The Bivariate Transmuted Family of Distributions: Theory and Applications

The bivariate distributions are useful in simultaneous modeling of two random variables. These distributions provide a way to model models. The bivariate families of distributions are not much widely explored and in this article a new family of bivariate distributions is proposed. The new family will extend the univariate transmuted family of distributions and will be helpful in modeling complex joint phenomenon. Statistical properties of the new family of distributions are explored which include marginal and conditional distributions, conditional moments, product and ratio moments, bivariate reliability and bivariate hazard rate functions. The maximum likelihood estimation (MLE) for parameters of the family is also carried out. The proposed bivariate family of distributions is studied for the Weibull baseline distributions giving rise to bivariate transmuted Weibull (BTW) distribution. The new bivariate transmuted Weibull distribution is explored in detail. Statistical properties of the new BTW distribution are studied which include the marginal and conditional distributions, product, ratio and conditional momenst. The hazard rate function of the BTW distribution is obtained. Parameter estimation of the BTW distribution is also done. Finally, real data application of the BTW distribution is given. It is observed that the proposed BTW distribution is a suitable fit for the data used.     

Optimisation of solar photovoltaic (PV) parameters using meta-heuristics

Microsystem Technologies - This paper presents a critical analysis of the meta-heuristic techniques used in various researches on the optimisation of photovoltaic (PV) parameters, which involves...     

Robust pose invariant face recognition using coupled latent space discriminant analysis

We propose a novel pose-invariant face recognition approach which we call Discriminant Multiple Coupled Latent Subspace framework. It finds the sets of projection directions for different poses such that the projected images of the same subject in different poses are maximally correlated in the latent space. Discriminant analysis with artificially simulated pose errors in the latent space makes it robust to small pose errors caused due to a subject’s incorrect pose estimation. We do a comparative analysis of three popular latent space learning approaches: Partial Least Squares (PLSs), Bilinear Model (BLM) and Canonical Correlational Analysis (CCA) in the proposed coupled latent subspace framework. We experimentally demonstrate that using more than two poses simultaneously with CCA results in better performance. We report state-of-the-art results for pose-invariant face recognition on CMU PIE and FERET and comparable results on MultiPIE when using only four fiducial points for alignment and intensity features.     

Application of vertical drainage to dewatering seacoasts

One of the most common difficulties arising when building roads and railway lines in seacoast areas is the high watertable in these regions. Among the applied dewatering methods, the most effective seems to be vertical drainage permanently lowering the level of underground water. Application of this method has also been carried out in Iraq. One should consider the fact that the vertical drainage method permits dewatering of not only the existing targets but also the areas designated for new construction. Lowering the watertable allows stabilization of the bed, and that secures stability and resistance of the foundation. The vertical drainage system depends upon underground water intake flowing to the drains from the directions of watershed in order to avoid its damming up under the building site. Dewatering according to the drainage system is much more efficient than open drain systems applied until now. From the technical point of view the system under discussion is much easier to operate, it consumes, less time and at the same time limits the number of people employed, workmen, engineers, and engineering equipment. Moreover, it has the advantage of dispensing with the expenses connected with the construction of passes and bridges, which are indispensable when the open drain ditches systems are applied. One opening of the proposed drainage may drain about 50 ha. The method is much more economical and much more efficient provided the whole drainage system is properly planned, and properly executed.     

An improved light attenuation technique for measuring large interfacial areas

A laser-based light attenuation technique was successfully used to measure interfacial areas as high as 5832 m²/m³ and Sauter mean bubble diameter varying between 50 and 5600 μm. Good agreement between this approach and the photographic technique was obtained particularly at low gas holdups.     

Silhouette-based human action recognition using SAX-Shapes

Human action recognition is an important problem in Computer Vision. Although most of the existing solutions provide good accuracy results, the methods are often overly complex and computationally expensive, hindering practical applications. In this regard, we introduce the combination of time-series representation for the silhouette and Symbolic Aggregate approXimation (SAX), which we refer to as SAX-Shapes, to address the problem of human action recognition. Given an action sequence, the extracted silhouettes of an actor from every frame are transformed into time series. Each of these time series is then efficiently converted into the symbolic vector: SAX. The set of all these SAX vectors (SAX-Shape) represents the action. We propose a rotation invariant distance function to be used by a random forest algorithm to perform the human action recognition. Requiring only silhouettes of actors, the proposed method is validated on two public datasets. It has an accuracy comparable to the related works and it performs well even in varying rotation.     

High PVC film‐forming composite latex particles via miniemulsification,part 1: Preparation

Miniemulsification technology was used to encapsulate TiO₂ particles inside a styrene/n‐butyl acrylate copolymer with high loading levels (11 to 70% PVC (pigment volume concentration)). In this approach, a St/BA copolymer dissolved in toluene in the presence of a costabilizer (hexadecane) was mixed with a dispersion of TiO₂ particles in toluene and sonified, and then emulsified in an aqueous surfactant solution by sonification. The effect of sonification time on both the dispersibility of the TiO₂ particles in the presence of the copolymer and hexadecane and on the encapsulated particle size was investigated. Particle size analysis by dynamic light scattering showed that these composite latexes are quite stable. It was also found that as the TiO₂ loading increased from 11 to 43% PVC, the particle size of the TiO₂ dispersion decreased while the polymer‐encapsulated TiO₂ particle size increased. The effect of surfactant concentration (sodium lauryl sulfate, SLS) on the encapsulated particle size was investigated using four different SLS concentrations in the 11% PVC system. The results showed that as the SLS concentration increased the particle size decreased, as expected. Also it was found that the minimum surfactant concentration that gives stable encapsulated TiO₂ particles is above 10 mM SLS. The role of HD in the recipe was studied for an artificial latex containing no TiO₂ and one prepared at 11% PVC, in terms of particle size before and after solvent stripping, and its effect on the T_g. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 4504–4516, 2006     

PRIVACY LEAKAGE IN HEALTH SOCIAL NETWORKS

Members of health social networks may be susceptible to privacy leaks by the amount of information they leave behind. The threat to privacy increases when members of these networks reuse their pseudonyms in other social networks. The risk of re‐identifying users from such networks requires quantitative estimates to evaluate its magnitude. The estimates will enable managers and members of health social communities to take corrective measures. We introduce a new re‐identification attack, the social network attack, that takes advantage of the fact that users reuse their pseudonyms. To demonstrate the attack, we establish links between MedHelp and Twitter (two popular social networks) based on matching pseudonyms. We used Bayesian networks to model the re‐identification risk and used stylometric techniques to identify the strength of the links. On the basis of our model 7‐11. 8% of the MedHelp members in the sample population who reused their pseudonyms in Twitter were re‐identifiable compared with 1% who did not. The risk estimates were measured at the 5% risk threshold. Our model was able to re‐identify users with a sensitivity of 41% and specificity of 96%. The potential for re‐identification increases as more data is accumulated from these profiles, which makes the threat of re‐identification more serious.     

Bathymetry and siltation rate for Dokan Reservoir,Iraq

The Dokan Reservoir dam is a concrete cylindrical arch with gravity abutments, located on the Lesser Zab River about 60 km from the city of Sulaimani in north‐eastern Iraq. A bathymetric survey was conducted in November 2014 for a period of 10 days, using an echo sounder of 200‐kHz single beam. The survey results indicated an annual average sediment deposition of 3.8 million m³. Thirty‐two sediment samples were collected from the reservoir bed. The ratio of gravel, sand, silt and clay was 15:14:48:23, respectively. The reservoir bed is covered mainly with silt. The sediments are composed of silty clay (77.6%), silty sandy clay (10%), sandy gravely silty clay (1.2%) and gravely sandy silty clay (1%).