Cost-Effectiveness of Population-Based Tobacco Control Interventions on the Health Burden of Cardiovascular Diseases in Vietnam.

This study sought to assess the cost-effectiveness of population-based tobacco control interventions, which included health promotion and education, smoke-free models, cessation programs, warning on package, marketing bans, and raising tax. Standardized activity-based costing ingredient approach was applied with the provider perspective to calculate interventions cost from 2013 to 2017. The potential health impacts of the aforementioned interventions were calculated through a Microsoft Excel-based modeling adapted from Higashi et al and Ngalesoni et al. All six population-based tobacco control interventions were highly cost-effective with ranges from 1405 VND (Vietnamese Dong) to 135 560 VND per DALY (disability-adjusted life year) averted. It was identified that raising cigarette taxes and applying health warnings on tobacco packages are the most favorable, cost-effective interventions. The results from this study provide a robust message that calls for increased attention and efforts in developing an appropriate policy agenda, which jointly integrates both political and community-based interventions, to maximize intervention impact on tobacco use.

Novel Models of Image Permutation and Diffusion Based on Perturbed Digital Chaos.

Most of chaos-based cryptosystems utilize stationary dynamics of chaos for the permutation and diffusion, and many of those are successfully attacked. In this paper, novel models of the image permutation and diffusion are proposed, in which chaotic map is perturbed at bit level on state variables, on control parameters or on both. Amounts of perturbation are initially the coordinate of pixels in the permutation, the value of ciphered word in the diffusion, and then a value extracted from state variables in every iteration. Under the persistent perturbation, dynamics of chaotic map is nonstationary and dependent on the image content. The simulation results and analyses demonstrate the effectiveness of the proposed models by means of the good statistical properties of transformed image obtained after just only a single round.

Comparative Study of Three Steganographic Methods Using a Chaotic System and Their Universal Steganalysis Based on Three Feature Vectors.

In this paper, we firstly study the security enhancement of three steganographic methods by using a proposed chaotic system. The first method, namely the Enhanced Edge Adaptive Image Steganography Based on LSB Matching Revisited (EEALSBMR), is present in the spatial domain. The two other methods, the Enhanced Discrete Cosine Transform (EDCT) and Enhanced Discrete Wavelet transform (EDWT), are present in the frequency domain. The chaotic system is extremely robust and consists of a strong chaotic generator and a 2-D Cat map. Its main role is to secure the content of a message in case a message is detected. Secondly, three blind steganalysis methods, based on multi-resolution wavelet decomposition, are used to detect whether an embedded message is hidden in the tested image (stego image) or not (cover image). The steganalysis approach is based on the hypothesis that message-embedding schemes leave statistical evidence or structure in images that can be exploited for detection. The simulation results show that the Support Vector Machine (SVM) classifier and the Fisher Linear Discriminant (FLD) cannot distinguish between cover and stego images if the message size is smaller than 20% in the EEALSBMR steganographic method and if the message size is smaller than 15% in the EDCT steganographic method. However, SVM and FLD can distinguish between cover and stego images with reasonable accuracy in the EDWT steganographic method, irrespective of the message size.