Chemical recalcitrance of biomolecules, physical protection by soil minerals and spatial inaccessibility to decomposer organisms are hypothesized to be primary controls on soil organic matter (SOM) turnover. Previous studies have observed increased sequestration of plant derived aliphatic compounds in experimentally warmed soils but did not identify the mechanisms for this enhanced preservation...

As a neural approach, Kohonen's Self-Organizing Map (SOM) has not been explored as thoroughly as the MLP, especially for the soft classification. In this paper, we propose two non-parametric algorithms for the SOM to provide soft classification outputs. These algorithms, which are labeling-frequency-based and are called SOM Commitment (SOMC) and SOM Typicality (SOM-T), expressing in the first c...

Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data cannot be analyzed by fully automatic methods but require the involvement of the human analyst’s expertise. For a comprehensive analysis, the data need to be considered from two complementary perspectives: (1) as spatial di...

BACKGROUND Sphincter of Oddi manometry (SOM) is recommended in the evaluation of suspected Type II sphincter of Oddi dysfunction (SOD2), though its utility is uncertain. Little is known about the practice of expert endoscopists in the United States regarding SOD2. METHODS An anonymous electronic survey was distributed to 128 expert biliary endoscopists identified from U.S. advanced endoscopy ...

This paper focuses on an automated ANN classification system consisting of two modules: an unsupervised Kohonen’s Self-Organizing Mapping (SOM) neural network module, and a supervised Multilayer Perceptron (MLP) neural network module using the Backpropagation (BP) training algorithm. Two training algorithms were provided for the SOM network module: the standard SOM, and a refined SOM learning a...

We propose a site-occupying model (SOM) to evaluate hydrogen solubility in metal because there is a discrepancy between the concept of the site-blocking model and experimental fact, as shown in this work. SOM is based on the experimental fact that hydrogen atoms in metal cannot come closer to each other than about 0.21 nm under hydrogen pressure of 1 MPa or less. We evaluate the hydrogen solubi...

We have experimented with a bio-inspired selforganizing texture and hardness perception system which automatically learns to associate the representations of the two submodalities with each other. To this end we have developed a microphone based texture sensor and a hardness sensor that measures the compression of the material at a constant pressure. The system is based on a novel variant of th...

Based on the Self-Organizing Map (SOM) algorithm, development of effective solutions for visual analysis and retrieval in complex data is possible. Example application domains include retrieval in multimedia data bases, and analysis in financial, text, and general highdimensional data sets. While early work defined basic concepts for data representation and visual mappings for SOM-based analysi...

In this paper we provide an in-depth evaluation of the SOM as a feasible tool for nonlinear adaptive filtering. A comprehensive survey of existing SOM-based and related architectures for learning input-output mappings is carried out and the application of these architectures to nonlinear adaptive filtering is formulated. Then, we introduce two simple procedures for building RBF-based nonlinear ...

The kernel method has become a useful trick and has been widely applied to various learning models to extend their nonlinear approximation and classification capabilities. Such extensions have also recently occurred to the Self-Organising Map (SOM). In this paper, two recently proposed kernel SOMs are reviewed, together with their link to an energy function. The Self-Organising Mixture Network ...