scholarly journals Editorial: State of the Art CT and Image Quality, Radiation and Contrast Dose

Dose-Response ◽  
2021 ◽  
Vol 19 (4) ◽  
pp. 155932582110568
Author(s):  
Carlo Cavaliere
Keyword(s):  
Image Quality ◽  
State Of The Art ◽  
Point Of View ◽  
Contrast Dose ◽  
Research Fields ◽  
Iodinated Contrast ◽  
Improve Patient Management ◽  
Manufacturing Technologies ◽  
New Research ◽  
Technological Improvements

A special issue of the journal Dose-Response entitled “State of the Art CT and Image Quality, Radiation and Contrast Dose” is proposed. Technological improvements on CT scanners have the potentiality to reduce the issues related to ionizing radiation administration, opening new insights toward innovative applications also thanks to the contamination of other research fields like artificial intelligence algorithms and additive manufacturing technologies. In order to approach these new research directions, a multidisciplinary team becomes needed, overcoming the clinical and radiological point of view and enriching the workflow with different contributes. The real weight of these afferents on patient’s management remains to be assessed and characterized. The main topics will be related to innovative CT applications able to improve patient management and treatment assessment and reduce patients risks due to radiation exposure and iodinated contrast injection.

scholarly journals Deep Learning for Historical Document Analysis and Recognition—A Survey

2020 ◽  
Vol 6 (10) ◽  
pp. 110
Author(s):  
Francesco Lombardi ◽  
Simone Marinai
Keyword(s):  
Deep Learning ◽  
State Of The Art ◽  
Point Of View ◽  
Historical Documents ◽  
Learning Approaches ◽  
Historical Document ◽  
Research Directions ◽  
Research Fields ◽  
Definition Of ◽  
Novel Applications

Nowadays, deep learning methods are employed in a broad range of research fields. The analysis and recognition of historical documents, as we survey in this work, is not an exception. Our study analyzes the papers published in the last few years on this topic from different perspectives: we first provide a pragmatic definition of historical documents from the point of view of the research in the area, then we look at the various sub-tasks addressed in this research. Guided by these tasks, we go through the different input-output relations that are expected from the used deep learning approaches and therefore we accordingly describe the most used models. We also discuss research datasets published in the field and their applications. This analysis shows that the latest research is a leap forward since it is not the simple use of recently proposed algorithms to previous problems, but novel tasks and novel applications of state of the art methods are now considered. Rather than just providing a conclusive picture of the current research in the topic we lastly suggest some potential future trends that can represent a stimulus for innovative research directions.

Towards a Legal Turn in the Ethics of Immigration

2017 ◽  
Vol 4 (1) ◽  
pp. 31-55 ◽  
Author(s):  
Johan Rochel
Keyword(s):  
Point Of View ◽  
Immigration Law ◽  
Research Fields ◽  
Ethical Debate ◽  
Law And Ethics ◽  
Normative Practice ◽  
Principle Of Proportionality ◽  
New Research ◽  
Promising Development ◽  
Migration Law

This contribution presents the case for a ‘legal turn’ in the ethical debate on immigration. The legal turn is an invitation directed mainly at philosophers to take law as a normative practice seriously, to draw upon the normative resources which it entails and to look for cooperation opportunities with legal scholars. In the continuation of the debates on the ethics of immigration, this legal turn represents an important opportunity for philosophy to gain more relevance in the legal and political realms by affirming its capacity to inspire and guide concrete legal evolutions. This piece proposes both a methodological argument on how to make room for the contributions made by ethical theory within a legal argument and an exemplification of this innovative approach as a way to uncover new research fields for both immigration law and ethics. This legal turn represents a promising development of the consistency-based approach used widely by philosophers arguing from the point of view of liberal and democratic values and highlighting inconsistency in immigration policy. The legal turn pleads for a new locus for ethical investigation (namely immigration law) and proposes a methodology labelled as a ‘normative reflexive dialogue’. The potential of this dialogue will be exemplified through the principle of proportionality, a decisive principle for migration law and ethics.

Dosimetry and optimization in digital radiography based on the contrast-detail resolution

2018 ◽  
Vol 6 (3) ◽  
Author(s):  
Wilson Otto Gomes Batista ◽  
Alexandre Gomes De Carvalho
Keyword(s):  
Image Quality ◽  
Inverse Image ◽  
Point Of View ◽  
Complete Analysis ◽  
Portable Devices ◽  
Evaluation Tool ◽  
Air Kerma ◽  
Direct Radiography ◽  
Definition Of ◽  
Entrance Surface Air Kerma

Contrast-detail (C-D) curves are useful in evaluating the radiographic image quality in a global way. The objective of the present study was to obtain the C-D curves and the inverse image quality figure. Both of these parameters were used as an evaluation tool for abdominal and chest imaging protocols. The C-D curves were obtained with the phantom CDRAD 2.0 in computerized radiography and the direct radiography systems (including portable devices). The protocols were 90 and 102 kV in the range of 2 to 20 mAs for the chest and 80 kV in the range of 10 to 80 mAs for the abdomen. The incident air kerma values were evaluated with a solid state sensor. The analysis of these C-D curves help to identify which technique would allow a lower value of the entrance surface air kerma, Ke, while maintaining the image quality from the point of view of C-D detectability. The results showed that the inverse image quality figure, IQFinv, varied little throughout the range of mAs, while the value of Ke varied linearly directly with the mAs values. Also, the complete analysis of the curves indicated that there was an increase in the definition of the details with increasing mAs. It can be concluded that, in the transition phase for the use of the new receptors, it is necessary to evaluate and adjust the practised protocols to ensure, at a minimum, the same levels of the image quality, taking into account the aspects of the radiation protection of the patient.

Judicial geography as a legal science and academic discipline

2019 ◽  
Vol 5 (4) ◽  
pp. 122-137
Author(s):  
Almaz F. Abdulvaliev
Keyword(s):  
Criminal Law ◽  
Climatic Factors ◽  
Academic Discipline ◽  
Preliminary Investigation ◽  
Criminal Procedure ◽  
Mapping Method ◽  
Research Field ◽  
Point Of View ◽  
Theoretical Development ◽  
New Research

This article presents the conceptual foundations for the formation of a new research field “Judicial Geography”, including the prerequisites for its creation, academic, and theoretical development, both in Russia and abroad. The purpose of the study is to study the possibility of applying geographical methods and means in criminal law, criminal procedure, and in judicial activity in general via the academic direction “Judicial Geography”. The author describes in detail the main elements of judicial geography and its role and significance for such legal sciences, as criminal law, criminal procedure, criminalistics, and criminology among others. The employed research methods allow showing the main vectors of the development of judicial geography, taking into account the previous achievements of Russian and worldwide academics. The author indicates the role and place of judicial geography in the system of legal sciences. This study suggests a concept of using scientific geographical methods in the study of various legal phenomena of a criminal and criminal-procedural nature when considering the idea of building judicial bodies and judicial instances, taking into account geographical and climatic factors. In this regard, the author advises to introduce the special course “Judicial Geography”, which would allow law students to study the specifics of the activities of the judiciary and preliminary investigation authorities from a geographical point of view, as well as to use various geographical methods, including the mapping method, in educational and practical activities. The author concludes that forensic geography may become a new milestone for subsequent scientific research in geography and jurisprudence.

scholarly journals Advances in the Application of Machine Learning Techniques for Power System Analytics: A Survey

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4776
Author(s):  
Seyed Mahdi Miraftabzadeh ◽  
Michela Longo ◽  
Federica Foiadelli ◽  
Marco Pasetti ◽  
Raul Igual
Keyword(s):  
Machine Learning ◽  
Power Systems ◽  
Smart Grids ◽  
State Of The Art ◽  
Smart Cities ◽  
Power Grids ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
New Research ◽  
Traditional Approaches

The recent advances in computing technologies and the increasing availability of large amounts of data in smart grids and smart cities are generating new research opportunities in the application of Machine Learning (ML) for improving the observability and efficiency of modern power grids. However, as the number and diversity of ML techniques increase, questions arise about their performance and applicability, and on the most suitable ML method depending on the specific application. Trying to answer these questions, this manuscript presents a systematic review of the state-of-the-art studies implementing ML techniques in the context of power systems, with a specific focus on the analysis of power flows, power quality, photovoltaic systems, intelligent transportation, and load forecasting. The survey investigates, for each of the selected topics, the most recent and promising ML techniques proposed by the literature, by highlighting their main characteristics and relevant results. The review revealed that, when compared to traditional approaches, ML algorithms can handle massive quantities of data with high dimensionality, by allowing the identification of hidden characteristics of (even) complex systems. In particular, even though very different techniques can be used for each application, hybrid models generally show better performances when compared to single ML-based models.

scholarly journals The Metano Modeling Toolbox MMTB: An Intuitive, Web-Based Toolbox Introduced by Two Use Cases

Metabolites ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 113
Author(s):  
Julia Koblitz ◽  
Sabine Will ◽  
S. Riemer ◽  
Thomas Ulas ◽  
Meina Neumann-Schaal ◽  
...  
Keyword(s):  
Metabolic Networks ◽  
Point Of View ◽  
Use Cases ◽  
Mathematical Methods ◽  
State Behavior ◽  
Web Based ◽  
Research Fields ◽  
Balance Analysis ◽  
Metabolic Models ◽  
User Friendly

Genome-scale metabolic models are of high interest in a number of different research fields. Flux balance analysis (FBA) and other mathematical methods allow the prediction of the steady-state behavior of metabolic networks under different environmental conditions. However, many existing applications for flux optimizations do not provide a metabolite-centric view on fluxes. Metano is a standalone, open-source toolbox for the analysis and refinement of metabolic models. While flux distributions in metabolic networks are predominantly analyzed from a reaction-centric point of view, the Metano methods of split-ratio analysis and metabolite flux minimization also allow a metabolite-centric view on flux distributions. In addition, we present MMTB (Metano Modeling Toolbox), a web-based toolbox for metabolic modeling including a user-friendly interface to Metano methods. MMTB assists during bottom-up construction of metabolic models by integrating reaction and enzymatic annotation data from different databases. Furthermore, MMTB is especially designed for non-experienced users by providing an intuitive interface to the most commonly used modeling methods and offering novel visualizations. Additionally, MMTB allows users to upload their models, which can in turn be explored and analyzed by the community. We introduce MMTB by two use cases, involving a published model of Corynebacterium glutamicum and a newly created model of Phaeobacter inhibens.

scholarly journals Light Field Image Quality Enhancement by a Lightweight Deformable Deep Learning Framework for Intelligent Transportation Systems

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1136
Author(s):  
David Augusto Ribeiro ◽  
Juan Casavílca Silva ◽  
Renata Lopes Rosa ◽  
Muhammad Saadi ◽  
Shahid Mumtaz ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Intelligent Transportation Systems ◽  
Light Field ◽  
State Of The Art ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Machine Learning Algorithms ◽  
Learning Framework ◽  
Reconstruction Methods

Light field (LF) imaging has multi-view properties that help to create many applications that include auto-refocusing, depth estimation and 3D reconstruction of images, which are required particularly for intelligent transportation systems (ITSs). However, cameras can present a limited angular resolution, becoming a bottleneck in vision applications. Thus, there is a challenge to incorporate angular data due to disparities in the LF images. In recent years, different machine learning algorithms have been applied to both image processing and ITS research areas for different purposes. In this work, a Lightweight Deformable Deep Learning Framework is implemented, in which the problem of disparity into LF images is treated. To this end, an angular alignment module and a soft activation function into the Convolutional Neural Network (CNN) are implemented. For performance assessment, the proposed solution is compared with recent state-of-the-art methods using different LF datasets, each one with specific characteristics. Experimental results demonstrated that the proposed solution achieved a better performance than the other methods. The image quality results obtained outperform state-of-the-art LF image reconstruction methods. Furthermore, our model presents a lower computational complexity, decreasing the execution time.

scholarly journals Sustainable Agri-Food Processes and Circular Economy Pathways in a Life Cycle Perspective: State of the Art of Applicative Research

2021 ◽  
Vol 13 (5) ◽  
pp. 2472
Author(s):  
Teodora Stillitano ◽  
Emanuele Spada ◽  
Nathalie Iofrida ◽  
Giacomo Falcone ◽  
Anna Irene De Luca
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Circular Economy ◽  
Social Life ◽  
Food Systems ◽  
State Of The Art ◽  
Terrestrial Ecosystems ◽  
Point Of View ◽  
Social Life Cycle Assessment ◽  
Qualitative Synthesis

This study aims at providing a systematic and critical review on the state of the art of life cycle applications from the circular economy point of view. In particular, the main objective is to understand how researchers adopt life cycle approaches for the measurement of the empirical circular pathways of agri-food systems along with the overall lifespan. To perform the literature review, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was considered to conduct a review by qualitative synthesis. Specifically, an evaluation matrix has been set up to gather and synthesize research evidence, by classifying papers according to several integrated criteria. The literature search was carried out employing scientific databases. The findings highlight that 52 case studies out of 84 (62% of the total) use stand-alone life cycle assessment (LCA) to evaluate the benefits/impacts of circular economy (CE) strategies. In contrast, only eight studies (9.5%) deal with the life cycle costing (LCC) approach combined with other analyses while no paper deals with the social life cycle assessment (S-LCA) methodology. Global warming potential, eutrophication (for marine, freshwater, and terrestrial ecosystems), human toxicity, and ecotoxicity results are the most common LCA indicators applied. Only a few articles deal with the CE assessment through specific indicators. We argue that experts in life cycle methodologies must strive to adopt some key elements to ensure that the results obtained fit perfectly with the measurements of circularity and that these can even be largely based on a common basis.

scholarly journals A New Measure of Complementarity in Market Basket Data

2021 ◽  
Vol 16 (4) ◽  
pp. 670-681
Author(s):  
Radosław Puka ◽  
Stanislaw Jedrusik
Keyword(s):  
Large Data ◽  
Point Of View ◽  
Detailed Data ◽  
Market Basket ◽  
Economic Theories ◽  
Empirical Verification ◽  
Preliminary Results ◽  
Research Fields ◽  
It Systems ◽  
Real Market

Modern IT systems collect detailed data on each activity, transaction, forum entry, conversation and many other areas. The availability of large data volumes in the business, industry and research fields opens up new opportunities for the empirical verification of various economic theories and laws. The analysis of big datasets in turn allows us to look at many issues from a new point of view and see the dependencies that are otherwise difficult to derive. In this paper, we propose a new measure for dependencies between goods in market basket data. The introduced measure was inspired by the well-known microeconomic concept of complementarity. Due to its similar properties to those of complementarity, the new measure was called basket complementarity (b-complementarity). B-complementarity not only measures the strength of dependencies between goods but also measures the direction of these dependencies. The values of the proposed measure can be relatively easily calculated using market basket data. This paper also presents a simple example illustrating this new concept, areas of possible application (e.g., in e-commerce) and preliminary results of searching for goods that meet the criteria of basket complementarity in real market basket data.

Sign in / Sign up

Export Citation Format

Share Document