Search results for "Machine"
showing 10 items of 2592 documents
Evaluation of a Support Vector Machine Based Method for Crohn’s Disease Classification
2019
Crohn’s disease (CD) is a chronic, disabling inflammatory bowel disease that affects millions of people worldwide. CD diagnosis is a challenging issue that involves a combination of radiological, endoscopic, histological, and laboratory investigations. Medical imaging plays an important role in the clinical evaluation of CD. Enterography magnetic resonance imaging (E-MRI) has been proven to be a useful diagnostic tool for disease activity assessment. However, the manual classification process by expert radiologists is time-consuming and expensive. This paper proposes the evaluation of an automatic Support Vector Machine (SVM) based supervised learning method for CD classification. A real E-…
Energy recovery from rectangular weirs in wastewater treat-ment plants
2022
Hydraulic turbines for energy recovery in wastewater treatment plants, with relatively large discharges and small head jumps, are usually screw or Kaplan types. In the specific case of a small head jump (about 3 m) underlying a rectangular weir in the major Palermo (Italy) treat-ment plant, a traditional Kaplan solution is compared with two other ones: a Hydrostatic Pres-sure Machine (HPM) located in the upstream channel and a cross-flow turbine located in a specif-ic underground room downstream the same channel.
How adolescents navigate Wikipedia to answer questions / ¿Cómo navegan los adolescentes en Wikipedia para contestar preguntas?
2015
AbstractIn one experiment, we explored how high school students use hyperlink relevance cues while they navigate to answer questions from hypertexts. Current evidence has shown that students may navigate by either performing a deep semantic analysis of the relationship between the question and the existing hyperlinks, or by matching words in the question to words in the hyperlink labels. We focused on how students combine both cues during navigation, and how comprehension skills relate to the use of such cues. Our study revealed that 14 year old students (N = 53) selected hyperlinks by relying to a similar degree on both word matching and semantic overlap. Furthermore, when there was a conf…
Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
2021
The British journal of surgery 108(11), 1274-1292 (2021). doi:10.1093/bjs/znab183
Do networks matter? Network involvement and policy learning in Nordic regions
2017
ABSTRACTThe capacities of regions to form networks are an important feature of regional cooperation. This article assesses why Nordic regions engage in network activities and what new organizational patterns of collaboration emerge. It draws on historical data from a 2006–2008 survey of elected regional politicians from the Nordic countries. The article argues that through this process, participation in cross-border networks matters for regional learning as measured by the policy-choices of regions.
A cultural heritage experience for visually impaired people
2020
Abstract In recent years, we have assisted to an impressive advance of computer vision algorithms, based on image processing and artificial intelligence. Among the many applications of computer vision, in this paper we investigate on the potential impact for enhancing the cultural and physical accessibility of cultural heritage sites. By using a common smartphone as a mediation instrument with the environment, we demonstrate how convolutional networks can be trained for recognizing monuments in the surroundings of the users, thus enabling the possibility of accessing contents associated to the monument itself, or new forms of fruition for visually impaired people. Moreover, computer vision …
Quantifying and Processing Biomedical and Behavioral Signals
2019
Cyclotron radiation emission spectroscopy signal classification with machine learning in project 8
2019
The Cyclotron Radiation Emission Spectroscopy (CRES) technique pioneered by Project 8 measures electromagnetic radiation from individual electrons gyrating in a background magnetic field to construct a highly precise energy spectrum for beta decay studies and other applications. The detector, magnetic trap geometry, and electron dynamics give rise to a multitude of complex electron signal structures which carry information about distinguishing physical traits. With machine learning models, we develop a scheme based on these traits to analyze and classify CRES signals. Understanding and proper use of these traits will be instrumental to improve cyclotron frequency reconstruction and help Pro…
Condition Monitoring Technologies for Synthetic Fiber Ropes - a Review
2020
This paper presents a review of different condition monitoring technologies for fiber ropes. Specifically, it presents an overview of the articles and patents on the subject, ranging from the early 70’s up until today with the state of the art. Experimental results are also included and discussed in a conditionmonitoring context,where failuremechanisms and changes in physical parameters give improved insight into the degradation process of fiber ropes. From this review, it is found that automatic width measurement has received surprisingly little attention, and might be a future direction for the development of a continuous condition monitoring system for synthetic fiber ropes.
Machine learning at the interface of structural health monitoring and non-destructive evaluation
2020
While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities and consider ultrasonic/guided-wave inspection as a technology at the interface of the two methodologies. It will discuss how data-based/machine learning analysis provides a powerful approach to ultrasonic NDE/SHM in terms of the available algorithms, and more generally, how different techniques can accommodate the very substantial quantities of data that are provided by modern monitoring campaigns. Several machine learning methods will be illu…