Concealing a Secret Message in a Colour Image Using an Electronic Workbench

Steganography is the art of concealing security data in media, such as pictures, audio, video, text, and protocols. The objective of this paper is hiding a secret message in a colour image to prevent an attacker from accessing the message. This is important because more people use the Internet all the time and network connections are spread around the world. The hidden secret message uses two general algorithms that are embedded and extracted. This paper proposes a new algorithm to conceal a secret message in a colour image in LSB. This algorithm includes three phases: 1) dividing the colour image into a number of blocks, 2) concealing the secret message, and 3) transmitting the stego-image from the sender in a multiplexer network and receiving it through a demultiplexer network using an electronic workbench. The outcome of the new algorithm demonstrates good efficiency, high security, and robustness and is executed quickly. The system is evaluated through the measurements of mean square error, peak signal-to-noise ratio, correlation, histogram, and capacity.

Evaluation of slip ratio correlations in two-phase flow

Critical flow is one of the essential parameters in LOCA accident analysis in which pressure difference is very high. Void fraction (α), in another term, slip ratio, s, is the key parameter that could affect critical flow prediction. Henry-Fauske (HF) model is the model for critical flow calculation existing in current computer codes such as MARS, RELAP, TRACE. However, the limitation of this model is slip ratio s=1. By modified the slip ratio correlation, the paper focuses on evaluating the HF model. Among the chosen correlations for slip ratio, Smith correlation is the best option for this purpose. The results in our paper showed that while the original Smith correlation with k=0.4 is suggested for horizontal tests, the modified one with k=0.2 could be applied for vertical tests.

Integrated Quantitative Neuro-transcriptome Analysis of Several Brain Areas in Human Trisomy 21

Background Although Down syndrome (DS) is a trisomy of chromosome 21 being the most frequent human chromosomal disorder mainly associated with variables dysfunctions. Objective In this context, we aimed to analyze and compare the disruption of transcriptome of several brain areas from individuals with DS and euploid controls as a new approach to consider a global systemic differential disruption of gene expression beyond of chromosome 21. Methods We used data from a DNA microarray experiment with ID GSE59630 previously deposited in the GEO DataSet of NCBI database. The array contained log2 values of 17,537 human genes expressed in several aeras of human brain. We calculated the differential gene expression (Z-ratio) of all genes. Results We found several differences in gene expression along the DS brain transcriptome, not only in the genes located at chromosome 21 but in other chromosomes. Moreover, we registered the lowest Z-ratio correlation between the age ranks of 16–22 weeks of gestation and 39–42 years (R 2 = 0.06) and the highest Z-ratio correlation between the age ranks of 30–39 years and 40–42 years (R 2 = 0.89). The analysis per brain areas showed that the hippocampus and the cerebellar cortex had the most different gene expression pattern when compared to the brain as a whole. Conclusions Our results support the hypothesis of a systemic imbalance of brain protein homeostasis, or proteostasis network of cognitive and neuroplasticity process as new model to explain the important effect on the neurophenotype of trisomy that occur not only in loci of chromosome 21 but also in genes located in other chromosomes.

A New Approach to The Pathogenesis of Down Syndrome: An Integrated Quantitative Neuro-Transcriptome Analysis of Several Brain Areas in Human Trisomy 21.

Background: Although Down syndrome (DS) is a trisomy of chromosome 21 being the most frequent human chromosomal disorder mainly associated with variable levels of intellectual disability and other dysfunctions, the only dose disbalance effect would not enough to explain its genetic and functional complexity neurophenotype. In this context, we aimed to analyze and compare the disruption of transcriptome of several brain areas from individuals with DS and euploid controls as a new approach to consider a global systemic differential disruption of gene expression beyond of chromosome 21. Methodology: To perform the analysis carried out in the present study, we used data from a DNA microarray experiment with ID GSE59630 previously deposited in the GEO DataSet of NCBI database. The array contained log2 values of 17,537 human genes expressed in several aeras of human brain. The data was collected from 58 postmortem brain samples of individuals with DS and 58 samples from euploid controls. We calculated the differential gene expression (Z-ratio) of all genes from the microarray according to the several brain areas, gene distribution per chromosome and age ranks. Results: We found several differences in gene expression along the DS brain transcriptome, not only in the genes located at chromosome 21 but in other chromosomes. Moreover, we registered the lowest Z-ratio correlation between the age ranks of 16-22 weeks of gestation and 39-42 years (R2=0.06) and the highest Z-ratio correlation between the age ranks of 30-39 years and 40-42 years (R2=0.89). The analysis per brain areas showed that the hippocampus and the cerebellar cortex had the most different gene expression pattern when compared to the brain as a whole. Conclusions: Our results revealed the complexity of gene expression networks in the transcriptome profiles of hippocampus, dorsolateral prefrontal cortex (DFC) and cerebellar cortex (CBC). Moreover, our approach opens a new vision of the genomic complexity of DS as a pathology of multiple and complex variables that are playing altogether to modeling their pathogenesis.

Effects of Rounding and Truncating Methods of Quantization Error and SQNR for Sine Signal

Within the Analog to Digital Conversion (ADC), quantization noise is a duplicate of a Quantization Error (QE) which is introduced by quantization. In signal processing and telecommunication systems, the noise is non-linear and depends on the signal type. During the analog, Sine signal converts to the digital (ADC) process, the two methods are used Rounding and Truncating in-order to eliminate the error produced in the digitization process. The rounding method quantize assigns each sample of sine signal to the nearest quantization level. However, making the Truncating would have assigned each sample of sine signal to the quantization level below it. This paper compares the rounding and truncating methods of QE for sine signal, signal to quantization noise ratio, correlation coefficient, and regression equation of a line for both methods. Then, it calculates the residual sum of squares and compares it to the regression equations of the lines.