International Journal of Modern Physics C

Speech enhancement has been an intensive research for several decades to enhance the noisy speech that is corrupted by additive noise, multiplicative noise or convolutional noise. Even after decades of research it is still the most challenging problem, because most papers rely on estimating the noise during the nonspeech activity assuming that the background noise is uncorrelated (statistically independent of speech signal), nonstationary and slowly varying, so that the noise characteristics estimated in the absence of speech can be used subsequently in the presence of speech, whereas in a real time environment such assumptions do not hold for all the time. In this paper, we discuss the historical development of approaches that starts from the year 1970 to, the recent, 2013 for enhancing the noisy speech corrupted by additive background noise. Seeing the history, there are algorithms that enhance the noisy speech very well as long as a specific application is concerned such as the In-car noisy environments. It has to be observed that a speech enhancement algorithm performs well with a good estimation of the noise Power Spectral Density (PSD) from the noisy speech. Our idea pops up based on this observation, for online speech enhancement (i.e. in a real time environment) such as mobile phone applications, instead of estimating the noise from the noisy speech alone, the system should be able to monitor an environment continuously and classify it. Based on the current environment of the user, the system should adapt the algorithm (i.e. enhancement or estimation algorithm) for the current environment to enhance the noisy speech.

We develop a heterogeneous continuum model based upon a car-following model for a nonlane-based system taking lateral separation into account. The criterion for linear stability analysis and traveling wave solution of the homogeneous case is studied. The consideration of the lateral separation not only stabilizes the flow but also shrinks the critical region. For heterogeneous case, the fundamental diagram is examined for two different equilibrium speed-density functions and the effect of lane width is investigated for different compositions of heterogeneous traffic. The theoretical findings agree well with the results of numerical simulation which justifies the applicability of the model to a nonlane-based system.

In this paper, we demonstrate a set of fundamental conditions required for the formulation of a thermohydrodynamic lattice Boltzmann model at an arbitrary Prandtl number. A specific collision operator form is then proposed that is in compliance with these conditions. It admits two independent relaxation times, one for viscosity and another for thermal conductivity. But more importantly, the resulting thermohydrodynamic equations based on such a collision operator form is theoretically shown to remove the well-known non-Galilean invariant artifact at nonunity Prandtl numbers in previous thermal lattice Boltzmann models with multiple relaxation times.

We study the introduction of lexical innovations into a community of language users. Lexical innovations, i.e. new term added to people's vocabulary, plays an important role in the process of language evolution. Nowadays, information is spread through a variety of networks, including, among others, online and offline social networks and the World Wide Web. The entire system, comprising networks of different nature, can be represented as a multi-layer network. In this context, lexical innovations diffusion occurs in a peculiar fashion. In particular, a lexical innovation can undergo three different processes: its original meaning is accepted; its meaning can be changed or misunderstood (e.g. when not properly explained), hence more than one meaning can emerge in the population. Lastly, in the case of a loan word, it can be translated into the population language (i.e. defining a new lexical innovation or using a synonym) or into a dialect spoken by part of the population. Therefore, lexical innovations cannot be considered simply as information. We develop a model for analyzing this scenario using a multi-layer network comprising a social network and a media network. The latter represents the set of all information systems of a society, e.g. television, the World Wide Web and radio. Furthermore, we identify temporal directed edges between the nodes of these two networks. In particular, at each time-step, nodes of the media network can be connected to randomly chosen nodes of the social network and vice versa. In doing so, information spreads through the whole system and people can share a lexical innovation with their neighbors or, in the event they work as reporters, by using media nodes. Lastly, we use the concept of "linguistic sign" to model lexical innovations, showing its fundamental role in the study of these dynamics. Many numerical simulations have been performed to analyze the proposed model and its outcomes.

While a more integrated central counterparty (CCP) network via interoperability will provide users more cost efficient clearing and settlement services, it also increases the default transmission through the system. Using epidemic spreading model, it is found that a vertically interoperated CCP network is more robust compared with a horizontally interoperated one when certain condition is satisfied. Variation of the different transmission rates from both internal and external sources leads to different equilibrium. The safe range which is free from the crisis explosion state is identified and can be reached with certain policy coordination among nations.

The local majority rule is extensively accepted as a paradigmatic model to reflect the formation of opinion. In this paper, we study a model of opinion formation where opinion update rule is not based on the majority rule or linear selection probability but on a strengthen selection probability controlled by an adjustable parameter β. In particular, our proposed probability function can proximately fit the two extreme cases–linear probability function and majority rule or in between the two cases under different values of β. By studying such model on different kinds of networks, including different regular networks and complex networks, we find that there exists an optimal value of β giving the most efficient convergence to consensus regardless of the topology of networks. This work reveals that, compared with the majority rule and linear selection probability, the strengthen selection probability might be a more proper model in understanding the formation of opinions in society.

The Schwinger model with N_f ≥ 2 flavors is a simple example for a fermionic model with zero chiral condensate Σ (in the chiral limit). We consider numerical data for two light flavors, based on simulations with dynamical chiral lattice fermions. We test properties and predictions that were put forward in the recent literature for models with Σ = 0, which include IR conformal theories. In particular, we probe the decorrelation of low lying Dirac eigenvalues, and we discuss the mass anomalous dimension and its IR extrapolation. Here, we encounter subtleties, which may urge caution with analogous efforts in other models, such as multi-flavor QCD.

Possible ways of obtaining information about the solutions of Izhikevich's "simple model" for a spiking neuron are considered. The method of power series in time is reviewed. From a different viewpoint, in the case of constant input and weak recovery scale effects, advantage is taken of a small-parameter expansion. The obtained approximations can be expressed in terms of elementary functions.

In many markets, large and small firms coexist. As large firms can in principle out-compete small ones, the actual presence of the latter asks for an explanation. In ours, we focus on the dimensionality of markets, which can change as a consequence of product innovations, preference elaboration or institutions. We show that increasing market dimensionality substantially enlarges the market periphery relative to the market center, which creates new potential niches for small firms. We thereby provide a parsimonious explanation for small firm subsistence.

This paper carries out the image encryption with a revised and modified cryptosystem based on a rule-90 cellular automaton. For this purpose, we used an appropriate and convenient matrix approach to implement the main components of the encryption system, two indexed families of permutations and a pseudo-random bit generator. Furthermore, we modify the encryption scheme for improving its security. This makes our encryption proposal resist some common attacks, e.g. chosen plain-text attack, and the encryption and decryption processes are performed in a flexible way. Also, some security aspects of the cryptosystem are evaluated with a series of statistical tests exhibiting good results. It is believed that this proposal fits naturally in the present digital technology and is capable of achieving high levels of performance.

Traffic demand is one of the most important factors to affect the traffic flow pattern or load distribution in congested networks. In this paper, we investigate the load distributions and relations between the load and degree of the node for different traffic demands in scale-free networks. Different kinds of load distributions are obtained under different traffic demands. Furthermore, the impact of link capacity on load distribution in congested scale-free networks is also discussed.

Previously many studies on online social networks simply analyze the static topology in which the friend relationship once established, then the links and nodes will not disappear, but this kind of static topology may not accurately reflect temporal interactions on online social services. In this study, we define four types of users and interactions in the interaction (dynamic) network. We found that active, disappeared, new and super nodes (users) have obviously different strength distribution properties and this result also can be revealed by the degree characteristics of the unweighted interaction and friendship (static) networks. However, the active, disappeared, new and super links (interactions) only can be reflected by the strength distribution in the weighted interaction network. This result indicates the limitation of the static topology data on analyzing social network evolutions. In addition, our study uncovers the approximately stable statistics for the dynamic social network in which there are a large variation for users and interaction intensity. Our findings not only verify the correctness of our definitions, but also helped to study the customer churn and evaluate the commercial value of valuable customers in online social networks.