Visual analysis of image collections

Multidimensional Visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image-Projection Explorer for Images-a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus offering improved analysis and exploration capabilities. The visual mappings employ similarity-based multidimensional projections and point placement to layout the data on a plane for visual exploration. In addition to its application to image databases, we also illustrate how the proposed approach can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.

Two-Phase Mapping for Projecting Massive Data Sets

Most multidimensional projection techniques rely on distance (dissimilarity) information between data instances to embed high-dimensional data into a visual space. When data are endowed with Cartesian coordinates, an extra computational effort is necessary to compute the needed distances, making multidimensional projection prohibitive in applications dealing with interactivity and massive data. The novel multidimensional projection technique proposed in this work, called Part-Linear Multidimensional Projection (PLMP), has been tailored to handle multivariate data represented in Cartesian high-dimensional spaces, requiring only distance information between pairs of representative samples. This characteristic renders PLMP faster than previous methods when processing large data sets while still being competitive in terms of precision. Moreover, knowing the range of variation for data instances in the high-dimensional space, we can make PLMP a truly streaming data projection technique, a trait absent in previous methods.

Thermal analysis of biodegradable microparticles containing ciprofloxacin hydrochloride obtained by spray drying technique

Thermal analysis has been extensively used to obtain information about drug-polymer interactions and to perform pre-formulation studies of pharmaceutical dosage forms. In this work, biodegradable microparticles of poly(D,L-lactide-co-glycolide) (PLGA) containing ciprofloxacin hydrochloride (CP) in various drug:polymer ratios were obtained by spray drying. The main purpose of this study was to investigate the effect of the spray drying process on the drug-polymer interactions and on the stability of microparticles using differential scanning calorimetry (DSC), thermogravimetry (TG) and derivative thermogravimetry (DTG) and infrared spectroscopy (IR). The results showed that the high levels of encapsulation efficiency were dependant on drug:polymer ratio. DSC and TG/DTG analyses showed that for physical mixtures of the microparticles components the thermal profiles were different from those signals obtained with the pure substances. Thermal analysis data disclosed that physical interaction between CP and PLGA in high temperatures had occurred. The DSC and TG profiles for drug-loaded microparticles were very similar to the physical mixtures of components and it was possible to characterize the thermal properties of microparticles according to drug content. These data indicated that the spray dryer technique does not affect the physicochemical properties of the microparticles. In addition, the results are in agreement with IR data analysis demonstrating that no significant chemical interaction occurs between CP and PLGA in both physical mixtures and microparticles. In conclusion, we have found that the spray drying procedure used in this work can be a secure methodology to produce CP-loaded microparticles. (C) 2007 Elsevier B.V. All rights reserved.