One of the features of wireless sensor networks is that the nodes in this network have limited power sources. Therefore, assessment of energy consumption in these networks is very important. What has been common practice has been the use of traditional simulators to evaluate the energy consumption of the nodes in these networks. Simulators often have problems such as fluctuating output values i...

in this study, several artificial neural networks (anns) were developed to estimate seed and grain corn yields in parsabad moghan, iran. the data was collected by a face-to-face interview method from 144 corn farms during 2011. the energy ratios for seed and grain corns were calculated as 0.89 and 2.65, respectively. several multilayer perceptron anns with six neurons in the input layer and one...

Considered in this short note is the design of output layer nodes of feedforward neural networks for solving multi-class classification problems with r (r ≥ 3) classes of samples. The common and conventional setting of output layer, called “one-to-one approach” in this paper, is as follows: The output layer contains r output nodes corresponding to the r classes. And for an input sample of the i...

We present all the 3D CNN models in the experiment section. We experiment with projective D-TSDF volumes with different resolution values: 16, 32 and 64. Figure 1a presents the network architecture when the input is projective D-TSDF volumes with 32×32×32 resolution. We use this 3D CNN model to compare with state-of-the-art methods on the MSRA dataset [2] and the NYU dataset [3]. However, when ...

Hepatic stellate cell (HSC) activation is the critical event of liver fibrosis. Abnormality of miR-16 expression induces their activation. However, the action model of miR-16 remains to be elucidated because of its multiple-targeted manner. Here, we report that miR-16 restoration exerted a wide-range impact on transcriptome (2,082 differentially expressed transcripts) of activated HSCs. Integra...

A virtual chemical spectrophotometer for the simultaneous analysis of nickel (Ni) and cobalt (Co) was developed based on an artificial neural network (ANN). The developed ANN correlates the respective concentrations of Co and Ni given the absorbance profile of a Co-Ni mixture based on the BeerâĂŹs Law. The virtual chemical spectrometer was trained using a 3-layer jump connection neural network ...

A feed-forward multilayer neural net is trained to learn the correspondence between seismic data and well logs. The introduction of a virtual input layer, connected to the nominal input layer through a special nonlinear transfer function, enables ultrafast (single iteration), near-optimal training of the net using numerical algebraic techniques. A unique computer code, named DeepNet, has been d...

A hierarchical self-organising neural network is described for the detection of unusual pedestrian behaviour in video-based surveillance systems. The system is trained on a normal data set, with no prior information about the scene under surveillance, thereby requiring minimal user input. Nodes use a trace activation rule and feedforward connections, modified so that higher layer nodes are sens...