Numerical and experimental mapping of small root zones using optimized surface and borehole resistivity tomography

Geophysics ◽  
2011 ◽  
Vol 76 (2) ◽  
pp. G25-G35 ◽  
Author(s):  
Said Attia al Hagrey ◽  
Torsten Petersen
Keyword(s):  
Small Data ◽  
Optimization Approach ◽  
Electrode Arrays ◽  
Spatiotemporal Resolution ◽  
Data Set ◽  
Resistivity Tomography ◽  
Root Zones ◽  
Small Root ◽  
Input Model ◽  
Surface Borehole

An exact mapping of root zones is essential to understand plant growth, root biomass, and soil functions important for environmental and climatic management and protection. Numerical and experimental techniques of the electrical resistivity tomography were applied in 2D and 3D to resolve small root zones in the centimeter range. Numerically, we studied two scenarios of conductive and resistive root zones as a function of (1) eight different quadripole electrode configurations (standard, nonstandard, and optimized), (2) four different survey designs with electrode arrays at the soil surface and in boreholes, and (3) eight different inversion constraints. The best resolved output tomogram was evaluated semiquantitatively using the criteria of visual similarity to the input model, least data set, rms error, and iteration number and quantitatively by the model difference relative to the input model. The results showed that the surface-borehole configurations have the best resolution for the whole root zone. The single-surface and borehole surveys resolve only the respective upper and middle-lower root parts. The results reflect the potential of the optimization approach to generate small data sets of far higher resolution than the standard sets. Based on these results, we used the surface-borehole survey around a young hibiscus planted in a sandy soil in a laboratory experiment. The surface-borehole surveys using small, optimized configurations result in an optimum spatiotemporal resolution for simultaneous applications for 3D mapping of targets (root zones and water and soil heterogeneities) and 4D monitoring of their processes.

scholarly journals Computation of Optimized Electrode Arrays for 3-D Electrical Resistivity Tomography Surveys

2021 ◽  
Vol 11 (14) ◽  
pp. 6394
Author(s):  
Kleanthis Simyrdanis ◽  
Nikos Papadopoulos ◽  
Dimitrios Oikonomou
Keyword(s):  
Electrical Resistivity ◽  
Electrical Resistivity Tomography ◽  
Jacobian Matrix ◽  
Optimization Technique ◽  
Optimization Approach ◽  
Electrode Arrays ◽  
Data Set ◽  
Resistivity Tomography ◽  
Parallel Lines ◽  
Comprehensive Data

The present study explores the applicability and effectiveness of an optimization technique applied to electrical resistivity tomography data. The procedure is based on the Jacobian matrix, where the most sensitive measurements are selected from a comprehensive data set to enhance the least resolvable parameters of the reconstructed model. Two existing inversion programs in two and three dimensions are modified to incorporate this new approach. Both of them are selecting the optimum data from an initial comprehensive data set which is comprised of merged conventional arrays. With the two-dimensional (2-D) optimization approach, the most sensitive measurements are selected from a 2-D survey profile and then a clone of the resulting optimum profile reproduces a three-dimensional (3-D) optimum data set composed of equally spaced parallel lines. In a different approach, with the 3-D optimization technique, the optimum data are selected from a 3-D data set of equally spaced individual parallel lines. Both approaches are compared with Stummer’s optimization technique which is based on the resolution matrix. The Jacobian optimization approach has the advantage of selecting the optimum data set without the need for the solution of the inversion problem since the Jacobian matrix is calculated as part of the forward resistivity problem, thus being faster from previous published approached based on the calculation of the sensitivity matrix. Synthetic 3-D data based on the extension of previous published works for the 2-D optimization case and field data from two case studies in Greece are tested, thus verifying the validity of the present study, where fewer measurements from the initial data set (about 15–50%) are able to reconstruct a model similar with the one produced from the original comprehensive data set.

scholarly journals 2D Model Study of CO2Plumes in Saline Reservoirs by Borehole Resistivity Tomography

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Said A. al Hagrey
Keyword(s):  
Measurement Errors ◽  
Optimization Approach ◽  
Data Set ◽  
Current Electrode ◽  
Resistivity Tomography ◽  
Model Study ◽  
Cap Rock ◽  
The Common ◽  
Current Flows ◽  
Host Reservoir

The performance of electrical resistivity tomography (ERT) in boreholes is studied numerically regarding changes induced by CO2sequestration in deep saline reservoirs. The new optimization approach is applied to generate an optimized data set of only 4% of the comprehensive set but of almost similar best possible resolution. Diverse electrode configurations (mainly tripotentialαandβ) are investigated with current flows and potential measurements in different directions. An extensive 2.5D modeling (>100,000 models) is conducted systematically as a function of multiparameters related to hydrogeology, CO2plume, data acquisition and methodology. ERT techniques generally are capable to resolve storage targets (CO2plume, saline host reservoir, and impermeable cap rock), however with the common smearing effects and artefacts. Reconstructed tomograms show that the optimized and multiply oriented configurations have a better-spatial resolution than the lateral arrays with splitting of potential and current electrode pairs between boreholes. The later arrays are also more susceptible to telluric noise but have a lower level of measurement errors. The resolution advance of optimized and multiply oriented configurations is confirmed by lower values for ROI (region of index) and residual (relative model difference). The technique acceptably resolves targets with an aspect ratio down to 0.5.

On the Use of Blades Stagger and Stacking in Turbine Stage Optimization

2010 ◽  
Author(s):  
Mohammad Arabnia ◽  
Wahid Ghaly
Keyword(s):  
Three Dimensional ◽  
Small Data ◽  
Optimization Approach ◽  
Streamwise Vorticity ◽  
Ann Model ◽  
Data Set ◽  
Flow Losses ◽  
Design Variables ◽  
Artificial Neural Network Ann ◽  
Stage Efficiency

The flow in modern turbines is highly three dimensional and fairly complex. This paper presents a practical and effective optimization approach to minimize 3D-related flow losses by re-staggering and re-stacking the blades. This approach is applied to the redesign of a low speed high subsonic single stage turbine, that was designed and tested in Hannover, Germany. The optimization is performed at the design point and the objective function is given by a weighted sum of individual objectives, namely stage efficiency and streamwise vorticity downstream of the rotor and stator, and is penalized with one constraint, namely the design mass flow rate. A Genetic Algorithm (GA) is coupled with a Response Surface Approximation (RSA) of the Artificial Neural Network (ANN) type. A relatively small data set of high fidelity 3D flow simulations that is obtained using Fluent, is used to train and test the ANN model. The variation of stagger angle and stacking are parametrically represented using a quadratic rational Bezier curve (QRBC). The QRBC parameters are directly related to the design variables, namely the rotor and stator lean & sweep angles, and their stagger distribution. Moreover, it results in eliminating infeasible shapes and in reducing the number of design variables to a minimum while providing a wide design space for the blade shape. This optimization approach results in an improvement of 1.74% to 1.91% in stage efficiency. This optimization approach is found to be helpful in understanding the physical implications of the design variables and in interpreting their effect on the stage performance.

The Lyapunov Exponent Variance of an Electronic Manufacturing Enterprise’s Daily Qualified Rate Time Series by Improved Small Data Sets Approach

2012 ◽  
Vol 197 ◽  
pp. 271-277
Author(s):  
Zhu Ping Gong
Keyword(s):  
Time Series ◽  
Lyapunov Exponent ◽  
Chaotic Time Series ◽  
Quality System ◽  
Quality Level ◽  
Largest Lyapunov Exponent ◽  
Small Data ◽  
Data Set ◽  
Electronic Manufacturing ◽  
Small Data Set

Small data set approach is used for the estimation of Largest Lyapunov Exponent (LLE). Primarily, the mean period drawback of Small data set was corrected. On this base, the LLEs of daily qualified rate time series of HZ, an electronic manufacturing enterprise, were estimated and all positive LLEs were taken which indicate that this time series is a chaotic time series and the corresponding produce process is a chaotic process. The variance of the LLEs revealed the struggle between the divergence nature of quality system and quality control effort. LLEs showed sharp increase in getting worse quality level coincide with the company shutdown. HZ’s daily qualified rate, a chaotic time series, shows us the predictable nature of quality system in a short-run.

scholarly journals Classification of jujube defects in small data sets based on transfer learning

2021 ◽  
Author(s):  
Jianping Ju ◽  
Hong Zheng ◽  
Xiaohang Xu ◽  
Zhongyuan Guo ◽  
Zhaohui Zheng ◽  
...  
Keyword(s):  
Transfer Learning ◽  
Loss Function ◽  
Training Model ◽  
Parameter Distribution ◽  
Test Accuracy ◽  
Small Data ◽  
Data Sets ◽  
Data Set ◽  
Small Data Sets

AbstractAlthough convolutional neural networks have achieved success in the field of image classification, there are still challenges in the field of agricultural product quality sorting such as machine vision-based jujube defects detection. The performance of jujube defect detection mainly depends on the feature extraction and the classifier used. Due to the diversity of the jujube materials and the variability of the testing environment, the traditional method of manually extracting the features often fails to meet the requirements of practical application. In this paper, a jujube sorting model in small data sets based on convolutional neural network and transfer learning is proposed to meet the actual demand of jujube defects detection. Firstly, the original images collected from the actual jujube sorting production line were pre-processed, and the data were augmented to establish a data set of five categories of jujube defects. The original CNN model is then improved by embedding the SE module and using the triplet loss function and the center loss function to replace the softmax loss function. Finally, the depth pre-training model on the ImageNet image data set was used to conduct training on the jujube defects data set, so that the parameters of the pre-training model could fit the parameter distribution of the jujube defects image, and the parameter distribution was transferred to the jujube defects data set to complete the transfer of the model and realize the detection and classification of the jujube defects. The classification results are visualized by heatmap through the analysis of classification accuracy and confusion matrix compared with the comparison models. The experimental results show that the SE-ResNet50-CL model optimizes the fine-grained classification problem of jujube defect recognition, and the test accuracy reaches 94.15%. The model has good stability and high recognition accuracy in complex environments.

scholarly journals 2D–3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ryoya Shiode ◽  
Mototaka Kabashima ◽  
Yuta Hiasa ◽  
Kunihiro Oka ◽  
Tsuyoshi Murase ◽  
...  
Keyword(s):  
Wrist Joint ◽  
High Accuracy ◽  
Training Data ◽  
Small Data ◽  
Data Set ◽  
Accuracy Estimation ◽  
X Ray ◽  
Learning Network ◽  
Forearm Bone ◽  
Deep Learning Network

AbstractThe purpose of the study was to develop a deep learning network for estimating and constructing highly accurate 3D bone models directly from actual X-ray images and to verify its accuracy. The data used were 173 computed tomography (CT) images and 105 actual X-ray images of a healthy wrist joint. To compensate for the small size of the dataset, digitally reconstructed radiography (DRR) images generated from CT were used as training data instead of actual X-ray images. The DRR-like images were generated from actual X-ray images in the test and adapted to the network, and high-accuracy estimation of a 3D bone model from a small data set was possible. The 3D shape of the radius and ulna were estimated from actual X-ray images with accuracies of 1.05 ± 0.36 and 1.45 ± 0.41 mm, respectively.

A Comparison Study of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition

2005 ◽  
Author(s):  
Jungeui Hong ◽  
Elizabeth A. Cudney ◽  
Genichi Taguchi ◽  
Rajesh Jugulum ◽  
Kioumars Paryani ◽  
...  
Keyword(s):  
Neural Network ◽  
Small Data ◽  
Data Sets ◽  
Comparison Study ◽  
Data Set ◽  
Set Size ◽  
Breast Cancer Study ◽  
Discriminant Ability ◽  
Small Data Sets ◽  
Multivariate Pattern

The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to compare the ability of the Mahalanobis-Taguchi System and a neural network to discriminate using small data sets. We examine the discriminant ability as a function of data set size using an application area where reliable data is publicly available. The study uses the Wisconsin Breast Cancer study with nine attributes and one class.

Decennial multi-approach monitoring of thermo-hydro-mechanical processes, Kammstollen outdoor laboratory, Zugspitze (Germany)

2021 ◽  
Author(s):  
Riccardo Scandroglio ◽  
Till Rehm ◽  
Jonas K. Limbrock ◽  
Andreas Kemna ◽  
Markus Heinze ◽  
...  
Keyword(s):  
Electrical Resistivity ◽  
Electrical Resistivity Tomography ◽  
Environmental Research ◽  
Permafrost Degradation ◽  
Earth Surface ◽  
Data Set ◽  
Resistivity Tomography ◽  
Near Surface ◽  
Permafrost Rock ◽  
Austrian Alps

<p>The warming of alpine bedrock permafrost in the last three decades and consequent reduction of frozen areas has been well documented. Its consequences like slope stability reduction put humans and infrastructures at high risk. 2020 in particular was the warmest year on record at 3000m a.s.l. embedded in the warmest decade.</p><p>Recently, the development of electrical resistivity tomography (ERT) as standard technique for quantitative permafrost investigation allows extended monitoring of this hazard even allowing including quantitative 4D monitoring strategies (Scandroglio et al., in review). Nevertheless thermo-hydro-mechanical dynamics of steep bedrock slopes cannot be totally explained by a single measurement technique and therefore multi-approach setups are necessary in the field to record external forcing and improve the deciphering of internal responses.</p><p>The Zugspitze Kammstollen is a 850m long tunnel located between 2660 and 2780m a.s.l., a few decameters under the mountain ridge. First ERT monitoring was conducted in 2007 (Krautblatter et al., 2010) and has been followed by more than one decade of intensive field work. This has led to the collection of a unique multi-approach data set of still unpublished data. Continuous logging of environmental parameters such as rock/air temperatures and water infiltration through joints as well as a dedicated thermal model (Schröder and Krautblatter, in review) provide important additional knowledge on bedrock internal dynamics. Summer ERT and seismic refraction tomography surveys with manual and automated joints’ displacement measurements on the ridge offer information on external controls, complemented by three weather stations and a 44m long borehole within 1km from the tunnel.</p><p>Year-round access to the area enables uninterrupted monitoring and maintenance of instruments for reliable data collection. “Precisely controlled natural conditions”, restricted access for researchers only and logistical support by Environmental Research Station Schneefernerhaus, make this tunnel particularly attractive for developing benchmark experiments. Some examples are the design of induced polarization monitoring, the analysis of tunnel spring water for isotopes investigation, and the multi-annual mass monitoring by means of relative gravimetry.</p><p>Here, we present the recently modernized layout of the outdoor laboratory with the latest monitoring results, opening a discussion on further possible approaches of this extensive multi-approach data set, aiming at understanding not only permafrost thermal evolution but also the connected thermo-hydro-mechanical processes.</p><p> </p><p> </p><p>Krautblatter, M. et al. (2010) ‘Temperature-calibrated imaging of seasonal changes in permafrost rock walls by quantitative electrical resistivity tomography (Zugspitze, German/Austrian Alps)’, Journal of Geophysical Research: Earth Surface, 115(2), pp. 1–15. doi: 10.1029/2008JF001209.</p><p>Scandroglio, R. et al. (in review) ‘4D-Quantification of alpine permafrost degradation in steep rock walls using a laboratory-calibrated ERT approach (in review)’, Near Surface Geophysics.</p><p>Schröder, T. and Krautblatter, M. (in review) ‘A high-resolution multi-phase thermo-geophysical model to verify long-term electrical resistivity tomography monitoring in alpine permafrost rock walls (Zugspitze, German/Austrian Alps) (submitted)’, Earth Surface Processes and Landforms.</p>

P–184 Assisted hatching does not improve live birth rates, a prospective double-blinded randomized study

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
V Montalvo ◽  
J Masso ◽  
A Garcia-Faura ◽  
B Marques ◽  
M Lopez-Teijon
Keyword(s):  
Live Birth ◽  
Human Embryos ◽  
Assisted Hatching ◽  
Small Data ◽  
Success Rates ◽  
Birth Rates ◽  
Data Set ◽  
Positive Effects ◽  
Live Birth Rates ◽  
Frozen Embryo Transfers

Abstract Study question Does Assisted hatching (AH) improve success rates when applied to frozen embryo transfers? Summary answer AH does not improve implantation, ongoing pregnancy or live birth rates when applied to thawed embryos. What is known already Vitrification has been proven to be the most efficient technique to preserve human embryos. However, vitrification has some consequences for the embryos, zona pellucida (ZP) hardening being one of them. Multiple studies suggest the need to apply laser Assisted hatching or ZP thinning to thawed embryos in order to improve success rates. Still, there is not enough evidence to ensure the utility of AH, and considering the great variation in design between studies more evidence is needed. Study design, size, duration Study performed from October 2019 and January 2020. Disregarding embryos with natural Hatching and PGT-A. Embryos that, immediately after thawing, were completely expanded (trophectoderm in contact with ZP) were also excluded from the study. We applied a randomization to choose in which embryos we had to perform AH. Neither the gynecologist nor the embryologist performing the embryo transfer knew whether the embryo had AH performed or not. Participants/materials, setting, methods 353 frozen embryo transfers of one blastocist were considered for the study, 71 excluded for expansion after thawing, 65 excluded because of PGT-A, 103 in which we performed AH (AH+) and 114 without AH (AH-). In the AH+ group we performed laser-AH of 1/3 of the ZP, avoiding to damage the trophectoderm and performing the laser shots as far away to the ICM as possible. We used Chi-square testing to assess the effects of AH. Main results and the role of chance We assessed all relevant clinical data parameters. No statistical differences were found in egg age, maternal age, embryo quality, nor endometrial thickness between groups. Implantation and miscarriage rates were equivalent between AH+ group (40.9%; 20.5%) and AH- group (47.4%; 18.5%). The main outcome of this study was live birth rates. No statistical differences were found between groups (AH-= 38.6%; AH + = 30.1%; p = 03221) proving that making it easier to get out of the ZP does not affect success rates. Analyzing the data from the excluded embryos we found no improvement on live birth rates when embryos were expanded just after thawing (38.0%; p = 0.457). As expected, PGT-A embryos yielded higher live birth rates (52.3%; p < 0,05) Limitations, reasons for caution Preliminary study with a small data set. Wider implications of the findings: This study suggest that thawed embryos have the capacity to get out of the ZP regardless if AH was performed or not. Having no positive effects, AH seems to be unnecessary in this scenario. Trial registration number Not applicable

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