Estimating derivatives and integrals with Kriging

International audienceThis paper formalizes a methodology based on Kriging, a technique developped by geostatisticians, for estimating derivatives and integrals of signals that are only known via possibly irregularly spaced and noisy observations. This finds direct applications, e.g., in system identification when differential algebra is used to express parameters as nonlinear functions of the inputs and outputs and their derivatives. The procedure is quite simple to implement, and allows confidence intervals on the predicted values to be derived

An informational approach to the global optimization of expensive-to-evaluate functions

In many global optimization problems motivated by engineering applications, the number of function evaluations is severely limited by time or cost. To ensure that each evaluation contributes to the localization of good candidates for the role of global minimizer, a sequential choice of evaluation points is usually carried out. In particular, when Kriging is used to interpolate past evaluations, the uncertainty associated with the lack of information on the function can be expressed and used to compute a number of criteria accounting for the interest of an additional evaluation at any given point. This paper introduces minimizer entropy as a new Kriging-based criterion for the sequential choice of points at which the function should be evaluated. Based on \emph{stepwise uncertainty reduction}, it accounts for the informational gain on the minimizer expected from a new evaluation. The criterion is approximated using conditional simulations of the Gaussian process model behind Kriging, and then inserted into an algorithm similar in spirit to the \emph{Efficient Global Optimization} (EGO) algorithm. An empirical comparison is carried out between our criterion and \emph{expected improvement}, one of the reference criteria in the literature. Experimental results indicate major evaluation savings over EGO. Finally, the method, which we call IAGO (for Informational Approach to Global Optimization) is extended to robust optimization problems, where both the factors to be tuned and the function evaluations are corrupted by noise.Comment: Accepted for publication in the Journal of Global Optimization (This is the revised version, with additional details on computational problems, and some grammatical changes

Interactions of maize and Italian ryegrass in a living mulch system: (2)Nitrogen and water dynamics

Water and nitrogen availability may limit the growth of the main crop competing with a cover crop in a living mulch system. Some aspects of the dynamics of water (soil water content and deep percolation) and nitrogen (concentration in soil solution and leachate) were studied in maize (Zea mays L.) sown into a bare soil (BS, conventional cropping) or into a living Italian ryegrass (Lolium multiflorum Lam.) mulch (LM) during three years. Eight lysimeters (1.0 by 1.0m square surface area and 1.1m deep) with ceramic suction cups, TDR probes and a drainage pipe were used each. In LM a 0.3m wide strip was kept free of grass around the maize row. The living mulch reduced the soil water content between 0.3 and 0.9m soil depth, which remained lower even after intense rainfall. Deep percolation over the entire maize crop season was at least 40% lower in the LM compared to the BS treatment. In LM the nitrate concentrations in the soil solution and in the leachate (usually <10mgL−1) were very low. In BS the nitrate concentration in the leachate reached as much as 70mgL−1. Losses of N in LM did not reach 1% of the values observed in BS. Reduced water and N availability in LM contribute to explain the decrease in growth and yield of the maize plants, and are in good agreement with the dense root system developed in this cropping system as compared to BS. The challenge for the development of living mulch systems is to improve the uptake of water and nitrogen by the roots of the main crop in a competitive environment without affecting the capacity of the cover crop to prevent N losses by leachin

Identifying and modeling the integrated design process of net Zero Energy buildings

peer reviewedHigh Performance Buildings (HPB), including Net Zero Energy Buildings (NZEBs) and nearly Zero Energy Buildings (nZEB) are emerging as an important market in Europe and around the world. However, there are very few studies that aim to model the process of HPBs and define key design processes, decisions and competencies of design teams. More importantly, there is hardly any documentation processes on tools currently being used to design high performance building. Therefore, the purpose of this paper is to identify, model and propose a generic integrated process maps for HPB. The generic process map focuses on the design phases steps, roles and tools used. The research methodology is based on literature review and a case study. With the help of a process modelling software (TIBCO), a Swiss office building (Green Office) is used to validate the produced process maps. The visual maps delivers insights on the integrated design process reporting on the means of improving the delivery of HPBs

Kriging for indirect measurement, with application to flow measurement

International audienceKriging, a technique originating from geostatistics, is employed to build black-box models to be used to predict a quantity of interest based on the values taken by some experimental factors. This attractive alternative to more popular techniques such as neural networks is first presented. It is then applied to the measurement of the flow in a water pipe from the observation of speed at given points of a cross section. A pure black-box model turns out not to be satisfactory, and two approaches are suggested for incorporating prior knowledge. The second one, which is more systematic also turns out to provide much better performance

Bayesian optimization for parameter identification on a small simulation budget

International audienceBayesian optimization uses a probabilistic model of the objective function to guide the search for the optimum. It is particularly interesting for the optimization of expensive-to-evaluate functions. For the last decade, it has been increasingly used for industrial optimization problems and especially for numerical design involving complex computer simulations. We feel that Bayesian optimization should be considered with attention by anyone who has to identify the parameters of a model based on a very limited number of model simulations because of model complexity. In this paper, we wish to describe, as simply as possible, how Bayesian optimization can be used in parameter identification and to present a new application. We concentrate on two algorithms, namely EGO (for Efficient Global Optimization) and IAGO (for Informational Approach to Global Optimization), and describe how they can be used for parameter identification when the budget for evaluating the cost function is severely limited. Some open questions that must be addressed for theoretical and practical reasons are indicated

High Sensitivity Array Observations of the z=4.4z = 4.4 QSO BRI 1335-0417

We present sensitive phase-referenced VLBI results on the radio continuum emission from the $z=4.4$ QSO BRI 1335--0417. The observations were carried out at 1.4 GHz using the High Sensitivity Array (HSA). Our sensitive VLBI image at $189 \times 113$ mas ($1.25 \times 0.75$ kpc) resolution shows continuum emission in BRI 1335--0417 with a total flux density of $208 \pm 46 \mu$Jy, consistent with the flux density measured with the VLA. The size of the source at FWHM is $255 \times 138$ mas ($1.7 \times 0.9$ kpc) and the derived intrinsic brightness temperature is $\sim 3.5\times 10^4$ K. No continuum emission is detected at the full VLBI resolution ($32 \times 7$ mas, $211 \times 46$ pc), with a 4$\sigma$ point source upper limit of 34 $\mu$Jy beam$^{-1}$, or an upper limit to the intrinsic brightness temperature of $5.6\times 10^5$ K. The highest angular resolution with at least a 4.5$\sigma$ detection of the radio continuum emission is $53 \times 27$ mas ($0.35 \times 0.18$ kpc). At this resolution, the image shows a continuum feature in BRI 1335--0417 with a size of $64 \times 35$ mas ($0.42 \times 0.23$ kpc) at FWHM, and intrinsic brightness temperature of $\sim 2\times 10^5$ K. The extent of the observed continuum sources at 1.4 GHz and the derived brightness temperatures show that the radio emission (and thus presumably the far-infrared emission) in BRI 1335--0417 is powered by a major starburst, with a massive star formation rate of order a few thousand M_{\odot} {\rm yr}^{-1}$. Moreover, the absence of any compact high-brightness temperature source suggests that there is no radio-loud AGN in this$z=4.4$ QSO.Comment: 13 pages, 3 figures, AJ accepte

Potential Environmental and Health Impact of Pesticides Use and Safety Measures Adopted by Cocoa Farmers in Akyemansa District in the Eastern Region of Ghana

Pesticides are used in agriculture to control pests and diseases which affect crops and farm animals, and hence to increase yield.  Pesticides are used by most farmers in the production of cocoa in Ghana. However, the improper use of pesticides can adversely affect the environment and human health. This study was conducted to assess the likely environmental and human health impact of the different pesticides used, and the safety measures adopted during pesticide application by cocoa farmers in the Akyemansa District, Ghana. Data were collected from 250 randomly selected farmers using interviews, field observations and focus group discussions on the pesticides used by the cocoa farmers, the safety measures adopted and the time of application. The total Environmental Impact Quotient (EIQ) values of the different pesticides used were determined, and were used to compare their likely impact on the environment and human health. Demographic data collected were analyzed using SPSS version 16 software package. Results from this study showed that, the farmers used 24 pesticides, out of which 10 (41.6%) were insecticides, 8 (33.3%) were herbicides, and 6 (25%) were fungicides. The total EIQ values of the different pesticides used ranged between 55.58 and 15.33.  130 (52%) of the respondents did not use Personal Protective Equipments (PPEs). Also, 145 (58%) respondents applied the pesticides and waited for some days before harvesting the cocoa. Over half, 156 (62.4%) of the respondents ate their meal before the application of pesticides, 70 (28%) ate their meals when they finished spraying after either washing their hands with water and soap or water only. But the rest stopped the spraying, ate their meals and continued. Cocoa farmers in Akyemansa mostly used insecticides to control pests and diseases and also adopted both safe and unsafe measures during pesticide application. Chlorfenvinphos, an insecticide had the highest total EIQ value (55.58), while Glyphosate, a herbicide had the lowest value (15.33). Bifenthrin (Akate master) and Imidacloprid (Confidor), moderately hazardous insecticides were most likely to impact negatively on the environment and human health. Keywords: Pesticides, Environmental Impact Quotient, Health, Safety, Cocoa

A powerful radio-loud quasar at the end of cosmic reionization

We present the discovery of the radio-loud quasar PSO J352.4034-15.3373 at z=5.84 pm 0.02. This quasar is the radio brightest source known, by an order of magnitude, at z~6 with a flux density in the range of 8-100 mJy from 3GHz to 230MHz and a radio loudness parameter R>~1000. This source provides an unprecedented opportunity to study powerful jets and radio-mode feedback at the highest redshifts, and presents the first real chance to probe deep into the neutral intergalactic medium by detecting 21 cm absorption at the end of cosmic reionization.Comment: ApJL accepted on May 8, 2018. See the companion paper by Momjian et a

Global optimization of expensive-to-evaluate functions: an empirical comparison of two sampling criteria

In many global optimization problems motivated by engineering applications, the number of function evaluations is severely limited by time or cost. To ensure that each of these evaluations usefully contributes to the localization of good candidates for the role of global minimizer, a stochastic model of the function can be built to conduct a sequential choice of evaluation points. Based on Gaussian processes and Kriging, the authors have recently introduced the informational approach to global optimization (IAGO) which provides a onestep optimal choice of evaluation points in terms of reduction of uncertainty on the location of the minimizers. To do so, the probability density of the minimizers is approximated using conditional simulations of the Gaussian process model behind Kriging. In this paper, an empirical comparison between the underlying sampling criterion called conditional minimizer entropy (CME) and the standard expected improvement sampling criterion (EI) is presented. Classical tests functions are used as well as sample paths of the Gaussian model and an actual industrial application. They show the interest of the CME sampling criterion in terms of evaluation savings