The Elaboration Likelihood Model (ELM) uses central (more thoughtful) and peripheral (less thoughtful) routes of persuasion to maximize communication effectiveness. This research implements ELM to investigate the relative importance of different aspects of the user experience in online shopping. Of all the issues surrounding online shopping, convenience, access to information, and trust were fo...

In this paper, a new sequential learning algorithm is constructed by combining the Online Sequential Extreme Learning Machine (OS-ELM) and Kalman filter regression. The Kalman Online Sequential Extreme Learning Machine (KOSELM) handles the problem of multicollinearity of the OS-ELM, which can generate poor predictions and unstable models. The KOSELM learns the training data one-by-one or chunk-...

In this paper, a recently developed machine learning algorithm referred to as Extreme Learning Machine (ELM) is used to classify five mental tasks from different subjects using electroencephalogram (EEG) signals available from a well-known database. Performance of ELM is compared in terms of training time and classification accuracy with a Backpropagation Neural Network (BPNN) classifier and al...

O IL EPILUMINESCENCE microscopy (ELM), surface microscopy, dermatoscopy, and dermoscopy all refer to the same process of examination of cutaneous lesions with an incident light magnification system with oil at the skin-microscope interface. This technique greatly increases the morphological detail that is visualized, which results in an improvement in the diagnostic accuracy of most pigmented s...

The extreme learning machine (ELM) is a newly emerging supervised learning method. In order to use the information provided by unlabeled samples and improve the performance of the ELM, we deformed the kernel in the ELM by modeling the marginal distribution with the graph Laplacian, which is built with both labeled and unlabeled samples. We further approximated the deformed kernel by means of ra...

This paper is devoted to yet unpublished electrode-less methods (ELM) of cell layers impedance measurement based on transformer principle. The main advantage of ELM is elimination uncertainties caused by interface between electrodes and measured electrolyte. The method of avoiding distortion caused by non-ideal transformer transfer function ("deconvolution") and errors caused by residual voltag...

The problem of knowledge extraction from the data left by web users during their interactions is a very attractive research task. The extracted knowledge can be used for different goals such as service personalization, site structure simplification, web server performance improvement or even for studying the human behavior. We constructed a system, called ELM (Event Logger Manager), able to reg...

BACKGROUND Effective and accurate diagnosis of attention-deficit/hyperactivity disorder (ADHD) is currently of significant interest. ADHD has been associated with multiple cortical features from structural MRI data. However, most existing learning algorithms for ADHD identification contain obvious defects, such as time-consuming training, parameters selection, etc. The aims of this study were a...

For understanding of the physics processes determining the radial profiles of the plasma pressure in the advanced tokamak plasmas, correlation between the edge and the internal transport barriers (ETB and ITB) has been studied. We fond that the edge pedestal beta, βp-ped, increases almost linearly with the total βp over a wide range of the plasma current for the type I ELMing H-mode, and the de...

Extreme Support Vector Machine (ESVM) is a nonlinear robust SVM algorithm based on regularized least squares optimization for binary-class classification. In this paper, a novel algorithm for regression tasks, Extreme Support Vector Regression (ESVR), is proposed based on ESVM. Moreover, kernel ESVR is suggested as well. Experiments show that, ESVR has a better generalization than some other tr...