Browsing Institutt for datateknologi og informatikk by Title
Now showing items 4745-4764 of 6615
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Preventing Over-Enhancement Using Modified ICSO Algorithm
(Peer reviewed; Journal article, 2023)This paper proposes an Image Contrast Enhancement (ICE) method based on using an Improved Chicken Swarm Optimization (ICSO) algorithm to enhance images while at the same time preventing over-enhancement. In the optimization ... -
Principles, Techniques, and Tools for Explicit and Automatic Parallelization
(Doctoral theses at NTNU;2019:81, Doctoral thesis, 2019)The end of Dennard scaling also brought an end to frequency scaling as a means to improve performance. Chip manufacturers had to abandon frequency and superscalar scaling as processors became increasingly power constrained. ... -
Prioritisation of security in agile software development projects
(Doctoral theses at NTNU;2022:285, Doctoral thesis, 2022)Agile software development is driven by business value, and strives towards visible progressthrough features. Consequently, the somewhat invisible and overarching aspect of softwaresecurity is at the risk of being neglected.A ... -
PrivaCity: A Chatbot Serious Game to Raise the Privacy Awareness of Teenagers
(Master thesis, 2018)In the modern society collection of data happens everywhere, and consequently, privacy is an ever-growing concern. It has been shown that people, and especially teenagers, lack awareness around the data they share and the ... -
A privacy aware recommendation system for Android apps
(Master thesis, 2015)Recommender systems are an increasingly popular in e-commerce today. Companies such as Netflix and Amazon relies on them to create an ever increasing portion of their income. These systems often comes at the price of ... -
Privacy in Location aware Systems for Social Interaction
(Master thesis, 2008)Social network services like Facebook, and instant messaging services like MSN Messenger have gained an enormous popularity in just a few years, and are undoubtedly popular among users.hat happens when these networks are ... -
Privacy in Recommender Systems: Can Recommendations Reveal Your Location?
(Master thesis, 2021)Anbefalingssystemer har blitt en essensiell del av brukeropplevelsen online, og hjelper brukere til å navigere seg gjennom en overflod av tilgjengelig informasjon, produkter og tjenester. I denne sammenheng har en rekke ... -
Privacy in Recommender Systems: Inferring User Personality Traits From Personalized Movie Recommendations
(Master thesis, 2023)Anbefalingssystemer er personaliserte systemer som samler inn brukerdata for å anbefale og skreddersy innhold. Denne masteroppgaven undersøker hvordan personlighetstrekk kan utledes fra personaliserte topp 10-filmanbefalinger ... -
Privacy in Recommender Systems: Inferring User Personality Traits From Personalized Movie Recommendations
(Master thesis, 2023)Anbefalingssystemer er personaliserte systemer som samler inn brukerdata for å anbefale og skreddersy innhold. Denne masteroppgaven undersøker hvordan personlighetstrekk kan utledes fra personaliserte topp 10-filmanbefalinger ... -
Privacy Leaks in Recommender Lists: Exploring Obfuscation Techniques to Preserve Privacy
(Master thesis, 2023)Flesteparten av dagens digitale tjenester benytter en eller annen form for et anbefalingssystem. En stor ulempe med disse anbefalingssystemene er at de baserer seg på store mengder med persondata, noe som gjør dem utsatte ... -
Privacy-preserving data search with fine-grained dynamic search right management in fog-assisted Internet of Things
(Journal article; Peer reviewed, 2019)Fog computing, as an assisted method for cloud computing, collects Internet of Things (IoT) data to multiple fog nodes on the edge of IoT and outsources them to the cloud for data search, and it reduces the computation ... -
Privacy-Preserving Decentralized Calculation in Digital Contact Tracing
(Master thesis, 2021)Kontaktsporing er en manuell prosess som brukes av helsebyråer for å kartlegge individers sosiale interaksjoner, og utføres når enkeltpersoner blir smittet for å identifisere andre i faresonen. Covid-19 pandemien økte ... -
Privacy-Preserving Federated Learning Applied to Decentralized Data
(Bachelor thesis, 2021)I dagens samfunn er teknologien i konstant utvikling, og på grunn av dette blir det samlet inn og lagret en økende mengde data. De siste årene har mange firmaer samlet store mengder data fra diverse datakilder, slik som ... -
Privacy-preserving tax-case processing
(Chapter, 2019)Tax-case processing is based on a classification of common taxable conditions, e.g. retirement benefits, social security benefits, income brackets. Based on those, groups of people fall under certain categorizations and ... -
Private vs. Public cloud: Simplicity over security?
(Master thesis, 2023)Kontekst: Bruken av Skytjenester er en voksende trend blant organisasjoner over hele verden. Dette i samspill med at cybercrime er en voksende trussel, gir en bekymring av at organisasjoner gir for mye tillit til utenlandske ... -
A Probabilistic Bag-to-Class Approach to Multiple-Instance Learning
(Peer reviewed; Journal article, 2020)Multi-instance (MI) learning is a branch of machine learning, where each object (bag) consists of multiple feature vectors (instances)—for example, an image consisting of multiple patches and their corresponding feature ... -
Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting
(Peer reviewed; Journal article, 2021)Data-driven forecasts of air quality have recently achieved more accurate short-term predictions. However, despite their success, most of the current data-driven solutions lack proper quantifications of model uncertainty ... -
Probabilistic framework for multi-target tracking using multi-camera: applied to fall detection
(Master thesis, 2010)The developments in health care lead to longer life expectancy in developed countries. The growth of the number of seniors put new challenges to health care services, caregivers and family members. One of the major challenges ... -
Probabilistic Models with Deep Neural Networks
(Peer reviewed; Journal article, 2021)Recent advances in statistical inference have significantly expanded the toolbox of probabilistic modeling. Historically, probabilistic modeling has been constrained to very restricted model classes, where exact or approximate ... -
Probing Gravity Waves in the Middle Atmosphere Using Infrasound From Explosions
(Peer reviewed; Journal article, 2023)This study uses low-frequency, inaudible acoustic waves (infrasound) to probe wind and temperature fluctuations associated with breaking gravity waves (GWs) in the middle atmosphere. Building on an approach introduced by ...