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Fueled by the rapid growth of internet, steganography has emerged as one of the promising techniques in the communication system to obscure the data. Steganography is defined as the process of concealing the data or message within media files without affecting the perception of the image. Media files, like audio, video, image, etc., are utilized to embed the message. Nowadays, steganography is also used to transmit the medical information or diagnostic reports. The paper aims to discuss these issues.

In this paper, the novel wavelet transform-based steganographic method is proposed for secure data communication using OFDM system. The embedding and extraction process in the proposed steganography method exploits the wavelet transform. Initially, the cost matrix is estimated by the following three aspects: pixel intensity, edge transformation and wavelet transform. The cost estimation matrix provides the location of the cover image where the message is to be entrenched. Then, the wavelet transform is utilized to embed the message into the cover image according to the cost value. Subsequently, in the extraction process, the wavelet transform is applied to the embedded image to retrieve the message efficiently. Finally, in order to transfer the secret information over the channel, the newly developed wavelet-based steganographic method is employed for the OFDM system.

The experimental results are evaluated and performance is analyzed using PSNR and MSE parameters and then compared with existing systems. Thus, the outcome of our wavelet transform steganographic method achieves the PSNR of 71.5 dB which ensures the high imperceptibility of the image. Then, the outcome of the OFDM-based proposed steganographic method attains the higher PSNR of 71.07 dB that proves the confidentiality of the message.

In the authors’ previous work, the embedding and extraction process was done based on the cost estimation matrix. To enhance the security throughout the communication system, the novel wavelet-based embedding and extraction process is applied to the OFDM system in this paper. The idea behind this method is to attain a higher imperceptibility and robustness of the image.

The present study utilizes daily mean time series of meteorological parameters (air temperature, relative humidity, barometric pressure and wind speed) and daily totals of rainfall data to understand the changes in these parameters during 17 years period i.e. 1990 to 2006. The analysis of the above data is made using continuous and discrete wavelet transforms because it provides a time‐frequency representation of an analyzed signal in the time domain. Moreover, in the recent years, wavelet methods have become useful and powerful tools for analysis of the variations, periodicities, trends in time series in general and meteorological parameters in particular. In present study, both continues and discrete wavelet transforms were used and found to be capable of showing the increasing or decreasing trends of the meterorological parameters with. The seasonal variability was also very well represented by the wavelet analysis used in this study. High levels of compressions were obtained retaining the originality of the signals.

The technique for hiding confidential data in specific digital media by enhancing the graphical contents is known as watermarking. The dissemination of information over a secure channel is essential for multimedia applications. The purpose of this study is to develop a secure communication approach for OFDM system.

This paper exploits a secure communication in the orthogonal frequency division multiplexing (OFDM) system using wavelet-based video watermarking technique. In this work, the Chronological-MS algorithm is used for securing the data communication in the OFDM system. Here, the secret message is embedded in video frames using wavelet transform for hiding sensitive information and the hidden information is transmitted over the OFDM system. The Chronological-MS algorithm is used for selecting the optimal regions in the video for embedding secret message. In embedding phase, wavelet coefficients are obtained by applying wavelet transform on the frame for embedding the secret message. Meanwhile, in extraction phase, the inverse wavelet transform is applied to extract the secret message.

Considering number of frames, the maximum Peak signal-to-noise ratio (PSNR) value is attained by proposed Wavelet + Chronological MS method for Video 2 with value 73.643 dB, respectively. Meanwhile, the minimum mean squared error (MSE) attained by the proposed Wavelet + Chronological MS method is when considering number of frames with MSE values as 0.001 for both Videos 1 and 2. The minimum bit error rate (BER) value is attained by the proposed method with value 0.00009 considering random noise with Video 1. Thus, the proposed Wavelet + Chronological MS have shown better results than the existing techniques.

This work proposes a wavelet-based watermarking method using Chronological-MS, for initiating secured communication over an OFDM. One of the main advantages of wavelets is that they offer a simultaneous localization in time and frequency domain. Hence, the proposed method offers the highly secured data transmission over the OFDM.

One way to analyze electrochemical signals is the wavelet transform, which transforms a signal into another representation whereby the signal information is presented in a multi‐scale manner. Using the inverse wavelet transform, it is also possible to split a signal into different components of different frequency intervals. The inverse wavelet transform is the concept underpinning this paper, the aim of which is to demonstrate that high‐frequency variations in current signals are as valuable as low‐frequency variations.

The set‐up for the experiments carried out consisted of two identical carbon steel working electrodes exposed to simulated concrete pore solution, sparged simultaneously with SO₂ and CO₂. The corresponding electrochemical current signal was studied using wavelet transform.

High‐frequency components of current signals are as informative as low‐frequency components. High‐frequency variations could show some electrochemical activities that are not obvious in the other parts.

This paper shows that high‐frequency variations can be taken into consideration along with low‐frequency variations, since both can provide complementary information about electrochemical activities.

This study examines the tracking error (TE) of a sample of sector exchange traded funds (ETFs) using spectral techniques.

TE is examined by computing its power spectrum using the wavelet transform. The wavelet transform maps the TE time series from the time domain to the time–frequency domain. Albeit the wavelet transform is a more complicated mathematical tool compared with the Fourier transform, it also has important advantages such as that it allows to analyze non-stationary data and to detect transient behavior.

Results show that changes in the TE of a sample of sector ETFs are captured by the wavelet transform. Moreover, the authors also find that the wavelet coherence function can be used as a measure of TE in the time–frequency domain.

The study shows that the wavelet coherence function can be used as a reliable measure of TE.

Interturn winding faults, one of the most important causes of power transformers failures, cannot be detected by existing detection methods until they develop into high‐level faults with more severe damage to the transformer. The purpose of this paper is to describe development of a new discrete wavelet transform (DWT) based approach for detection of winding interturn faults.

The following approach was accomplished for development of the proposed fault detection method in this study. The DWT was first applied to decompose the terminal current signals of a transformer, which in turn were obtained from simulations using a finite elements method model of the transformer, into a series of wavelet components. Based on the characteristic features associated with interturn faults extracted from the decomposed waveforms of the terminal currents, a detection scheme was developed. An experimental setup was used to validate the proposed detection method.

The results of this study demonstrate the efficacy of DWT applied on terminal currents of the transformer to identify interturn faults on the windings well before such faults lead to a catastrophic failure. It is believed that, based on the present findings, there definitely exists scope for improving interturn fault diagnosis with wavelet transform.

Performing more detailed studies to find all relevant characteristics of the wavelet transform in this application, identifying the location of the faulted turns along winding, applying the method for indicating early stages of turn insulation deterioration and evaluating other type of wavelets for this application would be some future directions of this research.

With the proposed method, it is becoming possible to detect early signs of the fault occurrence, so that the necessary corrective actions can be taken to prevent long‐lasting outages and reduce down times of the faulty power transformer. The method will be particularly useful as a complement for the classical protection devices of the power transformers.

Some recent studies have been carried out regarding the application of DWT for discrimination between an internal fault and other disturbances such as magnetizing inrush and external faults. This paper extends those studies for the detection of interturn faults using more quantitative and qualitative characteristics features.

The aim of this paper is to show that the use of energy distribution plot (EDP), usually employed by researchers to characterize the behavior of electrochemical signals in the framework of wavelet transform, could provide better understanding of the electrochemical behavior of a corroding surface if used along with the plot that is obtained from the standard deviation (SD) of partial signals (SDPS). A partial signal (PS) is obtained by limiting the inverse discrete wavelet transform to one crystal, and hence an SDPS is obtained by computing the SD of the corresponding PS.

The electrochemical current signals, obtained from two identical working electrodes (carbon steel electrodes) exposed to simulated concrete pore solution, sparged simultaneously with SO₂ and CO₂ were studied using wavelet transforms.

The results show two steps of passive oxide layer formation: formation of defective passive oxide layer, and strengthening of the passive oxide layer. The passive oxide layer breakdown where CO₂ as well as SO₂ are involved occurred at a pH of approximately 11. Both the EDP and SDPS plots should be used, simultaneously, to characterize the processes occurring on the surfaces of the exposed electrodes.

The results that were obtained can be regarded as the basis for better understanding and improvement of the noise analysis method.

This paper studies the corrosion behavior of carbon steel rebar before and after the simultaneous introduction of CO₂ and SO₂ gases in simulated pore solution, using EDP and SDPS plots obtained from the electrochemical current signals at different pH values.

When designing the electrode widths of the electrode-width-weighted (EWW) input interdigital transducers (IDTs) according to the envelope amplitudes of the wavelet function, the EWW wavelet transform processor (WTP) using surface acoustic wave (SAW) devices can be fabricated. The electrode widths have influence on the frequency characteristic of the EWW WTP using SAW devices. The purpose of this research is to solve the influence of the electrode width accuracy on the frequency characteristic of the EWW WTP using SAW devices.

In order to solve the influence of the electrode width accuracy on the frequency characteristics of the EWW WTP using SAW devices, the function between the electrode widths and the −3 dB bandwidth is derived. That the −3 dB bandwidth varies as the electrode widths is known according to this function so that the exposure time and the etching are presented as the two key problems.

Solutions to these problems are achieved in this study. As long as there is accurate exposure time, the precision IDTs (i.e. the precision electrode widths) will be obtained. The accuracy of the exposure time for the EWW WTP using SAW devices is ±1 per cent. Because the dry etching is a type of etching technology in gas medium, it can etch nanometer lines, even more fine lines, so that the dry etching is used in EWW WTP using SAW devices.

Research highlights solving the influence of the electrode width accuracy on the frequency characteristic for the EWW WTP using SAW devices; deriving the function between the electrode widths and the −3 dB bandwidth (it is known from this function that the −3 dB bandwidth varies as the electrode widths); and presenting the exposure time and the etching as two key problems.

The purpose of this paper, with reference to compression of different images' portions with various qualities, is to obtain a high‐compression coefficient.

Usually, not all parts of a medical image have equal significance. Also, an image's background can be combined with noise. This method separates a part of the video which is moving from a part that is stationary.

This process results in the high‐quality compression of medical frames.

Separating parts of a frame using 2D and 3D wavelet transform makes a valuable contribution to biocybernetics.

In real life, excitations are highly non-stationary in frequency and amplitude, which easily induces resonant vibration to structural responses. Conventional control algorithms in this case cannot guarantee cost-effective control effort and efficient structural response alleviation. To this end, this paper proposes a novel adaptive linear quadratic regulator (LQR) by integrating wavelet transform and genetic algorithm (GA).

In each time interval, multiresolution analysis of real-time structural responses returns filtered time signals dominated by different frequency bands. Minimization of cost function in each frequency band obtains control law and gain matrix that depend on temporal-frequency band, so suppressing resonance-induced filtered response signal can be directly achieved by regulating gain matrix in the temporal-frequency band, leading to emphasizing cost-function weights on control and state. To efficiently subdivide gain matrices in resonant and normal frequency bands, the cost-function weights are optimized by a developed procedure associated to genetic algorithm. Single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) structures subjected to near- and far-fault ground motions are studied.

Resonant band requires a larger control force than non-resonant band to decay resonance-induced peak responses. The time-varying cost-function weights generate control force more cost-effective than time-invariant ones. The scheme outperforms existing control algorithms and attains the trade-off between response suppression and control force under non-stationary excitations.

Proposed control law allocates control force amounts depending upon resonant or non-resonant band in each time interval. Cost-function weights and wavelet decomposition level are formulated in an elegant manner. Genetic algorithm-based optimization cost-efficiently results in minimizing structural responses.