Gå til innhold
  • Send

  • Kategori

  • Sorter etter

  • Antall per side

Fant 9758 publikasjoner. Viser side 73 av 391:

Publikasjon  
År  
Kategori

Spatial distribution of short- and medium-chain chlorinated paraffins in European background air

Möckel, Claudia; Halvorsen, Helene Lunder; Pedersen, Lovise Skogeng; Krogseth, Ingjerd Sunde; Bohlin-Nizzetto, Pernilla; Borgen, Anders; Schlabach, Martin; Breivik, Knut

2018

Spatial distribution of residential wood combustion emissions in the Nordic countries: How well national inventories represent local emissions?

Paunu, Ville-Veikko; Karvosenoja, Niko; Segersson, David; Lopez-Aparicio, Susana; Nielsen, Ole-Kenneth; Plejdrup, Marlene S.; Thorsteinsson, Throstur; Niemi, Jarkko V; Vo, Dam Thanh; van der Gon, Hugo A.C. Denier; Brandt, Jørgen; Geels, Camilla

Elsevier

2021

Spatial distribution of polybrominated diphenyl ethers in trout from Norwegian lakes.

Mariussen, E.; Fjeld, E.; Strand-Andersen, M.; Hjerpset, M.; Schlabach, M.

2003

Spatial distribution of Dechlorane Plus and dechlorane related compounds in European background air

Skogeng, Lovise Pedersen; Halvorsen, Helene Lunder; Breivik, Knut; Eckhardt, Sabine; Herzke, Dorte; Möckel, Claudia; Krogseth, Ingjerd Sunde

The highly chlorinated chemical Dechlorane Plus (DP) was introduced as a replacement flame retardant for Mirex, which is banned through the Stockholm Convention (SC) for its toxicity (T), environmental persistence (P), potential for bioaccumulation (B) and long-range environmental transport potential (LRETP). Currently, Dechlorane Plus is under consideration for listing under the Stockholm Convention and by the European Chemical Agency as it is suspected to also have potential for P, B, T and LRET. Knowledge of atmospheric concentrations of chemicals in background regions is vital to understand their persistence and long-range atmospheric transport but such knowledge is still limited for Dechlorane Plus. Also, knowledge on environmental occurrence of the less described Dechlorane Related Compounds (DRCs), with similar properties and uses as Dechlorane Plus, is limited. Hence, the main objective of this study was to carry out a spatial mapping of atmospheric concentrations of Dechlorane Plus and Dechlorane Related Compounds at background sites in Europe. Polyurethane foam passive air samplers were deployed at 99 sites across 33 European countries for 3 months in summer 2016 and analyzed for dechloranes. The study showed that syn- and anti-DP are present across the European continent...

Frontiers Media S.A.

2023

Spatial distribution of dechlorane plus and analogs in European background air

Skogeng, Lovise Pedersen; Möckel, Claudia; Halvorsen, Helene Lunder; Krogseth, Ingjerd Sunde; Eckhardt, Sabine; Breivik, Knut

2020

Spatial distribution of cyclic volatile methyl siloxanes (cVMS) within the Norwegian Arctic. NILU F

Warner, N.A.; Evenset, A.; Christensen, G.; Gabrielsen, G.W.; Borgå, K.; Leknes, H.

2010

Spatial and temporal trends in e-waste related organic pollutants in a developing economy - A pilot study

Nipen, Maja; Vogt, Rolf David; Borgå, Katrine; Haarr, Ane; Mwakalapa, Eliezer Brown; Schlabach, Martin; Bohlin-Nizzetto, Pernilla; Mmochi, Aviti John; Breivik, Knut

2019

Spatial and seasonal variations of hexachlorocyclohexanes (HCHs) and hexachlorobenzene (HCB) in the Arctic atmosphere.

Su, Y.; Hung, H.; Blanchard, P.; Patton, G.W.; Kallenborn, R.; Konoplev, A.; Fellin, P.; Li, H.; Geen, C.; Stern, G.; Rosenberg, B.; Barrie, L.A.

2006

Sovereignty-Aware Intrusion Detection on Streaming Data: Automatic Machine Learning Pipeline and Semantic Reasoning

Chatterjee, Ayan; Gopalakrishnan, Sundar; Mondal, Ayan

Intrusion Detection Systems (IDS) are critical in safeguarding network infrastructures against malicious attacks. Traditional IDSs often struggle with knowledge representation, real-time detection, and accuracy, especially when dealing with high-throughput data. This paper proposes a novel IDS framework that leverages machine learning models, streaming data, and semantic knowledge representation to enhance intrusion detection accuracy and scalability. Additionally, the study incorporates the concept of Digital Sovereignty, ensuring that data control, security, and privacy are maintained according to national and regional regulations. The proposed system integrates Apache Kafka for real-time data processing, an automatic machine learning pipeline (e.g., Tree-based Pipeline Optimization Tool (TPOT)) for classifying network traffic, and OWL-based semantic reasoning for advanced threat detection. The proposed system, evaluated on NSL-KDD and CIC-IDS-2017 datasets, demonstrated qualitative outcomes such as local compliance, reduced data storage needs due to real-time processing, and improved adaptability to local data laws. Experimental results reveal significant improvements in detection accuracy, processing efficiency, and Sovereignty alignment.

Elsevier

2025

Sovereignty in Automated Stroke Prediction and Recommendation System with Explanations and Semantic Reasoning

Chatterjee, Ayan

Personalized approaches are required for stroke management due to the variability in symptoms, triggers, and patient characteristics. An innovative stroke recommendation system that integrates automatic predictive analysis with semantic knowledge to provide personalized recommendations for stroke management is proposed by this paper. Stroke exacerbation are predicted and the recommendations are enhanced by the system, which leverages automatic Tree-based Pipeline Optimization Tool (TPOT) and semantic knowledge represented in an OWL Ontology (StrokeOnto). Digital sovereignty is addressed by ensuring the secure and autonomous control over patient data, supporting data sovereignty and compliance with jurisdictional data privacy laws. Furthermore, classifications are explained with Local Interpretable Model-Agnostic Explanations (LIME) to identify feature importance. Tailored interventions based on individual patient profiles are provided by this conceptual model, aiming to improve stroke management. The proposed model has been verified using public stroke dataset, and the same dataset has been utilized to support ontology development and verification. In TPOT, the best Variance Threshold + DecisionTree Classifier pipeline has outperformed other supervised machine learning models with an accuracy of 95.2%, for the used datasets. The Variance Threshold method reduces feature dimensionality with variance below a specified threshold of 0.1 to enhance predictive accuracy. To implement and evaluate the proposed model in clinical settings, further development and validation with more diverse and robust datasets are required.

Elsevier

2025

South Durban Basin multi-point plan. Case study report. A Governance Information Publication, Series C, Book 12

Guastella, L.; Knudsen, S.

2007

South Asia Basins: LOICZ global change assessment and synthesis of river catchment - coastal sea interaction and human dimensions. LOICZ Reseach and Studies, 32

Ramesh, R.; Purvaja, R.; Lakshmi, A.; Newton, A.; Kremer, H.H.; Weichselgartner, J. (eds.)

2009

Publikasjon
År
Kategori