10876880
Multimedia materials for teaching signal processing
Rapidly advancing capabilities in PC-based multimedia technology are providing new opportunities for delivery of educational material. Multimedia technology is being introduced at all levels of the degrees in Electronics and Communications at the University of New England (UNE). In this paper attention is drawn the use of multimedia technology through the example of a fourth-year education package on signal processing. We have used this multimedia education package for teaching and learning during formal class periods and to encourage students to use the technology in their own personal study and projects in order to increase their engineering generic skills. The success of the venture has encouraged us to extend the technology to other selected units in the UNE engineering programs.
42418095
An Improved ALOHA Algorithm for RFID Tag Identification
One of problems that we faced for Radio frequency identification (RFID) systems is that the collision between tags which lowers the efficiency of the RFID systems. One of the popular anti-collision algorithms is ALOHA-type algorithms, which are simple and have good performance when the number of tags to be read is reasonable small. In this paper, an enhanced dynamic framed slotted ALOHA algorithm for RFID is extended to a more general close form, hence reference [9] becomes only one special case described in our paper. The improved ALOHA algorithm for RFID tag identifications has much larger capacity to handle the cases when the tag numbers increasing largely while every frame keeping the optimum system efficiency 35.5%. Simulation results show that the proposed algorithm improves the efficiency nicely in comparison with the conventional algorithms keeping >80% as the previous paper shown.
621625
Image noise removal in Nakagami fading channels via Bayesian estimator
A maximum likelihood for Bayesian estimator based on alpha-stable was discussed in our previous papers. It is in terms of closer to a realistic situation, and unlike previous methods used for Bayesian estimator, for the case discussed here it is not necessary to know the variance of the noise. The Bayesian estimator here is based on in a Nakagami fading channel. Our previous research results has been extended to that Bayesian estimator that we investigated is still working well for the image noise removal in Nakagami fading channels. As an example, an improved Bayesian estimator (soft and hard threshold methods), is illustrated in our discussion
6974885
Image multi-noise removal by wavelet-based Bayesian estimator
Images are in many cases degraded even before they are encoded. The major noise sources, in terms of distributions, are Gaussian noise, Poisson noise and impulse noise. Noise acquired by images during transmission would be Gaussian in distribution, while images such as emission and transmission tomography images, X-ray films, and photographs taken by satellites are usually contaminated by quantum noise, which is Poisson distributed. Poisson shot noise is a natural generalization of a compound Poisson process when the summands are stochastic processes starting at the points of the underlying Poisson process. Unlike additive Gaussian noise, Poisson noise is signal-dependent and consequently separating signal from noise is more difficult. In our previous papers we discussed a wavelet-based maximum likelihood for Bayesian estimator that recovers the signal component of wavelet coefficients in original images using an alpha-stable signal prior distribution. In this paper, it is demonstrated that the method can be extended to multi-noise sources comprising Gaussian, Poisson, and impulse noise. Results of varying the parameters of the Bayesian estimators of the model are presented after an investigation of /spl alpha/-stable simulations for a maximum likelihood estimator. As an example, a colour image is processed and presented to illustrate the effectiveness of this method.
42013296
On the computational hardness based on linear FPT-reductions
The notion of linear fpt-reductions has been recently introduced to derive strong computational lower bounds for well-known NP-hard problems. In this paper, we formally investigate the notion of W[t]-hardness under the linear fpt-reduction, and study the structural properties of the corresponding complexity classes. Additional complexity lower bounds on important computational problems are established. Some observations on structural properties of the standard parameterized hierarchy, the W -hierarchy, are also presented.
12321641
Locally Balanced Incremental Hierarchical Discriminant Regression
Incremental hierarchical discriminant regression faces several challenging issues: (a) a large input space with a small output space and (b) nonstationary statistics of data sequences. In the first case (a), there maybe few distinct labels in the output space while the input data distribute in a high dimensional space. In the second case (b), a tree has to be grown when only a limited data sequence has been observed. In this paper, we present the Locally Balanced Incremental Hierarchical Discriminant Regression (LBIHDR) algorithm. A novel node self-organization and spawning strategy is proposed to generate a more discriminant subspace by forming multiple clusters for one class. The algorithm was successfully applied to different kinds of data set.
1605324
Using contextual information to improve retrieval performance
In this paper, we propose a contextual retrieval framework which incorporates the user and global contextual information into the probabilistic retrieval model. We investigate different techniques of using contextual information to improve information retrieval performance in details. In particular, (1) we use the related text contextual information for query expansion; (2) we use the granularity information to construct the document level index and paragraph level index; (3) we use the geographic information for filtering. In addition, a new term weighting function BM5O is proposed based on the global context information. This framework is adaptable and extensible. If there is a new context category, we can extend the existing search system to accommodate it. Finally, we report our experimental findings on TREC data sets.
5435479
Towards A Streams-Based Framework for Defining Location-Based Queries
An infrastructure is emerging that supports the delivery of on-line, location-enabled services to mobile users. Such services involve novel database queries, and the database research community is quite active in proposing techniques for the efficient processing of such queries. In parallel to this, the management of data streams has become an active area of research. While most research in mobile services concerns performance issues, this paper aims to establish a formal framework for defining the semantics of queries encountered in mobile services, most notably the so-called continuous queries that are particularly relevant in this context. Rather than inventing an entirely new framework, the paper proposes a framework that builds on concepts from data streams and temporal databases. Definitions of example queries demonstrates how the framework enables clear formulation of query semantics and the comparison of queries. The paper also proposes a categorization of location-based queries.
17235430
A generalized global alignment algorithm
MOTIVATION
Homologous sequences are sometimes similar over some regions but different over other regions. Homologous sequences have a much lower global similarity if the different regions are much longer than the similar regions.


RESULTS
We present a generalized global alignment algorithm for comparing sequences with intermittent similarities, an ordered list of similar regions separated by different regions. A generalized global alignment model is defined to handle sequences with intermittent similarities. A dynamic programming algorithm is designed to compute an optimal general alignment in time proportional to the product of sequence lengths and in space proportional to the sum of sequence lengths. The algorithm is implemented as a computer program named GAP3 (Global Alignment Program Version 3). The generalized global alignment model is validated by experimental results produced with GAP3 on both DNA and protein sequences. The GAP3 program extends the ability of standard global alignment programs to recognize homologous sequences of lower similarity.


AVAILABILITY
The GAP3 program is freely available for academic use at http://bioinformatics.iastate.edu/aat/align/align.html.