13300465
Robust sequence memory in sparsely-connected networks with controllable steady-state period
A novel sparsely-connected neural network for sequence memory with controllable steady-state period is proposed in this study. By introducing a new exponential kernel sampling function and the sampling interval parameter, the steady-state period can be controlled, and the steady-state time steps is equal to the sampling interval parameter. Ascribing to the exponential kernel sampling function, the sequence storage capacity is enlarged compared with the existing sequence memory models. Owning to the sparsely-connected of Gaussian distribution, the model produces the efficient use of synapse resources, but the sequence storage capacity is decreased compared with the fully-connected networks. The study also gives a significant result that the networks of different dimensions have the same synapse connection efficiency if they are with the same connection mean degree.
16312564
A new hybrid model for time-series prediction
This paper proposed a new hybrid model in order to increase time series prediction accuracy. This hybrid model considers the routine time prediction technique like AR, ANN or any others as atomic building block. A linear hybrid technique is used to combine their forecast result into the final result. The hybrid algorithm was tested against three different kinds of time series data. Experiments results showed the effectiveness of the proposed hybrid model.
18984298
Block Standstill and Homogeneity Based Fast Motion Estimation Algorithm for H.264 Video Coding
The paper proposed a fast motion estimation algorithm based on the spatial homogeneity and temporal standstill of video sequences. It classified a frame into different regions such as standstill, stationary or dynamic region. For MBs lying in the standstill region, motion estimation is skipped; for MBs lying in the stationary region, motion estimation is applied once to an MB in the region, and the resulting motion vector will be used by other MBs in the same region. Normal motion estimation is only carried out in the dynamic region. The new algorithm can be used either by itself alone, or by combining with other existing fast motion estimation methods. Experimental results show that the new algorithm can significantly improve the time efficiency of the H.264 encoder, and is able to achieve an average reduction of 27% in encoding, with an average PSNR loss of only 0.09 dB and 0.42% bit rate increase, compared with the original H.264 reference software.
14283892
Analyzing the Energy-Time Trade-Off in High-Performance Computing Applications
Although users of high-performance computing are most interested in raw performance both energy and power consumption has become critical concerns. One approach to lowering energy and power is to use high-performance cluster nodes that have several power-performance states so that the energy-time trade-off can be dynamically adjusted. This paper analyzes the energy-time trade-off of a wide range of applications-serial and parallel-on a power-scalable cluster. We use a cluster of frequency and voltage-scalable AMD-64 nodes, each equipped with a power meter. We study the effects of memory and communication bottlenecks via direct measurement of time and energy. We also investigate metrics that can, at runtime, predict when each type of bottleneck occurs. Our results show that, for programs that have a memory or communication bottleneck, a power-scalable cluster can save significant energy with only a small time penalty. Furthermore, we find that, for some programs, it is possible to both consume less energy and execute in less time by increasing the number of nodes while reducing the frequency-voltage setting of each node
10141936
Complexity-based rate distortion optimization with perceptual tuning for scalable video coding
This paper has proposed a content adaptive rate-distortion optimization scheme for scalable video coding. To adaptively determine the tradeoff between texture and motion coding, the scheme first makes use of spatial and temporal complexities to adjust the Lagrangian multiplier for all the macroblocks in a frame. After that, the Lagrangian multiplier for every macroblock of the frame is further refined using local perceptual cues. To ensure optimal local selection of the Lagrangian multiplier, several characteristics of human visual system have been taken into account to guide the adjustment. Experiments have shown that the proposed scheme could effectively adapt the adjustment of Lagrangian multiplier to video contents and the subjective quality of the reconstructed frames could be improved without compromising PSNR.
8585778
Web-based infectious disease reporting using XML forms
OBJECTIVE
Exploring solutions for infectious disease information sharing among hospital and public health information systems is imperative to the improvement of disease surveillance and emergent response. This paper aimed at developing a method to directly transmit real-time data of notifiable infectious diseases from hospital information systems to public health information systems on the Internet by using a standard eXtensible Markup Language (XML) format.


METHODS
The mechanism and work flow by which notifiable infectious disease data are created, reported and used at health agencies in China was evaluated. The capacity of all participating providers to use electronic data interchange to submit transactions of data required for the notifiable infectious disease reporting was assessed. The minimum data set at national level that is required for reporting for national notifiable infectious disease surveillance was determined. The standards and techniques available worldwide for electronic health data interchange, such as XML, HL7 messaging, CDA and ATSM CCR, etc. were reviewed and compared, and an XML implementation format needed for this purpose was defined for hospitals that are able to access the Internet to provide a complete infectious disease reporting.


RESULTS
There are 18,703 county or city hospitals in China. All of them have access to basic information infrastructures including computers, e-mail and the Internet. Nearly 10,000 hospitals possess hospital information systems used for electronically recording, retrieving and manipulating patients' information. These systems collect 23 data items required in the minimum data set for national notifiable infectious disease reporting. In order to transmit these data items to the disease surveillance system and local health information systems instantly and without duplication of data input, an XML schema and a set of standard data elements were developed to define the content, structure and semantics of the data set. These standards make it possible to view and analyse the data accurately outside the hospital information systems in many different document formats. The paper also identified other issues involved in notifiable disease reporting in the future, such as the adoption of approved vocabulary standards and implementation problems such as the route, secure transfer, parsing, and objective identifying of the XML message.


CONCLUSIONS
XML is an increasingly important standard for exchange and transmission of data between disparate applications and systems. As in its early stages of developing an interoperable health information system in China, the XML document structures could be a way to exchange the notifiable case information among interest parties on the web at present.
207290821
Discriminating between photorealistic computer graphics and natural images using fractal geometry
Rendering technology in computer graphics (CG) is now capable of producing highly photorealistic images, giving rise to the problem of how to identify CG images from natural images. Some methods were proposed to solve this problem. In this paper, we give a novel method from a new point of view of image perception. Although the photorealistic CG images are very similar to natural images, they are surrealistic and smoother than natural images, thus leading to the difference in perception. A part of features are derived from fractal dimension to capture the difference in color perception between CG images and natural images, and several generalized dimensions are used as the rest features to capture difference in coarseness. The effect of these features is verified by experiments. The average accuracy is over 91.2%.