Advanced search
Showing result 1 - 5 of 218 essays matching the above criteria.
-
1. Shifting focus from yields to food supply : an evaluation of the ‘number of people fed per hectare’ indicator at farm and national level
University essay from SLU/Department of Molecular SciencesAbstract : The challenge of feeding a growing global population while reducing the pressure on climate and ecosystems has gained much attention in research over the last decades. A crucial yet often overlooked aspect in research addressing this complex challenge is the efficiency of food production in meeting nutritional needs within the constraints of global cropland resources. READ MORE
-
2. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks
University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)Abstract : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. READ MORE
-
3. Prototyping and Evaluation of a Lightweight Simulator Concept Combining Physical and Digital Assets
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : Serious injuries often occur in high-risk environments such as warfare, urban combat, and traffic accidents. The medical proficiency of soldiers and first responders in these situations is paramount. READ MORE
-
4. Achieving Cost-Effective Testing for Serverless Based Applications
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : Testing serverless applications poses unique challenges compared to traditional applications, such as the abstraction of its inner workings and how the pay-per-usage model means tests incur monetary costs. With the goal of studying practitioner’s approaches on this topic of cost-efficiency, we conducted five interviews and distributed a survey which received six responses. READ MORE
-
5. MetaStackVis: Visually-Assisted Performance Evaluation of Metamodels in Stacking Ensemble Learning
University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Abstract : Stacking, also known as stacked generalization, is a method of ensemble learning where multiple base models are trained on the same dataset, and their predictions are used as input for one or more metamodels in an extra layer. This technique can lead to improved performance compared to single layer ensembles, but often requires a time-consuming trial-and-error process. READ MORE
