Iranian Journal of Electrical and Electronic Engineering

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In this paper we present a new accurate steganalysis method for the LSB

replacement steganography. The suggested method is based on the changes that occur in the

histogram of an image after the embedding of data. Every pair of neighboring bins of a

histogram are either inter-related or unrelated depending on whether embedding of a bit of

data in the image could affect both bins or not. We show that the overall behavior of all

inter-related bins, when compared with that of the unrelated ones, could give an accurate

measure for the amount of the embedded data. Both analytical analysis and simulation

results show the accuracy of the proposed method. The suggested method has been

implemented and tested for over 2000 samples and compared with the RS Steganalysis

method. Mean and variance of error were 0.0025 and 0.0037 for the suggested method

where these quantities were 0.0070 and 0.0182 for the RS Steganalysis. Using 4800

samples, we showed that the performance of the suggested method is comparable with

those of the RS steganalysis for JPEG filtered images. The new approach is applicable for

the detection of both random and sequential LSB embedding.

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Band-notch characteristic has been of great interest recently to overcome the electromagnetic interference of Ultra-wideband systems (UWB) with other existing ones. In this paper, we present a novel microstrip-fed antenna with band rejection property appropriate for UWB applications. Band-notch characteristic has been achieved by adding a rectangular resonant element to the ground section. A prototype was fabricated and measured based upon optimal parameters. Experimental results show consistency with simulation results. Measurement results confirm that the antenna covers the UWB band and satisfies a band rejection in the frequency span of 5 GHz to 5.7 GHz to restrain it from interference with Wireless Local Area Network (WLAN). Then, to achieve better isolation, a rectangular strip is appended to the band-notch creating part of the ground section to enhance obtained VSWR up to 30 through simulation. In addition, by applying a similar technique, a dual band-notched characteristic with an average simulated VSWR of around 13.75 has been achieved for WLAN and the downlink of X band satellite communication systems with each more than 10. Features such as small size, omnidirectional pattern and perfect isolation make the antenna suitable for any UWB applications.

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The Micro-Grid (MG) stability is a significant issue that must be maintained in all operational modes. Usually, two control strategies can be applied to MG; V/f control and PQ control strategies. MGs with V/f control strategy should have some Distributed Generators (DGs) which have fast responses versus load changes. The Flywheel Energy Storage System (FESS) has this characteristic. The FESS, which converts the mechanical energy to electrical form, can generate electrical power or absorb the additional power in power systems or MGs. In this paper, the FESS structure modeled in detail and two control strategies (V/f and PQ control) are applied for this application. In addition, in order to improve the MG frequency and voltage stability, two complementary controllers are proposed for the V/f control strategy; conventional PI and Fuzzy Controllers. A typical low voltage network, including FESS is simulated for four distinct scenarios in the MATLAB/ Simulink environment. It is shown that fuzzy controller has better performance than conventional PI controller in islanded microgrid.

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Using mobile phones for medical applications are proliferating due to high-quality embedded sensors. Jaundice, a yellow discoloration of the skin caused by excess bilirubin, is a prevalent physiological problem in newborns. While moderate amounts of bilirubin are safe in healthy newborns, extreme levels are fatal and cause devastating and irreversible brain damage. Accurate tests to measure jaundice require a blood draw or dedicated clinical devices facing difficulty where clinical technology is unavailable. This paper presents a smartphone-based screening tool to detect neonatal hyperbilirubinemia caused by the high bilirubin production rate. A machine learning regression model is trained on a pretty large dataset of images, including 446 samples, taken from newborns' sternum skin in four medical centers in Iran. The learned model is then used to estimate the level of bilirubin. Experimental results show a mean absolute error of 1.807 mg/dl and a correlation of 0.701 between predicted bilirubin by the proposed method and the TSB values as ground truth.