Browsing ODA Open Digital Archive by Title
Now showing items 12118-12137 of 17120
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Precarity in Nordic working life?
(Chapter; Peer reviewed, 2019)This chapter discusses the relevance of the concept of ‘precarity’, understood as work conditioned by a lack of security and predictability, in a Nordic context, and links precariousness to both formal work arrangements ... -
Predicting ADHD in Children Using Eye-Tracking Data and Mathematical Modeling
(Master thesis, 2023)Attention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent neurobiological condition with far-reaching implications for a child's academic achievement, well-being, and social interactions. Despite its impact, current ... -
Predicting Cell Cleavage Timings from Time-Lapse Videos of Human Embryos
(Peer reviewed; Journal article, 2023)Assisted reproductive technology is used for treating infertility, and its success relies on the quality and viability of embryos chosen for uterine transfer. Currently, embryologists manually assess embryo development, ... -
Predicting Compressive Strength of Concrete Containing Recycled Aggregate Using Modified ANN with Different Optimization Algorithms
(Applied Sciences;Volume 11, Issue 2, Journal article; Peer reviewed, 2021-01-06)Using recycled aggregate in concrete is one of the best ways to reduce construction pollu- tion and prevent the exploitation of natural resources to provide the needed aggregate. However, recycled aggregates affect the ... -
Predicting compressive strength of CRM samples using Image processing and ANN
(IOP Conference Series: Materials Science and Engineering;volume 899, Peer reviewed; Journal article, 2020)Quality of concrete is majorly ascertained through its compressive strength which has a significant role in the stability of concrete structures. In this study, artificial neural network (ANN) and image processing (IP) ... -
Predicting COVID-19 exposure risk perception using machine learning
(Journal article; Peer reviewed, 2023)Background Self-perceived exposure risk determines the likelihood of COVID-19 preventive measure compliance to a large extent and is among the most important predictors of mental health problems. Therefore, there is a need ... -
Predicting disease severity in multiple sclerosis using multimodal data and machine learning
(Peer reviewed; Journal article, 2023)Background Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity. Methods We have analysed a prospective ... -
Predicting Finnish subject-teachers’ ICT use in Home Economics based on teacher- and school-level factors
(Education Inquiry;volume 12, issue 1, Peer reviewed; Journal article, 2020-06-24)This survey-based study (N = 161) investigates the direct and indirect effects of teacher- and school-level factors on subject-teachers’ use of ICT in Home Economics (HE). Structural equation modelling was used to test the ... -
Predicting High Delays in Mobile Broadband Networks
(IEEE Access;Volume 9: 2021, Peer reviewed; Journal article, 2021-12-24)The number of applications that run over mobile networks, expecting bounded end-to-end delay, is increasing steadily. However, the stochastic and shared nature of the wireless medium makes providing such guarantees ... -
Predicting missing pairwise preferences from similarity features in group decision making
(Knowledge-Based Systems;Volume 256, 28 November 2022, 109860, Peer reviewed; Journal article, 2022)In group decision-making (GDM), fuzzy preference relations (FPRs) refer to pairwise preferences in the form of a matrix. Within the field of GDM, the problem of estimating missing values is of utmost importance, since many ... -
Predicting moisture condensation risk on the radiant cooling floor of an office using integration of a genetic algorithm-back-propagation neural network with sensitivity analysis
(Journal article; Peer reviewed, 2022)Pre-dehumidification time (𝜏�pre ) and pre-dehumidification energy consumption (Epre ) play important roles in preventing the condensation of moisture on the floors of rooms that use a radiant floor cooling (RFC) ... -
Predicting peek readiness-to-train of soccer players using long short-term memory recurrent neural networks
(International Workshop on Content-Based Multimedia Indexing, CBMI;, Conference object, 2019)We are witnessing the emergence of a myriad of hardware and software systems that quantifies sport and physical activities. These are frequently touted as game changers and important for future sport developments. The vast ... -
Predicting performance and scaling behaviour in a data center with multiple application servers
(Master thesis, 2006)As web pages become more user friendly and interactive we see that objects such as pictures, media files, cgi scripts and databases are more frequently used. This development causes increased stress on the servers due ... -
Predicting performance of in-situ microbial enhanced oil recovery process and screening of suitable microbe-nutrient combination from limited experimental data using physics informed machine learning approach
(Bioresource Technology;, Peer reviewed; Journal article, 2022)Screening of suitable microbe-nutrient combination and prediction of oil recovery at the initial stage is essential for the success of Microbial Enhanced Oil Recovery (MEOR) technique. However, experimental and physics-based ... -
Predicting Psychological Distress During the COVID-19 Pandemic: Do Socioeconomic Factors Matter?
(Peer reviewed; Journal article, 2022) -
Predicting Remaining Fatigue Life of Topside Piping Using Deep Learning
(International Conference on Applied Artificial Intelligence (ICAPAI);2021 International Conference on Applied Artificial Intelligence (ICAPAI), Conference object, 2021-06-29)Topside piping is the most commonly failed equipment in the Petroleum and Maritime industry. The prominent degradation mechanism causing piping failure is fatigue which results in unnecessary hydrocarbon release from these ... -
Predicting Sensor Events, Activities, and Time of Occurrence Using Binary Sensor Data From Homes With Older Adults
(IEEE Access;Volume 7, Journal article; Peer reviewed, 2019-08-08)We present a comprehensive study of state-of-the-art algorithms for the prediction of sensor events and activities of daily living in smart homes. Data have been collected from eight smart homes with real users and 13-17 ... -
Predicting stable employment trajectories among young people with disabilities
(Peer reviewed; Journal article, 2023)Research aiming to explain disabled people’s inequalities in the labour market has primarily focused on transitional factors between school and work, wage gaps, or socioeconomic background characteristics as expla- nations ... -
Predicting suicide attempts among Norwegian adolescents without using suicide-related items: a machine learning approach
(Journal article; Peer reviewed, 2023)Introduction: Research on the classification models of suicide attempts has predominantly depended on the collection of sensitive data related to suicide. Gathering this type of information at the population level can be ... -
Predicting TCP congestion through active and passive measurments
(Master thesis, 2005)The Transmission Control Protocol (TCP) has proved to be a reliable transport protocol that has withstood the test of time. It is part of the TCP/IP protocol suite deployed on the Internet, and it currently supports a ...