A novel semi-fragile forensic watermarking scheme for remote sensing images

Peer-reviewed

A semi-grand canonical Monte Carlo simulation model for ion binding to ionizable surfaces: Proton binding of carboxylated latex particles as a case study

In this paper, we present a computer simulation study of the ion binding process at an ionizable surface using a semi-grand canonical Monte Carlo method that models the surface as a discrete distribution of charged and neutral functional groups in equilibrium with explicit ions modelled in the context of the primitive model. The parameters of the simulation model were tuned and checked by comparison with experimental titrations of carboxylated latex particles in the presence of different ionic strengths of monovalent ions. The titration of these particles was analysed by calculating the degree of dissociation of the latex functional groups vs. pH curves at different background salt concentrations. As the charge of the titrated surface changes during the simulation, a procedure to keep the electroneutrality of the system is required. Here, two approaches are used with the choice depending on the ion selected to maintain electroneutrality: counterion or coion procedures. We compare and discuss the difference between the procedures. The simulations also provided a microscopic description of the electrostatic double layer (EDL) structure as a function of pH and ionic strength. The results allow us to quantify the effect of the size of the background salt ions and of the surface functional groups on the degree of dissociation. The non-homogeneous structure of the EDL was revealed by plotting the counterion density profiles around charged and neutral surface functional groups. © 2011 American Institute of Physics.

Optimal capital structure: a trade-off model and its empirical testing

In the present research we have set forth a new, simple, Trade-Off model that would allow us to calculate how much debt and, by default, how much equity a company should have, using easily available information and calculating the cost of debt dynamically on the basis of the effect that the capital structure of the company has on the risk of bankruptcy; in an attempt to answer this question. The proposed model has been applied to the companies that make up the Dow Jones Industrial Average (DJIA) in 2007. We have used consolidated financial data from 1996 to 2006, published by Bloomberg. We have used simplex optimization method to find the debt level that maximizes firm value. Then, we compare the estimated debt with real debt of companies using statistical nonparametric Mann-Whitney. The results indicate that 63% of companies do not show a statistically significant difference between the real and the estimated debt.

Empirical study of correlated survival times for recurrent events with proportional hazards margins and the effect of correlation and censoring.

Background: In longitudinal studies where subjects experience recurrent incidents over a period of time, such as respiratory infections, fever or diarrhea, statistical methods are required to take into account the within-subject correlation. Methods: For repeated events data with censored failure, the independent increment (AG), marginal (WLW) and conditional (PWP) models are three multiple failure models that generalize Cox"s proportional hazard model. In this paper, we revise the efficiency, accuracy and robustness of all three models under simulated scenarios with varying degrees of within-subject correlation, censoring levels, maximum number of possible recurrences and sample size. We also study the methods performance on a real dataset from a cohort study with bronchial obstruction. Results: We find substantial differences between methods and there is not an optimal method. AG and PWP seem to be preferable to WLW for low correlation levels but the situation reverts for high correlations. Conclusions: All methods are stable in front of censoring, worsen with increasing recurrence levels and share a bias problem which, among other consequences, makes asymptotic normal confidence intervals not fully reliable, although they are well developed theoretically.

Research on the suitability of organosolv semi-chemical triticale fibers as reinforcement for recycled hdpe composites

The main objective of this research was to study the feasibility of incorporating organosolv semi-chemical triticale fibers as the reinforcing element in recycled high density polyethylene (HDPE). In the first step, triticale fibers were characterized in terms of chemical composition and compared with other biomass species (wheat, rye, softwood, and hardwood). Then, organosolv semi-chemical triticale fibers were prepared by the ethanolamine process. These fibers were characterized in terms of its yield, kappa number, fiber length/diameter ratio, fines, and viscosity; the obtained results were compared with those of eucalypt kraft pulp. In the second step, the prepared fibers were examined as a reinforcing element for recycled HDPE composites. Coupled and non-coupled HDPE composites were prepared and tested for tensile properties. Results showed that with the addition of the coupling agent maleated polyethylene (MAPE), the tensile properties of composites were significantly improved, as compared to non-coupled samples and the plain matrix. Furthermore, the influence of MAPE on the interfacial shear strength (IFSS) was studied. The contributions of both fibers and matrix to the composite strength were also studied. This was possible by the use of a numerical iterative method based on the Bowyer-Bader and Kelly-Tyson equations