Maximum Path Information and Fokker-Planck Equation

We present in this paper a rigorous method to derive the nonlinear Fokker-Planck (FP) equation of anomalous diffusion directly from a generalization of the principle of least action of Maupertuis proposed by Wang for smooth or quasi-smooth irregular dynamics evolving in Markovian process. The FP equation obtained may take two different but equivalent forms. It was also found that the diffusion constant may depend on both q (the index of Tsallis entropy) and the time t.Comment: 7 page

Optimising energy efficiency of non-orthogonal multiple access for wireless backhaul in heterogeneous cloud radio access network

This paper studies the downlink problem of a cloud-based central station (CCS) to multiple base stations (BSs) in a heterogeneous cellular network sharing the same time and frequency resources. We adopt non-orthogonal multiple access (NOMA) and propose power allocation for the wireless downlink in the heterogeneous cloud radio access network (HCRAN). Taking into account practical channel modelling with power consumptions at BSs of different cell types (e.g. macro-cell, micro-cell, etc.) and backhauling power, we analyse the energy efficiency (EE) of the practical HCRAN utilising NOMA. Simulation results indicate that the proposed NOMA for the HCRAN outperforms the conventional orthogonal frequency division multiple access (OFDMA) scheme in terms of providing higher EE of up to four times. Interestingly, the results reveal a fact that the EE of the NOMA approach is not always an increasing function of the number of BSs but varies as a quasiconcave function. This motivates us to further introduce an optimisation problem to find the optimal number of BSs that maximises the EE of the HCRAN. It is shown that, with a low power supply at the CCS, a double number of micro BSs can be served by HCRAN providing an improved EE of up to 1.6 times compared to the macro BSs and RRHs, while they achieve the same EE performance with high-power CCS

Aspect-Based Sentiment Analysis Using a Two-Step Neural Network Architecture

The World Wide Web holds a wealth of information in the form of unstructured texts such as customer reviews for products, events and more. By extracting and analyzing the expressed opinions in customer reviews in a fine-grained way, valuable opportunities and insights for customers and businesses can be gained. We propose a neural network based system to address the task of Aspect-Based Sentiment Analysis to compete in Task 2 of the ESWC-2016 Challenge on Semantic Sentiment Analysis. Our proposed architecture divides the task in two subtasks: aspect term extraction and aspect-specific sentiment extraction. This approach is flexible in that it allows to address each subtask independently. As a first step, a recurrent neural network is used to extract aspects from a text by framing the problem as a sequence labeling task. In a second step, a recurrent network processes each extracted aspect with respect to its context and predicts a sentiment label. The system uses pretrained semantic word embedding features which we experimentally enhance with semantic knowledge extracted from WordNet. Further features extracted from SenticNet prove to be beneficial for the extraction of sentiment labels. As the best performing system in its category, our proposed system proves to be an effective approach for the Aspect-Based Sentiment Analysis

Rate of convergence in the Smoluchowski-Kramers approximation for mean-field stochastic differential equations

In this paper we study a second-order mean-field stochastic differential systems describing the movement of a particle under the influence of a time-dependent force, a friction, a mean-field interaction and a space and time-dependent stochastic noise. Using techniques from Malliavin calculus, we establish explicit rates of convergence in the zero-mass limit (Smoluchowski-Kramers approximation) in the $L^p$-distances and in the total variation distance for the position process, the velocity process and a re-scaled velocity process to their corresponding limiting processes