Introduction. Particle Swarm Optimization (PSO) is a heavy-duty algorithm that is used to identify the optimum (maximum or minimum) solution of a formula with multiple unknown factors. PSO algorithms are used widely for various optimization problems, and all face the same challenge. Being iterative algorithms that in each iteration perform a mathematical formula, PSO algorithms demand a high capacity of physical resources and are often time consuming. This combination is even more challenging when executing a PSO algorithm on the cloud since expensive resources used over a long time come at a high cost and cheaper resources struggle to perform the task. To avoid high costs and achieve the best possible performance, one needs to choose the correct computational resources and configure them accordingly. Objectives. The goal of this study is to identify the optimum tools and configurations to execute a PSO algorithm on Microsoft’s cloud platform, Azure. To achieve that, we choose the Azure resources that are designed to perform deterministic tasks and to be distributed and scaled automatically by Azure. Those are Azure Functions and Azure Durable Functions. We experiment with various configurations, and we collect and compare the results to draw conclusions about which combination performs best. Methods. To identify which combination of Azure resources and configuration performs best in the cloud (Microsoft Azure), we perform experiments and collect metrics which we then aggregate and compare with each other, as well as with the metrics collected by executing the same combination on-premises. During those experiments, we execute the same PSO algorithm using the same variables, the values of which were calculated before performing the experiments. Results. Upon performing the experiments, we collected the results of each experiment, which consist of the time it took to execute, the number of zeros (beyond the decimal point) found in the result, as well as the Global Priority percentage which lead to that result. The results indicate differences both between the on-premises and on-cloud execution and between the various configurations and Azure resources. Conclusion. We succeeded in finding a combination using Azure Durable Functions with the appropriate configuration, which vastly outperforms all others. Concluding, the outcome of this study is that heavy-duty algorithms, such as PSO, can indeed be executed on Azure, with significantly improved performance, when using the right configuration and exploiting the resources to their whole extent. Additionally, we learned that an appropriately configured Azure resource can even outperform an identical execution on-premises (using equal resources).

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Website scaling has been an issue since the inception of the web. The demand for user generated content and personalized web pages requires the use of a database for a storage engine. Unfortunately, scaling the database to handle large amounts of traffic is still a problem many companies face. One such company is iFixit, a provider of free, publicly-editable, online repair manuals. Like many websites, iFixit uses Memcached to decrease database load and improve response time. However, the caching strategy used is a very ad hoc one and therefore can be greatly improved. Most research regarding web application caching focuses on cache invalidation, the process of keeping cached content consistent with the permanent data store. Generational caching is a technique that involves including the object’s last modified date in the cache key. This ensures that cache keys change when- ever the object is modified, which effectively invalidates all relevant cache entries. Fine-grained caching is now very simple because the developer doesn’t need to explicitly delete all possible cache keys that might need to be invalidated when an object is modified. This is particularly useful for caching arbitrary fragments of HTML without increasing the complexity of cache invalidation. In this work, we describe the process of implementing a caching strategy based on generational caching concepts in iFixit’s website. Our implementation yielded a 20% improvement in page response time by caching fragments of HTML and results of database queries.

DOGMA is a distributed computing architecture developed at Brigham Young University. It makes use of idle computers to provide additional computing resources to applications, similar to Seti@home. DOGMA's ability to scale to large numbers of computers is hindered by its strict client-server architecture. Recent research with DOGMA has shown that introducing localized peer-to-peer downloading abilities enhances DOGMA's performance while reducing the amount of network and server usage. This thesis proposes to further extend the peer-to-peer abilities of DOGMA to include peering client server communication by creating dynamic clusters of clients. The client clusters aggregate their communication with only one client communicating with the server directly. This further reduces the network traffic and server usage allowing more clients to connect to a single server and increasing the overall scalability of DOGMA systems.

This dissertation is a collection of papers on anomalous phenomena in physics, biology, and sociology. These phenomena are primarily analyzed in terms of their temporal and spatiotemporal statistical properties. The analysis is based on both numerical simulations and, in some cases, real-world physiological and sociological data. The primary methods of analysis are diffusion entropy analysis, power spectral analysis, multifractal analysis, and survival (or waiting-time) analysis.

Hybrid rocket propulsion technology shows promise for the next generation of sounding rockets and small launch vehicles. This paper seeks to provide details on the process of developing hybrid propulsion systems to the academic and amateur rocket communities to assist in future research and development. Scaling hybrid rocket motors for use in sounding rockets has been a challenge due to the inadequacies in traditional boundary layer analysis. Similarity scaling is an amendment to traditional boundary layer analysis which is helpful in removing some of the past scaling challenges. Maintaining geometric similarity, oxidizer and fuel similarity and mass flow rate to port diameter similarity are the most important scaling parameters. Advances in composite technologies have also increased the performance through weight reduction of sounding rockets through and launch vehicles. Technologies such as Composite Overwrapped Pressure Vessels (COPV) for use as fuel and oxidizer tanks on rockets promise great advantages in flight performance and manufacturing cost. A small scale COPV, carbon fiber ablative nozzle and a N class hybrid rocket motor were developed, manufactured and tested to support the use of these techniques in future sounding rocket development. The COPV exhibited failure within 5% of the predicted pressure and the scale motor testing was useful in identifying a number of improvements needed for future scaling work. The author learned that small scale testing is an essential step in the process of developing hybrid propulsion systems and that ablative nozzle manufacturing techniques are difficult to develop. This project has primarily provided a framework for others to build upon in the quest for a method to easily develop hybrid propulsion systems sounding rockets and launch vehicles.

This study investigates the performance of concrete sidewalks placed using hot and cold weather concreting practices. The effect that curing methods, types of deicers, and supplementary cementitious material content have on the scaling resistance of concrete is examined in the laboratory and the field. After one winter, petrographic analysis was conducted on the cores from the sidewalk panels. The results from field evaluation indicate that the concrete sidewalks placed using hot weather concreting showed better resistance against scaling than those placed using cold weather concreting. The results also suggest that the effect of curing method depends on the concreting procedure type. The results confirm the maximum limits recommended by ACI 201.2R Guide for Durable Concrete, the mix proportions with fly ash less than 25% and slag less than 50% have shown better scaling resistance. Based on the petrographic analysis, a correlation between the properties of concrete determined through petrography and scaling on a sidewalk could not be determined.

Microalgae are one of the oldest types of lifeforms on this planet and dead algae are one source for the oil that we extract from the ground. This oil has a major part in the technology advances of humanity, to levels unimaginable not long ago. Unfortunately, this oil is one of the major reasons for the global warming and other environmental issues caused by humans. Therefore, much effort is made on new technologies to decrease the use of fossil oil and other fossil material in favor for so called renewable sources. In this work focus is on production of biomass that can be used for processing to other bulk materials, mainly chemicals. This is also a highly potential market, the amount of materials derived from fossil sources are at least 422 million metric tons per year. The issue though is that the production costs for algae are still fairly high and can’t compete with the market price of fossil raw materials. Two algae species, Scenedesmus obliquus and Coelastrella sp., were cultivated in 6 pilot size ponds (500 L) and the results were compared to a lab experiment (0.5 L). The lab experiment was earlier performed by the author’s supervisors with the same species. The algae in the ponds were cultivated outdoor with flue gas in semi-closed ponds and the resulting biomass was allowed to sediment spontaneously. Scenedesmus obliquus was successfully cultivated in the pilot, but the system was not suitable for cultivation of Coelastrella sp. The main aim of this work was to evaluate if it is possible to predict the amount of biomass produced in the pilot cultivation based on the results from the previously performed lab cultivation. The conclusion based on the results in this work is that it not possible to predict the biomass production in the pilot based on lab experiments. The properties and behavior of different algae species can be very different in different systems, and the setups in this study differed too much. However, the results indicate that the pilot system has a high efficiency and can maintain a monoculture outdoors for at least 18 days as well as that the supply of flue gas highly affects the growth of the algae Scenedesmus obliquus.

With scant research to draw upon with respect to the maintenance of vertical scales over time, decisions around the creation and performance of vertical scales over time necessarily suffers due to the lack of information. Undetected item parameter drift (IPD) presents one of the greatest threats to scale maintenance within an item response theory (IRT) framework. There is also still an outstanding question as to the utility of the Rasch model as an underlying viable framework for establishing and maintaining vertical scales. Even so, this model is currently used for scaling many state assessment systems. Most criticisms of the Rasch model in this context have not involved simulation. And most have not acknowledged conditions in which the model may function sufficiently to justify its use in vertical scaling. To address these questions, vertical scales were created from real data using the Rasch and 3PL models. Ability estimates were then generated to simulate a second (Time 2) administration. These simulated data were placed onto the base vertical scales using a horizontal vertical scaling approach and a mean-mean transformation. To examine the effects of IPD on vertical scale maintenance, several conditions of IPD were simulated to occur within each set of linking items. In order to evaluate the viability of using the Rasch model within a vertical scaling context, data were generated and calibrated at Time 2 within each model (Rasch and 3PL) as well as across each model (Rasch data generataion/3PL calibration, and vice versa). Results pertaining the first question of the effect IPD has on vertical scale maintenance demonstrate that IPD has an effect directly related to percentage of drifting linking items, the magnitude of IPD exhibited, and the direction. With respect to the viability of using the Rasch model within a vertical scaling context, results suggest that the Rasch model is perfectly viable within a vertical scaling context in which the model is appropriate for the data. It is also clearly evident that where data involve varying discrimination and guessing, use of the Rasch model is inappropriate.