Sökning: "Clean labels"
Visar resultat 1 - 5 av 6 uppsatser innehållade orden Clean labels.
1. Predicting inflow and infiltration to wastewater networks based on temperature measurements
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : Sewer pipelines are deteriorating due to aging and sub optimal material selections, leading to the infiltration of clean ground and rainfall water into the pipes. It is estimated that a significant portion (up to 40-50%) of the water entering wastewater treatment plants is actually clean infiltrated water. LÄS MER
2. Production, utilization and implementation of coconut charcoal in rural Mozambique: As a clean cooking fuel and a way to improve economic empowerment of women in Linga Linga
Master-uppsats, Lunds universitet/Institutionen för energivetenskaperSammanfattning : Luftförorening är ett globalt hälsoproblem och i Moçambique orsakas inomhusluftförorening främst av matlagning över öppen eld. Denna studie undersöker potentialen hos kokosnötskol som en renare bränslekälla för matlagning och som en möjlig inkomstkälla för kvinnor i byn Linga Linga, Moçambique. LÄS MER
3. Coming Clean : An exploratory study of sustainable consumption and clean label consumer motivations
Kandidat-uppsats, Jönköping University/IHH, FöretagsekonomiSammanfattning : Background: The food industry has become one of the key actors in today’s sustainability equation. Consumers are becoming more conscious than ever before, putting more thought into ingredients and packaging. The number one trend of 2020 is clean label food, thus inviting for research within this specific field. LÄS MER
4. Exploring Cross-lingual Sublanguage Classification with Multi-lingual Word Embeddings
Master-uppsats, Linköpings universitet/Statistik och maskininlärningSammanfattning : Cross-lingual text classification is an important task due to the globalization and the increased availability of multilingual data. This thesis explores the method of implementing cross-lingual classification on Swedish and English medical corpora. LÄS MER
5. Learning from noisy labelsby importance reweighting: : a deep learning approach
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Noisy labels could cause severe degradation to the classification performance. Especially for deep neural networks, noisy labels can be memorized and lead to poor generalization. LÄS MER