Hydraulic properties at the North Sea island of Borkum derived from joint inversion of magnetic resonance and electrical resistivity soundings

For reliably predicting the impact of climate changes on salt/freshwater systems below barrier islands, a long-term hydraulic modelling is inevitable. As input we need the parameters porosity, salinity and hydraulic conductivity at the catchment scale, preferably non-invasively acquired with geophysical methods. We present a methodology to retrieve the searched parameters and a lithological interpretation by the joint analysis of magnetic resonance soundings (MRS) and vertical electric soundings (VES). Both data sets are jointly inverted for resistivity, water content and decay time using a joint inversion scheme. Coupling is accomplished by common layer thicknesses. <br><br> We show the results of three soundings measured on the eastern part of the North Sea island of Borkum. Pumping test data is used to calibrate the petrophysical relationship for the local conditions in order to estimate permeability from nuclear magnetic resonance (NMR) data. Salinity is retrieved from water content and resistivity using a modified Archie equation calibrated by local samples. As a result we are able to predict porosity, salinity and hydraulic conductivities of the aquifers, including their uncertainties. <br><br> The joint inversion significantly improves the reliability of the results. Verification is given by comparison with a borehole. A sounding in the flooding area demonstrates that only the combined inversion provides a correct subsurface model. Thanks to the joint application, we are able to distinguish fluid conductivity from lithology and provide reliable hydraulic parameters as shown by uncertainty analysis. <br><br> These findings can finally be used to build groundwater flow models for simulating climate changes. This includes the improved geometry and lithological attribution, and also the parameters and their uncertainties

Hydraulic properties at the North Sea island of Borkum derived from joint inversion of magnetic resonance and electrical resistivity soundings

For reliably predicting the impact of climate changes on salt/freshwater systems below barrier islands, a long-term hydraulic modelling is inevitable. As input we need the parameters porosity, salinity and hydraulic conductivity at the catchment scale, preferably non-invasively acquired with geophysical methods. We present a methodology to retrieve the searched parameters and a lithological interpretation by the joint analysis of magnetic resonance soundings (MRS) and vertical electric soundings (VES). Both data sets are jointly inverted for resistivity, water content and decay time using a joint inversion scheme. Coupling is accomplished by common layer thicknesses. We show the results of three soundings measured on the eastern part of the North Sea island of Borkum. Pumping test data is used to calibrate the petrophysical relationship for the local conditions in order to estimate permeability from nuclear magnetic resonance (NMR) data. Salinity is retrieved from water content and resistivity using a modified Archie equation calibrated by local samples. As a result we are able to predict porosity, salinity and hydraulic conductivities of the aquifers, including their uncertainties. The joint inversion significantly improves the reliability of the results. Verification is given by comparison with a borehole. A sounding in the flooding area demonstrates that only the combined inversion provides a correct subsurface model. Thanks to the joint application, we are able to distinguish fluid conductivity from lithology and provide reliable hydraulic parameters as shown by uncertainty analysis. These findings can finally be used to build groundwater flow models for simulating climate changes. This includes the improved geometry and lithological attribution, and also the parameters and their uncertainties. © Author(s) 2012

Improving the accuracy of 1D SNMR surveys using the multi-central-loop configuration

Temeljna svrha i cilj ovoga rada bilo je ispitati koliko su potrošači skloni dijeljenju svojih turističkih iskustva s drugima te putem kojih medija. Osim navedenog, drugi cilj provedenog istraživanja bilo je utvrditi koliko su potrošačima važna iskustva i komentari drugih posjetitelja u procesu donošenja odluke o kupnji. Istraživanje je provedeno metodom ispitivanja, a kao instrument korišten je anketni upitnik sastavljen od 22 pitanja. Utvrđivanjem problema istraživanja, postavljene su tri hipoteze. Od tri hipoteze, u potpunosti je dokazana samo prva koja pretpostavlja da su potrošačima tuđa iskustva i komentari od velike važnosti kod planiranja i odabira putovanja. Druga hipoteza je djelomično potvrđena, tj. potvrđeno je da su potrošači skloni dijeliti svoja iskustva s drugima u situaciji kada su jako zadovoljni dok s druge strane nije potvrđeno kako su potrošači skloni dijeliti svoja iskustva u situaciji kada su nezadovoljni uslugom ili proizvodom. Na kraju, potvrđena je i treća hipoteza koja pretpostavlja kako su potrošači skloni dijeljenju vlastitog turističkog iskustva putem više društvenih medija, iako je utvrđeno kako najveći broj ispitanika ne dijeli svoja turistička iskustva. Istraživano je i mišljenje ispitanika o turističkoj destinaciji iz snova, a iznenađujuće, najveći broj ispitanika je navelo hrvatske destinacije kao svoje destinacije iz snova kao i one koje su im dosada pružile najnezaboravnije turističko iskustvo. Potrebno je provesti detaljnija istraživanja kako bi se detaljnije istražilo novije društvene medije koji su dostupni potrošačima za dijeljenje svog iskustva

Improving the accuracy of 1D SNMR surveys using the multi-central-loop configuration

A multi-central loop configuration has been studied through forward and inverse modelling of synthetics and real data. This set-up takes advantage of the multichannel features of the NMR device and consists of using several (2 to 3) additional receiver loops displayed concentrically with the main transmitter/receiver loop, which all record the NMR signal simultaneously within a single acquisition. If the loop diameters are chosen appropriately, the kernel sensitivity distributions for each receiver loop can show complementary features. Inverting simultaneously the data sets obtained through each different receiver loop can then enhance the accuracy of the final model. To do so, a 1D QT inversion scheme in the frequency domain dedicated to the inversion of multiple data sets is being used. One challenging feature is to adapt the regularization of the inverse process so as to handle correctly the noise originating from different data sets. The efficiency of this multi-central loop acquisition set-up and procedure is being assessed through the forward and inverse modelling of several scenarios implying varying aquifer characteristics. Finally a field case is being presented that was conducted on a low noise level site located in Germany, where conditions were favourable to the implementation and testing of circular multi-central loop configurations.We also introduce a new method for determining NMR parameters, named the prediction-focused-approach (PFA), that is based on statistical analysis of a large number of simple models. We observe, using synthetic examples, that the effciency of the method benefits from the use of the multi-central-loop configurations

Software Product Line Engineering via Software Transplantation

For companies producing related products, a Software Product Line (SPL) is a software reuse method that improves time-to-market and software quality, achieving substantial cost reductions.These benefits do not come for free. It often takes years to re-architect and re-engineer a codebase to support SPL and, once adopted, it must be maintained. Current SPL practice relies on a collection of tools, tailored for different reengineering phases, whose output developers must coordinate and integrate. We present Foundry, a general automated approach for leveraging software transplantation to speed conversion to and maintenance of SPL. Foundry facilitates feature extraction and migration. It can efficiently, repeatedly, transplant a sequence of features, implemented in multiple files. We used Foundry to create two valid product lines that integrate features from three real-world systems in an automated way. Moreover, we conducted an experiment comparing Foundry's feature migration with manual effort. We show that Foundry automatically migrated features across codebases 4.8 times faster, on average, than the average time a group of SPL experts took to accomplish the task

Evolving AVX512 Parallel C Code Using GP

Using 512 bit Advanced Vector Extensions, previous development history and Intel documentation, BNF grammar based genetic improvement automatically ports RNAfold to AVX, giving up to a 1.77 fold speed up. The evolved code pull request is an accepted GI software maintenance update to bioinformatics package ViennaRNA

A Survey of Genetic Improvement Search Spaces

Genetic Improvement (GI) uses automated search to improve existing software. Most GI work has focused on empirical studies that successfully apply GI to improve software's running time, fix bugs, add new features, etc. There has been little research into why GI has been so successful. For example, genetic programming has been the most commonly applied search algorithm in GI. Is genetic programming the best choice for GI? Initial attempts to answer this question have explored GI's mutation search space. This paper summarises the work published on this question to date

Gin: Genetic Improvement Research Made Easy

Genetic improvement (GI) is a young field of research on the cusp of transforming software development. GI uses search to improve existing software. Researchers have already shown that GI can improve human-written code, ranging from program repair to optimising run-time, from reducing energy-consumption to the transplantation of new functionality. Much remains to be done. The cost of re-implementing GI to investigate new approaches is hindering progress. Therefore, we present Gin, an extensible and modifiable toolbox for GI experimentation, with a novel combination of features. Instantiated in Java and targeting the Java ecosystem, Gin automatically transforms, builds, and tests Java projects. Out of the box, Gin supports automated test-generation and source code profiling. We show, through examples and a case study, how Gin facilitates experimentation and will speed innovation in GI

Test Model Coverage Analysis under Uncertainty

In model-based testing (MBT) we may have to deal with a non-deterministic model, e.g. because abstraction was applied, or because the software under test itself is non-deterministic. The same test case may then trigger multiple possible execution paths, depending on some internal decisions made by the software. Consequently, performing precise test analyses, e.g. to calculate the test coverage, are not possible. This can be mitigated if developers can annotate the model with estimated probabilities for taking each transition. A probabilistic model checking algorithm can subsequently be used to do simple probabilistic coverage analysis. However, in practice developers often want to know what the achieved aggregate coverage, which unfortunately cannot be re-expressed as a standard model checking problem. This paper presents an extension to allow efficient calculation of probabilistic aggregate coverage, and moreover also in combination with k-wise coverage