Sökning: "Scaling Social Impact"
Visar resultat 1 - 5 av 18 uppsatser innehållade orden Scaling Social Impact.
1. Scaling up social enterprises to tackle environmental problems : A study exploring scale-up challenges, solutions, and opportunities of social enterprises tackling environmental problems
Master-uppsats,Sammanfattning : AbstractBackground: Among the biggest threats to mankind are various environmental problems which have been mainly triggered by human interference with the planet. There have been various ineffective efforts to mitigate these detrimental effects. LÄS MER
2. Using Approximate Computing Circuits to Optimize Power of an ASIC
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : The growing demand for network cameras to support real-time image processing and machine-learning applications has created a need for low-power solutions. Although technology scaling makes complex computations feasible, voltage scaling is limited, leading to higher power density and dark silicon problems. LÄS MER
3. Föräldrastil och skärmtid - En kvantitativ undersökning om sambandet mellan den auktoritära föräldrastilen och barns skärmtid
Kandidat-uppsats, Lunds universitet/SocialhögskolanSammanfattning : Introduction and method: The aim of this study was to investigate the relationship between the authoritarian parenting style and children's screen time. The study included parents of children between the ages of 0-6 years (n=397). LÄS MER
4. Food for transformation – food for thought : The development of transformative capacity of niche initiatives in the Greater Cape Town area and the Stockholm city-region
Master-uppsats, Stockholms universitet/Stockholm Resilience CentreSammanfattning : As the global food system causes environmental degradation and contributes to detrimental health effects, a transformation is vital for a sustainable and fair future for all. Research on food system transformation and the role of food initiatives have increased. LÄS MER
5. Machine Learning Modeling using Heterogeneous Transfer Learning in the Edge Cloud
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : 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. LÄS MER