Abstract Multilevel models are effective marketing analytic tools that can test for consumer differences in longitudinal data. A two-part multilevel model is a special case of developed semi-continuous data, such as data include combination zeros and continuous values. For repeated measures media use informs market research about consumer-specific likeliness to media, level across time, variati...

The paper presents ultra-high-capacity transmission technologies based on multi-core space-division-multiplexing. In order to realize high-capacity multi-core fiber (MCF) transmission, investigation of low crosstalk fiber and connection technology is important, and high-density signal generation using multilevel modulation and crosstalk management are also key technologies. 1 Pb/s multi-core fi...

This paper reviews multi-dimensional space-time multilevel codes (ST-MLCs). Basic construction methods, including conventional STCs. The spacetime multilevel encoders partition a dimensional signaling space, which spans all transmit antennas. Complexity of detection/ decoding can be reduced by multi-dimensional partitioning. Space time multistage decoder for the proposed ST-MLCs is reviewed. Th...

The paper extends existing models for multilevel multivariate data with mixed response types to handle quite general types and patterns of missing data values in a wide range of multilevel generalized linear models. It proposes an efficient Bayesian modelling approach that allows missing values in covariates, including models where there are interactions or other functions of covariates such as...

Streamlined mean field variational Bayes algorithms for efficient fitting and inference in large models for longitudinal and multilevel data analysis are obtained. The number of operations is linear in the number of groups at each level, which represents a two orders of magnitude improvement over the naïve approach. Storage requirements are also lessened considerably. We treat models for the Ga...

In this paper we study the application of user-dependent score fusion to multilevel speaker recognition. After reviewing related works in multimodal biometric authentication, a new score fusion technique is described. The method is based on a form of Bayesian adaptation to derive the personalized fusion functions from prior user-independent data. Experimental results are reported using the MIT ...

This paper presents a novel context-aware methodology for modelling and measuring user-perceived quality of experience (QoE) over time. In particular, we create a context-aware model for QoE modelling and measurement using dynamic Bayesian networks (DBN) and a context-aware state-space approach. The proposed model is then used to infer and determine users’ QoE in a sequential manner. We perform...