Whetstone Trained Spiking Deep Neural Networks to Spiking Neural Networks

A deep neural network is a non-spiking artificial neural network which uses multiple structured layers to extract features from the input. Spiking neural networks are another type of artificial neural network which closely mimic biology with time dependent pulses to transmit information. Whetstone is a training algorithm for spiking deep neural networks. It modifies the back propagation algorithm, typically used in deep learning, to train a spiking deep neural network, by converting the activation function found in deep neural networks into a threshold used by a spiking neural network. This work converts a spiking deep neural network trained from Whetstone to a traditional spiking neural network in the TENNLab framework. This conversion decomposes the dot product operation found in the convolutional layer of spiking deep neural networks to synapse connections between neurons in traditional spiking neural networks. The conversion also redesigns the neuron and synapse structure in the convolutional layer to trade time for space. A new architecture is created in the TENNLab framework using traditional spiking neural networks, which behave the same as the spiking deep neural network trained by Whetstone before conversion. This new architecture verifies the converted spiking neural network behaves the same as the original spiking deep neural network. This work can convert networks to run on other architectures from TENNLab, and this allows networks from those architectures to be trained with back propagation from Whetstone. This expands the variety of training techniques available to the TENNLab architectures

Media as Other Information for Fundamental Valuation

The media is an important information intermediary. We investigate the informational role of the media by examining whether media content, measured by the sentiment of news articles, contains information about a firm’s fundamental value beyond that conveyed in earnings, book value, and analyst forecasts. We show that incorporating media content into Ohlson’s (1995) residual income model generally improves its ability to predict future residual income, explain current stock prices, and predict future stock prices. Our results are strengthened when media coverage is higher and when media sentiment is more disperse

Emerging smart design of electrodes for micro-supercapacitors: a review

Owing to high power density and long cycle life, micro-supercapacitors (MSCs) are regarded as a prevalent energy storage unit for miniaturized electronics in modern life. A major bottleneck is achieving enhanced energy density without sacrificing both power density and cycle life. To this end, designing electrodes in a “smart” way has emerged as an effective strategy to achieve a trade-off between the energy and power densities of MSCs. In the past few years, considerable research efforts have been devoted to exploring new electrode materials for high capacitance, but designing clever configurations for electrodes has rarely been investigated from a structural point of view, which is also important for MSCs within a limited footprint area, in particular. This review article categorizes and arranges these “smart” design strategies of electrodes into three design concepts: layer-by-layer, scaffold-assisted and rolling origami. The corresponding strengths and challenges are comprehensively summarized, and the potential solutions to resolve these challenges are pointed out. Finally, the smart design principle of the electrodes of MSCs and key perspectives for future research in this field are outlined

A comparative study of marginal loss pricing algorithms in electricity markets

Due to the development of new technologies, change of generation mix and appearance of newly formed energy supply hubs, there is a large year-on-year change in the marginal loss factors in power systems. Since any change of marginal loss factors could have significant impacts on payment of loads and profitability of generators, it is necessary to carry out a comparative study on the loss factor-based locational marginal pricing methods. Considering that a systematic comparison of various locational marginal pricing methods has not been reported in existing publications, this work presents a comparative study of the loss factor-based locational marginal pricing methods that are widely adopted in electricity markets. Advantages and disadvantages of each locational marginal pricing method are explored in detail, and could serve as references in selecting appropriate locational marginal pricing methods in practice. The selected five locational marginal pricing models are tested in two standard power systems, that is, the IEEE 5-bus and 39-bus systems. Then, through numerical experiments and detailed analysis, key findings about the reference point dependency of loss factors, accuracy of loss estimation, load payment, generation income, and market settlement surplus are summarised and elaborated. It is found that marginal loss factors-based locational marginal pricing methods tend to produce a higher market settlement surplus and can lead to a lower generation income than other locational marginal pricing methods

CCD photometric study of the W UMa-type binary II CMa in the field of Berkeley 33

The CCD photometric data of the EW-type binary, II CMa, which is a contact star in the field of the middle-aged open cluster Berkeley 33, are presented. The complete R light curve was obtained. In the present paper, using the five CCD epochs of light minimum (three of them are calculated from Mazur et al. (1993)'s data and two from our new data), the orbital period P was revised to 0.22919704 days. The complete R light curve was analyzed by using the 2003 version of W-D (Wilson-Devinney) program. It is found that this is a contact system with a mass ratio $q=0.9$ and a contact factor $f=4.1$. The high mass ratio ($q=0.9$) and the low contact factor ($f=4.1$) indicate that the system just evolved into the marginal contact stage

Wetting equilibrium in a rectangular channel

When a capillary channel with corners is wetted by a fluid, there are regions where the fluid fills the whole cross-section and regions where only the corners are filled by the fluid. The fluid fraction of the partially-filled region, $s^*$, is an important quantity related to the capillary pressure. We calculate the value of $s^*$ for channels with a cross-section slightly deviated from a rectangle: the height is larger in the center than those on the two short sides. We find that a small change in the cross-section geometry leads to a huge change of $s^*$. This result is consistent with experimental observations.Comment: 23 pages, 8 figures, submitted to Soft Matte