution of plantar pressures and to evaluate time parameters while walking on a conveyor belt at v1 = 0.97 ms-1 and v2 = 0.56 ms-1 in straight shoes and high-heeled shoes. SonoSens Monitor Analyzer® (Gefremed, Chemnitz, Germany) was used to assess posture. The research group consisted of thirty healthy women wearing high-heeled shoes occasionally (age: 21.8 ± 2.09 years, weight: 55.7 ± 4.05 kg, height: 1.66 ± 0.03 m). Anova test and paired t-test were used for statistical analysis, and the Cohen coefficient d was used to calculate material significance. Results: Significant differences in time and plantar pressure variables were found when walking in high-heeled shoes compared to straight footwear. For both types of footwear, walking speed only affected time variables, but not dynamic...

Title: Intraindividual stability of performance and kinestetic abilities level in wedge play performed on golf players with different performance level Goal: Goal of this thesis is detect an intraindividual stability of full swing performance in wedge play and find out kinestetic abilities level of golf players with different performance level when they control distance of ball flight, club head speed and ball speed. Methods: There were 15 golfers participating in this study (n = 15). Tested subjects are characteristic by these values: age 18,36 ± 2,61, body height 180,86 ± 7,38, body weight 73,21 ± 10,25, HCP HCP -0,47 ± 1,53. Intraindividual stability of performance and kinestetic abilities level was tested by instrument TrackMan. Gained values were processed by statistical methods in Excel. Pearson coeficient was used to find out the dependence between data. Results: We found high level of intraindividual stability from test results. Significant difference was found between in distance, club head speed and ball speed parameters with and without feedback. Significant connetion between intaindividual stability and performance parameters was found only in 1/3 of cases, same as connection between kinethetic ability and performance parameters. Key words: Short game, golf swing, approach shots, abilities

Title: Influence of gait in high heels on posture, and division of pressure on the contact area level of the feet and the floor. Objective: The aim of the dissertation was to confirm how walking in high-heeled shoes influences the time and pressure parameters of the step cycle and posture during slow and very slow walking in low experienced wearers. Methods: The research study was an empirical, comparative intra-individual study. Pedar-X® measuring inserts (Novel, Munich, Germany) were used to measure the distribution of plantar pressures and to evaluate time parameters while walking on a conveyor belt at v1 = 0.97 ms-1 and v2 = 0.56 ms-1 in straight shoes and high-heeled shoes. SonoSens Monitor Analyzer® (Gefremed, Chemnitz, Germany) was used to assess posture. The research group consisted of thirty healthy women wearing high-heeled shoes occasionally (age: 21.8 ± 2.09 years, weight: 55.7 ± 4.05 kg, height: 1.66 ± 0.03 m). Anova test and paired t-test were used for statistical analysis, and the Cohen coefficient d was used to calculate material significance. Results: Significant differences in time and plantar pressure variables were found when walking in high-heeled shoes compared to straight footwear. For both types of footwear, walking speed only affected time variables, but not dynamic...

This thesis explores the use of computational chemistry and machine learning techniques to aid in the design of Metal-Organic Frameworks (MOFs) for use in postcombustion carbon capture and storage (PoC-CCS). PoC-CCS is an ongoing field of research which aims to selectively remove carbon dioxide, an important greenhouse gas, from the exhaust of fossil-fuel burning powerplants. By using a suite of advanced simulation techniques, high-throughput screenings were performed on thousands of MOFs to study their behaviour in a pressure swing adsorption (PSA) system. To develop a comprehensive picture of a material’s performance, the behaviour of individual gas molecules within the pores of the crystal structures to the material’s performance in industrial scale PSA columns was evaluated. To study the behaviour of individual gas molecules within the pores of a MOF, a new algorithm which can accurately determine the locations of gas binding sites was developed. This algorithm, which relies on probability distributions generated through grand canonical Monte Carlo simulations (GCMC), was optimized for CO2 with the goal of use in high-throughput screening. By tuning the user-controlled parameters for a desired gas, this algorithm, which was named the Guest Atom Localization Algorithm (GALA), was shown to accurately reproduce experimentally determined binding sites while being run in a high-throughput manner with no user intervention. Studying MOFs at the pore or crystal scale in this manner provides valuable insights into the behaviour of gases within the materials. A major shortcoming, however, is the lack of direct insight into the material’s behaviour in industrial systems. Materials scientists and MOF chemists have historically focused on a set of performance metrics measured at this scale; however, no clear connection can be made between such metrics and the performance of that sorbent material in a PSA column. To bridge this gap between MOF chemists and the process engineers studying the PSA systems, a large-scale screening of MOFs was performed using a sophisticated PSA simulator designed to reproduce the performance of an 80 kg PSA column. By supplying isotherms obtained using GCMC simulations to be used as inputs into the PSA simulator, a multi-scale high-throughput screening of MOFs for PoC-CCS was performed for the first time under coal-fired powerplant conditions. This multi-scale screening provided the ideal conditions to study the materials science performance metrics and their relationships to industrial PSA performance. To study this relationship, a series of machine learning and artificial intelligence techniques were employed. The primary goal was to extract important relationships between the materials science and industrial PSA performance metrics, with a secondary goal of developing a predictive model which could be used to accelerate the pace of materials discovery. Through the use of machine learning, several metrics were identified which could be used to predict whether a material could meet the minimum target of 95 % purity of captured CO2, and 90 % removal (or recovery) of CO2 from the flue gas stream. Among them was the isotherm parameters for N2, the most abundant species in the flue gas. This finding was significant as to date the focus among MOF chemists studying the PoC-CCS system was placed primarily on the CO2 metrics, with N2 only implicitly considered when calculating the CO2/N2 selectivity. Although several metrics were identified which could predict the purity and recovery targets, none of the conventional metrics tested could be used to estimate the energetic cost of capture or the size of the capture plant, both important considerations in evaluating the cost of capture. The relationship between N2 binding within the pores of the MOF and its ability to meet the purity-recovery targets was explored using GALA. Using a Tanimoto similarity metric and the ratio of single component and competitive loadings, the CO2 and N2 binding environments were studied. It was determined that when the N2 binding environment was significantly altered by the presence of CO2, the material was more likely to meet the purity-recovery targets. Further analysis found that this change in binding environments was correlated to a reduced N2 uptake in the presence of CO2, implying that the competition for binding sites within the pores of the MOF is an important indicator for the material’s ability to meet the purity-recovery target. For the first time, a direct relationship between the behaviour of individual gas molecules to industrial PSA performance can be reported. Although the PSA simulator used throughout this work has proven to be a powerful tool for materials discovery, several shortcomings still exist. The first is the method used by the simulator to predict the loadings at various points within the column. This method relies on single component isotherm data despite the ability of GCMC to simulate multi-component isotherms. An alternative method to using single component isotherms was proposed which relies on multi-component isotherm data and a linear interpolation model. The existing method was compared to the new proposed interpolation method, and it was found that the loadings predicted using the interpolation method were more accurate. The second shortcoming of the PSA simulator is the computational expense associated with the optimizations. Using the PSA simulator, a single material may take up to a week to be fully optimized on a high-performance computing cluster. To increase the pace of materials discovery, a surrogate model was developed using the data accumulated over the course of the work presented in this thesis. Using artificial neural networks, a suite of models was developed which reproduces the outputs of the PSA simulator and is able to optimize a single MOF in a matter of minutes. This suite of models, known as the Fossil Fuel Combustion for Carbon Capture and Storage (FoCAS) was used to perform a screening of over 4,000 materials.

This thesis investigates the potential of biomethane production in India, the impact of its integration into the energy mix, and the corresponding Greenhouse Gases (GHG) emission and potential reduction. India, with its huge population and being an agriculturally rich country, produces gigantic amounts of biodegradable waste from various sources such as Municipal Solid Waste (MSW),agricultural waste, animal husbandry, sugar industry, etc. Three different end-use scenarios: electricity generation, cooking fuel, and transportation fuel—are assessed in order to determine the decree to which current fossil fuels may be replaced and the net amount of greenhouse gas emissions that are saved by using this biomethane. The total biomethane generation potential according to the study conducted by the Ministry of New and Renewable Energy (MNRE) is 25.6 Billion Metric Standard Cubic Meters (BMSCM) and with the most efficient upgrading technology available (3-stage membrane filtration) the useful potential is 25.4 BMSCM. The electricity that can be produced from the biomethane potential available is 159.1 TWh, which corresponds to the optimistic value of GHG emission reduction of 89million tons. When used as a cooking fuel, biomethane can contribute immensely to satisfying the final thermal needs of India. It can satisfy more than half the combined total thermal energy from Compressed Natural Gas (CNG) and Liquefied Petroleum Gas (LPG) consumed in India and, at the same time, reduce 46.2 million tons of GHG emissions caused by it. The transportation sectoris the most suited and easy to adapt as an end-use application for biomethane. It was observed that biomethane as a replacement for Petrol for road transportation fuel presents the best scenario, since biomethane can reduce more than 71% of its consumption and respectively reduce more than 57 million tons of GHG emission, which is the second highest after electricity production. This thesis puts up a strong case to look at biomethane as a very important fuel towards India’starget to be net zero by 2070 and its plans to be self-reliant. Moreover, biomethane production usingthe path of anaerobic digestion provides not only a renewable source of energy but also food security with digestate being used as fertilizer and an opportunity to address the impact of climate change by preventing the emission of methane in the atmosphere which has a global warming potential of28 and burning of agricultural waste in the open field. Eventually, the production of biomethane prevents soil, air and water pollution. / Denna avhandling undersöker potentialen för biometanproduktion i Indien, effekterna av dess integration i energimixen och motsvarande utsläpp och potential för växthusgaser (GHG). minskning. Indien, med sin enorma befolkning och är ett jordbruksrikt land, producerar gigantiska mängder biologiskt nedbrytbart avfall från olika källor som kommunalt fast avfall (MSW), jordbruksavfall, djurhållning, sockerindustri, etc. Tre olika slutanvändningsscenarier: el produktion,matlagningsbränsle och transportbränsle – utvärderas för att fastställa till vilket dekret nuvarande fossila bränslen får ersättas och nettomängden växthusgasutsläpp som sparas genom att använda denna biometan. Den totala biometangenereringspotentialen enligt studien utförd av ministeriet för ny och förnybarenergi (MNRE) är 25,6 miljarder metriska standardkubikmeter (BMSCM) och med den mest effektiva uppgraderingstekniken som finns tillgänglig (3-stegs membranfiltrering) är den användbara potentialen 25,4 BMSCM. Den el som kan produceras från den tillgängliga biometanpotentialen är 159,1 TWh medan det optimistiska värdet av växthusgasutsläpp som är möjligt med användning av biometan för elproduktion är 89 miljoner ton. När biometan används som matlagningsbränsle kan det bidra oerhört mycket för att tillfredsställa Indiens slutliga termiska behov. Det kan tillfredsställa mer än halva finalen termisk energi som förbrukas i Indien och samtidigt samma miljon ton i utsläpp av växthusgaser som orsakas av den. Transportsektorn är den mest lämpade och lätta att anpassa som slutanvändningsprogram för biometan. Det observerades att biometan som ersättning för bensin som transportbränsle är det bästa scenariot eftersom biometan kan minskamer än 71 % av sin förbrukning och respektive minska mer än 57 miljoner ton växthusgasutsläpp, vilket är det näst högsta efter elproduktion. Den här avhandlingen ger ett starkt argument för att se biometan som ett mycket viktigt bränslemot Indiens mål att vara nettonoll år 2070 och dess planer på att vara självförsörjande. Dessutom ger biometanproduktion genom att använda vägen för anaerob rötning inte bara en förnybar energikälla utan också livsmedelssäkerhet med rötgas som används som gödningsmedel och en möjlighet att ta itu med effekterna av klimatförändringar genom att förhindra utsläpp av metan i atmosfären som har en global uppvärmningspotential på 28 och förbränning av jordbruksavfall på det öppna fältet. Så småningom förhindrar produktionen av biometan mark-, luft- och vattenföroreningar.