Search results for "computer.software_genre"

Performance assessment of individual and ensemble data-mining techniques for gully erosion modeling

2017

Gully erosion is identified as an important sediment source in a range of environments and plays a conclusive role in redistribution of eroded soils on a slope. Hence, addressing spatial occurrence pattern of this phenomenon is very important. Different ensemble models and their single counterparts, mostly data mining methods, have been used for gully erosion susceptibility mapping; however, their calibration and validation procedures need to be thoroughly addressed. The current study presents a series of individual and ensemble data mining methods including artificial neural network (ANN), support vector machine (SVM), maximum entropy (ME), ANN-SVM, ANN-ME, and SVM-ME to map gully erosion …

Improved GNSS positioning exploiting a vehicular P2P infrastructure

2010

This paper considers the possibility to exploit external altitude measurements to improve the performance of a Kalman based GNSS receiver. The altitude measurements are provided by means of a peer to peer network, that is supposed to be based on the evolution of the 802.11 standard for the vehicular environment, namely the WAVE (802.11p). The performance of such a system are investigated for different characteristics of the aiding measurement and for a different number and disposals of the aiding peers. The aiding measurement is obtained starting from the altitude measurements that the other peers in the network send to the aided user. The experiments highlight the need for a parameter that…

Agent's actions as a classification criteria for the state space in a learning from rewards system

2008

We focus in this paper on the problem of learning an autonomous agent's policy when the state space is very large and the set of actions available is comparatively short. To this end, we use a non-parametric decision rule (concretely, a nearest-neighbour strategy) in order to cluster the state space by means of the action that leads to a successful situation. Using an exploration strategy to avoid greedy behaviour, the agent builds clusters of positively-classified states through trial and error learning. In this paper, we implement a 3D synthetic agent which plays an 'avoid the asteroid' game that suits our assumptions. Using as the state space a feature vector space extracted from a visua…

On the role of procrastination for machine learning

1992

Feedback adaptation in web-based learning systems

2007

Feedback provided by a learning system to its users plays an important role in web-based education. This paper presents an overview of feedback studies and then concentrates on the problem of feedback adaptation in web-based learning systems. We introduce our taxonomy of feedback concept with regard to its functions, complexity, intention, time of occurrence, way of presentation, and level and way of its adaptation. We consider what can be adapted in feedback and how to facilitate feedback adaptation in web-based learning systems.

Estimation of National Colorectal-Cancer Incidence Using Claims Databases

2012

Background.The aim of the study was to assess the accuracy of the colorectal-cancer incidence estimated from administrative data.Methods.We selected potential incident colorectal-cancer cases in 2004-2005 French administrative data, using two alternative algorithms. The first was based only on diagnostic and procedure codes, whereas the second considered the past history of the patient. Results of both methods were assessed against two corresponding local cancer registries, acting as “gold standards.” We then constructed a multivariable regression model to estimate the corrected total number of incident colorectal-cancer cases from the whole national administrative database.Results.The firs…

PA 05-3-0690 Mavie-lab sports: a mhealth for injury prevention and risk management in sport

2018

Computational advances in smart-phone technology and the development of expert systems has been an opportunity to devise the MAVIE-Lab an innovative Mobile Health Application (mHealth) for primary prevention of Home, Leisure and Sport Injuries (HLIs). Here, we present MAVIE-Lab Sports, the first module of the application focused on sports injuries. MAVIE-Lab was developed in the framework of the MAVIE project. A large web-based cohort launched with the objective of prospectively collecting data related to HLIs. A sample size of 26 000 volunteers have been already enrolled in this cohort and the ultimate goal is to recruit 1 00 000 participants in France. As a first step, the MAVIE-Lab will …

Back-Propagation Artificial Neural Network for ERP Adoption Cost Estimation

2011

Published version of a chapter in the book: Enterprise information systems, vol 220, part 2, 180-187. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-24355-4_19 Small and medium size enterprises (SMEs) are greatly affected by cost escalations and overruns Reliable cost factors estimation and management is a key for the success of Enterprise Resource Planning (ERP) systems adoptions in enterprises generally and SMEs specifically. This research area is still immature and needs a considerable amount of research to seek solid and realistic cost factors estimation. Majority of research in this area targets the enhancement of estimates calculated by COCOMO family models.…

Learning main drivers of crop progress and failure in Europe with interpretable machine learning

2021

Abstract A wide variety of methods exist nowadays to address the important problem of estimating crop yields from available remote sensing and climate data. Among the different approaches, machine learning (ML) techniques are being increasingly adopted, since they allow exploiting all the information on crop progress and environmental conditions and their relations with crop yield, achieving reliable and accurate estimations. However, interpreting the relationships learned by the ML models, and hence getting insights about the problem, remains a complex and usually unexplored task. Without accountability, confidence and trust in the ML models can be compromised. Here, we develop interpretab…

Comparison of Causality Network Estimation in the Sensor and Source Space: Simulation and Application on EEG

2021

The usage of methods for the estimation of the true underlying connectivity among the observed variables of a system is increasing, especially in the domain of neuroscience. Granger causality and similar concepts are employed for the estimation of the brain network from electroencephalogram (EEG) data. Also source localization techniques, such as the standardized low resolution electromagnetic tomography (sLORETA), are widely used for obtaining more reliable data in the source space. In this work, connectivity structures are estimated in the sensor and in the source space making use of the sLORETA transformation for simulated and for EEG data with episodes of spontaneous epileptiform discha…