Search results for "artificial intelligence"
showing 10 items of 6122 documents
Learning non-linear time-scales with kernel -filters
2009
A family of kernel methods, based on the @c-filter structure, is presented for non-linear system identification and time series prediction. The kernel trick allows us to develop the natural non-linear extension of the (linear) support vector machine (SVM) @c-filter [G. Camps-Valls, M. Martinez-Ramon, J.L. Rojo-Alvarez, E. Soria-Olivas, Robust @c-filter using support vector machines, Neurocomput. J. 62(12) (2004) 493-499.], but this approach yields a rigid system model without non-linear cross relation between time-scales. Several functional analysis properties allow us to develop a full, principled family of kernel @c-filters. The improved performance in several application examples suggest…
Robust γ-filter using support vector machines
2009
This Letter presents a new approach to time-series modelling using the support vector machines (SVM). Although the g-filter can provide stability in several time-series models, the SVM is proposed here to provide robustness in the estimation of the g-filter coefficients. Examples in chaotic time-series prediction and channel equalization show the advantages of the joint SVM g-filter. Teoría de la Señal y Comunicaciones
A Simple Fusion Method for Image Time Series Based on the Estimation of Image Temporal Validity
2015
High-spatial-resolution satellites usually have the constraint of a low temporal frequency, which leads to long periods without information in cloudy areas. Furthermore, low-spatial-resolution satellites have higher revisit cycles. Combining information from high- and low- spatial-resolution satellites is thought a key factor for studies that require dense time series of high-resolution images, e.g., crop monitoring. There are several fusion methods in the bibliography, but they are time-consuming and complicated to implement. Moreover, the local evaluation of the fused images is rarely analyzed. In this paper, we present a simple and fast fusion method based on a weighted average of two in…
Análisis de métodos de validación cruzada para la obtención robusta de parámetros biofísicos
2015
[EN] Non-parametric regression methods are powerful statistical methods to retrieve biophysical parameters from remote sensing measurements. However, their performance can be affected by what has been presented during the training phase. To ensure robust retrievals, various cross-validation sub-sampling methods are often used, which allow to evaluate the model with subsets of the field dataset. Here, two types of cross-validation techniques were analyzed in the development of non-parametric regression models: hold-out and k-fold. Selected non-parametric linear regression methods were least squares Linear Regression (LR) and Partial Least Squares Regression (PLSR), and nonlinear methods were…
Trajectory of Affordances: Insights from a case of telemedicine in Nepal
2017
Although Affordance Theory has become increasingly influential in the Information Systems (IS) literature, the exact process through which the affordances of IT are actualised is less studied. In t ...
An IoT and Fog Computing-Based Monitoring System for Cardiovascular Patients with Automatic ECG Classification Using Deep Neural Networks
2020
Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a high level of applicability in cardiology. The objective of this work is to present an IoT-based monitoring system for cardiovascular patients. The system sends the ECG signal to a Fog layer service by using the LoRa communication protocol. Also, it includes an AI algorithm based on deep learning for the detection of Atrial Fibrillation and other heart rhythms. The automatic detection of arrhythmias can be complementary to the diagnosis made by the physician, achieving a better clinical vision that improves therapeutic decision making. The performance of the proposed system is evaluated on a…
Adaptation of the Model for Assessment of Telemedicine (MAST) for IoT Telemedicine Services
2017
Internet of Things (IoT) based solutions and services may be used to support and extend the independent living of older adults in their living environments by responding to real needs of caregivers, service providers and public authorities. Telemedicine and telehealth platforms are among the various types of IoT services that could support the provision of health services. Current Health Technology Assessment (HTA) models that are used for the evaluation of telehealth and telemedicine services do not consider IoT aspects. HTA models would ideally need to be extended to include IoT platforms, for an optimal introduction of IoT in everyday provision of health and care services. This paper pre…
Decision support system for telemedicine based on multiple expertise
2002
This paper discusses results of the research in the area of artificial intelligence applications in telemedicine. The main goal of research is to manage multiple expertise obtained from experts-physicians in different countries to develop decision support medical system of broad earmarking based on telecommunication tools. The multilevel representation of medical data is discussed based on the apparatus of metastatistics. The technique is able to acquire semantically essential information from complex dynamics of quasi-periodical medical signals by applying recursively ordinary statistical tools. The voting-type technique is used to find consensus among medical experts in their description …
Knowledge-based modelling applied to synucleinopathies
2015
International audience; The adoption of telemedicine technologies has enabled collaborative programs involving a variety of links among distributed medical structures and health officials and professionals. The use for telemedicine for transmission of medical data and the possibility for several distant physicians to share their knowledge on given medical cases provides clear benefits, but also raises several unsolved conceptual and technical challenges. The seamless exchange and access of medical information between medical structures, health professionals, and patients is a prerequisite for the harmonious development of this new medical practice. This paper proposes a new approach of sema…
Design of temperature control system using conventional PID and Intelligent Fuzzy Logic controller
2015
In this paper, we present the design of temperature control for industrial heat treating furnace by using Intelligent Fuzzy Logic and PID controllers. Temperature control is important in heating processes as it can disqualify materials in terms of their physical properties when not well performed. Obviously PID temperature controller is the most used in industries to control non-linear processes. Consequently, it has been found that the output response from Fuzzy Logic is very accurate in terms of overshoot and steady state error when compared to that of PID. Moreover, both temperature controllers are modeled and simulated using MATLAB software.