• Accident Prediction Model Using Machine Learning. Accuracy of Predicted Model 

      Sohel, Mohammed Abdul (Master thesis; Mastergradsoppgave, 2021-06-22)
      Logistic regression is a predictive model machine learning algorithm that displays the results in a binary form, mostly used in prediction multivariable and as an advanced version of linear regression, here we used to predict the accuracy of our model. Current accident prediction model in Norway is Tusi is a risk based model used in predicting tunnel accidents but it has some problems and loose ends ...
    • Active Infrared Observation for Ice Detection in Anti/De-Icing Systems for Marine Applications in Arctic Region 

      Rashid, Taimur; Khawaja, Hassan Abbas (Conference object; Konferansebidrag, 2016-12-08)
      The number of shipping operations is on the rise in the Arctic region. As a result of these increased activities, significant challenges are being encountered with respect to safety and reliability. One of the challenges is an accretion of ice. The icing on ships and offshore structures is caused by atmospheric sources and sea spray. The sea spray is the main source of icing and is generated by the ...
    • Active learning for enhanced understanding of "ship damage stability" 

      Johansen, Kåre; Batalden, Bjørn-Morten (Journal article; Tidsskriftsartikkel, 2018)
      Active Learning has always played an important part of seamen’s education. Transfer of experience have from ancient time been practiced in an active learner-centered field where unexperienced seamen got involved in their own learning by being supervised by experienced seamen, when practicing seaman related activities. This learning practice was supreme before the introduction of “modern” maritime ...
    • Advanced Data Analytics towards Energy Efficient and Emission Reduction Retrofit Technology Integration in Shipping 

      Perera, Lokukaluge Prasad; Ventikos, N P; Rolfsen, Sven; Öster, Anders (Chapter; Bokkapittel, 2021)
      An overview of integrating two energy efficient and emission reduction technologies to improve ship energy efficiency under advanced data analytics is presented in this study. The proposed technologies consist of developing engine and propulsion innovations that will be experimented under laboratory conditions and large-model-scale sea trials, respectively. These experiments will collect large ...
    • Advanced data cluster analyses in digital twin development for marine engines towards ship performance quantification 

      Taghavi, Mahmood; Perera, Lokukaluge Prasad Channa (Journal article; Tidsskriftartikkel; Peer reviewed, 2024-02-24)
      Due to the growing rate of energy consumption, it is necessary to develop frameworks for enhancing ship energy efficiency. This paper proposes a solution for this issue by introducing a digital twin framework for quantifying ship performance. For this purpose, extensive low-level clustering is performed using Gaussian Mixture Models (GMM) with the Expectation Maximization algorithm on a dataset ...
    • Adventure-based cruise tourism and emergency response -training for increased polar-water emergency management competence 

      Sætren, Gunhild Birgitte; Stenhammer, Hege Christin; Andreassen, Natalia; Borch, Odd Jarl (Conference object; Konferansebidrag, 2021-11)
      Nature-based tourism has increased significantly in recent years. The special segment adventure travel has doubled in size, from 10 to 20 percent of the international tourism market. This type of tourism is characterized by visiting remote and spectacular areas, and uniqueness. One of the most popular type of adventure based travel is so-called expedition cruise. The number of cruise vessels is ...
    • Against the Trend-An tentative Data Analysis Method using Classical Regression against Machine Learning Approach 

      Yuan, Fuqing; Lu, Jinmei (Journal article; Tidsskriftartikkel, 2019)
      The machine learning approach is a new hot topic in recent years that are widely used in different sections, including industries, economy, disaster prediction and politics. After decades’ of development, the available machine learning algorithms are numerous and diverse. Traditional methods such as regression, classical statistical methods, are unfortunately laid aside as non-mainstream. This paper ...
    • The Agreement on Cooperation on Marine Oil Pollution Preparedness and Response in the Arctic 

      Rise, Ingvild Hoel (Master thesis; Mastergradsoppgave, 2014-06-01)
      This is a case study of the establishment of an oil spill response regime in the Arctic region. The context is the work of the Arctic Council and the development of the Agreement on Cooperation on Marine Oil Pollution Preparedness and Response in the Arctic. Three research topics are studied; regime, response system and the role of politics and professions. The Arctic oil spill response agreement ...
    • Airmanship - A qualitative approach 

      Nergård, Vegard (Journal article; Tidsskriftartikkel; Peer reviewed, 2014-10)
      The purpose of this study was to investigate how pilots themselves characterize a good pilot and airmanship, and how safety is created by the practice of knowledge. The purpose of this study was to get the insiders’ understanding of the concept of airmanship. Results indicate that the formulation of the concept of airmanship is complex, and it is first and foremost comprised of the knowledge about ...
    • An AIS-based deep learning framework for regional ship behavior prediction 

      Murray, Brian; Perera, Lokukaluge Prasad (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-05-27)
      This study presents a deep learning framework to support regional ship behavior prediction using historical AIS data. The framework is meant to aid in proactive collision avoidance, in order to enhance the safety of maritime transportation systems. In this study, it is suggested to decompose the historical ship behavior in a given geographical region into clusters. Each cluster will contain trajectories ...
    • An AIS-Based Multiple Trajectory Prediction Approach for Collision Avoidance in Future Vessels 

      Murray, Brian; Perera, Lokukaluge Prasad (Peer reviewed; Bok; Chapter, 2019-11-11)
      This study presents a method to predict the future trajectory of a target vessel using historical AIS data. The purpose of such a prediction is to aid in collision avoidance in future vessels. The method presented in this study extracts all trajectories present in an initial cluster centered about a vessel position. Features for each trajectory are then generated using Principle Component Analysis ...
    • Alt er sukret med risiko. Bruk av risikostyringsteori ved utforming av endringsforslag som berører akuttkirurgi i Nasjonal Helse- og Sykehusplan 

      Tellefsen, Jon Iver Eira (Master thesis; Mastergradsoppgave, 2016-12-17)
      Oppgaven tar for seg utfordringer i helsevesenet tilknyttet risikostyring. Det skal foretas en gjennomgang av plan- og beslutningsprosessene rundt stortingsmeldingen Nasjonal Helse- og Sykehusplan (2016-2019), for å se nærmere på hvordan prosessene har ført til den foreslåtte omorganiseringen. Sentralisering av akuttkirurgi vil være oppgavens case. Oppgavens problemstilling er: I hvilken grad er de ...
    • Ambient air quality and the effects of air pollutants on otolaryngology in Beijing 

      Zhang, Fengying; Xu, Jin; Zhang, Ziying; Meng, Haiying; Wang, Li; Lu, Jinmei; Wang, Wuyi; Kraft, Thomas (Journal article; Tidsskriftartikkel; Peer reviewed, 2015-07-09)
      Abstract To investigate temporal patterns, pollution concentrations and the health effects of air pollutants in Beijing we carried out time-series analyses on daily concentrations of ambient air pollutants and daily numbers of outpatient visits for otolaryngology over 2 years (2011– 2012) to identify possible health effects of air pollutants. The results showed that PM10 was the major air ...
    • Analysis of potential critical equipment and technical system on a modern PSV. Recommending a method for Troms Offshore Management AS 

      Løvmo, Signy Anita (Master thesis; Mastergradsoppgave, 2016-06-01)
      This thesis is a part of a master’s degree in Technology and Safety in the High North at the University of Tromsø- The Arctic University of Norway. The thesis has been written during the spring semester of 2016. Safety is a large part of maritime operations and all tools to improve safety and reliability is considered. Even in these days when economy in the oil related industry is worse than ever. ...
    • Analysis of the impact of deploying thermal protective immersion suits on evacuation time for passenger ships operating in polar waters 

      Azizpour, Hooshyar; Galea, Edwin R.; Deere, Steven; Erland, Sveinung; Batalden, Bjørn-Morten; Oltedal, Helle Asgjerd (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-06-22)
      For passenger vessels operating in polar waters, the Polar Code requires that in case of possibility of immersion in polar waters, thermal protective immersion suits (TPIS) should be available for all passengers. Thus, international standards require that TPIS can be donned within 2 min and that walking speeds are reduced by no more than 25%. Clearlythese requirements are arbitrary and do not ...
    • Analytical and Case Studies of a Sandwich Structure using Euler-Bernoulli Beam Equation 

      Xue, Hui; Khawaja, Hassan Abbas (Journal article; Tidsskriftartikkel; Peer reviewed, 2016-11)
      This paper presents analytical and case studies of sandwich structures. In this study, the Euler-Bernoulli beam equation is solved analytically for a four-point bending problem. Appropriate initial and boundary conditions are specified to enclose the problem. In addition, the balance coefficient is calculated and the Rule of Mixtures is applied. The focus of this study is to determine the effective ...
    • Analytical Study of Sandwich Structures using Euler–Bernoulli Beam Equation 

      Xue, Hui; Khawaja, Hassan Abbas (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-01)
      This paper presents an analytical study of sandwich structures. In this study, the Euler–Bernoulli beam equation is solved analytically for a four-point bending problem. Appropriate initial and boundary conditions are specified to enclose the problem. In addition, the balance coefficient is calculated and the Rule of Mixtures is applied. The focus of this study is to determine the effective material ...
    • Anomaly Detection for Environmental Data Using Machine Learning Regression 

      Yuan, Fuqing; Lu, Jinmei (Journal article; Peer reviewed, 2018)
      Environmental data exhibits as huge amount and complex dependency. Utilizing these data to detect anomaly is beneficial to the disaster prevention. Big data approach using the machine learning method has the advantage not requiring the geophysical and geochemical knowledge to detect anomaly. This paper using the popular support vector regression (SVR ) to model the correlation between factors. ...
    • Antimikrobiell resistens, en unnselig krise 

      Johansen, Margareth (Master thesis; Mastergradsoppgave, 2023-06-02)
      Man ser en økning i antimikrobiell resistens (AMR), og ifølge en global kartlegging, vil inntil ti millioner mennesker kunne dø av antimikrobiell resistens hvert år innen 2050. Denne økningen skyldes feilbruk og overforbruk i sektorer der midlene anvendes. Samfunn er avhengig av antimikrobielle midler, og ulempene som medfølger bruken (resistens) får lite oppmerksomhet. Utvikling og økning ...
    • Applicability Extent of 2-D Heat Equation for Numerical Analysis of a Multiphysics Problem 

      Khawaja, Hassan Abbas (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-01)
      This work focuses on thermal problems, solvable using the heat equation. The fundamental question being answered here is: what are the limits of the dimensions that will allow a 3-D thermal problem to be accurately modelled using a 2-D Heat Equation? The presented work solves 2-D and 3-D heat equations using the Finite Difference Method, also known as the Forward-Time Central-Space (FTCS) method, ...