Search for dissertations about: "improving data quality"
Showing result 1 - 5 of 372 swedish dissertations containing the words improving data quality.
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1. Contributions to the Use of Statistical Methods for Improving Continuous Production
Abstract : Complexity of production processes, high computing capabilities, and massive datasets characterize today’s manufacturing environments, such as those of continuous andbatch production industries. Continuous production has spread gradually acrossdifferent industries, covering a significant part of today’s production. READ MORE
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2. Quantifying Process Quality : The Role of Effective Organizational Learning in Software Evolution
Abstract : Real-world software applications must constantly evolve to remain relevant. This evolution occurs when developing new applications or adapting existing ones to meet new requirements, make corrections, or incorporate future functionality. READ MORE
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3. How can data science contribute to a greener world? : an exploration featuring machine learning and data mining for environmental facilities and energy end users
Abstract : 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. READ MORE
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4. Traffic Management in Software-Defined Data Center Networks
Abstract : Traffic management in data centers is paramount to improving network and application performance, thereby improving the quality of service by reducing network congestion, packet loss, and latency. However, the deployment and configuration of traffic management techniques are challenging due to diverse data-center traffic characteristics, large data center topologies, and the interplay of different protocols at the routing, transport, and link layer. READ MORE
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5. Improving quality of summative eHealth evaluations
Abstract : Summative evaluation, which is conducted at the end of an eHealth trial or implementation, assesses outcomes, produces evidence, and advances knowledge of eHealth implementations in healthcare provisions. Therefore, its high quality is essential in order to reap the benefits of the results generated by evaluation studies. READ MORE