Search results for "Bay"
showing 10 items of 1187 documents
Adaptive Sequential Interpolator Using Active Learning for Efficient Emulation of Complex Systems
2020
Many fields of science and engineering require the use of complex and computationally expensive models to understand the involved processes in the system of interest. Nevertheless, due to the high cost involved, the required study becomes a cumbersome process. This paper introduces an interpolation procedure which belongs to the family of active learning algorithms, in order to construct cheap surrogate models of such costly complex systems. The proposed technique is sequential and adaptive, and is based on the optimization of a suitable acquisition function. We illustrate its efficiency in a toy example and for the construction of an emulator of an atmosphere modeling system.
Intrusion Detection and Ejection Framework Against Lethal Attacks in UAV-Aided Networks: A Bayesian Game-Theoretic Methodology
2017
International audience; Advances in wireless communications and microelectronics have spearheaded the development of unmanned aerial vehicles (UAVs), which can be used to augment a ground network composed of sensors and/or vehicles in order to increase coverage, enhance the end-to-end delay, and improve data processing. While UAV-aided networks can potentially find applications in many areas, a number of issues, particularly security, have not been readily addressed. The intrusion detection system is the most commonly used technique to detect attackers. In this paper, we focus on addressing two main issues within the context of intrusion detection and attacker ejection in UAV-aided networks…
New Procedures of Pattern Classification for Vibration-Based Diagnostics via Neural Network
2014
In this paper, the new distance-based embedding procedures of pattern classification for vibration-based diagnostics of gas turbine engines via neural network are proposed. Diagnostics of gas turbine engines is important because of the high cost of engine failure and the possible loss of human life. Engine monitoring is performed using either ‘on-line’ systems, mounted within the aircraft, that perform analysis of engine data during flight, or ‘off-line’ ground-based systems, to which engine data is downloaded from the aircraft at the end of a flight. Typically, the health of a rotating system such as a gas turbine is manifested by its vibration level. Efficiency of gas turbine monitoring s…
Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling
2011
Abstract Urban drainage models are important tools used by both practitioners and scientists in the field of stormwater management. These models are often conceptual and usually require calibration using local datasets. The quantification of the uncertainty associated with the models is a must, although it is rarely practiced. The International Working Group on Data and Models, which works under the IWA/IAHR Joint Committee on Urban Drainage, has been working on the development of a framework for defining and assessing uncertainties in the field of urban drainage modelling. A part of that work is the assessment and comparison of different techniques generally used in the uncertainty assessm…
Uncertainty estimation of a complex water quality model: The influence of Box–Cox transformation on Bayesian approaches and comparison with a non-Bay…
2012
Abstract In urban drainage modelling, uncertainty analysis is of undoubted necessity. However, uncertainty analysis in urban water-quality modelling is still in its infancy and only few studies have been carried out. Therefore, several methodological aspects still need to be experienced and clarified especially regarding water quality modelling. The use of the Bayesian approach for uncertainty analysis has been stimulated by its rigorous theoretical framework and by the possibility of evaluating the impact of new knowledge on the modelling predictions. Nevertheless, the Bayesian approach relies on some restrictive hypotheses that are not present in less formal methods like the Generalised L…
Variable Selection in Predictive MIDAS Models
2014
In short-term forecasting, it is essential to take into account all available information on the current state of the economic activity. Yet, the fact that various time series are sampled at different frequencies prevents an efficient use of available data. In this respect, the Mixed-Data Sampling (MIDAS) model has proved to outperform existing tools by combining data series of different frequencies. However, major issues remain regarding the choice of explanatory variables. The paper first addresses this point by developing MIDAS based dimension reduction techniques and by introducing two novel approaches based on either a method of penalized variable selection or Bayesian stochastic searc…
A Bayesian Network Model for Fire Assessment and Prediction
2015
Smartphones and other wearable computers with modern sensor technologies are becoming more advanced and widespread. This paper proposes exploiting those devices to help the firefighting operation. It introduces a Bayesian network model that infers the state of the fire and predicts its future development based on smartphone sensor data gathered within the fire area. The model provides a prediction accuracy of 84.79i¾?% and an area under the curve of 0.83. This solution had also been tested in the context of a fire drill and proved to help firefighters assess the fire situation and speed up their work.
A predictive maintenance policy with imperfect monitoring
2010
For many systems,failure is a very dangerous or costly event. To reduce the occurrence of this event,it is necessary to implement a preventive maintenance policy to replace the critical elements before failure.Since elements do not often exhibit incipient faults, they are replaced before a complete exploiting of their useful life.To conjugate the objective of exploiting elements for almost all their useful life with the objective to avoid failure,condition based and,more recently,predictive maintenance policies have been proposed.This paper deals with this topic and proposes a procedure for the computation of the maintenance time that minimizes the global maintenance cost.By adopting a stoc…
BIOMASSA AND ACCUMULATION CARBON ON SEAGRASS Enhalus acroides IN GUNUNG BOTAK BAY COASTAL, WEST PAPUA
2018
Seagrass is a high level and a flowering plant that is fully adapted to life in the coastal and has ability to store carbon by 10% of the carbon content in the oceans. The research doing at Gunung Botak Bay Coastal South Manokwari Regency with objective of research to estimate seagrass density and to estimate rate accumulation of carbon from Enhalus acroides. Some the stages of the research done is density sample as long to period 2015 (April and Mei) into (September and Ocktober). Other sampling to collecting seagrass to estimate carbon storage in part like daun, rhizome root and substrat. Result to showing average carbon accumulation of seagrass in above below ground is rhizome part and h…
Population dynamic of the extinct European aurochs: genetic evidence of a north-south differentiation pattern and no evidence of post-glacial expansi…
2010
International audience; Abstract Background The aurochs ( Bos primigenius ) was a large bovine that ranged over almost the entirety of the Eurasian continent and North Africa. It is the wild ancestor of the modern cattle ( Bos taurus ), and went extinct in 1627 probably as a consequence of human hunting and the progressive reduction of its habitat. To investigate in detail the genetic history of this species and to compare the population dynamics in different European areas, we analysed Bos primigenius remains from various sites across Italy. Results Fourteen samples provided ancient DNA fragments from the mitochondrial hypervariable region. Our data, jointly analysed with previously publis…