Search results for " artificial intelligence"
showing 10 items of 1992 documents
Study of transmission parameters under controlled multipath environment using Rasp Pi3
2018
The evaluation of QoS in mobile multipath environments is an interesting topic in modern communications. The use of Raspberry Pi as a low cost microcomputer board developed in the United Kingdom by the Raspberry Pi Foundation can be helpful in onsite deployments. The Pi3 model has integrated WiFi and Bluetooth connectivity and also 4 USB ports to expand the device with all kinds of peripheral. Under the premise of offering the power of a computer at low prices, this device is one of the most affordable ways to have a particularly efficient and dynamic hardware accessible at a low price to develop a Wireless Sensor Netwok (WSN). The use of the Raspberry Pi3 permits the development of a power…
Evaluation of SLA-based decision strategies for VM scheduling in cloud data centers
2016
Service level agreements (SLAs) gain more and more importance in the area of cloud computing. An SLA is a contract between a customer and a cloud service provider (CSP) in which the CSP guarantees functional and non-functional quality of service parameters for cloud services. Since CSPs have to pay for the hardware used as well as penalties for violating SLAs, they are eager to fulfill these agreements while at the same time optimizing the utilization of their resources.In this paper we examine SLA-aware VM scheduling strategies for cloud data centers. The service level objectives considered are resource usage and availability. The sample resources are CPU and RAM. They can be overprovision…
Collaborative Activities and Methods
2016
Having described the context for collaborative activities (in Chap. 1), and reviewed the basic aspects of computer supported decision-making activities (in Chap. 2), we will present in this section several specific methods used in collaborative decision making. The methods and techniques presented in the chapter are independent of the information technologies upon they are instantiated.
Machine Learning Techniques for Automatic Depression Assessment
2018
Depression is one of the most common mood disorder that is inherently related to emotions, involving bad mood, low self-esteem and loss of interest in normal pleasurable activities. The aim of this work is to develop a framework based on the dataset provided by AVEC'14 for depression assessment. The proposed work presents two different motion representation methods: a) Gabor Motion History Image (GMHI), and b) Motion History Image (MHI). Several combinations of appearance-based low level features are extracted from both motion representations. These features were further combined with statistically derived features, and used for training and testing with several machine learning techniques.…
ACCURATE DENSE STEREO MATCHING FOR ROAD SCENES
2017
International audience; Stereo matching task is the core of applications linked to the intelligent vehicles. In this paper, we present a new variant function of the Census Transform (CT) which is more robust against radiometric changes in real road scenes. We demonstrate that the proposed cost function outperforms the conventional cost functions using the KITTI benchmark. The cost aggregation method is also updated for taking into account the edge information. This enables to improve significantly the aggregated costs especially within homogenous regions. The Winner-Takes-All (WTA) strategy is used to compute disparity values. To further eliminate the remainder matching ambiguities , a post…
Periodic Variance Maximization using Generalized Eigenvalue Decomposition applied to Remote Photoplethysmography estimation
2018
International audience; A generic periodic variance maximization algorithm to extract periodic or quasi-periodic signals of unknown periods embedded into multi-channel temporal signal recordings is described in this paper. The algorithm combines the notion of maximizing a periodicity metric combined with the global optimization scheme to estimate the source periodic signal of an unknown period. The periodicity maximization is performed using Generalized Eigenvalue Decomposition (GEVD) and the global optimization is performed using tabu search. A case study of remote photoplethysmography signal estimation has been utilized to assess the performance of the method using videos from public data…
Cooperative compressive power spectrum estimation in wireless fading channels
2017
This paper considers multiple wireless sensors that cooperatively estimate the power spectrum of the signals received from several sources. We extend our previous work on cooperative compressive power spectrum estimation to accommodate the scenario where the statistics of the fading channels experienced by different sensors are different. The signals received from the sources are assumed to be time-domain wide-sense stationary processes. Multiple sensors are organized into several groups, where each group estimates a different subset of lags of the temporal correlation. A fusion centre (FC) combines these estimates to obtain the power spectrum. As each sensor group computes correlation esti…
Machine Learning for Modeling the Biomechanical Behavior of Human Soft Tissue
2016
An accurate modeling of the biomechanical properties of human soft tissue is crucial in many clinical applications, such as, radiotherapy administration or surgery. The finite element method (FEM) is the usual choice to carry out such modeling due to its high accuracy. However, FEM is computationally very costly, and hence, its application in real-time or even off-line with short delays are still challenges to overcome. This paper proposes a framework based on Machine Learning to learn FEM modeling, thus having a tool able to yield results that may be sufficiently fast for clinical applications. In particular, the use of ensembles of Decision Trees has shown its suitability in modeling the …
Subpixel determination of imperfect circles characteristics
2008
This article deals with the problem of the determination of characteristics of imperfect circular objects in discrete images, namely the radius and center coordinates. To limit distortion, a multi-level method based on active contours was developed. Its originality is to furnish a set of geometric envelopes in one pass, with a correspondence between grayscale and a regularity scale. The adequacy of this approach was tested with several methods, among them is the Radon-based method. More particularly, this study indicates the relevance of the use of active contours combined with a Radon transform-based method which was improved using a fitting considering the discrete implementation of the R…
Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML)
2017
International audience; This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilities for representing probabilistic (stochastic) machine-learning algorithms that are widely used for constructing predictive models taking the associated uncertainties into consideration. The newly released PMML version 4.3, which includes the GPR model, provides new features: confidence bounds and distribution for the pred…