Search results for "Pears"
showing 10 items of 51 documents
Diagnostic efficacy of panoramic mandibular index to identify postmenopausal women with low bone mineral densities
2011
Objectives: The aim of the study was to compare and assess the accuracy of panoramic mandibular index (PMI) and antegonial index (AI) in the panoramic radiographs of postmenopausal women with normal and low skeletal bone mineral densities( BMD) diagnosed by using dual energy x-ray absorptiometry ( DXA). Study Design: In panoramic radiographs obtained from 40 post menopausal women( 20 normal and 20 osteoporo tic) aged between 50-75 who’s BMD has already been assessed by a DXA, the mean was calculated for PMI and AI index values measured in the right and left mandibles. The PMI and AI index values were evaluated using the student’s t test. The correlation between the observers for indices was…
Validity and reliability of Veloflex to measure active cervical range of motion in asymptomatic and symptomatic subjects
2021
Background Neck pain has a high annual incidence and decreases the cervical active range of motion (ROM). Clinicians use various methods to evaluate cervical range of motion (CROM) that some of them have also been proposed to give instant feedback. Accordingly, this study aimed to examine the validity and reliability of Veloflex (VF) to measure the CROM by comparison with the cervical range of motion (CROM) device, and to examine their test-retest reliability. Methods Thirty-eight healthy and 20 symptomatic participants were evaluated. Cervical flexion-extension, side bending, and rotations were tested in two sessions, first by the CROM and VF and in the second only with the VF. To evaluat…
Distance Functions, Clustering Algorithms and Microarray Data Analysis
2010
Distance functions are a fundamental ingredient of classification and clustering procedures, and this holds true also in the particular case of microarray data. In the general data mining and classification literature, functions such as Euclidean distance or Pearson correlation have gained their status of de facto standards thanks to a considerable amount of experimental validation. For microarray data, the issue of which distance function works best has been investigated, but no final conclusion has been reached. The aim of this extended abstract is to shed further light on that issue. Indeed, we present an experimental study, involving several distances, assessing (a) their intrinsic sepa…
Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks
2020
In near future it is assumable that automated unmanned aerial platforms are coming more common. There are visions that transportation of different goods would be done with large planes, which can handle over 1000 kg payloads. While these planes are used for transportation they could similarly be used for remote sensing applications by adding sensors to the planes. Hyperspectral imagers are one this kind of sensor types. There is need for the efficient methods to interpret hyperspectral data to the wanted water quality parameters. In this work we survey the performance of neural networks in the prediction of water quality parameters from remotely sensed hyperspectral data in freshwater basin…
Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology
2021
[EN] Background and objective: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies directly affect this region. In order to characterize the left ventricle, it is necessary to extract its volume. In this work we present a neural network architecture that is capable of directly estimating the left ventricle volume in short axis cine Magnetic Resonance Imaging in the end-diastolic frame and provide a segmentation of the region which is the basis of the volume calculation, thus offering explain-ability to the estimated value. Methods: The network was des…
A methodology to assess the intrinsic discriminative ability of a distance function and its interplay with clustering algorithms for microarray data …
2013
Abstract Background Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from statistics to computer science. Following Handl et al., it can be summarized as a three step process: (1) choice of a distance function; (2) choice of a clustering algorithm; (3) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research. Results A procedure is proposed for the assessment of the discriminative ability of a distance functi…
Continuity correction of pearson’s chi-square test in 2x2 contingency tables: A mini-review on recent development
2022
The Pearson’s chi-square test represents a nonparametric test more used in Biomedicine and Social Sciences, but it introduces an error for 2 x 2 contingency tables, when a discrete probability distribution is approximated with a continuous distribution. The first author to introduce the continuity correction of Pearson’s chi-square test has been Yates F. (1934). Unfortunately, Yates’s correction may tend to overcorrect of p-value, this can implicate an overly conservative result. Therefore many authors have introduced variants Pearson’s chi-square statistic, as alternative continuity correction to Yates’s correction. The goal of this paper is to describe the most recent continuity correctio…
Building energy performance forecasting: A multiple linear regression approach
2019
Abstract Different ways to evaluate the building energy balance can be found in literature, including comprehensive techniques, statistical and machine-learning methods and hybrid approaches. The identification of the most suitable approach is important to accelerate the preliminary energy assessment. In the first category, several numerical methods have been developed and implemented in specialised software using different mathematical languages. However, these tools require an expert user and a model calibration. The authors, in order to overcome these limitations, have developed an alternative, reliable linear regression model to determine building energy needs. Starting from a detailed …
The exchange rates – indicators for assessing the financial performance of the companies from Romania
2016
Abstract The research aims to determine the financial performance of the companies listed and traded on the Bucharest Stock Exchange from the manufacturing sector in Romania, compared with the performance recorded by the Bucharest Stock Exchange, based on the exchange rates. It was concluded that the financial performance of the companies included in the research, quantified on the basis of the exchange rates, decreased significantly with the arrival of the financial and economic crisis, currently, the companies being unable to reach the level of performance recorded before the crisis.
Video-Based Heartbeat Rate Measuring Method Using Ballistocardiography
2017
International audience; Video-based heartbeat rate measurement is a rapidly growing application in remote health monitoring. Video-based heartbeat rate measuring methods operate mainly by estimating photoplethysmography or ballistocardiography signals. These methods operate by estimating the microscopic color change in the face or by estimating the microscopic rigid motion of the head/facial skin. However, the robustness to motion artifacts caused by illumination variance and motion variance of the subject poses main challenge. We present a video-based heartbeat rate measuring framework to overcome these problems by using the principle of ballistocardiography. In this paper, we proposed a b…