I present empirical comparisons between a standard statistical translation model and an equivalent Maximum Entropy model. Results show that the Maximum Entropy model is promising, but highly sensitive to the method of feature selection.

Identifying the terror attack, illegal public gathering or other mass events risks by utilizing cameras is an important concern both in crowd security area and in pattern recognition research area. This paper provides a physical entropy model to measure the crowd security level. The entropy model was created by identifying individuals’ moving velocity and the related probability. The individual...

Solvent entropy is a force to consider in protein folding and protein design but is difficult to model. It is investigated here in the context of the hp model: Two types of residues, hydrophobic and hydrophilic, are modeled on a lattice. Nine chains and two- and three-dimensional simulations are compared. We show that considering solvent entropy alone, efficient folding of lattice chains (ident...

The relative volume of spin states in the phase space is introduced for the ±J model of spin glasses. Analysis of its temperature dependence shows that the Nishimori line separates the pure ferromagnetic-like region in the high-temperature side of the ferromagnetic phase from the randomness-dominated region in the low-temperature side. The peak value of the relative volume of the perfect ferrom...

Thermodynamical and magnetic properties of the half-filled, two-site Hubbard model have been discussed within the framework of the Tsallis nonextensive statistics, in which the entropic index q plays an important role, the conventional Boltzman-Gibbs statistics being recovered in the limit of q = 1. The temperature dependence of the entropy, specific heat and magnetic susceptibility, and the ma...

This paper describes a method to incorporate the HMM output constraints in frame based hybrid NN/HMM systems during training. While usually the NN parameters are adjusted to maximize the cross-entropy between the frame target probabilities and the network predictions assuming statistically independent outputs in time, in the approach described here the full likelihood of the utterance(s) using ...

The [GLP & MEMM] pricing model (= [Geometric Lévy Process & Minimal Entropy Martingale Measure] pricing model) has been introduced as a pricing model for the incomplete financial market. This model has many good properties and is applicable to very wide classes of underlying asset price processes including the geometric stable processes. We explain those good properties and see several examples...

We develop the “Draw My-Topics” Toolkit, which provides a fast way to incorporate social scientists’ concerns and interests into the standard topic model. Instead of using raw corpus with primitive processing as input, an algorithm based on Vector Space Model and Conditional Entropy are used to connect social scientists’ subjective want and the unsupervised topic models’ output. Space for users...

We implement a confidence estimation stage for a speech recognition system by using two maximum entropy models. These models takes information from various sources including a set of scores which have proved to be useful in confidence estimation tasks, and efficiently combine those scores. Two different approaches of the maximum entropy model are developed. First a basic model which takes advan...

High-entropy alloys (HEAs) are new alloys that contain five or more elements in roughly-equal proportion. We present new experiments and theory on the deformation behavior of HEAs under slow stretching (straining), and observe differences, compared to conventional alloys with fewer elements. For a specific range of temperatures and strain-rates, HEAs deform in a jerky way, with sudden slips tha...