• Enabling Edge Computing In 5G Via Local Area Data Network : Implementation and Experiments 

  Jalal, Junaid (Master thesis, 2019)

  The benefits of cloud computing are eclipsing when compared to other technologies, but the applications of cloud computing are very much cloud computing also has limitations due to its centralized architecture. The centralized ...

• Road Detection as a part of the Reward System for Reinforcement Learning-based Autonomous Cars 

  Holen, Martin (Master thesis, 2019)

  Human drivers are subject to numerous flaws. It is common that the driversget tired and lose control of the vehicle, and some even get drunk or high, whichresults in dangerous situations for themselves and others.Autonomous ...

• Investigative decision making : the use of storytelling in e-learning for training police students 

  Antoniv, Olha (Master thesis, 2019)

  Purpose–“E-learning is not intended to replace the traditional classroom setting, but to provide new opportunities for interaction and communication between students and instructor or teacher” (Zhang et al., 2004). The ...

• DinosARs - Learning with the help of augmented reality 

  Aastveit, Knut-Erik Krogstad (Master thesis, 2019)

  A two-dimensional way of interacting with learning material has been the norm fora long time. We’ve read books, taken notes and been taught from a blackboard sinceyouth, and has for most of us worked out just fine, but ...

• Using Course Movie Trailers to Affect Intrinsic Motivation 

  Røssland, Even Vinjor; Vogler, Franziska Maria (Master thesis, 2019)

  This master’s thesis investigates the connection between movie trailer emotions, suchas curiosity, inspiration, interest, and excitement and motivation in order to examine ifa course movie trailer can be utilized to affect ...

• Using Mobile Devices as a Supportive Tool to Engage and Interest Young Students in e-Health 

  Olsen, Joakim Torblå (Master thesis, 2019)

  This thesis explores if mobile devices could be used as a supportive elementto engage and interest young students in e-health by developing a prototypeto handle simulations of e-health scenarios in a serious game setting. ...

• A Deep Learning Approach for Recognizing Daily Movement Patterns through Accelerometer Data 

  Johansen, Sahand; Johannessen, Tommy Sandtorv (Master thesis, 2018)

  Physical activity is a key factor in the treatment of chronic diseases such asdiabetes, cardiovascular disease, and depression. Doctors and personal trainershave limited methods to accurately monitor and classify a patients ...

• A comparison of database systems for rapid search results in large amounts of leaked data 

  Prebensen, Nicolai (Master thesis, 2019)

  A large portion of the information on the Internet is stored in databases, since databases arethe natural place among online services for storage of user information. Hackers occasionallybreach web sites and publish ...

• Expanding on the end-to-end memory network for goal-oriented dialogue 

  Taraldsen, Peter Arentz; Vatne, Vegard (Master thesis, 2019)

  A series of end-to-end models have been proposed in order to satisfy therequirements of the Dialog System Technology Challenge: building an end-to-end dialog system for goal-oriented applications. While ...

• A Machine Learning based Prediction Model for Bursty Traffic in 5G mMTC Networks 

  Søraa, Aasmund (Master thesis, 2019)

  The rapid growth in popularity for the Internet of Things (IoT) has paved the way for a newtype of communication, called Machine-type Communication (MTC), causing substantially in-creased traffic volume. The existing network ...

• The Maritime Pickup and Delivery Problem with Cost and Time Window Constraints : System Modeling and A* Based Solution 

  Dambakk, Christopher (Master thesis, 2019)

  In the ship chartering business, more and more shipment ordersare based on pickup and delivery in an on-demand manner ratherthan conventional scheduled routines. In this situation, it is nec-essary to ...

• A Machine Learning Approach to Predict Accidents using Real Spatiotemporal Road Data 

  Heer, Jonas Gunneng; Johnsen, Einar Martin Egeland (Master thesis, 2019)

  Konfidensiell til / confidential until 01.07.2024

• Design and implementation of wake-up radios for long-range wireless IoT devices 

  Frøytlog, Anders (Master thesis, 2019)

  As the development within Internet of things IoT increases rapidly andthe market starts to utilize its potential, an enormous effort is being madein both academia and industry to optimize solutions according to the mar-ket ...

• Computer Vision based Auxiliary System for Computer Assembly: System Design and implementation 

  Bøtun, Erik; Halvorsen, Henrik Bugge (Master thesis, 2019)

  This thesis proposes a solution that employs AI in assisting a human withlittle or no technical background for computer assembly in real-time with-out any form of other assistance. To achieve this goal, a state-of-the-artobject ...

• SNOMED on FHIR Transmission of clinical data with the Fast Healthcare Interoperability Resources protocol (HL7-FHIR) utilizing Systematized Nomenclature of Medicine - Clinical Terms (SNOMED-CT) 

  Hassan, Waqar (Master thesis, 2019)

  The exchange of information at the level of semantic interoperability needs some infor-mation model and clinical terminology work together. Electronic records of the patientmust include the terminologies in order to give ...

• A deep learning segmentation approach to calories and weight estimation of food images 

  Isaksen, Runar; Knudsen, Eirik Bø; Walde, Aline Iyagizeneza (Master thesis, 2019)

  Today’s generation is very aware of what they are eating and the amountof calories in their food. Eating too many calories can lead to increasedweight, which has become a big health issue. A study from 2016 ...

• A Scalable Architecture for Parallel Execution of the Tsetlin Machine 

  Olsen, Anders Refsdal (Master thesis, 2019)

  With the Tsetlin Machine recently released, much research has been done on itscapabilities, with great success. However, the lack of tools available, and generalknowledge of the Tsetlin Machine prevents it from being ...

• On the use of Denoising Autoencoders and Deep Convolutional Adversarial Networks for Automated Removal of Date Stamps 

  Anderson, Nicolas; Paavola, Mikael; Sognnes, Johnny (Master thesis, 2019)

  This thesis investigates to what extent the deep learning models such as DenoisingAutoencoder (DAE) and Deep Convolution General Adversarial Net (DCGAN)automate the removal of the date stamps from images with high resolution ...

• A DEEP LEARNING SEGMENTATION APPROACH FOR AUTOMATIC INVOICE IDENTIFICATION 

  Samdal, Ellen Synnøve (Master thesis, 2019)

  The research on object detection has come a long way and has in recent years become so efficient andreliable that we see many practical applications in simple detection of objects in pictures to advancesegmentation in video ...

• E-Health : A smartphone-based e-health application for enhancing rural healthcare with the integration of medical sensor devices 

  Khatiwada, Pankaj (Master thesis, 2019)

  The purpose of this research is to develop a smartphone or tablet based eHealth applica-tion to assist health workers in remote regions of different parts of the world with record-ing medical information and with the ...

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