An Audio Watermarking Algorithm Based on Minimum Energy Harmonic Phase Deflection

<div>Renewable harvesting clean and hydrogen energy using the benefits of novel multicatalytic materials of high entropy alloy (HEA equimolar Cu-Ag-Au-Pt-Pd) from formic acid with minimum energy input has been achieved in the present investigation. The synthesis effect of pristine elements in the HEA drives the electro-oxidation reaction towards non-carbonaceous pathway . The atomistic simulation based on DFT rationalize the distinct lowering of the d-band center for the individual atoms in the HEA as compared to the pristine counterparts. This catalytic activity of the HEA has also been extended to methanol electro-oxidation to show the unique capability of the novel catalyst. The nanostructured HEA, properties using a combination of casting and cry omilling techniques can further be utilized as fuel cell anode in direct formic acid/methanol fuel cells (DFFE).<br></div>

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An Approach For Real Time Audio Watermarking Using Wavetable Alternation In Digital Instruments

i-manager’s Journal on Electronics Engineering ◽

10.26634/jele.1.4.1511 ◽

2011 ◽

Vol 1 (4) ◽

pp. 50-55

Author(s):

M. Vadivel ◽

V. Saravanan

Keyword(s):

Real Time ◽

Audio Watermarking

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Compressive Sensing Audio Watermarking dengan Metode LWT dan QIM

ELKOMIKA Jurnal Teknik Energi Elektrik Teknik Telekomunikasi & Teknik Elektronika ◽

10.26760/elkomika.v6i3.405 ◽

2018 ◽

Vol 6 (3) ◽

pp. 405

Author(s):

IRMA SAFITRI ◽

NUR IBRAHIM ◽

HERLAMBANG YOGASWARA

Keyword(s):

Wavelet Transform ◽

Compressive Sensing ◽

Audio Watermarking ◽

Quantization Index Modulation ◽

Computationally Efficient ◽

Black And White ◽

Additional Information ◽

Audio Files ◽

Index Modulation ◽

Mp3 Compression

ABSTRAKPenelitian ini mengembangkan teknik Compressive Sensing (CS) untuk audio watermarking dengan metode Lifting Wavelet Transform (LWT) dan Quantization Index Modulation (QIM). LWT adalah salah satu teknik mendekomposisi sinyal menjadi 2 sub-band, yaitu sub-band low dan high. QIM adalah suatu metode yang efisien secara komputasi atau perhitungan watermarking dengan menggunakan informasi tambahan. Audio watermarking dilakukan menggunakan file audio dengan format *.wav berdurasi 10 detik dan menggunakan 4 genre musik, yaitu pop, classic, rock, dan metal. Watermark yang disisipkan berupa citra hitam putih dengan format *.bmp yang masing-masing berukuran 32x32 dan 64x64 pixel. Pengujian dilakukan dengan mengukur nilai SNR, ODG, BER, dan PSNR. Audio yang telah disisipkan watermark, diuji ketahanannya dengan diberikan 7 macam serangan berupa LPF, BPF, HPF, MP3 compression, noise, dan echo. Penelitian ini memiliki hasil optimal dengan nilai SNR 85,32 dB, ODG -8,34x10-11, BER 0, dan PSNR ∞.Kata kunci: Audio watermarking, QIM, LWT, Compressive Sensing. ABSTRACTThis research developed Compressive Sensing (CS) technique for audio watermarking using Wavelet Transform (LWT) and Quantization Index Modulation (QIM) methods. LWT is one technique to decompose the signal into 2 sub-bands, namely sub-band low and high. QIM is a computationally efficient method or watermarking calculation using additional information. Audio watermarking was done using audio files with *.wav format duration of 10 seconds and used 4 genres of music, namely pop, classic, rock, and metal. Watermark was inserted in the form of black and white image with *.bmp format each measuring 32x32 and 64x64 pixels. The test was done by measuring the value of SNR, ODG, BER, and PSNR. Audio that had been inserted watermark was tested its durability with given 7 kinds of attacks such as LPF, BPF, HPF, MP3 Compression, Noise, and Echo. This research had optimal result with SNR value of 85.32 dB, ODG value of -8.34x10-11, BER value of 0, and PSNR value of ∞.Keywords: Audio watermarking, QIM, LWT, Compressive Sensing.

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