Sökning: "datavetenskap umu"
Visar resultat 11 - 15 av 547 uppsatser innehållade orden datavetenskap umu.
11. Evaluating Performance of Pattern Searching Algorithms on Wildcard Patterns
Kandidat-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : The pattern matching problem is the problem of finding a set of sequential characters in a text of equal amount of characters or more. There are many applications for pattern matching algorithms e.g. search engines and databases. LÄS MER
12. Cognitive Overload in Mixed-Reality Interactions: A Qualitative Analysis
Magister-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : Mixed reality (MR) technology is trending in various sectors at the present time. In MR applications, due to the interactions between two realities, the potential of experiencing Cognitive Overload is high. Hence, the present qualitative study has been conducted to broaden the understanding of Cognitive Load in MR interventions. LÄS MER
13. Energy efficiency in modern programming languages.
Kandidat-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : Energy efficiency is a matter of importance that gets more apparent with every passing day. As we move towards more refined and advanced programming languages and structures where we premiere increases in productivity and ease of use, we rarely consider the implication this has on energy consumption. LÄS MER
14. Evaluation of Application and Platform ContinuousDeployment Strategies and Tools over Edge Clusters
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : The purpose of this thesis was the investigation of using Cloud Native tools in an On-prem Edge Deployment. Edge Computing allows software with explicit demands on latency, data management and reliability to utilize Cloud Computing by moving the compute power to the location of need while leaving the management in the Cloud. LÄS MER
15. A dynamic approach to sorting with respect to big data
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : This study introduces a dynamic approach to sorting, making use of predictions and data gathered during run-time to optimize the sorting of the current data set. This approach is used to develop a sorting algorithm called DynamicSort which partitions data and calculates a partial standard deviation for each partition to determine which of two sorting algorithms should be used to sort the partition. LÄS MER