Volume 2 Number 1 March 2011


Multimedia Streams Retrieval in Distributed Systems Using Learning Automata

Safiye Ghasemi, Amir Masoud Rahmani

Abstract Current academic Internet environment has enabled fast transfers of huge amounts of data, and has made high quality multimedia and collaborative applications a reality. This article describes a model for distributed multimedia retrieval which performs the retrieval of different multimedia to a variety of clients using learning automata algorithm named LAGridMSS. LAGridMSS allocates a proportion of bandwidth of each node for sending a specified file, and then applies learning automata to allocate packets of files to each node that contains the context. The files’ popularity and the remainder bandwidth of nodes are two main factors here for allocating packets to each node. Read More


Framework for Improving Annotation-Based Image Retrieval Performance

Phani Kidambi, Mary Fendley, S. Narayanan


Abstract As the proliferation of available and useful images on the web grows, novel methods and effective techniques are needed to retrieve these images in an efficient manner. Currently major commercial search engines utilize a process known as Annotation Based Image Retrieval (ABIR) to execute search requests focused on image retrieval. The ABIR technique primarily relies on the textual information associated with an image to complete the search and retrieval process. Using the game of cricket as the domain, we describe a benchmarking study that evaluates the effectiveness of three popular search engines in executing image-based searches. Second, we present details of an empirical study aimed at quantifying the impact of inter-human variability of the annotations on the effectiveness of search engines. Both these efforts are aimed at better understanding the challenges with image search and retrieval methods that purely rely on ad hoc annotations provided by the humans. Finally, we propose a framework that utilizes generic templates to aid the human’s cognitive capabilities to fill relevant for annotation needed in a specific domain in a more systematic way. The systematic annotation will not only reduce the mental task load on the human, but also would increase the precision and recall of a search engine. Read More


A Perceptually Adaptive Scheme for Image Watermarking by Bit Inverting Transformation

Tadahiko Kimoto


Abstract A perceptually adaptive scheme for image watermarking by use of the bit inverting transformation is developed. The transformation can change a signal level by both inverting a specified bit and altering the level at random within a limited range. From the analysis of the transformation properties, a perceptual model with two kinds of measures of level distortion is assumed for evaluating subjective visual qualities of the transformed image. Using the measurements of visual quality by the subjective evaluations of human observers, the subjective quality measure based on the perceptual model is derived by multiple linear regression analysis. This measure can estimate a subjective visual quality from the two distortion measurements of the transformed image. Read More


Automatic and Adaptive Fitting of the Cochlear Implant by Using Interactive Evolutionary Algorithms

Claire Bourgeois République, Albert Dipanda


Abstract Cochlear Implants (CI) are electronic devices that stimulate directly the auditory nerve to allow totally deaf patients to hear again. However they are more and more difficult to tune. The goal of this paper is to propose an automatic fitting method adaptable to different sound environments by using an interactive evolutionary algorithm. Real experiments on volunteer implanted patients are presented, which shows the efficiency of interactive evolution for this purpose. In the future, our goal is to add a piece of software to the CI signal processor that will automatically choose the best parameters setting depending on the class of the sound environment picked up by the microphone. Read More


Reduced Size Harmonic Suppressed Fractal Dipole Antenna with Integrated Reconfigurable Feature

Shipun Anuar Hamzah, Mazlina Esa, Nik Noordini Nik Abd Malik, Mohd Khairul Hisham Ismail


Abstract The presence of harmonics are undesirable in many applications as the overall system performance will be significantly degraded. By employing the fractal technology into an antenna, it is possible to provide reduction on the physical size, increment of its operating bandwidth and directivity. However, the technique can cause significant undesired harmonics problems associated with higher order modes of the antenna. This paper presents the design of a reduced size Koch fractal meander dipole antenna that has tunable capability of a reconfigurable operation within the observed range of 400 MHz to 3.5 GHz. The work involves both simulation and measurements. Each undesired harmonic is removed using one or two stubs. A microwave switch-able dipole antenna concept using Koch curve integrated with open circuit stubs is presented. The structure employed fractal technology that can eliminate higher order modes. With the utilization of Koch curves, it is shown that the antenna size is reduced, but the number of higher order modes has proportionally increased. The size of the proposed antenna is small with regards to the operating frequency. The incorporation of the stub has improved the antenna performance as desired. Read More