Viser treff 283-302 av 627

    • Integrating libpesto with subversion 

      Jakobsen, Oleg (Master thesis; Mastergradsoppgave, 2007-06-15)
      Subversion, an open-source centralized version control system, developed by CoallabNet, is currently the second most popular version control system, after the ever popular CVS. Like CVS, Subversion uses a client-server architecture, but has a cleaner, modular architecture. One set of subversion modules, are the filesystem backends modules of subversion. Two ``official'' backends are currently ...
    • Integrating Various Sensor Readings from MySignals into a Standalone Mobile Health App 

      Koirala, Madhu (Master thesis; Mastergradsoppgave, 2021-05-22)
      This project integrates various health parameters Temperature, Heart Rate, Pulse Rate, Blood Pressure, Respiration Rate, ECG, EMG, GSR, Spirometry values, Snore, Blood Sugar, Body Positions and Weight measured through wired and wireless sensors, into a standalone mobile health app. It shows Health Status of the user based on these parameters, and displays the values in different colors for normal ...
    • Integration of HelseID with Third-Party Role Assignments Data 

      Fagermyr, Thomas L. (Master thesis; Mastergradsoppgave, 2021-08-31)
      The Norwegian healthcare sector is vast, with a substantial number of organizations employing plenty of people, and thereof, 7,300 are customers of Norsk Helsenett. Maintaining and keeping up-to-date information about access rights for these customers is a difficult, time-consuming, and manual task, especially since organizations often change personnel without notifying the system administrators. ...
    • Integration of solar latent heat storage towards optimal small-scale combined heat and power generation by Organic Rankine Cycle 

      Lizana, Jesus; Bordin, Chiara; Rajabloo, Talieh (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-16)
      Thermal energy and distributed electricity demand are continuously increased in areas poorly served by a centralized power grid. In many cases, the deployment of the electricity grid is not economically feasible. Small-scale Organic Rankine Cycle (ORC) appears as a promising technology that can be operated by solar energy, providing combined heat and power (CHP) generation. Additionally, thermal ...
    • Intelligent Offloading Distribution of High Definition Street Maps for Highly Automated Vehicles 

      Jomrich, Florian; Sharma, Aakash; Ruckelt, Tobias; Bohnstedt, Doreen; Steinmetz, Ralf (Journal article; Tidsskriftartikkel; Peer reviewed, 2018-11-24)
      Highly automated vehicles will change our personal mobility in the future. To ensure the safety and the comfort of their passengers, the cars have to rely on as many information regarding their current surrounding traffic situation, as they can obtain. In addition to classical sensors like cameras or radar sensors, automated vehicles use data from a so called High Definition Street Map. Through such ...
    • An Intent-Based Reasoning System for Automatic Generation of Drone Missions for Public Protection and Disaster Relief 

      Grønvold, Marcel André (Mastergradsoppgave; Master thesis, 2023-06-01)
      The utilization of drones for search and rescue operations has become more prevalent over the years. Drones can provide an aerial perspective which can aid first responders in gaining an overview of a situation. Autonomous drones can automate search and rescue operations by removing the human pilot, which can increase efficiency and lower costs. The increased development of machine learning models ...
    • Interactive visualizations of unstructured oceanographic data 

      Kirkvik, Simen Lund (Mastergradsoppgave; Master thesis, 2023-02-15)
      The newly founded company Oceanbox is creating a novel oceanographic forecasting system to provide oceanography as a service. These services use mathematical models that generate large hydrodynamic data sets as unstructured triangular grids with high-resolution model areas. Oceanbox makes the model results accessible in a web application. New visualizations are needed to accommodate land-masking and ...
    • Interdisciplinary optimism? Sentiment analysis of Twitter data 

      Weber, Charlotte Teresa; Syed, Shaheen (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-07-31)
      Interdisciplinary research has faced many challenges, including institutional, cultural and practical ones, while it has also been reported as a ‘career risk’ and even ‘career suicide’ for researchers pursuing such an education and approach. Yet, the propagation of challenges and risks can easily lead to a feeling of anxiety and disempowerment in researchers, which we think is counterproductive to ...
    • Internet of things DDoS mitigation. Preventing DDoS attacks using learning algorithms on limited hardware 

      Munch-Ellingsen, Peter (Master thesis; Mastergradsoppgave, 2017-10-01)
      DDoS attacks are becoming more and more common, and threatens the current infrastructure of the internet. Cheap new IoT devices have led to a lot of new devices that are poorly secured and can easily be compromised and used for such nefarious purposes. While there are many attemps at solving this problem this thesis looks at a solution which could be applied to typical home router. This would stop ...
    • Internet of Things Mini Display-based Motivation, Notification and Warning System for Groups of People with Diabetes Type 1 

      Mikalsen, Martin Haugen (Master thesis; Mastergradsoppgave, 2018-06-01)
      Diabetes is a complex and time-consuming affair for the people that are afflicted by the disease. A strict self-management regime needs to be followed to avoid short- and long-term complications, which requires a great deal of motivation and support from others. Low- or high-blood glucose levels can cause short- and long-term consequences, ranging from headaches and thirst to coma. In the last few ...
    • Intersecting near-optimal spaces: European power systems with more resilience to weather variability 

      Grochowicz, Aleksander; van Greevenbroek, Koen; Benth, Fred Espen; Zeyringer, Marianne (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-01-03)
      We suggest a new methodology for designing robust energy systems. For this, we investigate so-called near-optimal solutions to energy system optimisation models; solutions whose objective values deviate only marginally from the optimum. Using a refined method for obtaining explicit geometric descriptions of these near-optimal feasible spaces, we find designs that are as robust as possible to ...
    • An introduction to the TACOMA distributed system. Version 1.0 

      Johansen, Dag; Renesse, Robbert van; Schneider, Fred B. (Research report; Forskningsrapport, 1995-06)
      This report briefly introduces TACOMA Version 1.0. This distributed system supports agents, computations that can roam the internet. The report presents the TACOMA project, the computational model, how to get started, and the basic TACOMA abstractions.
    • Inverse and efficiency of heat transfer convex fin with multiple nonlinearities 

      Roy, Pranab Kanti; Mondal, Hiranmoy; Mallick, Ashis; Prasad, Dilip K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-07-22)
      In this article, we first propose the novel semi-analytical technique—modified Adomian decomposition method (MADM)—for a closed-form solution of the nonlinear heat transfer equation of convex profile with singularity where all thermal parameters are functions of temperature. The longitudinal convex fin is subjected to different boiling regimes, which are defined by particular values of n (power ...
    • Investigating and developing efficient federated learning for air pollution monitoring 

      Reinnes, Jørgen (Master thesis; Mastergradsoppgave, 2022-06-01)
      Location-based data may be considered highly private; as such, handling location-based data requires that it cannot be used to track a user. In a network of multiple edge devices that each collect data, training a machine learning model would typically involve transmitting the data securely to a central server which requires strict privacy rules. Federated learning solves the privacy problem ...
    • Investigating the effects of dynamic approximation methods on machine learning (ML) algorithms running on ML-specialized platforms 

      Haugen, Eirik (Master thesis; Mastergradsoppgave, 2021-05-15)
      This thesis discusses the application of optimizations to machine learning algorithms. In particular, we look at implementing these algorithms on specialized hardware, I.e. a Graphcore Intelligence Processing Unit, while also applying software optimizations that have been shown to improve performance of traditional workloads on general purpose CPUs. We discuss the feasibility of using these techniques ...
    • Investigating the latency cost of statistical learning of a Gaussian mixture simulating on a convolutional density network with adaptive batch size technique for background modeling 

      Phan, Hung Ngoc (Master thesis; Mastergradsoppgave, 2021-05-31)
      Background modeling is a promising field of study in video analysis, with a wide range of applications in video surveillance. Deep neural networks have proliferated in recent years as a result of effective learning-based approaches to motion analysis. However, these strategies only provide a partial description of the observed scenes' insufficient properties since they use a single-valued mapping ...
    • Investigating the security issues surrounding usage of Ephemeral data within Android environments 

      Høgset, Erlend Skog (Master thesis; Mastergradsoppgave, 2015-08-27)
      With mobile devices managing more and more of our personal data, for many it has become a ubiquitous resource. This is also true in the workplace where they are instituting Bring Your Own Device practices. While this saves the enterprise money in terms of equipment, it also increases the diversity of devices brought to work. This presents security problems as corporate data received and transmitted ...
    • An investigation of combined effect of infill pattern, density, and layer thickness on mechanical properties of 3D printed ABS by fused filament fabrication 

      Agrawal, Anant Prakash; Kumar, Virendra; Kumar, Jitendra; Paramasivam, Prabhu; Dhanasekaran, Seshathiri; Prasad, Lalta (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-05-23)
      Additive manufacturing technology and its benefits have a significant impact on different industrial applications. The 3D printing technologies help manufacture lightweight intricate geometrical designs with enhanced strengths. The present study investigates the blended effects of previously recommended parameters of different infill patterns (line, triangle, and concentric) and infill densities ...
    • IRON-MAN: An Approach to Perform Temporal Motionless Analysis of Video Using CNN in MPSoC 

      Dey, Somdip; Singh, Amit Kumar; Prasad, Dilip K.; McDonald-Maier, Klaus Dieter (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-07-20)
      This paper proposes a novel human-inspired methodology called IRON-MAN (Integrated RatiONal prediction and Motionless ANalysis) for mobile multi-processor systems-on-chips (MPSoCs). The methodology integrates analysis of the previous image frames of the video to represent the analysis of the current frame in order to perform Temporal Motionless Analysis of the Video (TMAV). This is the first work ...
    • IT2-GSETSK: An evolving interval Type-II TSK fuzzy neural system for online modeling of noisy data 

      Ashrafi, Mohammad; Prasad, Dilip K.; Quek, Chai (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-05-12)
      As a core part of a fuzzy neural system, the rule base antecedents and consequents may carry uncer- tainties because they are trained using noisy data. So, handling the uncertain rule base is an important need in some specific problems such as noisy non-dynamic problems which leads a better data model- ing. As a solution, Interval Type-II (IT2) version of GSETSK (Generic Self-Evolving ...