Multilayer Perceptrons (MLP) are formulated within Support Vector Machine (SVM) framework by constructing multilayer networks of SVMs. The coupled approximation scheme can take advantage of generalization capabilities of the SVM and the combinatory feature of the hidden layer of MLP. The network, the Multilayer Kerceptron (MLK) assumes its own backpropagation procedure that we shall derive here...

We present a new deterministic relational model derived from convolutional neural networks. Search-Convolutional Neural Networks (SCNNs) extend the notion of convolution to graph search to construct a rich latent representation that extracts local behavior from general graph-structured data. Unlike other neural network models that take graph-structured data as input, SCNNs have a parameterizati...

Quantitative analysis of superoxide anion (O2(·-)) has increasing importance considering its potential damages to organism. Herein, a novel Mn-superoxide dismutase (MnSOD) mimics, silica-manganous phosphate (SiO2-Mn3(PO4)2) nanoparticles, were designed and synthesized by surface self-assembly processes that occur on the surface of silica-phytic acid (SiO2-PA) nanoparticles. The composite nanopa...

During morphogenesis, various cellular activities are spatiotemporally coordinated on the protein regulatory background to construct the complicated, three-dimensional (3D) structures of organs. Computational simulations using 3D vertex models have been the focus of efforts to approach the mechanisms underlying 3D multicellular constructions, such as dynamics of the 3D monolayer or multilayer c...

Accurately modeling and predicting performance for largescale applications becomes increasingly difficult as system complexity scales dramatically. Analytic predictive models are useful, but are difficult to construct, usually limited in scope, and often fail to capture subtle interactions between architecture and software. In contrast, we employ multilayer neural networks trained on input data...

A current problem in microfluidics is that poly(dimethylsiloxane) (PDMS), used to fabricate many microfluidic devices, is not compatible with most organic solvents. Fluorinated compounds are more chemically robust than PDMS but, historically, it has been nearly impossible to construct valves out of them by multilayer soft lithography (MSL) due to the difficulty of bonding layers made of "non-st...

In recent years, both multilayer perceptrons and networks of spiking neurons have been used in applications ranging from detailed models of specific cortical areas to image processing. A more challenging application is to find solutions to functional equations in order to gain insights to underlying phenomena. Finding the roots of real valued monotonically increasing function mappings is the so...

abstract infiltration process is one of the most important components of the hydrological cycle. on the other hand, the direct measurement of infiltration process is laborious, time consuming and expensive. in this study, the possibility of predicting cumulative infiltration in specific time intervals, using readily available soil data and artificial neural networks (anns) was investigated. for...

Characterizing large-scale organization in networks, including multilayer networks, is one of the most prominent topics in network science and is important for many applications. One type of mesoscale feature is community structure, in which sets of nodes are densely connected internally but sparsely connected to other dense sets of nodes. Two of the most popular approaches for community detect...

  In this work,copper/palladium (Cu/Pd) multilayer nanowires were successfully prepared by electrodeposition method using polycarbonate template. The fabrication of Pd/Cu multilayer nanowires was controlled by analyzing the current–time transient during electrodeposition using potentiostat. The morphological properties of the nanowires were studied by scanning electron microscopy (SEM) and resu...