Search results for " Mach"
showing 10 items of 1388 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.
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
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 …
Inventando el crimen pasional: del lenguaje de gacetilla a la prensa de sucesos (España, 1892-1920)
2021
El terme «crim passional» va sorgir a la premsa espanyola el 1892. L’objectiu d’aquest treball és desvelar el perquè i entendre’n la relació amb la premsa sensacionalista i, en especial, amb la premsa especialitzada en successos. La nostra metodologia considera que la premsa és un motor cultural en la construcció de conceptes amb incidència social. Així, doncs, explorem la presència del terme «crim passional» en un bon nombre de diaris i setmanaris per observar com es va construir un marc mental de naturalesa emocional. Es revela la incidència del concepte en l’opinió pública i en el llenguatge jurídic, així com la seva rellevància en la justificació de la violència contra les dones.
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…
Network reconstruction for trans acting genetic loci using multi-omics data and prior information.
2022
Background: Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors…
Machine learning in remote sensing data processing
2009
Remote sensing data processing deals with real-life applications with great societal values. For instance urban monitoring, fire detection or flood prediction from remotely sensed multispectral or radar images have a great impact on economical and environmental issues. To treat efficiently the acquired data and provide accurate products, remote sensing has evolved into a multidisciplinary field, where machine learning and signal processing algorithms play an important role nowadays. This paper serves as a survey of methods and applications, and reviews the latest methodological advances in machine learning for remote sensing data analysis.
Distributed Real-Time Sentiment Analysis for Big Data Social Streams
2014
Big data trend has enforced the data-centric systems to have continuous fast data streams. In recent years, real-time analytics on stream data has formed into a new research field, which aims to answer queries about "what-is-happening-now" with a negligible delay. The real challenge with real-time stream data processing is that it is impossible to store instances of data, and therefore online analytical algorithms are utilized. To perform real-time analytics, pre-processing of data should be performed in a way that only a short summary of stream is stored in main memory. In addition, due to high speed of arrival, average processing time for each instance of data should be in such a way that…