Evaluation of the Immobilization of Coexisting Heavy Metal Ions of Pb, Cd , and Zn from Water by Dairy Manure-Derived Biochar: Performance and Reusability.

Heavy metals including Cd, Pb, and Zn are prevalent stormwater and groundwater contaminants derived from natural and human activities, and there is a lack of cost-effective treatment for their removal. Recently, biochar has been increasingly recognized as a promising low-cost sorbent that can be used to remediate heavy metal contaminated water. This study evaluates the immobilization/release performance of dairy manure-derived biochar (DM-BC) as a sustainable material for competitive removal of coexisting heavy metal ions from water and explains the underlying mechanism for regeneration/reusability of biochar.

Removal of Fluoride from Water Using a Calcium-Modified Dairy Manure-Derived Biochar.

This study investigated the removal of fluoride from water using a calcium-modified dairy manure-derived biochar (Ca-DM500). The Ca-DM500 showed a 3.82 - 8.

Query-based learning for aerospace applications.

Models of real-world applications often include a large number of parameters with a wide dynamic range, which contributes to the difficulties of neural network training. Creating the training data set for such applications becomes costly, if not impossible. In order to overcome the challenge, one can employ an active learning technique known as query-based learning (QBL) to add performance-critical data to the training set during the learning phase, thereby efficiently improving the overall learning/generalization.

Cancer classification using loss of heterozygosity data derived from single-nucleotide polymorphism genotyping arrays.

Single-Nucleotide Polymorphism (SNP) array is a recently introduced technology that genotypes more than 10,000 human SNPs on a single array. It has been shown that genome-wide Loss of Heterozygosity (LOH) calls can be derived by analyzing the genotypes calls measured by SNP arrays using paired tumor and normal tissue samples. The goal of this study is to evaluate the possibility of cancer classification using LOH calls.

ANNSTLF-a neural-network-based electric load forecasting system.

A key component of the daily operation and planning activities of an electric utility is short-term load forecasting, i.e., the prediction of hourly loads (demand) for the next hour to several days out.

Iterative image restoration using approximate inverse preconditioning.

Removing a linear shift-invariant blur from a signal or image can be accomplished by inverse or Wiener filtering, or by an iterative least-squares deblurring procedure. Because of the ill-posed characteristics of the deconvolution problem, in the presence of noise, filtering methods often yield poor results. On the other hand, iterative methods often suffer from slow convergence at high spatial frequencies.

Recognition and pose estimation of unoccluded three-dimensional objects from a two-dimensional perspective view by banks of neural networks.

This paper describes a neural network (NN) based system for recognition and pose estimation of an unoccluded three-dimensional (3-D) object from any single two-dimensional (2-D) perspective view. The approach is invariant to translation, orientation, and scale. First, the binary silhouette of the object is obtained and normalized for translation and scale.

Stereopsis by constraint learning feed-forward neural networks.

A neural network (NN) approach to the problem of steropsis is presented. The correspondence problem (finding the correct matches between pixels of the epipolar lines of the stereo pair from among all the possible matches) is posed as a noniterative many-to-one mapping. Two multilayer feedforward NNs are utilized to learn and code this nonlinear and complex mapping using the backpropagation learning rule and a training set.

Age-related differences in binocular backward masking with visual noise.

Peripheral processing, as defined by Turvey (1973), was investigated in a study of binocular backward masking involving random visual noise. For young (mean age 20.3 years) and old (mean age 55.