Validating Co-Training Models for Web Image Classification

Co-training is a semi-supervised learning method that is designed to take advantage of the redundancy that is present when the object to be identified has multiple descriptions. Co-training is known to work well when the multiple descriptions are conditional independent given the class of the object. The presence of multiple descriptions of objects in the form of text, images, audio and video in multimedia applications appears to provide redundancy in the form that may be suitable for co-training. In this paper, we investigate the suitability of utilizing text and image data from the Web for co-training. We perform measurements to find indications of conditional independence in the texts and images obtained from the Web. Our measurements suggest that conditional independence is likely to be present in the data. Our experiments, within a relevance feedback framework to test whether a method that exploits the conditional independence outperforms methods that do not, also indicate that better performance can indeed be obtained by designing algorithms that exploit this form of the redundancy when it is present.

On the Fabrication of Microparticles Using Electrohydrodynamic Atomization Method

A new approach for the control of the size of particles fabricated using the Electrohydrodynamic Atomization (EHDA) method is being developed. In short, the EHDA process produces solution droplets in a controlled manner, and as the solvent evaporates from the surface of the droplets, polymeric particles are formed. By varying the voltage applied, the size of the droplets can be changed, and consequently, the size of the particles can also be controlled. By using both a nozzle electrode and a ring electrode placed axisymmetrically and slightly above the nozzle electrode, we are able to produce a Single Taylor Cone Single Jet for a wide range of voltages, contrary to just using a single nozzle electrode where the range of permissible voltage for the creation of the Single Taylor Cone Single Jet is usually very small. Phase Doppler Particle Analyzer (PDPA) test results have shown that the droplet size increases with increasing voltage applied. This trend is predicted by the electrohydrodynamic theory of the Single Taylor Cone Single Jet based on a perfect dielectric fluid model. Particles fabricated using different voltages do not show much change in the particles size, and this may be attributed to the solvent evaporation process. Nevertheless, these preliminary results do show that this method has the potential of providing us with a way of fine controlling the particles size using relatively simple method with trends predictable by existing theories.

Fabrication of Controlled Release Devices Using Supercritical Antisolvent Method

In this study, the supercritical antisolvent with enhanced mass transfer method (SASEM) is used to fabricate micro and nanoparticles of biocompatible and biodegradable polymer PLGA (poly DL lactide co glycolic acid). This process may be extended to the encapsulation of drugs in these micro and nanoparticles for controlled release purposes. Conventional supercritical antisolvent (SAS) process involves spraying a solution (organic solvent + dissolved polymer) into supercritical fluid (CO[subscript 2]), which acts as an antisolvent. The high rate of mass transfer between organic solvent and supercritical CO[subscript 2] results in supersaturation of the polymer in the spray droplet and precipitation of the polymer as micro or nanoparticles occurs. In the SASEM method, ultrasonic vibration is used to atomize the solution entering the high pressure with supercritical CO[subscript 2]. At the same time, the ultrasonic vibration generated turbulence in the high pressure vessel, leading to better mass transfer between the organic solvent and the supercritical CO₂. In this study, two organic solvents, acetone and dichloromethane (DCM) were used in the SASEM process. Phase Doppler Particle Analyzer (PDPA) was used to study the ultrasonic atomization of liquid using the ultrasonic probe for the SASEM process. Scanning Electron Microscopy (SEM) was used to study the size and morphology of the polymer particles collected at the end of the process.