Sequential Bayesian inference for implicit hidden Markov models and current limitations

Hidden Markov models can describe time series arising in various fields of science, by treating the data as noisy measurements of an arbitrarily complex Markov process. Sequential Monte Carlo (SMC) methods have become standard tools to estimate the hidden Markov process given the observations and a fixed parameter value. We review some of the recent developments allowing the inclusion of parameter uncertainty as well as model uncertainty. The shortcomings of the currently available methodology are emphasised from an algorithmic complexity perspective. The statistical objects of interest for time series analysis are illustrated on a toy "Lotka-Volterra" model used in population ecology. Some open challenges are discussed regarding the scalability of the reviewed methodology to longer time series, higher-dimensional state spaces and more flexible models.Comment: Review article written for ESAIM: proceedings and surveys. 25 pages, 10 figure

Motivating children to learn effectively: exploring the value of intrinsic integration in educational games

The concept of intrinsic motivation lies at the heart of the user engagement created by digital games. Yet despite this, educational software has traditionally attempted to harness games as extrinsic motivation by using them as a sugar coating for learning content. This article tests the concept of intrinsic integration as a way of creating a more productive relationship between educational games and their learning content. Two studies assessed this approach by designing and evaluating an educational game called Zombie Division to teach mathematics to 7- to 11-year-olds. Study 1 examined the learning gains of 58 children who played either the intrinsic, extrinsic, or control variants of Zombie Division for 2 hr, supported by their classroom teacher. Study 2 compared time on task for the intrinsic and extrinsic variants of the game when 16 children had free choice of which game to play. The results showed that children learned more from the intrinsic version of the game under fixed time limits and spent 7 times longer playing it in free-time situations. Together, these studies offer evidence for the genuine value of an intrinsic approach for creating effective educational games. The theoretical and commercial implications of these findings are discussed

A Sub-block Based Image Retrieval Using Modified Integrated Region Matching

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding followed by morphological dilation. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. The colour and texture feature vectors is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). A modified Integrated Region Matching (IRM) algorithm is used for finding the minimum distance between the sub-blocks of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.Comment: 7 page

Path storage in the particle filter

This article considers the problem of storing the paths generated by a particle filter and more generally by a sequential Monte Carlo algorithm. It provides a theoretical result bounding the expected memory cost by $T + C N \log N$ where $T$ is the time horizon, $N$ is the number of particles and $C$ is a constant, as well as an efficient algorithm to realise this. The theoretical result and the algorithm are illustrated with numerical experiments.Comment: 9 pages, 5 figures. To appear in Statistics and Computin

Deterministic atom-light quantum interface

The notion of an atom-light quantum interface has been developed in the past decade, to a large extent due to demands within the new field of quantum information processing and communication. A promising type of such interface using large atomic ensembles has emerged in the past several years. In this article we review this area of research with a special emphasis on deterministic high fidelity quantum information protocols. Two recent experiments, entanglement of distant atomic objects and quantum memory for light are described in detail.Comment: 50 pages (bookstyle) 15 graphs, to be published in "Advances in Atomic, Molecular, and Optical Physics" Vol. 54. (2006)(Some of the graphs here have lower resolution than in the version to be published