Today, information networks play an important role in supply chain management. Therefore, in this article, clustering-based routing protocols, which are one of the most important ways to reduce energy consumption in wireless sensor networks, are used to optimize the supply chain informational cloud network. Accordingly, first, a clustering protocol is presented using self-organizing map neu...

Both the Self-Organizing Map (SOM) and fuzzy ARTMAP neural network are trained based upon the competitive mechanism and use the “winner-take-all” rule. Previous studies developed soft classification algorithms for the SOM. This paper introduces the idea and proposes non-parametric measures for the fuzzy ARTMAP computational neural networks to handle spatial uncertainty in remotely sensed imager...

hot-wire spirometer uses a constant temperature anemometer (cta) for its operation. the working principle of cta, used for the measurement of fluid velocity and flow turbulence, is based on convective heat transfer from a hot-wire sensor to a fluid being measured. the calibration curve of a cta is nonlinear and cannot be easily extrapolated beyond its calibration range. therefore, a method for ...

The modular network SOM (mnSOM) proposed by authors is an extension and generalization of a conventional SOM in which each nodal unit is replaced by a module such as a neural network. It is expected that the mnSOM will extend the area of applications beyond that of a conventional SOM. We set out to establish the theory and algorithm of a mnSOM, and to apply it to several research topics, to cre...

Network activity in the lateral central amygdala (CeL) plays a crucial role in fear learning and emotional processing. However, the local circuits of the CeL are not fully understood and have only recently begun to be explored in detail. Here, we characterized the intrinsic circuits in the CeL using paired whole-call patch-clamp recordings, immunohistochemistry, and optogenetics in C57BL/6J wil...

Self-Organizing Map (SOM) is an unsupervised learning neural network and it is used for preserving the structural relationships in the data without prior knowledge. SOM has been applied in the study of complex problems such as vector quantizations, combinatorial optimization, and pattern recognition. This paper proposes a new usage of SOM as a tool for schema transformation hoping to achieve mo...

Large datasets can be analyzed through different linear and nonlinear methods. Most frequently used linear method is Principal Component Analysis (PCA) known also as EOF (Empirical Orthogonal Function) analysis, permitting both clustering and visualizing high-dimensional data items. However, many problems are nonlinear in nature, so, for analyzing such a problems some nonlinear methods will be ...

Subtypes of GABAergic interneurons (INs) are crucial for cortical function, yet their specific roles are largely unknown. In contrast to supra- and infragranular layers, where most somatostatin-expressing (SOM) INs are layer 1-targeting Martinotti cells, the axons of SOM INs in layer 4 of somatosensory cortex largely remain within layer 4. Moreover, we found that whereas layers 2/3 SOM INs targ...

A Web-based business always wants to have the ability to track users’ browsing behavior history. This ability can be achieved by using Web log mining technologies. In this paper, we introduce a Self-Organizing Map (SOM) based approach to mining Web log data. The SOM network maps the web pages into a two-dimensional map based on the users’ browsing history. Web pages with the similar browsing pa...