Search results for "Networks"
showing 10 items of 3260 documents
Effectively Predicting the Presence of Coronary Heart Disease Using Machine Learning Classifiers
2022
Coronary heart disease is one of the major causes of deaths around the globe. Predicating a heart disease is one of the most challenging tasks in the field of clinical data analysis. Machine learning (ML) is useful in diagnostic assistance in terms of decision making and prediction on the basis of the data produced by healthcare sector globally. We have also perceived ML techniques employed in the medical field of disease prediction. In this regard, numerous research studies have been shown on heart disease prediction using an ML classifier. In this paper, we used eleven ML classifiers to identify key features, which improved the predictability of heart disease. To introduce the prediction …
Machine learning for a combined electroencephalographic anesthesia index to detect awareness under anesthesia
2020
Spontaneous electroencephalogram (EEG) and auditory evoked potentials (AEP) have been suggested to monitor the level of consciousness during anesthesia. As both signals reflect different neuronal pathways, a combination of parameters from both signals may provide broader information about the brain status during anesthesia. Appropriate parameter selection and combination to a single index is crucial to take advantage of this potential. The field of machine learning offers algorithms for both parameter selection and combination. In this study, several established machine learning approaches including a method for the selection of suitable signal parameters and classification algorithms are a…
Mixed Fault Classification of Sensorless PMSM Drive in Dynamic Operations Based on External Stray Flux Sensors
2022
This paper aims to classify local demagnetisation and inter-turn short-circuit (ITSC) on position sensorless permanent magnet synchronous motors (PMSM) in transient states based on external stray flux and learning classifier. Within the framework, four supervised machine learning tools were tested: ensemble decision tree (EDT), k-nearest neighbours (KNN), support vector machine (SVM), and feedforward neural network (FNN). All algorithms are trained on datasets from one operational profile but tested on other different operation profiles. Their input features or spectrograms are computed from resampled time-series data based on the estimated position of the rotor from one stray flux sensor t…
Prediction of banana quality indices from color features using support vector regression
2015
Banana undergoes significant quality indices and color transformations during shelf-life process, which in turn affect important chemical and physical characteristics for the organoleptic quality of banana. A computer vision system was implemented in order to evaluate color of banana in RGB, L*a*b* and HSV color spaces, and changes in color features of banana during shelf-life were employed for the quantitative prediction of quality indices. The radial basis function (RBF) was applied as the kernel function of support vector regression (SVR) and the color features, in different color spaces, were selected as the inputs of the model, being determined total soluble solids, pH, titratable acid…
Deep learning approach for prediction of impact peak appearance at ground reaction force signal of running activity
2020
Protruding impact peak is one of the features of vertical ground reaction force (GRF) that is related to injury risk while running. The present research is dedicated to predicting GRF impact peak appearance by setting a binary classification problem. Kinematic data, namely a number of raw signals in the sagittal plane, collected by the Vicon motion capture system (Oxford Metrics Group, UK) were employed as predictors. Therefore, the input data for the predictive model are presented as a multi-channel time series. Deep learning techniques, namely five convolutional neural network (CNN) models were applied to the binary classification analysis, based on a Multi-Layer Perceptron (MLP) classifi…
Surface Ordering and Surface Segregation in Binary Alloys
1996
Many technologically relevant properties of metallic alloys are determined by the structure of their surfaces, especially in the field of catalysis and corrosion. One important aspect of a surface or grain boundaries is, that the stoichiometry of the alloy close to the surface normally differs from the bulk stoichiometry. Due to different interaction energies and different atom sizes of the components, one of them will get enriched at the surface, a phenomenon called surface segregation[1].
Static and dynamical properties of a supercooled liquid confined in a pore
2000
We present the results of a Molecular Dynamics computer simulation of a binary Lennard-Jones liquid confined in a narrow pore. The surface of the pore has an amorphous structure similar to that of the confined liquid. We find that the static properties of the liquid are not affected by the confinement, while the dynamics changes dramatically. By investigating the time and temperature dependence of the intermediate scattering function we show that the dynamics of the particles close to the center of the tube is similar to the one in the bulk, whereas the characteristic relaxation time tau_q(T,rho) of the intermediate scattering function at wavevector q and distance rho from the axis of the p…
Spinodal decomposition in thin films: Molecular-dynamics simulations of a binary Lennard-Jones fluid mixture
2005
We use molecular dynamics (MD) to simulate an unstable homogeneous mixture of binary fluids (AB), confined in a slit pore of width $D$. The pore walls are assumed to be flat and structureless, and attract one component of the mixture (A) with the same strength. The pair-wise interactions between the particles is modeled by the Lennard-Jones potential, with symmetric parameters that lead to a miscibility gap in the bulk. In the thin-film geometry, an interesting interplay occurs between surface enrichment and phase separation. We study the evolution of a mixture with equal amounts of A and B, which is rendered unstable by a temperature quench. We find that A-rich surface enrichment layers fo…
Fostering sustainable community outcomes through policy networks: a dynamic performance governance approach
2021
This chapter will illustrate how an “outside-in” view of policy making may implement a balanced perspective for assessing sustainable outcomes through an integrated Dynamic Performance Management and Governance framework. In the next sections such a framework will be illustrated and applied to different examples of collaborative networks. In the remaining part of this section practical implications from an “outside-in” view of policy making will be illustrated.
Recent advances in green industrial networking [Guest Editorial]
2016
The articles in this special section focus on green industrial networking. Due to the explosive increase in energy usage, it is essential that governmental and industrial institutions address this problem. Therefore, the development of green and low-carbon economy has recently become a hot issue in the industry. It is envisioned in such cases to meet the growing demands for industrial networking with limited resources. This is considered one of the challenges that needs to be addressed. Addressing such key problems will hopefully allow us to reach the realization of sustainable development. We believe that network technologies will be critical and will greatly contribute to achieving large-…