Search results for: audio watermarking

Authors: Jyoti Rani, Ashima Anand, Shivendra Shivani

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In recent years, physiological signals obtained in telemedicine have been stored independently from patient information. In addition, people have increasingly turned to mobile devices for information on health-related topics. Major authentication and security issues may arise from this storing, degrading the reliability of diagnostics. This study introduces an approach to reversible watermarking, which ensures security by utilizing the electrocardiogram (ECG) signal as a carrier for embedding patient information. In the proposed work, Pan-Tompkins++ is employed to convert the 1D ECG signal into a 2D signal. The frequency subbands of a signal are extracted using RDWT(Redundant discrete wavelet transform), and then one of the subbands is subjected to MSVD (Multiresolution singular valued decomposition for masking. Finally, the encrypted watermark is embedded within the signal. The experimental results show that the watermarked signal obtained is indistinguishable from the original signals, ensuring the preservation of all diagnostic information. In addition, the DnCNN (Denoising convolutional neural network) concept is used to denoise the retrieved watermark for improved accuracy. The proposed ECG signal-based watermarking method is supported by experimental results and evaluations of its effectiveness. The results of the robustness tests demonstrate that the watermark is susceptible to the most prevalent watermarking attacks.

Keywords: ECG, VMD, watermarking, PanTompkins++, RDWT, DnCNN, MSVD, chaotic encryption, attacks

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Authors: Farhan A. Alenizi

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Digital watermarking has evolved in the past years as an important means for data authentication and ownership protection. The images and video watermarking was well known in the field of multimedia processing; however, 3D objects' watermarking techniques have emerged as an important means for the same purposes, as 3D mesh models are in increasing use in different areas of scientific, industrial, and medical applications. Like the image watermarking techniques, 3D watermarking can take place in either space or transform domains. Unlike images and video watermarking, where the frames have regular structures in both space and temporal domains, 3D objects are represented in different ways as meshes that are basically irregular samplings of surfaces; moreover, meshes can undergo a large variety of alterations which may be hard to tackle. This makes the watermarking process more challenging. While the transform domain watermarking is preferable in images and videos, they are still difficult to implement in 3d meshes due to the huge number of vertices involved and the complicated topology and geometry, and hence the difficulty to perform the spectral decomposition, even though significant work was done in the field. Spatial domain watermarking has attracted significant attention in the past years; they can either act on the topology or on the geometry of the model. Exploiting the statistical characteristics in the 3D mesh models from both geometrical and topological aspects was useful in hiding data. However, doing that with minimal surface distortions to the mesh attracted significant research in the field. A 3D mesh blind watermarking technique is proposed in this research. The watermarking method depends on modifying the vertices' positions with respect to the center of the object. An optimal method will be developed to reduce the errors, minimizing the distortions that the 3d object may experience due to the watermarking process, and reducing the computational complexity due to the iterations and other factors. The technique relies on the displacement process of the vertices' locations depending on the modification of the variances of the vertices’ norms. Statistical analyses were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduced in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. To evaluate the algorithm's robustness against other common geometry and connectivity attacks, the watermarked objects were subjected to uniform noise, Laplacian smoothing, vertices quantization, simplification, and cropping. Experimental results showed that the approach is robust in terms of both perceptual and quantitative qualities. It was also robust against both geometry and connectivity attacks. Moreover, the probability of true positive detection versus the probability of false-positive detection was evaluated. To validate the accuracy of the test cases, the receiver operating characteristics (ROC) curves were drawn, and they’ve shown robustness from this aspect. 3D watermarking is still a new field but still a promising one.

Keywords: watermarking, mesh objects, local roughness, Laplacian Smoothing

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Authors: Bruno T. Gomes, José A. Menezes, Giordano Cabral

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With the popularity of smartphones, mobile apps emerge to meet the diverse needs, however the resources at the disposal are limited, either by the hardware, due to the low computing power, or the software, that does not have the same robustness of desktop environment. For example, in automatic audio classification (AC) tasks, musical information retrieval (MIR) subarea, is required a fast processing and a good success rate. However the mobile platform has limited computing power and the best AC tools are only available for desktop. To solve these problems the fast classifier suits, to mobile environments, the most widespread MIR technologies, seeking a balance in terms of speed and robustness. At the end we found that it is possible to enjoy the best of MIR for mobile environments. This paper presents the results obtained and the difficulties encountered.

Keywords: audio classification, audio extraction, environment mobile, musical information retrieval

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Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: feature generation, feature learning, genetic algorithm, music information retrieval

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Authors: Vishwa Joshi

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The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

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Authors: Sandra Cuenca, Danilo Santana, Anderson Reyes

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The following project is based on the manipulation of audio signals through the Matlab software, which has an audio signal that is modified, and its resultant obtained through the auxiliary port of the computer is passed through a signal amplifier whose amplified signal is connected to a tesla coil which has a behavior like a vumeter, the flashes at the output of the tesla coil increase and decrease its intensity depending on the audio signal in the computer and also the voltage source from which it is sent. The amplified signal then passes to the tesla coil being shown in the plasma sphere with the respective flashes; this activation is given through the specified parameters that we want to give in the MATLAB algorithm that contains the digital filters for the manipulation of our audio signal sent to the tesla coil to be displayed in a plasma sphere with flashes of the combination of colors commonly pink and purple that varies according to the tone of the song.

Keywords: auxiliary port, tesla coil, vumeter, plasma sphere

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Authors: Shrikrishna Mishra, Badri Yadav

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In this complex society of today where experiences are innumerable and varied, it is not at all possible to present every situation in its original colors hence the opportunities for learning by actual experiences always are not at all possible. It is only through the use of proper audio visual aids that the life situation can be trough in the class room by an enlightened teacher in their simplest form and representing the original to the highest point of similarity which is totally absent in the verbal or lecture method. In the presence of audio aids, the attention is attracted interest roused and suitable atmosphere for proper understanding is automatically created, but in the existing traditional method greater efforts are to be made in order to achieve the aforesaid essential requisite. Inspire of the best and sincere efforts on the side of the teacher the net effect as regards understanding or learning in general is quite negligible.

Keywords: Audio-Visual Aids, the secondary school teaching, complex society, audio

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Authors: Sanchali Das, Swapan Debbarma

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Music mood classification is developing in both the areas of music information retrieval (MIR) and natural language processing (NLP). Some of the Indian languages like Hindi English etc. have considerable exposure in MIR. But research in mood classification in regional language is very less. In this paper, powerful audio based feature for Kokborok Christian song is identified and mood classification task has been performed. Kokborok is an Indo-Burman language especially spoken in the northeastern part of India and also some other countries like Bangladesh, Myanmar etc. For performing audio-based classification task, useful audio features are taken out by jMIR software. There are some standard audio parameters are there for the audio-based task but as known to all that every language has its unique characteristics. So here, the most significant features which are the best fit for the database of Kokborok song is analysed. The regression-based model is used to find out the independent parameters that act as a predictor and predicts the dependencies of parameters and shows how it will impact on overall classification result. For classification WEKA 3.5 is used, and selected parameters create a classification model. And another model is developed by using all the standard audio features that are used by most of the researcher. In this experiment, the essential parameters that are responsible for effective audio based mood classification and parameters that do not significantly change for each of the Christian Kokborok songs are analysed, and a comparison is also shown between the two above model.

Keywords: Christian Kokborok song, mood classification, music information retrieval, regression

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Authors: A. Kebbeb, M. Mostefai, F. Benmerzoug, Y. Chahir

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The multimodal biometric identification is the combination of several biometric systems. The challenge of this combination is to reduce some limitations of systems based on a single modality while significantly improving performance. In this paper, we propose a new approach to the construction and the protection of a multimodal biometric database dedicated to an identification system. We use a topological watermarking to hide the relation between face image and the registered descriptors extracted from other modalities of the same person for more secure user identification.

Keywords: biometric databases, multimodal biometrics, security authentication, digital watermarking

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Authors: Md Shohidul Islam, Jongmyon Kim, Ui-pil Chong

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Medical image is an integral part of e-health care and e-diagnosis system. Medical image watermarking is widely used to protect patients’ information from malicious alteration and manipulation. The watermarked medical images are transmitted over the internet among patients, primary and referred physicians. The images are highly prone to corruption in the wireless transmission medium due to various noises, deflection, and refractions. Distortion in the received images leads to faulty watermark detection and inappropriate disease diagnosis. To address the issue, this paper utilizes error correction code (ECC) with (8, 4) Hamming code in an existing watermarking system. In addition, we implement the high complex ECC on a graphics processing units (GPU) to accelerate and support real-time requirement. Experimental results show that GPU achieves considerable speedup over the sequential CPU implementation, while maintaining 100% ECC efficiency.

Keywords: medical image watermarking, e-health system, error correction, Hamming code, GPU

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Authors: M. Samadzadeh Mahabadi, J. Shanbehzadeh

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This paper presents a hybrid digital image-watermarking scheme, which is robust against varieties of attacks and geometric distortions. The image content is represented by important feature points obtained by an image-texture-based adaptive Harris corner detector. These feature points are extracted from LL2 of 2-D discrete wavelet transform which are obtained by using the Harris-Laplacian detector. We calculate the Fourier transform of circular regions around these points. The amplitude of this transform is rotation invariant. The experimental results demonstrate the robustness of the proposed method against the geometric distortions and various common image processing operations such as JPEG compression, colour reduction, Gaussian filtering, median filtering, and rotation.

Keywords: digital watermarking, geometric distortions, geometrical attack, Harris Laplace, important feature points, rotation, scale invariant feature

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Authors: Jangje Park, So Young Kim

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The market demand for audio quality in mobile devices continues to increase, and audible buzz noise generated in time division communication is a chronic problem that goes against the market demand. In the case of time division type communication, the RF Power Amplifier (RF PA) is driven at the audio frequency cycle, and it makes various influences on the audio signal. In this paper, we measured the ground bounce noise generated by the peak current flowing through the ground network in the RF PA with the audio frequency; it was confirmed that the noise is the cause of the audible buzz noise during a call. In addition, a grounding method of the microphone device that can improve the buzzing noise was proposed. Considering that the level of the audio signal generated by the microphone device is -38dBV based on 94dB Sound Pressure Level (SPL), even ground bounce noise of several hundred uV will fall within the range of audible noise if it is induced by the audio amplifier. Through the grounding method of the microphone device proposed in this paper, it was confirmed that the audible buzz noise power density at the RF PA driving frequency was improved by more than 5dB under the conditions of the Printed Circuit Board (PCB) used in the experiment. A fundamental improvement method was presented regarding the buzzing noise during a mobile phone call.

Keywords: audio frequency, buzz noise, ground bounce, microphone grounding

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Authors: Mariya Yeldhos, G. Hema, Sowmya Narayanan, L. Dhiviyalakshmi

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Insomnia is one of the most prevalent psychological disorders worldwide. Some of the deficiencies of the current treatments of insomnia are: side effects in the case of sleeping pills and high costs in the case of psychotherapeutic treatment. In this paper, we propose a device which provides a combination of audio visual entrainment and acupressure based compression therapy for insomnia. This device provides drug-free treatment of insomnia through a user friendly and portable device that enables relaxation of brain and muscles, with certain advantages such as low cost, and wide accessibility to a large number of people. Tools adapted towards the treatment of insomnia: -Audio -Continuous exposure to binaural beats of a particular frequency of audible range -Visual -Flash of LED light -Acupressure points -GB-20 -GV-16 -B-10

Keywords: insomnia, acupressure, entrainment, audio-visual entrainment

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Authors: Apipol Penkitti

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The new normal or a new way of life stemmed from the COVID-19 outbreak, gave rise to a new form of social media: audio-based social platforms (ABSPs), known as Clubhouse, Twitter space, and Facebook live audio room. These platforms, on which audio-based communication is featured, became popular in a short span of time. The objective of the research study is to understand ABSPs users’ behaviors in Thailand. The study, in which functional attitude theory, uses and gratifications theory, and social influence theory are referred to, is conducted through consumer perceived utilitarian, hedonic, and social value that affect engagement. This research study is mixed method paradigm, utilizing Model of Triangulation as its framework. The data acquisition is proceeded through questionnaires from a sample of 384 male, female and LGBTQA+ individuals aged 25 - 34 who, from various occupations, have used audio-based social platform applications. This research study employs the structural equation modeling to analyze the relationships between variables, and it uses the semi - structured interviewing to comprehend the rationality of the variables in the study. The study found that hedonic value directly affects engagement.

Keywords: audio based social platform, engagement, hedonic, perceived value, social, utilitarian

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Authors: Analise Borg, Paul Micallef

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Over the past few years, the online multimedia collection has grown at a fast pace. Several companies showed interest to study the different ways to organize the amount of audio information without the need of human intervention to generate metadata. In the past few years, many applications have emerged on the market which are capable of identifying a piece of music in a short time. Different audio effects and degradation make it much harder to identify the unknown piece. In this paper, an audio fingerprinting system which makes use of a non-parametric based algorithm is presented. Parametric analysis is also performed using Gaussian Mixture Models (GMMs). The feature extraction methods employed are the Mel Spectrum Coefficients and the MPEG-7 basic descriptors. Bin numbers replaced the extracted feature coefficients during the non-parametric modelling. The results show that non-parametric analysis offer potential results as the ones mentioned in the literature.

Keywords: audio fingerprinting, mapping algorithm, Gaussian Mixture Models, MFCC, MPEG-7

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Authors: Michel Kulhandjian, Dimitris A. Pados

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The objective of this work is to develop a theoretical framework for reliable digital recording system identification from digital audio files alone, for forensic purposes. A digital recording system consists of a microphone and a digital sound processing card. We view the cascade as a system of unknown transfer function. We expect same manufacturer and model microphone-sound card combinations to have very similar/near identical transfer functions, bar any unique manufacturing defect. Input voice (or other) signals are modeled as non-stationary processes. The technical problem under consideration becomes blind deconvolution with non-stationary inputs as it manifests itself in the specific application of digital audio recording equipment classification.

Keywords: blind system identification, audio fingerprinting, blind deconvolution, blind dereverberation

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Authors: Heng Yang, Tao Luo, Yakun Zhang, Kai Wang, Wei Qin, Liang Xie, Ye Yan, Erwei Yin

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Recent years have seen that audio-visual recognition has shown great potential in a strong noise environment. The existing method of audio-visual recognition has explored methods with ResNet and feature fusion. However, on the one hand, ResNet always occupies a large amount of memory resources, restricting the application in engineering. On the other hand, the feature merging also brings some interferences in a high noise environment. In order to solve the problems, we proposed an effective framework with bidirectional distillation. At first, in consideration of the good performance in extracting of features, we chose the light model, Efficientnet as our extractor of spatial features. Secondly, self-distillation was applied to learn more information from raw data. Finally, we proposed a bidirectional distillation in decision-level fusion. In more detail, our experimental results are based on a multi-model dataset from 24 volunteers. Eventually, the lipreading accuracy of our framework was increased by 2.3% compared with existing systems, and our framework made progress in audio-visual fusion in a high noise environment compared with the system of audio recognition without visual.

Keywords: lipreading, audio-visual, Efficientnet, distillation

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Authors: Israa Sh. Tawfic, Sema Koc Kayhan

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In this paper, first, we propose least support orthogonal matching pursuit (LS-OMP) algorithm to improve the performance, of the OMP (orthogonal matching pursuit) algorithm. LS-OMP algorithm adaptively chooses optimum L (least part of support), at each iteration. This modification helps to reduce the computational complexity significantly and performs better than OMP algorithm. Second, we give the procedure for the invisible image watermarking in the presence of compressive sampling. The image reconstruction based on a set of watermarked measurements is performed using LS-OMP.

Keywords: compressed sensing, orthogonal matching pursuit, restricted isometry property, signal reconstruction, least support orthogonal matching pursuit, watermark

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Authors: Mark Kaahwa, Chang Zhu, Moses Muhumuza

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This study investigates the satisfaction of distance education university students (DEUS) with the use of audio media as a medium of instruction. Studying students’ satisfaction is vital because it shows whether learners are comfortable with a certain instructional strategy or not. Although previous studies have investigated the use of audio media, the satisfaction of students with an instructional strategy that combines radio teaching and podcasts as an independent teaching strategy has not been fully investigated. In this study, all lectures were delivered through the radio and students had no direct contact with their instructors. No modules or any other material in form of text were given to the students. They instead, revised the taught content by listening to podcasts saved on their mobile electronic gadgets. Prior to data collection, DEUS received orientation through workshops on how to use audio media in distance education. To achieve objectives of the study, a survey, naturalistic observations and face-to-face interviews were used to collect data from a sample of 211 undergraduate and graduate students. Findings indicate that there was no statistically significant difference in the levels of satisfaction between male and female students. The results from post hoc analysis show that there is a statistically significant difference in the levels of satisfaction regarding the use of audio media between diploma and graduate students. Diploma students are more satisfied compared to their graduate counterparts. T-test results reveal that there was no statistically significant difference in the general satisfaction with audio media between rural and urban-based students. And ANOVA results indicate that there is no statistically significant difference in the levels of satisfaction with the use of audio media across age groups. Furthermore, results from observations and interviews reveal that DEUS found learning using audio media a pleasurable medium of instruction. This is an indication that audio media can be considered as an instructional strategy on its own merit.

Keywords: audio media, distance education, distance education university students, medium of instruction, satisfaction

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Authors: Jan Doutreloigne

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The main goal of this paper is to develop a switching amplifier with optimized power efficiency for analog signals with a very high crest factor such as audio or DSL signals. Theoretical calculations show that a switching amplifier architecture based on multi-level pulse width modulation outperforms all other types of linear or switching amplifiers in that respect. Simulations on a 2 W multi-level switching audio amplifier, designed in a 50 V 0.35 mm IC technology, confirm its superior performance in terms of power efficiency. A real silicon implementation of this audio amplifier design is currently underway to provide experimental validation.

Keywords: audio amplifier, multi-level switching amplifier, power efficiency, pulse width modulation, PWM, self-oscillating amplifier

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Authors: S. C. Sharma, Ankit Gambhir, Rajeev Arya

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In today’s era data security is an important concern and most demanding issues because it is essential for people using online banking, e-shopping, reservations etc. The two major techniques that are used for secure communication are Cryptography and Steganography. Cryptographic algorithms scramble the data so that intruder will not able to retrieve it; however steganography covers that data in some cover file so that presence of communication is hidden. This paper presents the implementation of Ron Rivest, Adi Shamir, and Leonard Adleman (RSA) Algorithm with Image and Audio Steganography and Data Encryption Standard (DES) Algorithm with Image and Audio Steganography. The coding for both the algorithms have been done using MATLAB and its observed that these techniques performed better than individual techniques. The risk of unauthorized access is alleviated up to a certain extent by using these techniques. These techniques could be used in Banks, RAW agencies etc, where highly confidential data is transferred. Finally, the comparisons of such two techniques are also given in tabular forms.

Keywords: audio steganography, data security, DES, image steganography, intruder, RSA, steganography

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Authors: Retno Dwi Wahyuningrum, Sunarru Samsi Hariadi

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Education in agriculture is very significant; in a way that it can support farmers to improve their business. This can be done through certain media, such as printed, audio, and audio-visual media. To find out the effects of the media toward the knowledge, attitude, and motivation of farmers in order to adopt innovation, the study was conducted on 342 farmers, randomly selected from 12 farmer-groups, in the districts of Sleman and Bantul, Special Region of Yogyakarta Province. The study started from October 2014 to November 2015 by interviewing the respondents using a questionnaire which included 20 questions on knowledge, 20 questions on attitude, and 20 questions on adopting motivation. The data for the attitude and the adopting motivation were processed into Likert scale, then it was tested for validity and reliability. Differences in the levels of knowledge, attitude, and motivation were tested based on percentage of average score intervals of them and categorized into five interpretation levels. The results show that printed, audio, and audio-visual media give different impacts to the farmers. First, all media make farmers very aware to agricultural innovation, but the highest percentage is on theatrical play. Second, the most effective media to raise the attitude is interactive dialogue on Radio. Finally, printed media, especially comic, is the most effective way to improve the adopting motivation of farmers.

Keywords: agricultural education, printed media, audio media, audio-visual media, farmer knowledge, farmer attitude, farmer adopting motivation

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Authors: R. Rama Kishore, Sunesh

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This paper presents an optimized, robust, and secured watermarking technique. The methodology used in this work is the combination of entropy and chaotic grid map. The proposed methodology incorporates Discrete Cosine Transform (DCT) on the host image. To improve the imperceptibility of the method, the host image DCT blocks, where the watermark is to be embedded, are further optimized by considering the entropy of the blocks. Chaotic grid is used as a key to reorder the DCT blocks so that it will further increase security while selecting the watermark embedding locations and its sequence. Without a key, one cannot reveal the exact watermark from the watermarked image. The proposed method is implemented on four different images. It is concluded that the proposed method is giving better results in terms of imperceptibility measured through PSNR and found to be above 50. In order to prove the effectiveness of the method, the performance analysis is done after implementing different attacks on the watermarked images. It is found that the methodology is very strong against JPEG compression attack even with the quality parameter up to 15. The experimental results are confirming that the combination of entropy and chaotic grid map method is strong and secured to different image processing attacks.

Keywords: digital watermarking, discreate cosine transform, chaotic grid map, entropy

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Authors: Hrishi Rakshit, Pooneh Bagheri Zadeh

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This paper investigates the performance of drone classification methods using conventional DCNN with different hyperparameters, when additional drone audio data is embedded in the dataset for training and further classification. In this paper, first a custom dataset is created using different images of drones from University of South California (USC) datasets and Leeds Beckett university datasets with embedded drone audio signal. The three well-known DCNN architectures namely, Resnet50, Darknet53 and Shufflenet are employed over the created dataset tuning their hyperparameters such as, learning rates, maximum epochs, Mini Batch size with different optimizers. Precision-Recall curves and F1 Scores-Threshold curves are used to evaluate the performance of the named classification algorithms. Experimental results show that Resnet50 has the highest efficiency compared to other DCNN methods.

Keywords: drone classifications, deep convolutional neural network, hyperparameters, drone audio signal

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Authors: Jairo Vega, Fabian Chamba, Jordy Urgiles

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In this work, the implementation of a Matlabcontrolled Musical Tesla Coil and external audio signals was presented. First, the audio signal was obtained from a mobile device and processed in Matlab to modify it, adding noise or other desired effects. Then, the processed signal was passed through a preamplifier to increase its amplitude to a level suitable for further amplification through a power amplifier, which was part of the current driver circuit of the Tesla coil. To get the Tesla coil to generate music, a circuit capable of modulating and generating the audio signal by manipulating electrical discharges was used. To visualize and listen to these discharges, a small Faraday cage was built to attenuate the external electric fields. Finally, the implementation of the musical Tesla coil was concluded. However, it was observed that the audio signal volume was very low, and the components used heated up quickly. Due to these limitations, it was determined that the project could not be connected to power for long periods of time.

Keywords: Tesla coil, plasma, electrical signals, GNU Radio

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Authors: Hervé Zénouda

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This article seeks to shed light on an emerging creative field: "Audio games," at the crossroads between video games and computer music. Indeed, many applications, which propose entertaining audio-visual experiences with the objective of musical creation, are available today for different supports (game consoles, computers, cell phones). The originality of this field is the use of the gameplay of video games applied to music composition. Thus, composing music using interfaces but also cognitive logics that we qualify as "a-musicological" seem to us particularly interesting from the perspective of musical digital organology. This field raises questions about the representation of sound and musical structures and develops new instrumental gestures and strategies of musical composition. We will try in this article to define the characteristics of this field by highlighting some historical milestones (abstract cinema, game theory in music, actions, and graphic scores) as well as the novelties brought by digital technologies.

Keywords: audio-games, video games, computer generated music, gameplay, interactivity, synesthesia, sound interfaces, relationships image/sound, audiovisual music

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Authors: Shannon Steinmetz, Ellen Gethner

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In this paper, a theoretical foundation is developed for patterned segmentation of audio using the geometry of music and statistical manifold. We demonstrate image content clustering using conic space sonification. The algorithm takes a geodesic curve as a model estimator of the three-parameter Gamma distribution. The random variable is parameterized by musical centricity and centric velocity. Model parameters predict audio segmentation in the form of duration and frame count based on the likelihood of musical geometry transition. We provide an example using a database of randomly selected images, resulting in statistically significant clusters of similar image content.

Keywords: sonification, musical information geometry, image, content extraction, automated quantification, audio segmentation, pattern recognition

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Authors: Marthadale Acibo Semacio

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Speaking skill is a crucial part of English language teaching and learning. This actually shows the great importance of this skill in English language classes. Through speaking, ideas and thoughts are shared with other people, and a smooth interaction between people takes place. The study examined the levels of speaking proficiency of the control and experimental groups on pronunciation, grammatical accuracy, and fluency. As a quasi-experimental study, it also determined the presence or absence of significant changes in their speaking proficiency levels in terms of pronouncing the words correctly, the accuracy of grammar and fluency of a language given the two methods to the groups of students in the English language, using the traditional and audio-lingual methods. Descriptive and inferential statistics were employed according to the stated specific problems. The study employed a video presentation with prior information about it. In the video, the teacher acts as model one, giving instructions on what is going to be done, and then the students will perform the activity. The students were paired purposively based on their learning capabilities. Observing proper ethics, their performance was audio recorded to help the researcher assess the learner using the modified speaking rubric. The study revealed that those under the traditional method were more fluent than those in the audio-lingual method. With respect to the way in which each method deals with the feelings of the student, the audio-lingual one fails to provide a principle that would relate to this area and follows the assumption that the intrinsic motivation of the students to learn the target language will spring from their interest in the structure of the language. However, the speaking proficiency levels of the students were remarkably reinforced in reading different words through the aid of aural media with their teachers. The study concluded that using an audio-lingual method of teaching is not a stand-alone method but only an aid of the teacher in helping the students improve their speaking proficiency in the English Language. Hence, audio-lingual approach is encouraged to be used in teaching English language, on top of the chalk-talk or traditional method, to improve the speaking proficiency of students.

Keywords: audio-lingual, speaking, grammar, pronunciation, accuracy, fluency, proficiency

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Authors: Pavuluri Gopikrishna, B. Neelima

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Power line carrier communication means audio power transmission via power line and reception of the amplified audio power at the receiver as in the form of speaker output signal using power line as the channel medium. The main objective of this suggested work is to transmit our message signal after frequency modulation by the help of FM modulator IC LM565 which gives output proportional to the input voltage of the input message signal. And this audio power is received from the power line by the help of isolation circuit and demodulated from IC LM565 which uses the concept of the PLL and produces FM demodulated signal to the listener. Message signal will be transmitted over the carrier signal that will be generated from the FM modulator IC LM565. Using this message signal will not damage because of no direct contact of message signal from the power line, but noise can disturb our information.

Keywords: amplification, fm demodulator ic 565, fm modulator ic 565, phase locked loop, power isolation

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Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA

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In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.

Keywords: BER, DWT, extreme leaning machine (ELM), PSNR

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