Sökning: "matematisk likhet"
Visar resultat 1 - 5 av 11 uppsatser innehållade orden matematisk likhet.
1. Elevers uppfattning om likhetstecknet i matematik : En kvalitativ studie med kvantitativa drag
Uppsats för yrkesexamina på avancerad nivå, Stockholms universitet/Institutionen för ämnesdidaktikSammanfattning : Syftet med studien var att bidra till en djupare förståelse för de uppfattningar elever i årskurs 1-3 har om likhetstecknet i matematik. För att behandla studiens syfte och frågeställning genomfördes datainsamlingen genom två olika metoder, vilka bestod av ett skriftligt test samt semistrukturerade intervjuer. LÄS MER
2. Classification in Functional Data Analysis : Applications on Motion Data
Master-uppsats, Umeå universitet/Institutionen för matematik och matematisk statistikSammanfattning : Anterior cruciate knee ligament injuries are common and well known, especially amongst athletes.These injuries often require surgeries and long rehabilitation programs, and can lead to functionloss and re-injuries (Marshall et al., 1977). LÄS MER
3. Product Similarity Matching for Food Retail using Machine Learning
Master-uppsats, KTH/Matematisk statistikSammanfattning : Product similarity matching for food retail is studied in this thesis. The goal is to find products that are similar but not necessarily of the same brand which can be used as a replacement product for a product that is out of stock or does not exist in a specific store. LÄS MER
4. The anti-amyloidogenic chaperone DNAJB6 and its interaction with other chaperones
Kandidat-uppsats, Lunds universitet/Matematisk statistik; Lunds universitet/Kemiska institutionenSammanfattning : In order to maintain proteins’ functionality their native folding state must be preserved. Chaperones fold other proteins and DNAJ-chaperones may collaborate with Hsc70 chaperones to prevent aggregation of aggregation-prone peptides such as polyQ and Aβ42, which form fibrils in currently incurable diseases as Huntington’s and Alzheimer’s, respectively. LÄS MER
5. A study on the application of machine learning algorithms in stochastic optimal control
Master-uppsats, KTH/Matematisk statistikSammanfattning : By observing a similarity between the goal of stochastic optimal control to minimize an expected cost functional and the aim of machine learning to minimize an expected loss function, a method of applying machine learning algorithm to approximate the optimal control function is established and implemented via neural approximation. Based on a discretization framework, a recursive formula for the gradient of the approximated cost functional on the parameters of neural network is derived. LÄS MER