Essays about: "value added networks"
Showing result 1 - 5 of 27 essays containing the words value added networks.
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1. Quantification of DNA Nanoballs Using Image Processing Techniques
University essay from Uppsala universitet/Avdelningen Vi3Abstract : In gene editing, it is important to identify the number of edited and unedited nucleic acids in the development of new therapies and drugs. Countagen is developing a technology for accelerating genomic research and their product is called GeneAbacus. READ MORE
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2. 'Ukraine Is Alive' Ukrainian Music-Making in Swedish Emergency Residencies : The impact of war, displacement, migration and networks
University essay from Uppsala universitet/Institutionen för musikvetenskapAbstract : In February 2022 Russia’s invasion of Ukraine started the war that would lead to the largest refugee crisis in Europe since World War II. In response to the war, SWAN, the Swedish Artists Residency Network, initiated the project Emergency residencies. READ MORE
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3. Reconstruction of the energy of neutrinos with neural networks: Event-by-event uncertainty estimation
University essay from Uppsala universitet/HögenergifysikAbstract : When high-energy neutrinos interact with matter, radio waves will be emitted. Radio detectionallows us to measure UHE(> 1016eV) neutrinos by instrumenting a huge volume with a sparsearray of radio antenna stations at a low cost. READ MORE
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4. Age Prediction in Breast Cancer Risk Stratification : Additive Value of Age Prediction on Healthy Mammography Images in Breast Cancer Risk Models
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Breast cancer is the most common cancer type for women worldwide. Early detection is key to improve prognosis and treatment success. A cost-efficient way of finding breast cancer early is mammography screening on a population basis. A major issue with mammography screening is in-between screening cancers. READ MORE
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5. Machine Learning Modeling using Heterogeneous Transfer Learning in the Edge Cloud
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The dynamic nature of the edge cloud and future network infrastructures is another challenge to be added when modeling end-to-end service performance using machine learning. That is, a model that has been trained for one specific environment may see reductions in prediction accuracy over time due to e.g., routing, migration, or scaling decisions. READ MORE