scholarly journals Blind Audio Watermarking Based on Parametric Slant-Hadamard Transform and Hessenberg Decomposition

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 333
Author(s):  
Pranab Kumar Dhar ◽  
Azizul Hakim Chowdhury ◽  
Takeshi Koshiba
Keyword(s):  
State Of The Art ◽  
Audio Watermarking ◽  
Hadamard Transform ◽  
Watermark Image ◽  
Hessenberg Matrix ◽  
Multimedia Contents ◽  
Simulation Results ◽  
Ownership Protection ◽  
Host Signal ◽  
Square Matrix

Digital watermarking has been widely utilized for ownership protection of multimedia contents. This paper introduces a blind symmetric audio watermarking algorithm based on parametric Slant-Hadamard transform (PSHT) and Hessenberg decomposition (HD). In our proposed algorithm, at first watermark image is preprocessed to enhance the security. Then, host signal is divided into non-overlapping frames and the samples of each frame are reshaped into a square matrix. Next, PSHT is performed on each square matrix individually and a part of this transformed matrix of size m×m is selected and HD is applied to it. Euclidean normalization is calculated from the 1st column of the Hessenberg matrix, which is further used for embedding and extracting the watermark. Simulation results ensure the imperceptibility of the proposed method for watermarked audios. Moreover, it is demonstrated that the proposed algorithm is highly robust against numerous attacks. Furthermore, comparative analysis substantiates its superiority among other state-of-the-art methods.

scholarly journals SVD-Based Image Watermarking Using the Fast Walsh-Hadamard Transform, Key Mapping, and Coefficient Ordering for Ownership Protection

Symmetry ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 52 ◽  
Author(s):  
Tahmina Khanam ◽  
Pranab Kumar Dhar ◽  
Saki Kowsar ◽  
Jong-Myon Kim
Keyword(s):  
State Of The Art ◽  
Image Watermarking ◽  
Singular Values ◽  
Multimedia Data ◽  
Cover Image ◽  
Hadamard Transform ◽  
Art Methods ◽  
Walsh Hadamard Transform ◽  
Value Decomposition ◽  
Ownership Protection

Proof of ownership on multimedia data exposes users to significant threats due to a myriad of transmission channel attacks over distributed computing infrastructures. In order to address this problem, in this paper, an efficient blind symmetric image watermarking method using singular value decomposition (SVD) and the fast Walsh-Hadamard transform (FWHT) is proposed for ownership protection. Initially, Gaussian mapping is used to scramble the watermark image and secure the system against unauthorized detection. Then, FWHT with coefficient ordering is applied to the cover image. To make the embedding process robust and secure against severe attacks, two unique keys are generated from the singular values of the FWHT blocks of the cover image, which are kept by the owner only. Finally, the generated keys are used to extract the watermark and verify the ownership. The simulation result demonstrates that our proposed scheme is highly robust against numerous attacks. Furthermore, comparative analysis corroborates its superiority among other state-of-the-art methods. The NC of the proposed method is numerically one, and the PSNR resides from 49.78 to 52.64. In contrast, the NC of the state-of-the-art methods varies from 0.7991 to 0.9999, while the PSNR exists in the range between 39.4428 and 54.2599.

scholarly journals COVID-19 Diagnosis Using Capsule Network and Fuzzy C -Means and Mayfly Optimization Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ali Farki ◽  
Zahra Salekshahrezaee ◽  
Arash Mohammadi Tofigh ◽  
Reza Ghanavati ◽  
Behdad Arandian ◽  
...  
Keyword(s):  
State Of The Art ◽  
Optimal Method ◽  
X Ray ◽  
Suggested Technique ◽  
Improve Accuracy ◽  
Sensitivity Rate ◽  
Chest X Ray ◽  
Therapeutic Measures ◽  
Simulation Results ◽  
Day By Day

The COVID-19 epidemic is spreading day by day. Early diagnosis of this disease is essential to provide effective preventive and therapeutic measures. This process can be used by a computer-aided methodology to improve accuracy. In this study, a new and optimal method has been utilized for the diagnosis of COVID-19. Here, a method based on fuzzy C -ordered means (FCOM) along with an improved version of the enhanced capsule network (ECN) has been proposed for this purpose. The proposed ECN method is improved based on mayfly optimization (MFO) algorithm. The suggested technique is then implemented on the chest X-ray COVID-19 images from publicly available datasets. Simulation results are assessed by considering a comparison with some state-of-the-art methods, including FOMPA, MID, and 4S-DT. The results show that the proposed method with 97.08% accuracy and 97.29% precision provides the highest accuracy and reliability compared with the other studied methods. Moreover, the results show that the proposed method with a 97.1% sensitivity rate has the highest ratio. And finally, the proposed method with a 97.47% F 1 -score rate gives the uppermost value compared to the others.

State-of-the-Art Master Slave Flip-Flop Designs for Low Power VLSI Systems

2016 ◽  
pp. 166-198
Author(s):  
Kunwar Singh ◽  
Satish Chandra Tiwari ◽  
Maneesha Gupta
Keyword(s):  
Low Power ◽  
State Of The Art ◽  
Relative Power ◽  
Power Budget ◽  
Comprehensive Overview ◽  
Feedback Strategy ◽  
Flip Flop ◽  
Simulation Results

This chapter presents a comprehensive overview of the conventional fully static master slave flip-flops used in low power VLSI systems where power budget is critical. In addition, the chapter also presents alternative realization of fully static master-slave flip-flops utilizing a modified feedback strategy. The flip-flops designed on the basis of modified architecture have been explained in detail and compared with state-of-the-art master slave flip-flop designs available in the literature. Extensive capacitance calculations have been performed in terms of clock load and capacitance at internal nodes has also been estimated for all the flip-flop configurations. This is executed in order to compare their relative power and delay characteristics which are well supported by simulation results.

Digital Watermarking Techniques for Audio and Speech Signals

2011 ◽  
pp. 132-160
Author(s):  
Aparna Gurijala ◽  
John R. Deller Jr.
Keyword(s):  
Signal Processing ◽  
Performance Evaluation ◽  
Digital Watermarking ◽  
State Of The Art ◽  
Audio Watermarking ◽  
Speech Signals ◽  
Advantages And Disadvantages ◽  
Signal Features

The main objective of this chapter is to provide an overview of existing speech and audio watermarking technology and to demonstrate the importance of signal processing for the design and evaluation of watermarking algorithms. This chapter describes the factors to be considered while designing speech and audio watermarking algorithms, including the choice of the domain and signal features for watermarking, watermarked signal fidelity, watermark robustness, data payload, security, and watermarking applications. The chapter presents several state-of-the-art speech and audio watermarking algorithms and discusses their advantages and disadvantages. The various applications of watermarking and developments in performance evaluation of watermarking algorithms are also described.

Masking Models and Watermarking

2011 ◽  
pp. 93-116
Author(s):  
Mirko Luca Lobina ◽  
Luigi Atzori ◽  
Davide Mula
Keyword(s):  
Signal Processing ◽  
Intellectual Property ◽  
State Of The Art ◽  
The State ◽  
Audio Watermarking ◽  
Digital Right Management ◽  
The Future ◽  
Psychological Models ◽  
High Level ◽  
The Relationship

Many audio watermarking techniques presented in the last years make use of masking and psychological models derived from signal processing. Such a basic idea is winning because it guarantees a high level of robustness and bandwidth of the watermark as well as fidelity of the watermarked signal. This chapter first describes the relationship between digital right management, intellectual property, and use of watermarking techniques. Then, the crossing use of watermarking and masking models is detailed, providing schemes, examples, and references. Finally, the authors present two strategies that make use of a masking model, applied to a classic watermarking technique. The joint use of classic frameworks and masking models seems to be one of the trends for the future of research in watermarking. Several tests on the proposed strategies with the state of the art are also offered to give an idea of how to assess the effectiveness of a watermarking technique.

scholarly journals Blind Color Image Watermarking Using Fan Beam Transform and QR Decomposition

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 486
Author(s):  
Pranab Kumar Dhar ◽  
Pulak Hazra ◽  
Tetsuya Shimamura
Keyword(s):  
Color Image ◽  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Image Watermarking ◽  
Triangular Matrix ◽  
Structural Similarity ◽  
Qr Decomposition ◽  
Original Image ◽  
Color Image Watermarking ◽  
Multimedia Contents

Digital watermarking has been utilized effectively for copyright protection of multimedia contents. This paper suggests a blind symmetric watermarking algorithm using fan beam transform (FBT) and QR decomposition (QRD) for color images. At first, the original image is transferred from RGB to L*a*b* color model and FBT is applied to b* component. Then the b*component of the original image is split into m × m non-overlapping blocks and QRD is conducted to each block. Watermark data is placed into the selected coefficient of the upper triangular matrix using a new embedding function. Simulation results suggest that the presented algorithm is extremely robust against numerous attacks, and also yields watermarked images with high quality. Furthermore, it represents more excellent performance compared with the recent state-of-the-art algorithms for robustness and imperceptibility. The normalized correlation (NC) of the proposed algorithm varies from 0.8252 to 1, the peak signal-to-noise ratio (PSNR) varies from 54.1854 to 54.1892, and structural similarity (SSIM) varies from 0.9285 to 0.9696, respectively. In contrast, the NC of the recent state-of-the-art algorithms varies from 0.5193 to 1, PSNR varies from 38.5471 to 52.64, and SSIM varies from 0.9311 to 0.9663, respectively.

scholarly journals Tag Localization with Asynchronous Inertial-Based Shifting and Trilateration

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5204
Author(s):  
Alma’aitah ◽  
Eslim ◽  
Hassanein
Keyword(s):  
Low Power ◽  
Indoor Localization ◽  
State Of The Art ◽  
Location Estimation ◽  
Object Localization ◽  
Personal Area Networks ◽  
Matlab Simulation ◽  
Tag Localization ◽  
Simulation Results ◽  
Localization Data

Personal Area Networks (PAN) are key topologies in pervasive Internet of Things (IoT) localization applications. In the numerous object localization techniques, centralization and synchronization between the elements are assumed. In this paper, we leverage crowdsourcing from multiple fixed and mobile elements to enhance object localization. A cooperative crowdsourcing scheme is proposed to localize mobile low power tags using distributed and mobile/fixed readers for GPS assisted environments (i.e., outdoor) and fixed readers for indoors. We propose Inertial-Based Shifting and Trilateration (IBST) technique to provide an accurate reckoning of the absolute location of mobile tags. The novelty in our technique is its capability to estimate tag locations even when the tag is not covered by three readers to perform trilateration. In addition, IBST provides scalability since no processing is required by the low power tags. IBST technique is validated through extensive simulations using MATLAB. Simulation results show that IBST consistently estimates location, while other indoor localization solutions fail to provide such estimates as the state-of-the-art techniques require localization data to be available simultaneously to provide location estimation.

Case Study of the Puna Geothermal Power Plant and Proposed Retrofit H2S Gas Mitigation Strategies

2020 ◽  
Author(s):  
Kevin R. Anderson ◽  
Wael Yassine
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
State Of The Art ◽  
Mitigation Strategies ◽  
Geothermal Power Plant ◽  
Current State ◽  
Abatement Strategies ◽  
Simulation Results ◽  
Geothermal Power

Abstract This paper presents modeling of the Puna Geothermal Venture as a case study in understanding how the technology of geothermal can by successfully implemented. The paper presents a review of the Puna Geothermal Venture specifications, followed by simulation results carried out using NREL SAM and RETSCREEN analysis tools in order to quantify the pertinent metrics associated with the geothermal powerplant by retrofitting its current capacity of 30 MW to 60 MW. The paper closes with a review of current state-of-the art H2S abatement strategies for geothermal power plants, and presents an outline of how these technologies can be implemented at the Puna Geothermal Venture.

scholarly journals Super resolution DOA estimation based on deep neural network

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Wanli Liu
Keyword(s):  
Neural Network ◽  
Potential Application ◽  
Deep Neural Network ◽  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Super Resolution ◽  
Doa Estimation ◽  
Angular Distance ◽  
Signal To Noise ◽  
Simulation Results

AbstractRecently, deep neural network (DNN) studies on direction-of-arrival (DOA) estimations have attracted more and more attention. This new method gives an alternative way to deal with DOA problem and has successfully shown its potential application. However, these works are often restricted to previously known signal number, same signal-to-noise ratio (SNR) or large intersignal angular distance, which will hinder their generalization in real application. In this paper, we present a novel DNN framework that realizes higher resolution and better generalization to random signal number and SNR. Simulation results outperform that of previous works and reach the state of the art.

scholarly journals Graphene-based membranes: status and prospects

2016 ◽  
Vol 374 (2060) ◽  
pp. 20150024 ◽  
Author(s):  
Hee Wook Yoon ◽  
Young Hoon Cho ◽  
Ho Bum Park
Keyword(s):  
Graphene Oxide ◽  
Basal Plane ◽  
State Of The Art ◽  
Future Research ◽  
Two Dimensional ◽  
Research Directions ◽  
Graphene Layers ◽  
Future Research Directions ◽  
Simulation Results ◽  
Graphene Membranes

Recently, graphene-based membranes have been extensively studied, represented by two distinct research directions: (i) creating pores in graphene basal plane and (ii) engineering nanochannels in graphene layers. Most simulation results predict that porous graphene membranes can be much more selective and permeable than current existing membranes, also evidenced by some experimental results for gas separation and desalination. In addition, graphene oxide has been widely investigated in layered membranes with two-dimensional nanochannels, showing very intriguing separation properties. This review will cover state-of-the-art of graphene-based membranes, and also provide a material guideline on future research directions suitable for practical membrane applications.

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