Computing Curves Bounding Trigonometric Planar Maps: Symbolic and Hybrid Methods

2006 ◽  
pp. 70-91 ◽  
Author(s):  
Daniel Lichtblau
Keyword(s):  
Hybrid Methods ◽  
Planar Maps

Computational Property of Hybrid Methods with PSO and DE

2012 ◽  
Vol 132 (7) ◽  
pp. 1128-1135
Author(s):  
Kenichi Muranaka ◽  
Eitaro Aiyoshi
Keyword(s):  
Hybrid Methods ◽  
Computational Property

Classification of methods for generating pseudo-CT from MRI images for MRI-alone RT

2017 ◽  
Vol 1 (3) ◽  
pp. 54
Author(s):  
BOUKELLOUZ Wafa ◽  
MOUSSAOUI Abdelouahab
Keyword(s):  
Performance Metrics ◽  
Radiation Treatment ◽  
Hybrid Methods ◽  
Dose Calculation ◽  
Absolute Error ◽  
Ct Images ◽  
General Technique ◽  
Therapy Field ◽  
The Brain

Background: Since the last decades, research have been oriented towards an MRI-alone radiation treatment planning (RTP), where MRI is used as the primary modality for imaging, delineation and dose calculation by assigning to it the needed electron density (ED) information. The idea is to create a computed tomography (CT) image or so-called pseudo-CT from MRI data. In this paper, we review and classify methods for creating pseudo-CT images from MRI data. Each class of methods is explained and a group of works in the literature is presented in detail with statistical performance. We discuss the advantages, drawbacks and limitations of each class of methods. Methods: We classified most recent works in deriving a pseudo-CT from MR images into four classes: segmentation-based, intensity-based, atlas-based and hybrid methods. We based the classification on the general technique applied in the approach. Results: Most of research focused on the brain and the pelvis regions. The mean absolute error (MAE) ranged from 80 HU to 137 HU and from 36.4 HU to 74 HU for the brain and pelvis, respectively. In addition, an interest in the Dixon MR sequence is increasing since it has the advantage of producing multiple contrast images with a single acquisition. Conclusion: Radiation therapy field is emerging towards the generalization of MRI-only RT thanks to the advances in techniques for generation of pseudo-CT images. However, a benchmark is needed to set in common performance metrics to assess the quality of the generated pseudo-CT and judge on the efficiency of a certain method.

scholarly journals Strengthening the EU’s resilience to hybrid threats

European View ◽  
2021 ◽  
pp. 178168582110046
Author(s):  
Sandra Kalniete ◽  
Tomass Pildegovičs
Keyword(s):  
Case Studies ◽  
Presidential Election ◽  
Turning Point ◽  
Hybrid Methods ◽  
Cyber Attacks ◽  
Political Will ◽  
Member States ◽  
Eu Member States ◽  
Us Presidential Election ◽  
Hybrid Threats

Against the backdrop of the deterioration of EU–Russia relations in recent years, there has been a shift in the awareness of hybrid threats all across the Union. At the same time, there is evidence of a growing political will to strengthen resilience to these threats. While hostile foreign actors have long deployed hybrid methods to target Europe, Russia’s intervention in Ukraine in 2014, interference in the 2016 US presidential election, and repeated cyber-attacks and disinformation campaigns aimed at EU member states have marked a turning point, exposing Western countries’ unpreparedness and vulnerability to these threats. This article analyses the EU’s resilience to hybrid warfare from institutional, regulatory and societal perspectives, with a particular focus on the information space. By drawing on case studies from member states historically at the forefront of resisting and countering Russian-backed disinformation campaigns, this article outlines the case for a whole-of-society approach to countering hybrid threats and underscores the need for EU leadership in a standard-setting capacity.

The Application of Multicriteria Decision Analysis Methods in Health Care: A Literature Review

2021 ◽  
pp. 0272989X2110190
Author(s):  
Ilyas Khan ◽  
Liliane Pintelon ◽  
Harry Martin
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Decision Analysis ◽  
Medical Devices ◽  
Hybrid Methods ◽  
Multicriteria Decision Analysis ◽  
Multicriteria Decision ◽  
Health Care Decision ◽  
Wide Range ◽  
Care Decision

Objectives The main objectives of this article are 2-fold. First, we explore the application of multicriteria decision analysis (MCDA) methods in different areas of health care, particularly the adoption of various MCDA methods across health care decision making problems. Second, we report on the publication trends on the application of MCDA methods in health care. Method PubMed was searched for literature from 1960 to 2019 in the English language. A wide range of keywords was used to retrieve relevant studies. The literature search was performed in September 2019. Articles were included only if they have reported an MCDA case in health care. Results and Conclusion The search yielded 8,318 abstracts, of which 158 fulfilled the inclusion criteria and were considered for further analysis. Hybrid methods are the most widely used methods in health care decision making problems. When it comes to single methods, analytic hierarchy process (AHP) is the most widely used method followed by TOPSIS (technique for order preference by similarity to ideal solution), multiattribute utility theory, goal programming, EVIDEM (evidence and value: impact on decision making), evidential reasoning, discrete choice experiment, and so on. Interestingly, the usage of hybrid methods has been high in recent years. AHP is most widely applied in screening and diagnosing and followed by treatment, medical devices, resource allocation, and so on. Furthermore, treatment, screening and diagnosing, medical devices, and drug development and assessment got more attention in the MCDA context. It is indicated that the application of MCDA methods to health care decision making problem is determined by the nature and complexity of the health care problem. However, guidelines and tools exist that assist in the selection of an MCDA method.

scholarly journals Identification of an Obesogenic Dietary Pattern Using Partial Least Squares in a Nationally-Representative Sample of Canadian Adults

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 552-552
Author(s):  
Alena Ng ◽  
Mahsa Jessri ◽  
Mary L'Abbé
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Dietary Pattern ◽  
Fast Food ◽  
Representative Sample ◽  
Hybrid Methods ◽  
Nutritional Epidemiology ◽  
Obesogenic Diet ◽  
Dietary Components ◽  
Nationally Representative

Abstract Objectives Hybrid methods of dietary patterns analysis have emerged as a unique and informative way to study diet-disease relationships in nutritional epidemiology research. The objectives of this research were to identify an obesogenic dietary pattern using weighted PLS in nationally-representative Canadian survey data, and to identify key foods and/or beverages associated with the defined obesogenic pattern. Methods Data from one 24-hr dietary recall data from the cross-sectional Canadian Community Health Survey-Nutrition (CCHS) 2015 (n = 12,110 adults) were used. Weighed partial least squares (wPLS) was used to identify an obesogenic dietary pattern from 40 standardized food and/or beverage categories using the variables energy density, fibre density, and total fat as outcomes. The association between the derived dietary pattern and likelihood of obesity was examined using weighted multivariate logistic regression. Key dietary components highly associated with the derived pattern were identified. Results Compared to quartile one (i.e., those least adherent to an obesogenic dietary pattern), those in quartile four had a 2.40-fold increased odds of being obese (OR = 2.40, 95% CI = 1.91, 3.02, P-trend < 0.0001) with a monotonically increasing trend. Using a factor loading significance cut-off of ≥|0.17|, three food/beverage categories loaded positively for the derived obesogenic dietary pattern: fast food, carbonated drinks and salty snacks. Seven food/beverage categories loaded negatively (i.e., in the protective direction): consumption of whole fruits, orange vegetables, “other” vegetables (including vegetable juice), whole grains, dark green vegetables, legumes and soy, and pasta and rice. Conclusions This study pinpoints key dietary components that are associated with obesity and consumed among a nationally-representative sample of Canadians adults. Compared to a similarly-defined obesogenic diet identified by our research group in 2004, the top contributors to a Canadian-specific obesogenic diet in 2015 have remained consistent. This evidence may aid in developing targeted policies and dietary interventions for obesity and chronic disease prevention. Funding Sources Supported by grants from the Burroughs Wellcome Fund Innovation in Regulatory Science Award and the Canadian Institutes of Health Research.

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