Now showing items 1-20 of 204

    • Securitising the Future: Dystopian Migration Discourses in Poland and the Czech Republic 

      Bartoszewicz, Monika Gabriela; Eibl, Otto; El Ghamari, Magdalena (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-06-09)
      This paper presents findings of a comparative study carried out in Poland and the Czech Republic, which analysed the societal attitudes towards migration and migrants in Europe. Our research shows that the reaction to migration in Poland and the Czech Republic constitutes a reversed (bottom up) securitisation. Moreover, contrary to the majority of security challenges where the immediate threats are ...
    • Noise-intensification data augmented machine learning for day-ahead wind power forecast 

      Chen, Hao; Birkelund, Yngve; Batalden, Bjørn-Morten; Barabadi, Abbas (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-06-10)
      The day-ahead wind power forecast is essential for the designation of dispatch schedules for the grid and rational arrangement for production planning by power generation companies. This paper specifically investigates the effect of adding noise to the original wind data for forecasting models. Linear regression, artificial neural networks, and adaptive boosting predictive models based on ...
    • Maritime safety and the ISM code: a study of investigated casualties and incidents 

      Batalden, Bjørn-Morten; Sydnes, Are K. (Journal article; Tidsskriftartikkel; Peer reviewed, 2013-08-27)
      Abstract In 1993, the International Maritime Organization adopted the International Safety Management (ISM) Code which requires all shipping companies operating certain types of vessels to establish safety management systems. Nevertheless, two decades later, maritime safety remains a concern. This article studies 94 maritime cases investigated by the Maritime Accident Investigation Branch in the ...
    • A Holistic View of Health Infrastructure Resilience before and after COVID-19 

      Barabadi, Abbas; Mohammad Hossein, Ghiasi; Qaranhasanlou, Ali Nouri; Adel, Mottahedi (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-04)
      Background: Large-scale events such as COVID-19 show that there are situations that can lead to huge stress on health infrastructure systems (HIS). The pandemic reveals that it is very difficult to protect HIS from all kinds of possible hazards. They can be unpredictable and spread rapidly; hence, it is hard to find an effective mitigation strategy to completely protect society and its important ...
    • Spare Part Management Considering Risk Factors 

      Barabadi, Reza; Ataei, Mohammad; Khalokakaie, Reza; Barabadi, Abbas; Nouri, ali (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-01-01)
      The spare parts provision is a complex process, which needs a precise model to analyze all factors with their possible effects on the required number of spare parts. The required number of spare parts for an item can be calculated based on its reliability performance. Various factors can influence the reliability characteristics of an item, including operational environment, maintenance policy, ...
    • The Effect of Risk Factors on the Resilience of Industrial Equipmen 

      Barabadi, Abbas; Nori, Ali; Mottahedi, Adel; Rahim Azar, Ali; Zamani, Ali (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-01-01)
      Recently, to evaluate the response of systems against disruptive events, the application of the resilience concept has been increased. Resilience depicts the system’s ability to return to its normal operational status after the disruption. Various studies in the field of engineering and non-engineering systems have only considered systems’ performance indicators to estimate resilience. Therefore, ...
    • Availability Importance Measure for Various Operation Condition 

      Barabadi, Abbas; Nouri, ali; Hazrati, Ali; Zamani, Ali; Mokhberdoran, Mehdi (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-01-01)
      The concept of availability importance measures can be used to identifying critical components from the availability performance point of view. The availability of an item depends on the combined aspects of its reliability and maintainability performance indices. These indices are considerably affected by operational and environmental conditions such as; ambient temperature, precipitation, wind, ...
    • Industrial Equipment’s Throughput Capacity Analysis 

      Barabadi, Abbas; Nouri, ali; Hazrati, Ali; Khodayari, Aliasqar; Mokhberdoran, Mahdi (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-01-01)
      Throughput capacity (TC) is defined as the total amount of material processed or produced by the system in the given time. In practice, full capacity performance for industrial equipment is impossible because the failures are affected and cause a reduction. Therefore, failure interruptions, especially critical ones (bottlenecks), must be detected and considered in production management. From the ...
    • Development and Validation of a Safety Leadership Self-Efficacy Scale (SLSES) in Maritime Context 

      Kim, Tae-Eun; Sydnes, Are K.; Batalden, Bjørn-Morten Erdal (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-10-21)
      Extensive studies have highlighted the importance of leadership on safety in the maritime industry. However, current research lacks empirically tested theoretical models with valid and reliable scales for describing and measuring safety leadership in ship operations. This study reports the development and validation process of the first Safety Leadership Self-Efficacy Scale (SLSES) for assessing ...
    • Decomposing the Prediction Problem; Autonomous Navigation by neoRL Agents 

      Leikanger, Per Roald (Journal article; Tidsskriftartikkel, 2021-07-19)
      Navigating the world is a fundamental ability for any living entity. Accomplishing the same degree of freedom in technology has proven to be difficult. The brain is the only known mechanism capable of voluntary navigation, making neuroscience our best source of inspiration toward autonomy. Assuming that state representation is key, we explore the difference in how the brain and the machine represent ...
    • Finnmark Platform Composite Tectono-Sedimentary Element, Barents Sea 

      Henriksen, Erik; Ktenas, Dimitrios; Nielsen, Jesper Kresten (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-16)
      The Finnmark Platform Composite Tectono-Sedimentary Element (CTSE), located in the southern Barents Sea, is a northward-dipping monoclinal structural unit. It covers most of the southern Norwegian Barents Sea where it borders the Norwegian mainland. Except for the different age of basement, the CTSE extends eastwards into the Kola Monocline on the Russian part of the Barents Sea. <p> <p>The general ...
    • Criteria-Based Fuzzy Logic Risk Analysis of Wind Farms Operation in Cold Climate Regions 

      Barabadi, Abbas; Mustafa, Albara M. (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-02-12)
      Different risks are associated with the operation and maintenance of wind farms in cold climate regions, mainly due to the harsh weather conditions that wind farms experience in that region such as the (i) increased stoppage rate of wind turbines due to harsh weather conditions, (ii) limited accessibility to wind farms due to snow cover on roads, and (iii) cold stress to workers at wind farms. In ...
    • Comparative study of data-driven short-term wind power forecasting approaches for the Norwegian Arctic region 

      Chen, Hao; Birkelund, Yngve; Anfinsen, Stian Normann; Yuan, Fuqing (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-04-26)
      This paper conducts a systemic comparative study on univariate and multivariate wind power forecasting for five wind farms inside the Arctic area. The development of wind power in the Arctic can help reduce greenhouse gas emissions in this environmentally fragile region. In practice, wind power forecasting is essential to maintain the grid balance and optimize electricity generation. This study first ...
    • Numerical investigation on the cage-to-cage wake effect: A case study of a 4 × 2 cage array 

      Sim, Jaesub; Cheng, Hui; Aarsæther, Karl Gunnar; Li, Lin; Ong, Muk Chen (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-02-12)
      Aquaculture has been the world’s fastest-growing food producing method and grown to become the second-largest export industry in Norway during the past 40 years. Usually, the high-value fish such as Atlantic Salmon (<i>Salmo salar</i>) is raised in a multi-cage fish farm, where the flow interactions between fish cages exist. In this study, the interactions between fish cages are implemented into the ...
    • Challenges Associated with Creeping Disasters in Disaster Risk Science and Practice: Considering Disaster Onset Dynamics 

      Staupe-Delgado, Reidar; Rubin, Olivier (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-01-12)
      In this article, we set out to reconcile a general conceptualization of disaster temporalities by drawing on the epitome example of a creeping disaster, namely famine. Our argument is driven by the recognition that slowly manifesting disaster impacts pose distinct challenges for decision makers and researchers while there is a tendency for the disaster literature to overlook the role of disaster ...
    • Exploiting more robust and efficacious deep learning techniques for modeling wind power with speed 

      Chen, Hao; Staupe-Delgado, Reidar (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-11-27)
      Abstract Sound analyses of the nonlinear relationship between wind speed and power generation are crucial for the advancement of wind energy optimization. As an emerging artificial intelligence technology, deep learning has received growing attention from energy researchers for its outstanding ability to provide complex mappings. However, deep neural networks involve complex configurations, ...
    • Drawing lessons from the COVID-19 pandemic: Seven obstacles to learning from public inquiries in the wake of the crisis 

      Eriksson, Kerstin; Staupe-Delgado, Reidar; Holst, Jørgen (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-09-13)
      On March 11, 2020, the World Health Organization declared the emerging COVID-19 threat a pandemic following the global spread of the virus. A year later, a number of governments are being handed the concluding reports of national public inquiries tasked with investigating responses, mishaps, and identifying lessons for the future. The present article aims to identify a set of learning obstacles that ...
    • Observed and unobserved heterogeneity in failure data analysis 

      Zaki, Rezgar; Barabadi, Abbas; Barabady, Javad; Qarahasanlou, Ali Nouri (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-06-08)
      In reality, failure data are often collected under diffract operational conditions (covariates), leading to heterogeneity among the data. Heterogeneity can be classified as observed and unobserved heterogeneity. Un-observed heterogeneity is the effect of unknown, unrecorded, or missing covariates. In most reliability studies, the effect of unobserved covariates is neglected. This may lead to inaccurate ...
    • Performance Quantification of Icebreaker Operations in Ice Management by Numerical Simulations 

      Bjørnø, Jon; Skjetne, Roger; van den Berg, Marnix; Lu, Wenjun; Lubbad, Raed; Løset, Sveinung (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-11-15)
      The paper addresses the problem of quantifying and assessing the effectiveness of icebreaker operations in ice management (IM) using a high-fidelity simulator. The numerical model includes an accurate geometric representation of an icebreaker, a cylindrical protected structure, and a synthetic ice environment. A set of key performance indicators (KPIs) are defined and proposed to quantify the ...
    • An Evaluation on Diverse Machine Learning Algorithms for Hourly Univariate Wind Power Prediction in the Arctic 

      Chen, Hao; Birkelund, Yngve (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-12-23)
      Wind power forecasting is crucial for wind power systems, grid load balance, maintenance, and grid operation optimization. The utilization of wind energy in the Arctic regions helps reduce greenhouse gas emissions in this environmentally vulnerable area. In the present study, eight various models, seven of which are representative machine learning algorithms, are used to make 1, 2, and 3 step ...