A Canonical Genetic Algorithm for Blind Inversion of Linear Channels

It is well known the relationship between source separation and blind deconvolution: If a filtered version of an unknown i.i.d. signal is observed, temporal independence between samples can be used to retrieve the original signal, in the same manner as spatial independence is used for source separation. In this paper we propose the use of a Genetic Algorithm (GA) to blindly invert linear channels. The use of GA is justified in the case of small number of samples, where other gradient-like methods fails because of poor estimation of statistics.

Blind channel deconvolution of real world signals using source separation techniques

In this paper we present a method for blind deconvolution of linear channels based on source separation techniques, for real word signals. This technique applied to blind deconvolution problems is based in exploiting not the spatial independence between signals but the temporal independence between samples of the signal. Our objective is to minimize the mutual information between samples of the output in order to retrieve the original signal. In order to make use of use this idea the input signal must be a non-Gaussian i.i.d. signal. Because most real world signals do not have this i.i.d. nature, we will need to preprocess the original signal before the transmission into the channel. Likewise we should assure that the transmitted signal has non-Gaussian statistics in order to achieve the correct function of the algorithm. The strategy used for this preprocessing will be presented in this paper. If the receiver has the inverse of the preprocess, the original signal can be reconstructed without the convolutive distortion.

Alkali Content of Fly Ash – Measuring and Testing Strategies for Compliance, TR-628, 2015

Sodium and potassium are the common alkalis present in fly ash. Excessive amounts of fly ash alkalis can cause efflorescence problems in concrete products and raise concern about the effectiveness of the fly ash to mitigate alkali-silica reaction (ASR). The available alkali test, which is commonly used to measure fly ash alkali, takes approximately 35 days for execution and reporting. Hence, in many instances the fly ash has already been incorporated into concrete before the test results are available. This complicates the job of the fly ash marketing agencies and it leads to disputes with fly ash users who often are concerned with accepting projects that contain materials that fail to meet specification limits. The research project consisted of a lab study and a field study. The lab study focused on the available alkali test and how fly ash alkali content impacts common performance tests (mortar-bar expansion tests). Twenty-one fly ash samples were evaluated during the testing. The field study focused on the inspection and testing of selected, well documented pavement sites that contained moderately reactive fine aggregate and high-alkali fly ash. A total of nine pavement sites were evaluated. Two of the sites were control sites that did not contain fly ash. The results of the lab study indicated that the available alkali test is prone to experimental errors that cause poor agreement between testing labs. A strong (linear) relationship was observed between available alkali content and total alkali content of Class C fly ash. This relationship can be used to provide a quicker, more precise method of estimating the available alkali content. The results of the field study failed to link the use of high-alkali fly ash with the occurrence of ASR in the various concrete sites. Petrographic examination of the pavement cores indicated that Wayland sand is an ASR-sensitive aggregate. This was in good agreement with Iowa DOT field service records. It was recommended that preventative measures should be used when this source of sand is used in concrete mixtures.

A non-linear Bayesian approach for upscaling local-scale hydraulic conductivity measurements based on local- and regional-scale geophysical data

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Cardiac motion estimation by joint alignment of tagged MRI sequences

Image registration has been proposed as an automatic method for recovering cardiac displacement fields from Tagged Magnetic Resonance Imaging (tMRI) sequences. Initially performed as a set of pairwise registrations, these techniques have evolved to the use of 3D+t deformation models, requiring metrics of joint image alignment (JA). However, only linear combinations of cost functions defined with respect to the first frame have been used. In this paper, we have applied k-Nearest Neighbors Graphs (kNNG) estimators of the -entropy (H ) to measure the joint similarity between frames, and to combine the information provided by different cardiac views in an unified metric. Experiments performed on six subjects showed a significantly higher accuracy (p < 0.05) with respect to a standard pairwise alignment (PA) approach in terms of mean positional error and variance with respect to manually placed landmarks. The developed method was used to study strains in patients with myocardial infarction, showing a consistency between strain, infarction location, and coronary occlusion. This paper also presentsan interesting clinical application of graph-based metric estimators, showing their value for solving practical problems found in medical imaging.

Statistical mechanics of multi-edge networks

Statistical properties of binary complex networks are well understood and recently many attempts have been made to extend this knowledge to weighted ones. There are, however, subtle yet important considerations to be made regarding the nature of the weights used in this generalization. Weights can be either continuous or discrete magnitudes, and in the latter case, they can additionally have undistinguishable or distinguishable nature. This fact has not been addressed in the literature insofar and has deep implications on the network statistics. In this work we face this problem introducing multiedge networks as graphs where multiple (distinguishable) connections between nodes are considered. We develop a statistical mechanics framework where it is possible to get information about the most relevant observables given a large spectrum of linear and nonlinear constraints including those depending both on the number of multiedges per link and their binary projection. The latter case is particularly interesting as we show that binary projections can be understood from multiedge processes. The implications of these results are important as many real-agent-based problems mapped onto graphs require this treatment for a proper characterization of their collective behavior.

Economics of Using Calcium Chloride vs. Sodium Chloride for Deicing/Anti-Icing, TR-488, 2008

The use of chemicals is a critical part of a pro-active winter maintenance program. However, ensuring that the correct chemicals are used is a challenge. On the one hand, budgets are limited, and thus price of chemicals is a major concern. On the other, performance of chemicals, especially at lower pavement temperatures, is not always assured. Two chemicals that are used extensively by the Iowa Department of Transportation (Iowa DOT) are sodium chloride (or salt) and calcium chloride. While calcium chloride can be effective at much lower temperatures than salt, it is also considerably more expensive. Costs for a gallon of salt brine are typically in the range of $0.05 to $0.10, whereas calcium chloride brine may cost in the range of $1.00 or more per gallon. These costs are of course subject to market forces and will thus change from year to year. The idea of mixing different winter maintenance chemicals is by no means new, and in general discussions it appears that many winter maintenance personnel have from time to time mixed up a jar of chemicals and done some work around the yard to see whether or not their new mix “works.” There are many stories about the mixture turning to “mayonnaise” (or, more colorfully, to “snot”) suggesting that mixing chemicals may give rise to some problems most likely due to precipitation. Further, the question of what constitutes a mixture “working” in this context is a topic of considerable discussion. In this study, mixtures of salt brine and calcium chloride brine were examined to determine their ice melting capability and their freezing point. Using the results from these tests, a linear interpolation model of the ice melting capability of mixtures of the two brines has been developed. Using a criterion based upon the ability of the mixture to melt a certain thickness of ice or snow (expressed as a thickness of melt-water equivalent), the model was extended to develop a material cost per lane mile for the full range of possible mixtures as a function of temperature. This allowed for a comparison of the performance of the various mixtures. From the point of view of melting capacity, mixing calcium chloride brine with salt brine appears to be effective only at very low temperatures (around 0° F and below). However, the approach described herein only considers the material costs, and does not consider application costs or other aspects of the mixture performance than melting capacity. While a unit quantity of calcium chloride is considerably more expensive than a unit quantity of sodium chloride, it also melts considerably more ice. In other words, to achieve the same result, much less calcium chloride brine is required than sodium chloride brine. This is important in considering application costs, because it means that a single application vehicle (for example, a brine dispensing trailer towed behind a snowplow) can cover many more lane miles with calcium chloride brine than with salt brine before needing to refill. Calculating exactly how much could be saved in application costs requires an optimization of routes used in the application of liquids in anti-icing, which is beyond the scope of the current study. However, this may be an area that agencies wish to pursue for future investigation. In discussion with winter maintenance personnel who use mixtures of sodium chloride and calcium chloride, it is evident that one reason for this is because the mixture is much more persistent (i.e. it stays longer on the road surface) than straight salt brine. Operationally this persistence is very valuable, but at present there are not any established methods to measure the persistence of a chemical on a pavement. In conclusion, the study presents a method that allows an agency to determine the material costs of using various mixtures of salt brine and calcium chloride brine. The method is based upon the requirement of melting a certain quantity of snow or ice at the ice-pavement interface, and on how much of a chemical or of a mixture of chemicals is required to do that.

A new heuristic method for solving spatially constrained forest planning problems based on mitigation of infeasibilities radiating outward from a forced choice

[Abstract]

Short-term stability of testosterone and epitestosterone conjugates in urine samples: quantification by liquid chromatography-linear ion trap mass spectrometry.

A simple method using liquid chromatography-linear ion trap mass spectrometry for simultaneous determination of testosterone glucuronide (TG), testosterone sulfate (TS), epitestosterone glucuronide (EG) and epitestosterone sulfate (ES) in urine samples was developed. For validation purposes, a urine containing no detectable amount of TG, TS and EG was selected and fortified with steroid conjugate standards. Quantification was performed using deuterated testosterone conjugates to correct for ion suppression/enhancement during ESI. Assay validation was performed in terms of lower limit of detection (1-3ng/mL), recovery (89-101%), intraday precision (2.0-6.8%), interday precision (3.4-9.6%) and accuracy (101-103%). Application of the method to short-term stability testing of urine samples at temperature ranging from 4 to 37 degrees C during a time-storage of a week lead to the conclusion that addition of sodium azide (10mg/mL) is required for preservation of the analytes.

Simulating maize phenology as a function of air temperature with a linear and a nonlinear model

The objective of this study was to adapt a nonlinear model (Wang and Engel - WE) for simulating the phenology of maize (Zea mays L.), and to evaluate this model and a linear one (thermal time), in order to predict developmental stages of a field-grown maize variety. A field experiment, during 2005/2006 and 2006/2007 was conducted in Santa Maria, RS, Brazil, in two growing seasons, with seven sowing dates each. Dates of emergence, silking, and physiological maturity of the maize variety BRS Missões were recorded in six replications in each sowing date. Data collected in 2005/2006 growing season were used to estimate the coefficients of the two models, and data collected in the 2006/2007 growing season were used as independent data set for model evaluations. The nonlinear WE model accurately predicted the date of silking and physiological maturity, and had a lower root mean square error (RMSE) than the linear (thermal time) model. The overall RMSE for silking and physiological maturity was 2.7 and 4.8 days with WE model, and 5.6 and 8.3 days with thermal time model, respectively.