In this paper, a new state-space method for language modeling is presented. The complexity of the model is controlled by choosing the dimension of the state instead of the smoothing and back-off methods common in n-gram modeling. The model complexity also controls the generalization ability of the model, allowing the model to handle similar words in similar manner. We compare the state-space mo...

An agreement is an arrangement between two or more entities to do something. This implies a context in which terms the agreement is developed. This paper presents a model of such agreement context as an euclidean space. On the other hand, an agreement can also be seen as a Constraint Satisfaction Problem (CSP) which solution space models an agreement space. This will allow to have a mediator th...

In this paper we focus on the Personal Space (PS) as a nonverbal communication concept to build a new Human Computer Interaction. The analysis of people positions with respect to their PS gives an idea on the nature of their relationship. We propose to analyze and model the PS using Computer Vision (CV), and visualize it using Computer Graphics. For this purpose, we define the PS based on four ...

The extracellular space (ECS) of the brain is a thin region surrounding each cell that is filled with a medium resembling cerebrospinal fluid and an unknown amount of extracellular matrix. The ECS is difficult to study but diffusion measurements based on a point-source diffusion paradigm have begun to reveal the complex structure of this region. Despite the complexity, a modified version of Fic...

Binaural displays for immersive listening must model reverberant environments, multiple sound sources, and accommodate source and head motion. Many displays model such phenomena as a collection of spatially distributed point sources; source signals are filtered with multiple head-related transfer functions (HRTFs) and then combined into a single binaural signal for display. The computational lo...

In this paper we study a class of evolutionary models of industrial agglomeration with local positive feedbacks, which allow for a wide set of empirically-testable implications. Their roots rest in the Generalized Polya Urn framework. Here, however, we build on a birth-death process over a finite number of locations and a finite population of firms. The process of selection among production sit...

We present an Agent Based Model (ABM) named MIMICS (Modeling Inferential Minds in Conceptual Space), which shows how a social group develops abstract concepts for achieving agreement in communication. Agents describe concepts by assigning properties to them based on learning and communication interactions, trying to develop a conceptual space that discriminates as much as possible between two c...

A new method has been developed to compute the probability that each amino acid in a protein sequence is in a particular secondary structural element. Each of these probabilities is computed using the entire sequence and a set of predefined structural class models. This set of structural classes is patterned after Jane Richardson's taxonomy for the domains of globular proteins. For each structu...

We examine how the representation of space is affected by receptive field (RF) characteristics of the encoding population. Spatial responses were defined by overlapping Gaussian RFs. These responses were analyzed using multidimensional scaling to extract the representation of global space implicit in population activity. Spatial representations were based purely on firing rates, which were not ...