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Signed networks with positive and negative links attract considerable interest in their studying since they contain more information than unsigned networks. Community detection and sign (or attitude) prediction are still primary challenges, as the fundamental problems of signed network analysis. For this, a generative Bayesian approach is presented wherein 1) a signed stochastic blockmodel is proposed...
A simulation model for analyzing electromagnetic on-body wave propagations is proposed. The simulation method utilizes motion capture input data, a simplified human phantom model, and full wave electromagnetic simulation methods. A comparison of simulation results and experimental data for differently-sized human body models is shown.
The advancement of the Internet of Things and wireless sensors has paved the way for the development of new services for next-generation healthcare systems to enable superior communication between healthcare professionals. This paper presents key components of the Wiki-Health Analysis Framework, which enables an ecosystem to support scientists, developers, and professionals to publish their data analysis...
Recent developments of modern technologies such as cloud computing, wearable sensor devices and big data have significantly impacted people's daily lives, and offer real potential for an Internet-wide, people-centric ecosystem. These advances in technology will considerably extend human capabilities in acquiring, consuming and sharing personal health information. A future in which we are all equipped...
This paper discusses the urban simulation technology and application, and study for key technology mainly in erecting models for huge city zone. According to the request of urban simulation, we explain the key technology, such as construction of the models, technological route and three-dimensional scene, etc. in detail. Finally, we provide the conclusion.
High frequency stock return data tend to exhibit characteristics such as volatility clustering, volatility persistence, leverage effects, and properties of abnormal unconditional distributions reflected in the form of skewness, high peakedness, and excess kurtosis. Although traditional GARCH models that employ leptokurtic distributions have been found useful to account for the conditional heteroscedasticity...
Through analyzing non-linear, time-varying characteristics of the economic system and summing up the basic idea of nonlinear economic model, BP neural network is used to do non-linear economic modeling methodology and specific implementation steps, by which new ideas is put forward for the existence of model, and implementation of the circumstances in Matlab is given.
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