Localization as a technique to solve the complex and challenging problems besetting line-of-sight (LOS) and non-line-of-sight (NLOS) transmissions has recently attracted considerable attention in the wireless sensor network field. This paper proposes a strategy for eliminating NLOS localization errors during calculation of the location of mobile terminals (MTs) in unfamiliar indoor environments...

Phosphorylation of smooth muscle heavy meromyosin (HMM) has been shown to result in about a 25-fold increase in the steady-state Vmax of the actin-activated MgATPase activity from 0.07 s-1 for unphosphorylated HMM to 1.9 s-1 for phosphorylated HMM. The steady-state MgATPase activity of unphosphorylated HMM in the absence of actin is 0.004 s-1. The true extent of regulation might be even larger ...

Relaxation of both smooth and skeletal muscles appears to be caused primarily by inhibition of the step associated with Pi release in the actomyosin ATPase cycle, rather than by a block in the binding of the myosin X ATP and myosin X ADP X Pi complexes to actin. In skeletal muscle, troponin-tropomyosin not only causes marked inhibition of Pi release, but it also markedly inhibits the binding of...

In this paper, we extend the Maximum Likelihood (ML) training algorithm to the Minimum Classiica-tion Error (MCE) training algorithm for discriminatively estimating the state-dependent polynomial coeecients in the stochastic trajectory model or the trended HMM originally proposed in 2]. The main motivation of this extension is the new model space for smoothness-constrained, state-bound speech t...

This paper examines F0 modeling and generation techniques for spontaneous speech synthesis. In the previous study, we proposed a prosodic-unit HMM where the synthesis unit is defined as a segment between two prosodic events represented by a ToBI label framework. To take the advantage of the prosodicunit HMM, continuous F0 sequences must be modeled from discontinuous F0 data including unvoiced r...

We present a generative factor analyzed hidden Markov model (GFA-HMM) for automatic speech recognition. In a traditional HMM, the observation vectors are represented by mixture of Gaussians (MoG) that are dependent on discrete-valued hidden state sequence. The GFA-HMM introduces a hierarchy of continuousvalued latent representation of observation vectors, where latent vectors in one level are a...

When applied to interactive seminars, the detection of acoustic events from only audio information shows a large amount of errors, which are mostly due to the temporal overlaps of sounds. Video signals may be a useful additional source of information to cope with that problem for particular events. In this work, we aim at improving the detection of steps by using two audiobased Acoustic Event D...

Detection of acoustic events (AED) that take place in a meeting-room environment becomes a difficult task when signals show a large proportion of temporal overlap of sounds, like in seminar-type data, where the acoustic events often occur simultaneously with speech. Whenever the event that produces the sound is related to a given position or movement, video signals may be a useful additional so...

Player classification allows for considerable improvements on both game analytics and game adaptivity. With this paper we aim at reversing the ad-hoc tendency in player classification methods, by proposing an approach to player classification that can be integrated across different games and genres and is particularly suited to be used by game designers. This paper describes our generic method ...

∗ 0-7803-7952-7/03/$17.00  2003 IEEE. Abstract – A previous study successfully demonstrated the potential usefulness of Hidden Markov Model (HMM) analysis techniques in analyzing pilots’ eye-movement data to detect differences in scanning and attention patterns caused by display format changes. This paper focuses on assessing differences among pilots using the same display format. A flight sim...