Isothermal (liquid + liquid) equilibrium data at T = 313.15 K and isobaric (vapor + liquid + liquid) equilibrium data at 101.3 kPa for the ternary system (water + 1-butanol + p-xylene)

The (vapor + liquid), (liquid + liquid) and (vapor + liquid + liquid) equilibria of the ternary system (water + 1-butanol + p-xylene) have been determined. (Water + 1-butanol + p-xylene) is a type 2 heterogeneous ternary system with partially miscible (water + 1-butanol) and (water + p-xylene) pairs. By contrast, (1-butanol + p-xylene) is totally miscible under atmospheric conditions. This paper examines the (vapor + liquid) equilibrium in both heterogeneous and homogeneous regions at 101.3 kPa of pressure. (Liquid + liquid) equilibrium data at T = 313.15 K have also been determined, and for comparison, the obtained experimental data have been calculated by means of several thermodynamic models: UNIQUAC, UNIFAC and NRTL. Some discrepancies were found between the (vapor + liquid + liquid) correlations; however, the models reproduced the (liquid + liquid) equilibrium data well. The obtained data reveal a ternary heterogeneous azeotrope with mole fraction composition: 0.686 water, 0.146 1-butanol and 0.168 p-xylene.

Active Foreground Region Extraction and Tracking for Sports Video Annotation

Automatic video segmentation plays a vital role in sports videos annotation. This paper presents a fully automatic and computationally efficient algorithm for analysis of sports videos. Various methods of automatic shot boundary detection have been proposed to perform automatic video segmentation. These investigations mainly concentrate on detecting fades and dissolves for fast processing of the entire video scene without providing any additional feedback on object relativity within the shots. The goal of the proposed method is to identify regions that perform certain activities in a scene. The model uses some low-level feature video processing algorithms to extract the shot boundaries from a video scene and to identify dominant colours within these boundaries. An object classification method is used for clustering the seed distributions of the dominant colours to homogeneous regions. Using a simple tracking method a classification of these regions to active or static is performed. The efficiency of the proposed framework is demonstrated over a standard video benchmark with numerous types of sport events and the experimental results show that our algorithm can be used with high accuracy for automatic annotation of active regions for sport videos.