In HMM-based TTS, statistical models of static, velocity (delta), and acceleration (delta-delta) parameters are jointly trained in a unified, ML-based framework. Previous study has shown that the acceleration parameters are able to generate smoother trajectory with less distortions, but the effect has never been investigated in formal objective and subjective tests. In this paper, the effect of...

background:  the  current study examined race and ethnic differences in the separate and combined (additive) effects of anxiety, depression and problem drinking on the baseline and trajectory of subjective health among adult men in the united states. methods:  this longitudinal study used data from the fragile families and child well-being study. we included 4655 men, composed of 2407 blacks, 1...

High precision 4D flight path predictions are crucial for reliably optimizing the complex ATM/ATC system. The presented enhanced jet performance model provides a significant improvement over currently applied trajectory prediction methods. The use of purely analytical methods allows a high level of adoption of the real physical aircraft environment. This paper presents the model and applies the...

Cooperative trajectory mapping is an emerging technique that allows users to collaboratively map a person’s movements without using GPS measurements in indoor scenarios. This is accomplished by letting users periodically transmit limited amount of information, collected from their mobile phones, to a central server for processing. Cooperative mapping solutions have been proposed for application...

This paper considers the problem of spatial planning and open-loop control for underactuated AUVs. Given a smooth inertial 3D trajectory to be followed by some vehicle point, the developed algorithm uses the vehicle dynamic model, and computes the 3D corresponding body-fixed linear and angular velocities as well as vehicle orientations, yielding a feasible 6 DOF trajectory. Tracking controllers...

Symbolic Trajectory Evaluation (STE) is a powerful technique for hardware model checking. It is based on a 3-valued symbolic simulation, using 0,1 and X (”unknown”), where the X is used to abstract away values of the circuit nodes. Most STE tools are BDD-based and use a dual rail representation for the three possible values of circuit nodes. SAT-based STE tools typically use two variables for e...

We develop an object trajectory pattern learning method that has two significant advantages over past work. First, we represent trajectories in the HMM parameter space which overcomes the trajectory sampling problems of the existing methods. The proposed features are more expressive and enable detection of trajectory patterns that cannot be detected with the conventional trajectory representati...

Combining theorem proving and model checking o ers the tantalizing possibility of e ciently reasoning about large circuits at high levels of abstraction. We have constructed a system that seamlessly integrates symbolic trajectory evaluation based model checking with theorem proving in a higher-order classical logic. The approach is made possible by using the same programming language ( ) as bot...

Symbolic trajectory evaluation (STE) is a model checking technique that has been successfully used to verify many industrial designs. Existing implementations of STE reason at the level of bits, allowing signals in a circuit to take values from a lattice comprised of three elements: 0, 1, and X. This limits the amount of abstraction that can be achieved, and presents limitations to scaling STE ...