Effective human-robot cooperation requires robotic devices that understand human goals and intentions. We frame the problem of intent recognition as one of tracking and predicting human actions within the context of plan task sequences. A hybrid mode estimation approach, which estimates both discrete operating modes and continuous state, is used to accomplish this tracking based on possibly noi...

We present a method of incorporating the discrete dipole approximation (DDA) method with the point matching method to formulate the T -matrix for modeling arbitrarily shaped micro-sized objects. The T -matrix elements are calculated using point matching between fields calculated using vector spherical wave functions and DDA. When applied to microrotors, their discrete rotational and mirror symm...

Hybrid systems consist of continuous and discrete dynamics. These systems can be described with a set of modes, where in each mode the system is governed by a continuous dynamics, and different modes correspond to different continuous models. For hybrid systems, model-based fault detection and isolation (FDI) is a challenging task, since system’s prevailing dynamical model and the system's curr...

Travel demand is well announced as a crucial component of transportation planning. This paper aims to develop a direct demand model, denoting a more acceptable abstraction of reality, for intercity passengers in daily work and leisure trips in Tehran province. The model utilizes combined estimation across the data source, collected in 2011, of travelers originating from ...

Including provision for continuously varying behaviour as well as discrete state change is considered for Event-B. An extension of Event-B is sketched that accommodates continuous events (called pliant events) in between familiar discrete events (called mode events).

In this paper, we investigate the state estimation problem for a new class of discrete-time neural networks with Markovian jumping parameters as well as mode-dependent mixed time-delays. The parameters of the discrete-time neural networks are subject to the switching from one mode to another at different times according to a Markov chain, and the mixed time-delays consist of both discrete and d...

Mode choice analysis has received the most attention among discrete choice problems in travel behavior literature. Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. This paper investigates performance of mode choice analysis with classification methods decision trees, discriminant analysis and multinomial logit. Experi...

In this paper we present a discrete adjoint approach for the optimization of unsteady, turbulent flows. While discrete adjoint methods usually rely on the use of the reverse mode of Automatic Differentiation (AD), which is difficult to apply to complex unsteady problems, our approach is based on the discrete adjoint equation directly and can be implemented efficiently with the use of a sparse f...