Filaments of Meaning in Word Space

Word space models, in the sense of vector space models built on distributional data taken from texts, are used to model semantic relations between words. We argue that the high dimensionality of typical vector space models lead to unintuitive effects on modeling likeness of meaning and that the local structure of word spaces is where interesting semantic relations reside. We show that the local structure of word spaces has substantially different dimensionality and character than the global space and that this structure shows potential to be exploited for further semantic analysis using methods for local analysis of vector space structure rather than globally scoped methods typically in use today such as singular value decomposition or principal component analysis

The opportunistic replacement and inspection problem for components with a stochastic life time

The problem of finding efficient maintenance and inspection schemes in the case of components with a stochastic life time is studied and a mixed integer programming solution is proposed. The problem is compared with the two simpler problems of which the studied problem is a generalisation: The opportunistic replacement problem, assuming components with a deterministic life time and The opportunistic replacement problem for components with a stochastic life time, for maintenance schemes without inspections

Condition based maintenance of trains doors

As part of the project DUST financed by Vinnova, we have investigated whether event data generated on trains can be used for finding evidence of wear on train doors. We have compared the event data and maintenance reports relating to doors of Regina trains. Although some interesting relations were found, the overall result is that the information in event data about wear of doors is very limited

Variants of an explicit kernel-split panel-based Nyström discretization scheme for Helmholtz boundary value problems

The incorporation of analytical kernel information is exploited in the construction of Nyström discretization schemes for integral equations modeling planar Helmholtz boundary value problems. Splittings of kernels and matrices, coarse and fine grids, high-order polynomial interpolation, product integration performed on the fly, and iterative solution are some of the numerical techniques used to seek rapid and stable convergence of computed fields in the entire computational domain

Exploring the Economics of Sustainable Energy : A Comparative Analysis of LCOE and System Costs for Nuclear and Offshore Wind Projects in Norway

This study explores the impact of input factor variability and the scope of analysis on profitability calculations for nuclear and offshore wind power in the Norwegian power market. The research employs several data sources and combines LCOE calculations and Monte Carlo simulations to assess the impact of uncertain factors on profitability estimations. Additionally, regression analyses assess the relationship between the share of the different power technologies and balancing volumes in a system. Additionally, a comprehensive discussion on system costs is included to encompass the system cost concept fully. The study's main findings include that the LCOE of offshore wind projects primarily relies on the discount rate and capacity factor. On the other hand, a potential SMR project would be impacted mainly by CAPEX and OPEX. Additionally, we find that LCOE has two significant limitations. First, the metric fails to account for the value of longevity in power production, which contradicts long-term supply and environmental objectives. Secondly, it does not count for system costs occurring beyond the scope of the project. This makes the validity and significance of the LCOE metric vary among different stakeholder groups. Another important finding is a significant but low correlation between the penetration of the different power sources and balancing volumes. While an increase in wind power penetration level is associated with an increase in imbalance volumes, the opposite effect is observed when studying the relationship with nuclear power. This could have important implications for the total costs of electricity production and suggests that a holistic approach is essential for informed decision-making regarding the future Norwegian energy mix.nhhma

Chapter Introduction

democracy; normative theory; political theory; public administration; public policy; policymakin

Numerical domination and herring migrations

There is accumulating evidence in favour of the hypothesis that herring migrations are influenced by social learning. The “adopted-migrant hypothesis” postulates that recruit spawning herring learn migration patterns by schooling with older individuals. However, this learning can be interrupted if the stock is unstable or if there are lack of overlap between recruits and the adult stock. There have been five reported changes in the location of the wintering area of Norwegian spring spawning (NSS) herring during the last 50 years. These changes co-occur with the recruitment of relatively strong year classes to the spawning stock. Simulations of schools containing naïve and experienced fish have shown that when abundant enough, naïve individuals repel guidance from a minority of experienced individuals. This process is referred to as numerical domination. We argue that numerical domination obstruct social learning from adults to recruits and plays a key role in establishing new wintering areas in NSS herring

Ensemble Neural Networks for Remaining Useful Life (RUL) Prediction

A core part of maintenance planning is a monitoring system that provides a good prognosis on health and degradation, often expressed as remaining useful life (RUL). Most of the current data-driven approaches for RUL prediction focus on single-point prediction. These point prediction approaches do not include the probabilistic nature of the failure. The few probabilistic approaches to date either include the aleatoric uncertainty (which originates from the system), or the epistemic uncertainty (which originates from the model parameters), or both simultaneously as a total uncertainty. Here, we propose ensemble neural networks for probabilistic RUL predictions which considers both uncertainties and decouples these two uncertainties. These decoupled uncertainties are vital in knowing and interpreting the confidence of the predictions. This method is tested on NASA's turbofan jet engine CMAPSS data-set. Our results show how these uncertainties can be modeled and how to disentangle the contribution of aleatoric and epistemic uncertainty. Additionally, our approach is evaluated on different metrics and compared against the current state-of-the-art methods.Comment: 6 pages, 2 figures, 2 tables, conference proceedin

Kompleksitetsreduktion i medier. Tillid, troværdighed og økologiske fødevarer

A literature review on media research in trust, credibility and organic food. The result of the review is an astonishing lack of research in the relation between construction of credibility and trust in the media in relation to organic food products. Research in media, food, trust and credibily is presented and discussed and the are for new research in the combination of the different fields is proposed as necessary and important