Background: Innovation’s role in economic growth is crucial. Countries have acknowledged that and introduced innovation policies to promote economic growth since the ‘80s. But governments must have the capacity and effectiveness to support organizations and institutions for innovation, so the uneven development among countries raises the question of whether it is affected by government effectiveness. Objectives: This work investigates the interlink between government effectiveness as measured by the World Bank, and innovation performance, as measured by the European Innovation Scoreboard (EIS). Its objective is to identify how government effectiveness affects innovation performance. Methodology: This work follows a quantitative research strategy since the study is based on a large dataset and uses statistics to analyze data. To explore the impact of the variables, this work follows a panel regression approach. The data are publicly available by EU and World Bank. The data set consists of the Summary Innovation Index (SII) -an overall score in the EIS-, and the Government Effectiveness(GE) index from the World Bank during 2014-2020. Results: According to the analysis, the Fixed Effects Least Square Dummy Variables (FE-LSDV)regression model is superior to the other models (pooled OLS and Random Effects). The FE-LSDVmodel can explain 68.88% of the data. The analysis also shows that GE negatively impacts SII by a factor of -0,3228078. However, the P value and t-tests reveal that the correlation is not statistically significant. Conclusions: Our results contradict the previous studies. This may be due to the weaknesses identified in the previous studies, the time lag effect between the change in the government effectiveness index when the change in the innovation performance is noticeable, and the inverted U-shape relationship between innovation performance and government quality. Recommendations for future research: As future work can be suggested, an analysis including data from the previous funding periods. Also, the elasticity of innovation performance regarding government effectiveness within a larger time period can be studied. Furthermore, researchers can broaden the time period to include data over a minimum of 14 years period to investigate the time-lag effect and the inverted U-shape relationship.

The nitrogen reduction goals for the Chesapeake Bay are proving particularly difficult achieve. One of the contributing sources of N loading to the Bay is legacy N from groundwater springs. Denitrifying spring bioreactors are a best management practice that offers an opportunity to abate N from groundwater springs. The objective of this research is to estimate the regional abatement costs to remove legacy N using bioreactors. We identified 196 candidate springs for bioreactor installation that had a median spring flow of greater or equal to 100 m3 d-1 and greater or equal to 3 mg L-1. Under assumptions that 25% of the spring flow can be diverted to the bioreactor and a bioreactor N removal efficiency of 20%, we estimate that it would cost $3,325,400 yr-1 to abate 106,911 kg N yr-1. The driving factor of driving the unit costs of N removal is the amount of spring flow treated by the bioreactor. Further research is needed to understand how to optimize bioreactor performance and the benefits of increasing the percentage of spring flow treated given the impact these two factors on the cost-effectiveness of spring bioreactors in removing N. / Master of Science / There is a Chesapeake Bay Watershed total maximum daily load (TMDL) to reduce pollutants from going into the Bay. The reduction measures to achieve the TMDL goals must be in place by 2025. The nitrogen reduction goal for the Bay is proving particularly difficult to achieve. One of the contributing sources of N loading to the Bay is legacy N from groundwater springs. Denitrifying spring bioreactors are a best management practice that offers an opportunity to abate N from groundwater springs. One form of a denitrifying bioreactor is a hole in the ground filled with carbon substrate (i.e. woodchips) that is used to treat N rich water. Due to the conditions created in the spring bioreactor, the process of denitrification occurs, and N is removed from the water treated. The objective of this research is to estimate the regional abatement costs to remove legacy N using bioreactors. We identified 196 candidate springs for bioreactor installation that had a median spring flow of greater or equal to 100 m3 d-1 and greater or equal to 3 mg L-1. Under assumptions that 25% of the spring flow can be diverted to the bioreactor and a bioreactor N removal efficiency of 20%, we estimate that it would cost $3,325,400 yr-1 to abate 106,911 kg N yr-1. The driving factor of driving the unit costs of N removal is the amount of spring flow treated by the bioreactor. Further research is needed to understand how to optimize bioreactor performance and the benefits of increasing the percentage of spring flow treated given the impact these two factors on the cost-effectiveness of spring bioreactors in removing N.

A new domain of commercial applications demands the development of inexpensive parallel computing platforms to lower the cost of operations and increase the business profit. The calculation of returns on an IT investment is now important to justify the decision of upgrading or replacing parallel systems. This thesis presents a framework of the performance and economic factors that are considered when evaluating a parallel system. We introduce a metric called the cost/profit effective metric, which measures the effectiveness of a parallel system in terms of performance, cost and profit. This metric describes the profit obtained from the performance of three different domains for scaling: speed-up, throughput and/or scale-up. Cost is measured by the actual costs of a parallel system. We present two cases of study to demonstrate the application of this metric and analyze the results to support the evaluation of the parallel system on each case.

The primary purpose of this study was to determine if various types of distance education formats would be suitable for conducting a training course for a computer application. The study sought to determine if a face-toace format, interactive video format, minimally interactive online format or highly interactive and multimedia rich online format produced similar results in student performance in a training course for a computer application. The secondary purpose of this study was to determine if the increased cost of development of a highly interactive and multimedia rich online format was justified based on observed differences in student achievement in an online environment. This study consisted of 97 employees of the Mississippi State University Extension Service enrolled in the Introduction to Microsoft Excel 2007 course offered by the Computer Application Services Department of the Mississippi State University Extension Service. The result of an analysis of variance utilizing the method of instruction as the independent variable and the calculated change in score when subtracting the pretest score from the posttest score as the dependent variable resulted in a statistically significant difference in change scores based on treatment at the .05 level. The study also found that face-toace instruction had the lowest mean cost per unit gained for all methods of instruction studied and the highest mean achievement gained overall.

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