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...

Solid phase microextraction (SPME) coupled with gas chromatography was employed to estimate bioavailability of pyrene in soils with different properties of textures, organic matter contents (SOM) and aging periods. Experimental results indicated that biodegradation rates increased from 0.10 (sandy loam) to 0.15 (silty loam) microg g-1 hr1. By contrast, biodegradation rate decreased from 0.10(1....

Hippocampal theta rhythm arises from a combination of recently described intrinsic theta oscillators and inputs from multiple brain areas. Interneurons expressing the markers parvalbumin (PV) and somatostatin (SOM) are leading candidates to participate in intrinsic rhythm generation and principal cell (PC) coordination in distal CA1 and subiculum. We tested their involvement by optogenetically ...

Soil organic matter (SOM) is an important component of soils, and knowing the spatial distribution and variation of SOM is the premise for sustainably utilizing soils. The objective of this study was to compare geographically weighted regression (GWR) with regression kriging (RK) for estimating the spatial distribution of SOM using field-sample data in SOM and auxiliary data in correlated envir...

In the paper, text mining and visualization by self-organizing map (SOM) are investigated. At first, textual information must be converted into numerical one. The results of text mining and visualization depend on the conversion. So, the influence of some control factors (the common word list and usage of the stemming algorithm) on text mining results, when a document dictionary is created, is ...

We propose a neural preprocess approach for video-based gesture recognition system. Second-order neural network (SONN) and self-organizing map (SOM) are employed for extracting moving hand regions and for normalizing motion features respectively. The SONN is more robust to noise than frame difference technique. Obtained velocity feature vectors are translated into normalized feature space by th...

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...

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 ...

In this paper, we propose an enhanced parallel Selforganizing Map (SOM) framework based on heterogeneous system platform, specifically Central Processing Unit (CPU) and Graphic Processing Unit (GPU) soldered together on a single chip. The framework is to improve speed of parallel SOM using GPU since processing parallel SOM on GPU burden by communication latency due to isolate device architectur...