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.

Hydraulics has always been the first choice of actuation in off-road, construction and mining vehicles due to its power density, low cost, built in cooling and lubrication. However, the current state of our environment along with stricter regulations has brought light to newer technologies within hydraulics to improve the existing system. This urge to enhance efficiency and reduce energy consumption has led to a point where new technologies must be evaluated. One such technology is the programmable hydraulic pump called the digital displacement pump (DDP). This new pump may have the potential to revolutionize mobile hydraulics as it can be used to improve part load efficiencies, response and make it easier to control from a system perspective. The DDP is a radial piston pump that has been fit with solenoid on/off valves at the inlet of each cylinder to control the flow of the working fluid. The displacement setting of the pump depends on the displacement of each cylinder controlled digitally by the 'active' inlet valve. The pump can act as a single unit to supply one circuit or it can dedicate pistons for supplying several circuits in parallel using different pump outlet configurations. They can be setup to run in pressure controlled or flow controlled systems to achieve the above mentioned flow sharing capability. An energy study based on two fixed drive cycles (short and intermediate) are conducted on the existing system of a loader used for mining called the ST14 Battery. A breakdown of the energy consumption in the machine is created to look at the impact of the three main actuators (boom, bucket and steering), pump losses and throttling losses have. The losses due to simultaneous load handling and the energy that can be saved by swapping the pumps with a digital displacement pump are also found out and analysed. A model of the existing hydraulic system is made using Simulink and Hopsan using the data and results from the energy study. It will be used to simulate and evaluate future system architectures. This model is then used to simulate a system architecture where the existing pumps are swapped with digital displacement pumps. This architecture is more energy efficient due to the higher energy efficiency of the pump. The findings from the energy study and simulations are compared and results are obtained regarding power losses, energy consumption and overall usability of the models. The addition of the two DDP’s instead of the existing inline pumps has resulted in energy savings resulting in 4% more running time in the intermediate cycle and 5.6% in the short cycle while keeping the functionality of the machine.

No description available.

We address the problem of all-pairs shortest time communication of messages in futuregeneration 6G networks by modeling the highly dynamic characteristics of the network using a temporal graph. Based on this model, an elegant technique is proposed to devise an algorithm for finding the all-pairs shortest time paths in the temporal graph that can be used for all-pairs internodes communication of messages in the network. The proposed algorithm basically involves computations similar to only two matrix multiplication steps, once in the forward direction and then in the backward direction.

No description available.

This thesis project for a Master of Arts in Spanish Pedagogy consists of a four-week, ten-lesson unit on culture in the family. This unit is designed for a middle school Spanish I class and is intended to supplement Chapter 5 in the Realidades textbook in the cultural aspect of learning a foreign language. The intention is to engage students to consider cultural perspectives, or the “why” cultures do what they do. The lesson plans from the unit are based on backward design and are structured around essential questions including, “What constitutes an ideal family?” An emphasis is placed on cultural perspectives of individual families while incorporating the five C's of the World-Readiness Standards for Learning Languages. An analysis of student learning and outcomes are provided in the final chapter. Supplementary lesson plans and evidentiary student work, photos and videos are included as appendices.

No description available.

No description available.

No description available.

The goal of the thesis is to accurately predict future values of a company’s website visits and to estimate the uncertainty of those predictions. To achieve this, a dynamic regression model with an ARIMA error term is considered, using advertisement spending with lags and dummy variables for Black Friday and weekdays as predictors. After dividing the data into a training set and a test set, the order of the ARIMA error term is specified using the Box-Jenkins methodology. The initial model is then run through a backward elimination algorithm, which selects two models based on the Akaike Information Criterion and Bayes Information Criterion. As expected, the model selected using Bayes Information Criterion is more conservative in its choice of variables than the model specified using the Akaike Information Criterion. The forecasts made on the test set are complemented with normal and bootstrap-based prediction intervals in order to estimate the uncertainty of the predictions. These are then compared to the forecasts made using a simpler model, consisting of only the ARIMA error term. The thesis concludes that the dynamic regression models are twice as accurate as the simpler model and that they were on average off by 14% from the actual values. The prediction intervals for the dynamic regression models are slightly too pessimistic as they overstate the uncertainty of the model by about 10 percentage points in the 80% prediction interval and by 5 percentage points in the 95% prediction interval. There is no practical discrepancy in prediction power between the model selected using the Akaike Information Criterion and the one using Bayes Information Criterion. The accuracy of the prediction intervals is higher than in the simpler model even though both dynamic regression models have more residual autocorrelation.