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Information hiding of data in an audio file is an important thing that the media can be recognized by its ownership. The hidden information would be the important information which describes the copyright of the audio file. In this research, the binary data is inserted or hidden into the audio file by multicarrier modulation technique data hiding. The encoded binary data is modulated by multicarrier frequencies before embedding into the host audio. Data hiding capacity with this technique can achieve up to 40 bits per second in file mode with good audio imperceptibility. It also achieves perfect robustness for type of attack noise addition, linear speed change, multi band equalization, and echo addition. And this technique is still acceptable for type of attack, such as resampling attack, MP3 compression attack and filtering attack for cut off frequency more than 10 kHz regarding to the BER less than 10%. IntroductionMulticarrier modulation is a technique to modulate a baseband signal into several subcarrier at different frequencies in the same time. Prasad [1] said that OFDM basic principle is to split datastream into lower datastream transmitting simultaneously over several subcarriers. This principle is also called multicarrier modulation. The research about multicarrier modulation technique has been previously published on many papers and books. Nicola Marchetti [2] said that OFDM promises high data rate capability and uses available spectrum efficiently, which is a main reason OFDM was accepted by present telecommunication generation system. Data hiding by the OFDM method was already presented by Somnath [3]. His research is about hiding the grayscale image in OFDM signal where the image is read pixel by pixel and then converted the binary data into a complex number format and inserted the number via Quantized Index Modulation. In [4] Amirtharajan presented the paper describing the multicarrier steganography. He presented the image hiding by Spread Spectrum method combined with the Modulated Multicarrier signal in orthogonal radio frequency, but the robustness and imperceptibility were not explained.Shishkin [5] presented audio watermarking for Electronic Radiotelephone Identification in OFDM-based. He used Quantization Index Modulation as embedding method in frequency domain, but he didn't describe the imperceptibility and robustness. Garcia-Hernandez [6] proposed a high payload data-hiding scheme for audio signals in OFDM-based. The method which he used was to change the phase component of audio signal via a reduced-arc of M-order Phase Shift Keying (MPSK). It was modulated on selected frequency of the audio signals, however he only described the imperceptibility and capacity. The robustness was not described clearly.In this paper, we propose audio watermarking by multicarrier modulation method which the subcarrier signal are not orthogonal. This multicarrier watermarking is a watermarking process in which the hidden data is modulated by multicarrier by many frequencies from 0 to 22 kHz. The process of wat...

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This study investigated optical sensor system consist of sixteen light emitting diode (LED) in visible/near infrared region to detect palm oil fresh fruit bunch (FFB) quality. Practically, experience grader assessed FFB quality by its ripeness based on external features such as colour and number of detached fruitlets. However, different seed and plantation management resulting in FFB quality variation. Same external features not linearly correlate with FFB oil content that corresponding with industrial needs. The 660 nm LED is choosen to be used to estimate the oil content of FFB. Using linear discriminant analysis (LDA) with Mahalanobis distance, the accuracy of the systems is 79.8% and 88.2%. From 33 FFB oil content measurement, grader misclassified 4 out of 17 FFB as ripe FFB but with low oil content (<17.5%) and misclassified 7 out of 16 FFB as unripe but with high oil content (>=17.5%). Classifying model build from FFB from main plantation then tested to evaluate FFB from smallholder. Classification model generated from FFB oil content data showed more accurate result compared to model generated from visual inspection 66.7% compared to 52.1%. Model accuracies attained by Discriminant Analysis (DA) and k-Nearest Neighbors (k-NN) were 79.8% and 80.7%, respectively based on grader evaluation. Model accuracies based on FFB oil content was 88.2% for both classifying algorithms.