Paper dimensional stability in sheet-fed offset printing : Papperets dimensionsstabilitet i en arkoffsetpress

In offset printing, dampening solution is used to create a good balance in the process. If too much water is transferred to the paper, the sheet can change its size between the printing units, due to water absorption, and cause a problem with the colour register. This phenomenon is usually referred to as fanout. In this degree project, an investigation was made to see if the paper dimensions changed through its way in the sheet-fed printing process. The instrument Luchs Register Measuring Systems (Lynx) was used, and a method for measuring if the paper changed its dimensions with this instrument, was developed. Paper qualities with three different grammages were used, 90, 130 and 250 gsm. This investigation showed that all paper qualities changed their size with widening in the gripper edge in the range of 10 - 70 µm and in the trailing edge the increase was 10 - 130 µm. The elongations of the papers were in the range of 10- 300 µm. The papers with lowest grammage changed more than the heavier. To see if the print had been affected of the widening and elongation, print quality parameters like relative contrast, dot gain and mottle were correlated with the Lynx data from the sheets. The group of papers that gave correlations were in 130 gsm. The sheets had visual doubling and the combined standard deviation from the Lynx marks K3, K5 and K21 correlated with dot gain. When the variations increased so did the dot gain and this indicates that the doubling was due to the widening. There was also a correlation between the standard deviation from K3 and Mottle. The sheets widened with an average of 30 µm in the gripper edge and since there probably were doubling due to widening it also affected the Mottle values. What the widening depends on is hard to tell. Since widening was so small, it could be due to water absorption, papers being ironed out or maybe the sheets have been flattened out. It probably needs a more detailed investigation to find out what causes the widening. Further investigations about how print quality is affected by the register accuracy of a printing machine should include a print form with measuring areas close to the Lynx marks. The measuring areas should contain fine hairlines, negative text printed with at least two colours and some pictures to evaluate together with standard measuring should give a good knowledge about the subject.

Independent Domain of Symmetric Encryption using Least SignificantBit : Computer Vision, Steganography and Cryptography Techniques

The rapid development of data transfer through internet made it easier to send the data accurate and faster to the destination. There are many transmission media to transfer the data to destination like e-mails; at the same time it is may be easier to modify and misuse the valuable information through hacking. So, in order to transfer the data securely to the destination without any modifications, there are many approaches like cryptography and steganography. This paper deals with the image steganography as well as with the different security issues, general overview of cryptography, steganography and digital watermarking approaches.  The problem of copyright violation of multimedia data has increased due to the enormous growth of computer networks that provides fast and error free transmission of any unauthorized duplicate and possibly manipulated copy of multimedia information. In order to be effective for copyright protection, digital watermark must be robust which are difficult to remove from the object in which they are embedded despite a variety of possible attacks. The message to be send safe and secure, we use watermarking. We use invisible watermarking to embed the message using LSB (Least Significant Bit) steganographic technique. The standard LSB technique embed the message in every pixel, but my contribution for this proposed watermarking, works with the hint for embedding the message only on the image edges alone. If the hacker knows that the system uses LSB technique also, it cannot decrypt correct message. To make my system robust and secure, we added cryptography algorithm as Vigenere square. Whereas the message is transmitted in cipher text and its added advantage to the proposed system. The standard Vigenere square algorithm works with either lower case or upper case. The proposed cryptography algorithm is Vigenere square with extension of numbers also. We can keep the crypto key with combination of characters and numbers. So by using these modifications and updating in this existing algorithm and combination of cryptography and steganography method we develop a secure and strong watermarking method. Performance of this watermarking scheme has been analyzed by evaluating the robustness of the algorithm with PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error) against the quality of the image for large amount of data. While coming to see results of the proposed encryption, higher value of 89dB of PSNR with small value of MSE is 0.0017. Then it seems the proposed watermarking system is secure and robust for hiding secure information in any digital system, because this system collect the properties of both steganography and cryptography sciences.

Analysis of response to enteral infusion of levodopa in patients with Parkinson's disease

Objective: We present a new evaluation of levodopa plasma concentrations and clinical effects during duodenal infusion of a levodopa/carbidopa gel (Duodopa ) in 12 patients with advanced Parkinson s disease (PD), from a study reported previously (Nyholm et al, Clin Neuropharmacol 2003; 26(3): 156-163). One objective was to investigate in what state of PD we can see the greatest benefits with infusion compared with corresponding oral treatment (Sinemet CR). Another objective was to identify fluctuating response to levodopa and correlate to variables related to disease progression. Methods: We have computed mean absolute error (MAE) and mean squared error (MSE) for the clinical rating from -3 (severe parkinsonism) to +3 (severe dyskinesia) as measures of the clinical state over the treatment periods of the study. Standard deviation (SD) of the rating was used as a measure of response fluctuations. Linear regression and visual inspection of graphs were used to estimate relationships between these measures and variables related to disease progression such as years on levodopa (YLD) or unified PD rating scale part II (UPDRS II).Results: We found that MAE for infusion had a strong linear correlation to YLD (r2=0.80) while the corresponding relation for oral treatment looked more sigmoid, particularly for the more advanced patients (YLD>18).

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

Hglm: A package for fitting hierarchical generalized linear models

We present the hglm package for fitting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.

Fitting spatial models in the R package: hglm

We present a new version of the hglm package for fittinghierarchical generalized linear models (HGLM) with spatially correlated random effects. A CAR family for conditional autoregressive random effects was implemented. Eigen decomposition of the matrix describing the spatial structure (e.g. the neighborhood matrix) was used to transform the CAR random effectsinto an independent, but heteroscedastic, gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR model.This gives a computationally efficient algorithm for moderately sized problems (e.g. n<5000).

Fitting conditional and simultaneous autoregressive spatial models in hglm

We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.