Sökning: "Performance Analytics"
Visar resultat 11 - 15 av 47 avhandlingar innehållade orden Performance Analytics.
11. Miniaturized fluid system for high-pressure analytics
Sammanfattning : High-pressure chemistry can be used to determine the contents of blood or water samples and to discover new chemistries. However, working with chemistry at pressures of many tens, or even hundreds, of bars often requires expensive and stationary equipment, such as autoclaves or chromatographic systems like high-performance liquid chromatography (HPLC). LÄS MER
12. Quality-Impact Assessment of Software Products and Services in a Future Internet Platform
Sammanfattning : The idea of a Future Internet platform is to deliver reusable and common functionalities to facilitate making wide ranges of software products and services. The Future Internet platform, introduced by the Future Internet Public Private Partnership (FI-PPP) project, makes the common functionalities available through so-called Enablers to be instantly integrated into software products and services with less cost and complexity rather than a development from scratch. LÄS MER
13. From Condition Monitoring to Maintenance Management in Electric Power System Generation with focus on Wind Turbines
Sammanfattning : With increase in the number of sensors installed on sub-assemblies of industrial components, the amount of data collected is rapidly increasing. These data hold information in the areas of operation of the system and evolution of health condition of the components. LÄS MER
14. Data-driven Ship Performance Models - - Emphasis on Energy Efficiency and Fatigue Safety
Sammanfattning : Due to digitalization in the maritime industry, a huge amount of ship operation-related data has been collected. The main objective of this thesis is to exploit machine learning/big data analytics to build data-driven ship performance models, focusing on speed-power relationship modeling, and fatigue accumulation assessment during a ship’s operation at sea. LÄS MER
15. Performance Characterization of In-Memory Data Analytics on a Scale-up Server
Sammanfattning : The sheer increase in volume of data over the last decade has triggered research in cluster computing frameworks that enable web enterprises to extract big insights from big data. While Apache Spark defines the state of the art in big data analytics platforms for (i) exploiting data-flow and in-memory computing and (ii) for exhibiting superior scale-out performance on the commodity machines, little effort has been devoted at understanding the performance of in-memory data analytics with Spark on modern scale-up servers. LÄS MER