Sökning: "Muhammad Afzal"

Hittade 3 avhandlingar innehållade orden Muhammad Afzal.

  1. 1. Semiconductor-ionic Materials for Low Temperature Solid Oxide Fuel Cells

    Författare :Muhammad Afzal; Andrew R. Martin; Peter Lund; Hab. Armelle Ringuede; KTH; []
    Nyckelord :Semiconductor-ionic materials; electrolyte-layer free fuel cell; low temperature solid oxide fuel cell; fuel to electricity conversion; Schottky junction; theoretical and experimental curves; Halvledar-joniska material; elektrolytskikt-fri bränslecell; lågtemperatur fastoxidbränslecell; bränsle till elomvandling; Schottky junction; teoretiska och experimentella kurvor; Energy Technology; Energiteknik;

    Sammanfattning : Solid oxide fuel cell (SOFC) is considered as an attractive candidate for energy conversion within the fuel cell (FC) family due to several advantages including environment friendly, use of non-noble materials and fuel flexibility. However, due to high working temperatures, conventional SOFC faces many challenges relating to high operational and capital costs besides the limited selection of the FC materials and their compatibility issues. LÄS MER

  3. 2. Model-based System Testing of Safety-Critical Embedded Software

    Författare :Muhammad Nouman Zafar; Wasif Afzal; Eduard Paul Enoiu; Cyrille Artho; Mälardalens universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

    Sammanfattning : System-level testing of safety-critical embedded systems is complex and costly. MBT has shown promising results in terms of fault detection effectiveness and efficiency of test generation and execution. However, the industrial adoption of MBT approaches is slow and limited to specific industries and domains. LÄS MER

  4. 3. Deep Learning for Geo-referenced Data : Case Study: Earth Observation

    Författare :Nosheen Abid; Marcus Liwicki; Muhammad Zeshan Afzal; Luleå tekniska universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Artificial Intelligence; Machine Learning; Earth Observation; Computer Vision; Machine Learning; Maskininlärning;

    Sammanfattning : The thesis focuses on machine learning methods for Earth Observation (EO) data, more specifically, remote sensing data acquired by satellites and drones. EO plays a vital role in monitoring the Earth’s surface and modelling climate change to take necessary precautionary measures. LÄS MER