Efficient design and evaluation of countermeasures against fault attacks using formal verification

This paper presents a formal verification framework and tool that evaluates the robustness of software countermeasures against fault-injection attacks. By modeling reference assembly code and its protected variant as automata, the framework can generate a set of equations for an SMT solver, the solutions of which represent possible attack paths. Using the tool we developed, we evaluated the robustness of state-of-the-art countermeasures against fault injection attacks. Based on insights gathered from this evaluation, we analyze any remaining weaknesses and propose applications of these countermeasures that are more robust

In vitro propagation of four Iranian grape varieties: Influence of genotype and pretreatment with arbuscular mycorrhiza

There is a great demand for table grape saplings, mainly for commercial varieties indicating that micropropagation could be an effective method for their mass propagation. Internal contamination in woody plant species is an important problematic issue and arbuscular mycorrhizal fungi (AMF) have been known as potential plant biological protectors. In the present study, the glasshouse grown mother plants of four grape varieties ('Asgari', 'Khalili', 'Keshmeshi', and 'Shahroudi') were inoculated with AMF as pre-treatment. The fungi strains were Glomus mosseae, G. fasciculatum, G. intraradices and a mixture of all three species. The comparative in vitro performance of these genotypes was evaluated following optimization of in vitro growth conditions for each genotype. Furthermore, the positive effect of AMF inoculation of stock plant on micropropagation process was studied. Changes in biochemical features (total chlorophylls, total phenols and total sugars), growth parameters (root length and total leaf area) and in vitro behavior of AMF pretreated as well as control explants were recorded. The mycorrhizal association with grapevine roots was confirmed following root staining and evaluation of colonization rate. The results revealed a distinct difference and clear genotypic effect on various in vitro parameters of studied grape genotypes. The utilized inocula were found to have the capability of mycorrhizal association with grapevine roots, leading to enhancing phenolics as a defense mechanism, increasing sugars and chlorophyll and finally growth of whole plant corresponding to the grape variety and AMF strain. These results confirmed that health and physiological conditions of the stock plants are important parameters for in vitro grape culture establishment and suggest the integration of mycorrhizal technology with tissue culture to accomplish better results

Effect of a nanocomposite containing ostrich eggshell on calvarium healing in the rabbit: a pathologic study

ΔΕΝ ΔΙΑΤΙΘΕΤΑΙ ΠΕΡΙΛΗΨΗThe aim of the current study was to determine effect of a nanocomposite containing ostrich eggshell (NCOE) on the calvarium healing in the rabbit. Fresh ostrich eggshell was ground (300-500 μm), treated in phosphate-containing solutions and sterilized by gamma irradiation. Fifteen New Zealand white adult male rabbits were used. Four full-thickness skull defects were created in the calvarium. The first defect kept unfilled (control). The second defect was filled with autograft bone. The third defect was filled using NCOE. The fourth defect was filled with mixture of the autograft+NCOE bone. At 30, 60 and 90 days after surgery animals were euthanized and tissue specimens were collected and stained with hematoxylin eosin and trichrome staining method. Microsections were examined toassess the extent and intensity of inflammation, calvarium formation status and foreign body reaction. According to the results, filling defect significantly increased in NCOE-treated rabbits compared to the control group at 30 and 60 days post-surgery (P<0.05). There a statistically significant difference between experimental groups compared to the control group at 30 and 60 days post-surgery (P<0.05) while no statistically significant differences were observed among autograft, NCOE, autograft+NCOE (P>0.05). Also, absorb material significantly decreased in NCOE and autograft+NCOE groups compared to the control group at 60 days post-surgery (P<0.05). The filling defect significantly increased in autograft, NCOE and NCOE+autograft groups compared to the control group at 90 days post-surgery (P<0.05). There was no significant difference on inflammation and absorb material among the groups at 90 days post-surgery (P>0.05). These results suggested NCOE+autograft has improved the rate of calvarium healing in rabbits

Predicting air pollution in Tehran: Genetic algorithm and back propagation neural network

Suspended particles have deleterious effects on human health and one of the reasons why Tehran is effected is its geographically location of air pollution. One of the most important ways to reduce air pollution is to predict the concentration of pollutants. This paper proposed a hybrid method to predict the air pollution in Tehran based on particulate matter less than 10 microns (PM10), and the information and data of Aghdasiyeh Weather Quality Control Station and Mehrabad Weather Station from 2007 to 2013. Generally, 11 inputs have been inserted to the model, to predict the daily concentration of PM10. For this purpose, Artificial Neural Network with Back Propagation (BP) with a middle layer and sigmoid activation function and its hybrid with Genetic Algorithm (BP-GA) were used and ultimately the performance of the proposed method was compared with basic Artificial Neural Networks along with (BP) Based on the criteria of - R2-, RMSE and MAE.  The finding shows that BP-GA   has higher accuracy and performance. In addition, it was also found that the results are more accurate for shorter time periods and this is because the large fluctuation of data in long-term returns negative effect on network performance. Also, unregistered data have negative effect on predictions. Microsoft Excel and Matlab 2013 conducted the simulations

The Development of an Empirical Model for Estimation of the Sensitivity to Heat Stress in the Outdoor Workers at Risk

Background: Workers who work in hot environments may be at risk for heat stress. Exposure to heat can result in occupational illnesses, including heat stroke, heat cramps, and heat exhaustion. The risk of exposure to heat depends on individual, environmental, and occupational risk factors. Individual risk factors may decrease the individual’s tolerance to heat stress. Sensitivity as an intrinsic factor may predispose a person to heat stress. Aim: This study was aimed to determine the criteria for sensitivity parameter, specify their weights using the fuzzy Delphi-analytical hierarchy, and finally providing a model to estimate sensitivity. The significant of the study is presenting a model to estimate the sensitivity to heat stress. Materials and Methods: The expert’s opinions were used to extract the criteria in Delphi method. After determining the weight of each criterion, Fuzzy analytic hierarchy Process (FAHP), by mathematical principles matrix and triangular fuzzy numbers, was applied for the prioritization of criteria. Results: According to experts’ viewpoints and considering some exclusion, 10 of 36 criteria were selected. Among 10 selected criteria, age had the highest percentage of responses (90% (27/30)) and its relative weight was 0.063. After age, the highest percentages of response were assigned to the factors of preexisting disease (66.6% (20/30)), body mass index (56.6% (17/30)), work experience (53.3% (16/30)), and clothing (40% (16/30)), respectively. Other effective criteria on sensitivity were metabolic rate, daily water consumption, smoking habits, drugs that interfere with the thermoregulatory processes, and exposure to other harmful agents. Conclusions: Eventually, based on the criteria, a model for estimation of the workers’ sensitivity to heat stress was presented for the first time, by which the sensitivity is estimated in percent.Keywords: Heat stress, Sensitivity, Personal factors, Fuzzy AH

Edge Detection in SAR images using phase stretch transform

In this work a novel approach to edge detection on Synthetic Aperture Radar (SAR) images is introduced. The proposed method uses an optics inspired transform which emulates the diffraction of an image through a medium with nonlinear dispersive properties. The experimental results show that the output of the introduced Phase Stretch Transform (PST) in conjunction with further morphological operations can be effectively used for image edge detection

Edge Detection in Digital Images Using Dispersive Phase Stretch Transform

We describe a new computational approach to edge detection and its application to biomedical images. Our digital algorithm transforms the image by emulating the propagation of light through a physical medium with specific warped diffractive property. We show that the output phase of the transform reveals transitions in image intensity and can be used for edge detection