Search results for "CIS"

Non-destructive automatic determination of aspect ratio and cross-sectional properties of fibres

2015

A novel method for computerised estimation of the aspect ratio distribution and various cross-sectional geometrical properties of fibres in short-fibre reinforced composites is proposed. The method, based on X-ray micro-computed tomography, is non-destructive and does not require user intervention. Based on results on specially fabricated model material, the accuracy and precision of the method seems adequate. The method is applied in analysing a manufacturing process of wood fibre reinforced thermoplastic composite. The results indicate a significant decrease of the aspect ratio of fibres during the processing steps. Finally, the feasibility of the method is assessed by estimating paramete…

Accurate estimation of retinal vessel width using bagged decision trees and an extended multiresolution Hermite model.

2012

We present an algorithm estimating the width of retinal vessels in fundus camera images. The algorithm uses a novel parametric surface model of the cross-sectional intensities of vessels, and ensembles of bagged decision trees to estimate the local width from the parameters of the best-fit surface. We report comparative tests with REVIEW, currently the public database of reference for retinal width estimation, containing 16 images with 193 annotated vessel segments and 5066 profile points annotated manually by three independent experts. Comparative tests are reported also with our own set of 378 vessel widths selected sparsely in 38 images from the Tayside Scotland diabetic retinopathy scre…

5 Effects Of Low-intensity Concentric Combined With Blood Flow Restriction On Achilles Tendon

2014

Introduction Weight training is a useful tool in order to achieve muscular hypertrophy. However, the American College of Sports Medicine (ACSM) recommends intensities of 70% of one repetition maximum (1-RM). Those intensities may not be suitable for everyone because of the high mechanical stresses placed upon the joints [Loenneke, 2012]. Nowadays, it is common to combine low-intensity exercise (20–30% 1-RM) with blood flow restriction (BFR) because of the beneficial effects in increased muscular strength, hypertrophy, localised endurance and cardiorespiratory endurance [Pope, 2013]. Despite there is not many papers about the beneficial of this training, it is know that the tendon suffers so…

Automatic detection and classification of retinal vascular landmarks

2014

The main contribution of this paper is introducing a method to distinguish between different landmarks of the retina: bifurcations and crossings. The methodology may help in differentiating between arteries and veins and is useful in identifying diseases and other special pathologies, too. The method does not need any special skills, thus it can be assimilated to an automatic way for pinpointing landmarks; moreover it gives good responses for very small vessels. A skeletonized representation, taken out from the segmented binary image (obtained through a preprocessing step), is used to identify pixels with three or more neighbors. Then, the junction points are classified into bifurcations or…

L'acquaforte. Vincenzo Riolo, Francesco La Farina, Bartolomeo e Luca Costanzo incisori

2008

Active learning strategies for the deduplication of electronic patient data using classification trees.

2012

Graphical abstractDisplay Omitted Highlights? Active learning for medical record linkage is used on a large data set. ? We compare a simple active learning strategy with a more sophisticated variant. ? The active learning method of Sarawagi and Bhamidipaty (2002) 6] is extended. ? We deliver insights into the variations of the results due to random sampling in the active learning strategies. IntroductionSupervised record linkage methods often require a clerical review to gain informative training data. Active learning means to actively prompt the user to label data with special characteristics in order to minimise the review costs. We conducted an empirical evaluation to investigate whether…

ActRec: A Wi-Fi-Based Human Activity Recognition System

2020

In this paper, we develop a Wi-Fi-based activity recognition system called ActRec, which can be used for the remote monitoring of elderly. ActRec comprises two parts: radio-frequency (RF) sensing and machine learning. In the RF sensing part, two laptops act as transmitter and receiver to record the channel transfer function of an indoor environment. This RF data is collected in the presence of seven human participants performing three activities: walking, falling, and sitting. The RF data containing the fingerprints of user activity is then pre-processed with various signal processing algorithms to reduce noise effects and to estimate the mean Doppler shift (MDS) of each data sample. We pro…

Investment Decision Making and Risk

2013

Abstract The aim of the paper is to present how investment decisions are made and what investment risk is, what role it has in the investment decision. The decision itself is a subjective act, but it is based on both subjective and objective factors. Risk is an important component of every investment, thus it is necessary to analyse it as both, the objective component of the investment, and as the subjective factor of the investment decision making.

A fuzzy ranking strategy for portfolio selection applied to the Spanish stock market

2007

In this paper we present a fuzzy ranking procedure for the portfolio selection problem. The uncertainty on the returns of each portfolio is approximated by means of a trapezoidal fuzzy number. The expected return and risk of the portfolio are then characteristics of that fuzzy number. A rank index that accounts for both expected return and risk is defined, allowing the decision-maker to compare different portfolios. The paper ends with an application of that fuzzy ranking strategy to the Spanish stock market.

Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case.

2017

Abstract Objectives This paper is based on the analysis of the database of operations from a macro-case on money laundering orchestrated between a core company and a group of its suppliers, 26 of which had already been identified by the police as fraudulent companies. In the face of a well-founded suspicion that more companies have perpetrated criminal acts and in order to make better use of what are very limited police resources, we aim to construct a tool to detect money laundering criminals. Methods We combine Benford’s Law and machine learning algorithms (logistic regression, decision trees, neural networks, and random forests) to find patterns of money laundering criminals in the conte…