Essays about: "computational physics"

Showing result 1 - 5 of 78 essays containing the words computational physics.

  1. 1. Patterning of the neural tube: A 3D computational modelling approach

    University essay from Lunds universitet/Institutionen för astronomi och teoretisk fysik; Lunds universitet/Beräkningsbiologi och biologisk fysik

    Author : Ariane Ernst; [2019]
    Keywords : gene regulatory networks; neural tube patterning; patterning of the neural tube; dopaminergic neurons; parkinson s disease; computational modelling; stem cell; GRN; Biology and Life Sciences; Physics and Astronomy;

    Abstract : Neurodegenerative diseases such as Parkinson’s can be treated with stem-cell derived specialized neurons. In order to achieve precise directed neural differentiation in vitro we need to understand the gene regulatory mechanisms behind in vivo neural tube patterning. READ MORE

  2. 2. Machine Learning for Air Flow Characterization : An application of Theory-Guided Data Science for Air Fow characterization in an Industrial Foundry

    University essay from Karlstads universitet

    Author : Robin Lundström; [2019]
    Keywords : Machine learning; ML; Echo State Map; ESM; Echo State Network; ESN; Gaussian Process; GP; Computational Fluid Dynamics; CFD; Theory-Guided Data Science; TGDS; Physics-Guided Data Science; Data science; Cross-discipline; Hybrid model; MatLab; Maskininlärning; ML; Echo State Map; ESM; Echo State Network; ESN; Gaussiska Processer; GP; Beräkningsströmningsdynamik; CFD; MatLab;

    Abstract : In industrial environments, operators are exposed to polluted air which after constant exposure can cause irreversible lethal diseases such as lung cancer. The current air monitoring techniques are carried out sparely in either a single day annually or at few measurement positions for a few days. READ MORE

  3. 3. Machine learning and augmented data for automated treatment planning in complex external beam radiation therapy

    University essay from Högskolan i Gävle/Avdelningen för elektronik, matematik och naturvetenskap

    Author : Michael Lempart; [2019]
    Keywords : Machine Learning; Deep Learning; Data Augmentation; Treatment Planning; External Beam Radiation Therapy;

    Abstract : External beam radiation therapy is currently one of the most commonly used modalities for treating cancer. With the rise of new technologies and increasing computational power, machine learning, deep learning and artificial intelligence applications used for classification and regression problems have begun to find their way into the field of radiation oncology. READ MORE

  4. 4. Artificial Neural Networks to Solve Inverse Problems in Quantum Physics

    University essay from Lunds universitet/Matematisk fysik; Lunds universitet/Fysiska institutionen

    Author : Victor Lantz; [2019]
    Keywords : Artificial Neural Networks; ANN; Deep learning; Quantum physics; Inverse problem; Inverse; Machine learning; Density functional theory; DFT; Physics; Computational physics; Technology and Engineering;

    Abstract : Inverse problems are important in quantum physics as their solutions are essential in order to describe a number of systems using measurable information, e.g. excitation energies or material properties. The problem with inverse problems is that they are usually very hard to solve. READ MORE

  5. 5. Ab initio simulations of topological phase transitions in Dirac semimetal Cd3As2 doped with Zn and Mn impurities

    University essay from Linnéuniversitetet/Institutionen för fysik och elektroteknik (IFE)

    Author : Andrea Rancati; [2019]
    Keywords : Topological materials; Dirac semimetals; Weyl semimetals; ab initio simulation; first-principles;

    Abstract : In this work we exploit the unique characteristics of a Dirac semimetal material to be symmetry-protected, to investigate dierent topological phase transitions provided by chemical dopings, focusing in particular on the electronic, magnetic and topological properties of the doped systems, studied by the mean of rst-principles methods based on density functional theory (DFT) approach. In particular these doped systems, besides being of interest for investigating the role of topology in solid state physics, could have a great potential for practical application since the dierent topological phases that come along with the chemical dopings allow one to exploit the unique properties of topological materials. READ MORE