scholarly journals Information Extraction from Retinal Images with Agent-Based Technology

Processes ◽  
2018 ◽  
Vol 6 (12) ◽  
pp. 254 ◽  
Author(s):  
Pablo Chamoso ◽  
Sara Rodríguez ◽  
Luis García-Ortiz ◽  
Juan Corchado
Keyword(s):  
Retinal Vessel ◽  
Virtual Organizations ◽  
Retinal Vessels ◽  
Fundus Images ◽  
Agent Based ◽  
Medical Software ◽  
Wide Range ◽  
Clinical Tools ◽  
Effective Diagnosis

The study of retinal vessels can provide information on a wide range of illnesses in the human body. Numerous works have already focused on this new field of research and several medical software programs have been proposed to facilitate the close examination of retinal vessels. Some allow for the automatic extraction of information and can be combined with other clinical tools for effective diagnosis and further medical studies. This article proposes an Agent-based Virtual Organizations (VO) System which applies a novel methodology for taking measurements from fundus images and extracting information on the retinal vessel caliber. A case study was conducted to evaluate the performance of the developed system, and the fundus images of different patients were used to extract information. Its performance was compared with that of similar tools.

scholarly journals Retinal Vessel Segmentation Algorithm Based on Residual Convolution Neural Network

2021 ◽  
Vol 9 ◽  
Author(s):  
Shuang Xu ◽  
Zhiqiang Chen ◽  
Weiyi Cao ◽  
Feng Zhang ◽  
Bo Tao
Keyword(s):  
Neural Network ◽  
Retinal Vessel ◽  
Vessel Segmentation ◽  
Segmentation Algorithm ◽  
Convolution Neural Network ◽  
Superior Performance ◽  
Retinal Vessels ◽  
Fundus Images ◽  
Data Set ◽  
Retinal Vessel Segmentation

Retinal vessels are the only deep micro vessels that can be observed in human body, the accurate identification of which has great significance on the diagnosis of hypertension, diabetes and other diseases. To this end, a retinal vessel segmentation algorithm based on residual convolution neural network is proposed according to the characteristics of the retinal vessels on fundus images. Improved residual attention module and deep supervision module are utilized, in which the low-level and high-level feature graphs are joined to construct the encoder-decoder network structure, and atrous convolution is introduced to the pyramid pooling. The experiments result on the fundus image data set DRIVE and STARE show that this algorithm can obtain complete retinal vessel segmentation as well as connected vessel stems and terminals. The average accuracy on DRIVE and STARE reaches 95.90 and 96.88%, and the average specificity is 98.85 and 97.85%, which shows superior performance compared to other methods. This algorithm is verified feasible and effective for retinal vessel segmentation of fundus images and has the ability to detect more capillaries.

scholarly journals Emerging Spatiotemporal Patterns from Discrete Migration Dynamics of Heterogeneous Agents

2010 ◽  
Vol 2010 ◽  
pp. 1-13 ◽  
Author(s):  
J. K. Shin ◽  
Yuri Mansury
Keyword(s):  
Social Systems ◽  
Spatiotemporal Patterns ◽  
Agent Based ◽  
Wide Range ◽  
Generalized Framework ◽  
Potential Applications ◽  
Migration Dynamics ◽  
The Impact ◽  
Nonstationary Systems

We propose a discrete agent-based model to investigate the migration dynamics of heterogeneous individuals. Compatibility among agents of different types is expressed in terms of homophily parameters capturing the extent to which similar individuals are attracted to, or dissimilar individuals are repelled by, each other. Based on agent-based simulations, we establish the connection between emerging spatiotemporal patterns and the homophily parameters. Key results are presented in a novel phase diagram, which reveals a wide range of spatial patterns including the cell, worm, herd, amoeba, and swarm modes under the dynamic regime and the separation, ghetto, and integration modes under the stationary one. Our model thus provides a generalized framework encompassing both static equilibrium and nonstationary systems to investigate the impact of agent heterogeneity on population dynamics. We demonstrate potential applications of our model to social systems using sexual segregation of ungulate habitats as a case study.

Site specific agricultural soil management with the use of new technologies

2013 ◽  
Vol 16 (1) ◽  
pp. 59-67
Keyword(s):  
New Technologies ◽  
Digital Interface ◽  
Appropriate Treatment ◽  
Wide Range ◽  
Soil Variation ◽  
Soil Information ◽  
Remote Sensing Techniques ◽  
Agricultural Areas

<p>The Soil Science Institute of Thessaloniki produces new digitized Soil Maps that provide a useful electronic database for the spatial representation of the soil variation within a region, based on in situ soil sampling, laboratory analyses, GIS techniques and plant nutrition mathematical models, coupled with the local land cadastre. The novelty of these studies is that local agronomists have immediate access to a wide range of soil information by clicking on a field parcel shown in this digital interface and, therefore, can suggest an appropriate treatment (e.g. liming, manure incorporation, desalination, application of proper type and quantity of fertilizer) depending on the field conditions and cultivated crops. A specific case study is presented in the current work with regards to the construction of the digitized Soil Map of the regional unit of Kastoria. The potential of this map can easily be realized by the fact that the mapping of the physicochemical properties of the soils in this region provided delineation zones for differential fertilization management. An experiment was also conducted using remote sensing techniques for the enhancement of the fertilization advisory software database, which is a component of the digitized map, and the optimization of nitrogen management in agricultural areas.</p>

Oxford Studies in Ancient Philosophy, Volume 55

2018 ◽  
Keyword(s):  
Middle Ages ◽  
Ancient Philosophy ◽  
Recent Book ◽  
Loss Of Control ◽  
Ancient Greek ◽  
Original Essays ◽  
Constant Change ◽  
Wide Range ◽  
Metaphysical Principle

Oxford Studies in Ancient Philosophy provides, twice each year, a collection of the best current work in the field of ancient philosophy. Each volume features original essays that contribute to an understanding of a wide range of themes and problems in all periods of ancient Greek and Roman philosophy, from the beginnings to the threshold of the Middle Ages. From its first volume in 1983, OSAP has been a highly influential venue for work in the field, and has often featured essays of substantial length as well as critical essays on books of distinctive importance. Volume LV contains: a methodological examination on how the evidence for Presocratic thought is shaped through its reception by later thinkers, using discussions of a world soul as a case study; an article on Plato’s conception of flux and the way in which sensible particulars maintain a kind of continuity while undergoing constant change; a discussion of J. L. Austin’s unpublished lecture notes on Aristotle’s Nicomachean Ethics and his treatment of loss of control (akrasia); an article on the Stoics’ theory of time and in particular Chrysippus’ conception of the present and of events; and two articles on Plotinus, one that identifies a distinct argument to show that there is a single, ultimate metaphysical principle; and a review essay discussing E. K. Emilsson’s recent book, Plotinus.

scholarly journals Multi-Criteria, Co-Evolutionary Charging Behavior: An Agent-Based Simulation of Urban Electromobility

2021 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Lennart Adenaw ◽  
Markus Lienkamp
Keyword(s):  
Urban Areas ◽  
City Planning ◽  
User Behavior ◽  
Transport Sector ◽  
Simulation Framework ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Charging Station ◽  
Spatio Temporal

In order to electrify the transport sector, scores of charging stations are needed to incentivize people to buy electric vehicles. In urban areas with a high charging demand and little space, decision-makers are in need of planning tools that enable them to efficiently allocate financial and organizational resources to the promotion of electromobility. As with many other city planning tasks, simulations foster successful decision-making. This article presents a novel agent-based simulation framework for urban electromobility aimed at the analysis of charging station utilization and user behavior. The approach presented here employs a novel co-evolutionary learning model for adaptive charging behavior. The simulation framework is tested and verified by means of a case study conducted in the city of Munich. The case study shows that the presented approach realistically reproduces charging behavior and spatio-temporal charger utilization.

scholarly journals Discursive Strategies and Sequenced Institutional Change: The Case of Marriage Equality in the United States

2021 ◽  
pp. 003232172110205
Author(s):  
Giulia Mariani ◽  
Tània Verge
Keyword(s):  
United States ◽  
Institutional Change ◽  
The United States ◽  
Marriage Equality ◽  
Agent Based ◽  
Discursive Strategies ◽  
Policy Debates ◽  
The Status ◽  
Private Actors

Building on historical and discursive institutionalism, this article examines the agent-based dynamics of gradual institutional change. Specifically, using marriage equality in the United States as a case study, we examine how actors’ ideational work enabled them to make use of the political and discursive opportunities afforded by multiple venues to legitimize the process of institutional change to take off sequentially through layering, displacement, and conversion. We also pay special attention to how the discursive strategies deployed by LGBT advocates, religious-conservative organizations and other private actors created new opportunities to influence policy debates and tip the scales to their preferred policy outcome. The sequential perspective adopted in this study allows problematizing traditional conceptualizations of which actors support or contest the status quo, as enduring oppositional dynamics lead them to perform both roles in subsequent phases of the institutional change process.

scholarly journals Assessing the Relation between Mud Components and Rheology for Loss Circulation Prevention Using Polymeric Gels: A Machine Learning Approach

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1377
Author(s):  
Musaab I. Magzoub ◽  
Raj Kiran ◽  
Saeed Salehi ◽  
Ibnelwaleed A. Hussein ◽  
Mustafa S. Nasser
Keyword(s):  
Machine Learning ◽  
Rheological Properties ◽  
Nearest Neighbor ◽  
Drilling Fluid ◽  
Gradient Boosting ◽  
K Nearest Neighbor ◽  
Wide Range ◽  
Machine Learning Approach ◽  
Drilling Operations

The traditional way to mitigate loss circulation in drilling operations is to use preventative and curative materials. However, it is difficult to quantify the amount of materials from every possible combination to produce customized rheological properties. In this study, machine learning (ML) is used to develop a framework to identify material composition for loss circulation applications based on the desired rheological characteristics. The relation between the rheological properties and the mud components for polyacrylamide/polyethyleneimine (PAM/PEI)-based mud is assessed experimentally. Four different ML algorithms were implemented to model the rheological data for various mud components at different concentrations and testing conditions. These four algorithms include (a) k-Nearest Neighbor, (b) Random Forest, (c) Gradient Boosting, and (d) AdaBoosting. The Gradient Boosting model showed the highest accuracy (91 and 74% for plastic and apparent viscosity, respectively), which can be further used for hydraulic calculations. Overall, the experimental study presented in this paper, together with the proposed ML-based framework, adds valuable information to the design of PAM/PEI-based mud. The ML models allowed a wide range of rheology assessments for various drilling fluid formulations with a mean accuracy of up to 91%. The case study has shown that with the appropriate combination of materials, reasonable rheological properties could be achieved to prevent loss circulation by managing the equivalent circulating density (ECD).

scholarly journals Towards Regulatory-Compliant MLOps: Orazivio’s Journey from a Machine Learning Experiment to a Deployed Certified Medical Product

2021 ◽  
Vol 2 (5) ◽  
Author(s):  
Tuomas Granlund ◽  
Vlad Stirbu ◽  
Tommi Mikkonen
Keyword(s):  
Machine Learning ◽  
Joint Replacement ◽  
Medical Product ◽  
Medical Software ◽  
Continuous Delivery ◽  
Development Approach ◽  
Responding To Change ◽  
Agile Software ◽  
Engineering Practices

AbstractAgile software development embraces change and manifests working software over comprehensive documentation and responding to change over following a plan. The ability to continuously release software has enabled a development approach where experimental features are put to use, and, if they stand the test of real use, they remain in production. Examples of such features include machine learning (ML) models, which are usually pre-trained, but can still evolve in production. However, many domains require more plan-driven approach to avoid hazard to environment and humans, and to mitigate risks in the process. In this paper, we start by presenting continuous software engineering practices in a regulated context, and then apply the results to the emerging practice of MLOps, or continuous delivery of ML features. Furthermore, as a practical contribution, we present a case study regarding Oravizio, first CE-certified medical software for assessing the risks of joint replacement surgeries. Towards the end of the paper, we also reflect the Oravizio experiences to MLOps in regulatory context.

scholarly journals Retinal vessel segmentation with constrained-based nonnegative matrix factorization and 3D modified attention U-Net

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yang Yu ◽  
Hongqing Zhu
Keyword(s):  
Matrix Factorization ◽  
Nonnegative Matrix Factorization ◽  
Computational Cost ◽  
Three Dimensional ◽  
Nonnegative Matrix ◽  
Retinal Vessel ◽  
Classification Problem ◽  
Image Resolution ◽  
Retinal Vessels ◽  
Segmentation Task

AbstractDue to the complex morphology and characteristic of retinal vessels, it remains challenging for most of the existing algorithms to accurately detect them. This paper proposes a supervised retinal vessels extraction scheme using constrained-based nonnegative matrix factorization (NMF) and three dimensional (3D) modified attention U-Net architecture. The proposed method detects the retinal vessels by three major steps. First, we perform Gaussian filter and gamma correction on the green channel of retinal images to suppress background noise and adjust the contrast of images. Then, the study develops a new within-class and between-class constrained NMF algorithm to extract neighborhood feature information of every pixel and reduce feature data dimension. By using these constraints, the method can effectively gather similar features within-class and discriminate features between-class to improve feature description ability for each pixel. Next, this study formulates segmentation task as a classification problem and solves it with a more contributing 3D modified attention U-Net as a two-label classifier for reducing computational cost. This proposed network contains an upsampling to raise image resolution before encoding and revert image to its original size with a downsampling after three max-pooling layers. Besides, the attention gate (AG) set in these layers contributes to more accurate segmentation by maintaining details while suppressing noises. Finally, the experimental results on three publicly available datasets DRIVE, STARE, and HRF demonstrate better performance than most existing methods.

scholarly journals Using citizen science data to monitor the Sustainable Development Goals: a bottom-up analysis

2021 ◽  
Author(s):  
Laura Ballerini ◽  
Sylvia I. Bergh
Keyword(s):  
Sustainable Development ◽  
Citizen Science ◽  
Sustainable Development Goals ◽  
Comparative Case Study ◽  
Science Data ◽  
The Sustainable Development ◽  
Case Study Analysis ◽  
Wide Range ◽  
Development Goals

AbstractOfficial data are not sufficient for monitoring the United Nations Sustainable Development Goals (SDGs): they do not reach remote locations or marginalized populations and can be manipulated by governments. Citizen science data (CSD), defined as data that citizens voluntarily gather by employing a wide range of technologies and methodologies, could help to tackle these problems and ultimately improve SDG monitoring. However, the link between CSD and the SDGs is still understudied. This article aims to develop an empirical understanding of the CSD-SDG link by focusing on the perspective of projects which employ CSD. Specifically, the article presents primary and secondary qualitative data collected on 30 of these projects and an explorative comparative case study analysis. It finds that projects which use CSD recognize that the SDGs can provide a valuable framework and legitimacy, as well as attract funding, visibility, and partnerships. But, at the same time, the article reveals that these projects also encounter several barriers with respect to the SDGs: a widespread lack of knowledge of the goals, combined with frustration and political resistance towards the UN, may deter these projects from contributing their data to the SDG monitoring apparatus.

Sign in / Sign up

Export Citation Format

Share Document