Search results for " algorithm"
showing 10 items of 2538 documents
CAMLearn : a semantic context-aware recommender system architecture : application on m-learning domain
2015
Given the rapid emergence of new mobile technologies and the growth of needs of a moving society in training, works are increasing to identify new relevant educational platforms to improve distant learning. The next step in distance learning is porting e-learning to mobile systems. This is called m-learning. So far, learning environment was either defined by an educational setting, or imposed by the educational content. In our approach, in m-learning, we change the paradigm where the system recommends content and adapts learning follow to learner's context.
Online topology estimation for vector autoregressive processes in data networks
2017
An important problem in data sciences pertains to inferring causal interactions among a collection of time series. Upon modeling these as a vector autoregressive (VAR) process, this paper deals with estimating the model parameters to identify the underlying causality graph. To exploit the sparse connectivity of causality graphs, the proposed estimators minimize a group-Lasso regularized functional. To cope with real-time applications, big data setups, and possibly time-varying topologies, two online algorithms are presented to recover the sparse coefficients when observations are received sequentially. The proposed algorithms are inspired by the classic recursive least squares (RLS) algorit…
Horn growth rate and longevity: implications for natural and artificial selection in thinhorn sheep (Ovis dalli).
2007
We used horn measurements from natural and hunted mortalities of male thinhorn sheep Ovis dalli from Yukon Territory, Canada, to examine the relationship between rapid growth early in life and longevity. We found that rapid growth was associated with reduced longevity for sheep aged 5 years and older for both the hunted and natural mortality data sets. The negative relationship between growth rate and longevity in hunted sheep can at least partially be explained by morphologically biased hunting regulations. The same trend was evident from natural mortalities from populations that were not hunted or underwent very limited hunting, suggesting a naturally imposed mortality cost directly or in…
Study on New Product Development, by Networking
2015
The paper presents a situation of working in network in order to design or improve a new product. To implement theoretical models and to validate a working algorithm into a virtual research, there was proposed a specific theme from drilling and chamfering tool. The facilities offered by the research centers – database, software - led to rapid selection and configuration solutions, demonstrating achieving research productivity growth and a substantial reduction of times redesign.
Successive Reduction of Arms in Multi-Armed Bandits
2011
The relevance of the multi-armed bandit problem has risen in the past few years with the need for online optimization techniques in Internet systems, such as online advertisement and news article recommendation. At the same time, these applications reveal that state-of-the-art solution schemes do not scale well with the number of bandit arms. In this paper, we present two types of Successive Reduction (SR) strategies - 1) Successive Reduction Hoeffding (SRH) and 2) Successive Reduction Order Statistics (SRO). Both use an Order Statistics based Thompson Sampling method for arm selection, and then successively eliminate bandit arms from consideration based on a confidence threshold. While SRH…
Efficiency Improvement of Inverter-Fed Permanent Magnet Synchronous Motors
2003
In this paper a control algorithm for the efficiency improvement of inverter-fed permanent magnet synchronous motors (PMSMs) is presented. The proposed algorithm allows reducing the losses of the drive without reduction of its dynamic performances. In details, after recalling a dynamic model of the PMSM, which has been purposely modified and that takes into account the iron losses, the basic equations and the constraints to obtain the loss minimization are presented and discussed. Some simulations of a specific PMSM drive employing the proposed algorithm are performed. The results of these simulations show that the dynamic performances are maintained, and enhancement of the efficiency up to…
Assessment of Classifiers and Remote Sensing Features of Hyperspectral Imagery and Stereo-Photogrammetric Point Clouds for Recognition of Tree Specie…
2018
Recognition of tree species and geospatial information on tree species composition is essential for forest management. In this study, tree species recognition was examined using hyperspectral imagery from visible to near-infrared (VNIR) and short-wave infrared (SWIR) camera sensors in combination with a 3D photogrammetric canopy surface model based on RGB camera stereo-imagery. An arboretum with a diverse selection of 26 tree species from 14 genera was used as a test area. Aerial hyperspectral imagery and high spatial resolution photogrammetric color imagery were acquired from the test area using unmanned aerial vehicle (UAV) borne sensors. Hyperspectral imagery was processed to calibrated …
An automatic filtering algorithm for SURF-based registration of remote sensing images
2017
International audience; The registration of remote sensing images has been often a necessary step for further analyses of images taken at different times, different viewing geometry or with different sensors. For this task there exists many approaches. This paper focuses on the feature-based category of image registration methods. Particularly, we propose an improvement of the SURF algorithm on the point matching step. Indeed, in order to achieve a correct registration, a good matching of feature point is required. However The presence of outliers lead to a fail in the registration. Therefore, in this paper, we introduce an efficient method devoted to the detection and removal of such outli…
Fitting linear models and generalized linear models with large data sets in R
2009
We present an estimating algorithm to fit linear and generalized linear models not involving the QR decomposition. Some new R functions are presented and discussed. For large data sets, comparisons with respect to the well-known lm() and glm(), as well as to biglm() and bigglm() from the package biglm, show that the proposed functions speed up computation while preserving numerical stability and accuracy
The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with …
2021
Machine learning (ML) is applied in various logistic processes utilizing innovative techniques (e.g., the use of drones for automated delivery in e-commerce). Early challenges showed the insufficient drones’ steering capacity and cognitive gap related to the lack of theoretical foundation for controlling algorithms. The aim of this paper is to present a game-based algorithm of controlling behaviours in the relation between an operator (OP) and a technical object (TO), based on the assumption that the game is logistics-oriented and the algorithm is to support ML applied in e-commerce optimization management. Algebraic methods, including matrices, Lagrange functions, systems of differential e…