Sökning: "process control optimizing"
Visar resultat 16 - 20 av 44 avhandlingar innehållade orden process control optimizing.
16. How can data science contribute to a greener world? : an exploration featuring machine learning and data mining for environmental facilities and energy end users
Sammanfattning : Human society has taken many measures to address environmental issues. For example, deploying wastewater treatment plants (WWTPs) to alleviate water pollution and the shortage of usable water; using waste-to-energy (WtE) plants to recover energy from the waste and reduce its environmental impact. LÄS MER
17. Innovative Bioreactors for the Degradation of Polycyclic Aromatic Hydrocarbons
Sammanfattning : The development of biological reactors for the treatment of toxic and recalcitrant organic pollutants is a complex task. Firstly, microbial inoculation, acclimation and selection must be optimized to provide the best microflora possible. LÄS MER
18. Optimizing computed tomography : quality assurance, radiation dose and contrast media
Sammanfattning : Computed tomography (CT) is an important modality in radiology; it enables imaging of the inside of patients without superimposed anatomy. The radiation dose and quality of a CT image are highly dependent on the CT scanner, the scan settings and, if applicable, the timing and dosage of the intravenous contrast media (CM). LÄS MER
19. Some Aspects of Improving Initial Filling Conditions and Steel Cleanliness by Flow Pattern Control Using a Swirling Flow in the Uphill Teeming Process
Sammanfattning : The flow pattern has widely been recognized to have an impact on the exogenous non-metallic inclusion generation in the gating system and mold flux entrapment in the uphill teeming process. Thus, a well-controlled flow pattern during the teeming process can improve the quality of ingots and further increase the yield during steel production. LÄS MER
20. Machine learning for quantum information and computing
Sammanfattning : This compilation thesis explores the merger of machine learning, quantum information, and computing. Inspired by the successes of neural networks and gradient-based learning, the thesis explores how such ideas can be adapted to tackle complex problems that arise during the modeling and control of quantum systems, such as quantum tomography with noisy data or optimizing quantum operations, by incorporating physics-based constraints. LÄS MER