Search

Recently, we have observed an exponential increase of user-generated content (UGC) videos. The distinguished characteristic of UGC videos originates from the video production and delivery chain, as they are usually acquired and processed by non-professional users before uploading to the hosting platforms for sharing. As such, these videos usually undergo multiple distortion stages that may affect visual quality before ultimately being viewed. Inspired by the increasing consensus that the optimization of the video coding and processing shall be fully driven by the perceptual quality, in this paper, we propose to study the quality of the UGC videos from both objective and subjective perspectives. We first construct a UGC video quality assessment (VQA) database, aiming to provide useful guidance for the UGC video coding and processing in the hosting platform. The database contains source UGC videos uploaded to the platform and their transcoded versions that are ultimately enjoyed by end-users, along with their subjective scores. Furthermore, we develop an objective quality assessment algorithm that automatically evaluates the quality of the transcoded videos based on the corrupted reference, which is in accordance with the application scenarios of UGC video sharing in the hosting platforms. The information from the corrupted reference is well leveraged and the quality is predicted based on the inferred quality maps with deep neural networks (DNN). Experimental results show that the proposed method yields superior performance. Both subjective and objective evaluations of the UGC videos also shed lights on the design of perceptual UGC video coding.

Federated Learning (FL) is an emerging paradigm through which decentralized devices can collaboratively train a common model. However, a serious concern is the leakage of privacy from exchanged gradient information between clients and the parameter server (PS) in FL. To protect gradient information, clients can adopt differential privacy (DP) to add additional noises and distort original gradients before they are uploaded to the PS. Nevertheless, the model accuracy will be significantly impaired by DP noises, making DP impracticable in real systems. In this work, we propose a novel Noise Information Secretly Sharing (NISS) algorithm to alleviate the disturbance of DP noises by sharing negated noises among clients. We theoretically prove that: 1) If clients are trustworthy, DP noises can be perfectly offset on the PS; 2) Clients can easily distort negated DP noises to protect themselves in case that other clients are not totally trustworthy, though the cost lowers model accuracy. NISS is particularly applicable for FL across multiple IoT (Internet of Things) systems, in which all IoT devices need to collaboratively train a model. To verify the effectiveness and the superiority of the NISS algorithm, we conduct experiments with the MNIST and CIFAR-10 datasets. The experiment results verify our analysis and demonstrate that NISS can improve model accuracy by 19% on average and obtain better privacy protection if clients are trustworthy.

Despite the popularity of guitar effects, there is very little existing research on classification and parameter estimation of specific plugins or effect units from guitar recordings. In this paper, convolutional neural networks were used for classification and parameter estimation for 13 overdrive, distortion and fuzz guitar effects. A novel dataset of processed electric guitar samples was assembled, with four sub-datasets consisting of monophonic or polyphonic samples and discrete or continuous settings values, for a total of about 250 hours of processed samples. Results were compared for networks trained and tested on the same or on a different sub-dataset. We found that discrete datasets could lead to equally high performance as continuous ones, whilst being easier to design, analyse and modify. Classification accuracy was above 80\%, with confusion matrices reflecting similarities in the effects timbre and circuits design. With parameter values between 0.0 and 1.0, the mean absolute error is in most cases below 0.05, while the root mean square error is below 0.1 in all cases but one.

In this paper, a reversible data hiding algorithm for audio files based on code division multiplexing (CDM) is proposed. In the scheme, the orthogonal spreading sequences are employed to carry the embedding data, and the host audio file can also be recovered completely after the secret message has been extracted accurately. At the same time, according the orthogonal character of the spreading sequences, the secret message can be embedded into the audio files repeatedly, and most elements of the spreading sequences are mutually canceled in the process of multi-level data embedding, which maintains the audio file in good auditory even at high data embedding capacity. Moreover, only the receiver who holds the same spreading sequences, as the sender can restore the embedded data, which enhance the security of the proposed scheme. As shown in the experimental results, the CDM based reversible data hiding (RDH) algorithm for audio files can achieve higher data embedding capacity at the same audio distortion compared with those state-of-the-art audio RDH algorithms.

Audio steganography aims to exploit the human auditory redundancy to embed the secret message into cover audio, without raising suspicion when hearing it. However, recent studies have shown that the existing audio steganography can be easily exposed with the deep learning based steganalyzers by extracting high-dimensional features of stego audio for classification. The existing GAN-based steganography approaches mainly studied in images cover, less work is conducted on audio cover. In addition, though a few GAN-based audio steganography methods have been proposed, they still have room for improvements in perceptual quality and undetectability. In this work, we propose an audio steganography framework that could automatically learn to generate superior steganographic cover audio for message embedding. Specifically, the training framework of the proposed framework consists of three components, namely, generator, discriminator and trained deep learning based steganalyzer. Then the traditional message embedding algorithm LSBM, is employed to embed the secret message into the steganographic cover audio to obtain stego audio, which is delivered to the trained steganalyzer for misclassifying as cover audio. Once the adversarial training is completed among these three parties, one can obtain a well-trained generator, which could generate steganographic cover audio for subsequent message embedding. In the practice of our proposed method, the stego audio is produced by embedding the secret message into the steganographic cover audio using a traditional steganography method. Experimental results demonstrate that our proposed audio steganography can yield steganographic cover audio that preserves a quite high perception quality for message embedding. We have compared the detection accuracies with the existing audio steganography schemes as presented in our experiment, the proposed method exhibits lower detection accuracies against the state-of-the-art deep learning based steganalyzers, under various embedding rates. Codes are publicly available at https://github.com/Chenlang2018/Audio-Steganography-using-GAN.

Prosthetic is an artificial tool that replaces part of the human frame absent because of ailment, damage, or distortion. The current activities in Iraq draw interest to the upper limb discipline because of the growth in variety of amputees and. It is necessary to do extensive researches in this subject to help lessen the struggling of patients. This paper describes the design and development of low-cost prosthesis for people with transradial amputations. The presented design involves a hand with five fingers moving by means of a gear box mechanism. The design of this artificial hand allows five degrees of freedom(5DOF), one degree of freedom for each finger. The artificial hand works by an actuation system (6V) Polou motor with gear ratio equal to 50:1 due to its compactness and cheapness. The designed hand was manufactured by a 3D printing process using polylacticacid material (PLA). Some experimental were accomplished using the designed hand for gripping objects. Initially the EMG signal was recorded when the muscle contracted in one second, two seconds, three seconds. The synthetic hand was able to produce range of gesture and grasping moves separately just like the actual hand by using KNN classification which are complete hand Pinch, fist, and jack chuck. The simulation of the fingers movements was achieved using ANSYS software to analysis the movement (pinch, fist, and jack chuck), obtain bested of stress influencer at each finger, and maximum deformation at each movement.

As people increase their dependency on mobile applications and services, saving power consumption of mobile devices becomes an important challenge for supporting video streaming applications. This paper investigates how to minimize the power consumption of an organic light-emitting diode (OLED) display when displaying a video under consideration for the user’s visual experience. We first model the minimization problem as an OLED video scaling optimization problem. We then propose an algorithm to solve the optimization problem and prove that the algorithm is optimal in terms of power savings. We next introduce an energy-saving cloud service based on the algorithm. Finally, the results of the extensive experiments conducted on a commercial mobile smartphone with four real-world videos to evaluate the performance of the proposed algorithm are very encouraging.

As the elderly age, their hearing deteriorates and it becomes difficult to hear the sounds of daily life. Especially, “TV sound” is hard to hear for one in two elderly people. The cause is that the voice is drowned out by the BGM. In this research, we focus on the volume balance between voice and BGM in TV sound, and propose a volume balance adjustment method using sound source separation technology as a method to adjust these appropriately. In addition, the effectiveness of the proposed method will be evaluated through subjective evaluation. In order to improve your hearing of TV sounds, you need to emphasize them. Therefore, in this research, we propose a method to emphasize the sound by separating the TV sound into voice and BGM by the sound source separation technology, suppressing the gain of BGM, and then reintegrating it. In this study, Spleeter is used. Spleeter is a sound source separation software that uses supervised deep learning. It is mainly used to separate songs into parts, and the input music data can be divided into parts (Example: Vocal/Accompaniment). In the experiment, we used a mixture of voice and BGM as the sound of the TV. (We have prepared two types of voice, “Natural voice” and “Whispering voice”.) This simulated data is separated by Spleeter, and the gain of the BGM after separation is suppressed and mixed again. Eight male subjects in their twenties will be asked to hear the sound before and after processing to evaluate whether the ease of hearing the voice can be improved. As a result, it was found that increasing the ratio of voice improves the ease of hearing the voice. However, it was also found that the distortion generated in the process of sound source separation also affects the sound quality. Therefore, it can be said that it is necessary to improve the accuracy of sound source separation in order to further enhance the effect. In this study, we proposed a method to adjust the volume balance between voice and BGM to an appropriate level using sound source separation technology. In the future, we would like to consider ways to further improve hearing by improving the accuracy of sound source separation.

Cinema provides ‘privileged access’ ( Zubrycki 2011 ) into trans lives, recording and revealing private life experiences and moments that might never be seen, nor heard and after the time had passed, only present in memory and body for the individuals involved. Film, a temporal medium, creates theoretical issues, both in the presentation and representation of the trans body and for audiences in viewing the images. Specific narrative, stylistic and editing techniques including temporal disjunctions, may also give audiences a distorted view of trans bodily narratives that encompass a lifetime. Twenty first century cinema is simultaneously creating and erasing the somatechnical potentialities of trans. This article will explore temporal techniques in relation to recent trans cinema, comparing how three different filmmakers handle trans narratives. Drawing upon recent films including the Trans New Wave ( Ford 2014 , 2016a , 2016b ), such as the experimental animated autoethnographic short film Change Over Time (Ewan Duarte, United States, 2013), in tandem with the feature film 52 Tuesdays (Sophia Hyde, Australia, 2013), I will analyse the films as texts which show how filmmakers utilise temporality as a narrative and stylistic technique in cinematic trans narratives. These are texts where cinematic technologies converge with trans embodiment in ways that are constitutive of participants and audiences' understanding of trans lives. This analysis will be contrasted with the use of temporal displacement as a cinematic trope of negative affect, disembodiment and societal disjunction in the feature film Predestination (The Spierig Brothers, Australia, 2014), providing a further basis for scholarly critique of cinematic somatechnics in relation to the trans body.

In recent years, energy issues have become more prominent. To solve energy problems, distributed power generation has received great attention. Therefore, distributed power generation has also received extensive attention and rapid development. This puts higher requirements on the quality of the output power of the inverter. How to control the LCL type grid-connected inverter to achieve the goal of better output power quality is a hot and difficult point that needs to be overcome in recent years.In this paper, a simulation model of the LCL grid-connected inverter is established in the MATLAB/Simulink environment, the advantages of PI control are analyzed, and the LCL grid-connected inverter based on PI control is designed. Finally, simulation verification was performed under Simulink.

The audiovisual entertainment industry has entered a race to find the video encoder offering the best Rate/Distortion (R/D) performance for high-quality high-definition video content. The challenge consists in providing a moderate to low computational/hardware complexity encoder able to run Ultra High-Definition (UHD) video formats of different flavours (360∘, AR/VR, etc.) with state-of-the-art R/D performance results. It is necessary to evaluate not only R/D performance, a highly important feature, but also the complexity of future video encoders. New coding tools offering a small increase in R/D performance at the cost of greater complexity are being advanced with caution. We performed a detailed analysis of two evolutions of High Efficiency Video Coding (HEVC) video standards, Joint Exploration Model (JEM) and Versatile Video Coding (VVC) , in terms of both R/D performance and complexity. The results show how VVC, which represents the new direction of future standards, has, for the time being, sacrificed R/D performance in order to significantly reduce overall coding/decoding complexity.

The use of DC switching power supplies is relevant in various industries. DC switching power supply is considered as an example. The article contains a description of a DC power source with a power factor corrector. The results of the study of the object model considered in the article using MatLab Simulink are presented. The paper examines the characteristics of a pulse power supply for a personal computer. We also consider the possibility of using a power factor corrector to reduce the harmful effect of IIP on the supply network.

This article describes a discrete-time zoom analog-to-digital converter (ADC) intended for audio applications. It uses a coarse 5-bit SAR ADC in tandem with a fine third-order delta–sigma modulator ( $\Delta \Sigma \text{M}$ ) to efficiently obtain a high dynamic range. To minimize its over-sampling ratio (OSR) and, thus, its digital power consumption, the modulator employs a 2-bit quantizer and a loop filter notch. In addition, an extra feed-forward path minimizes the leakage of the SAR ADC’s quantization noise into the audio band. The prototype ADC occupies 0.27 mm2 in a 0.16- $\mu \text{m}$ technology. It achieves 109.8-dB DR, 106.5-dB SNDR, and 107.5-dB SNR in a 20-kHz bandwidth while dissipating 440 $\mu \text{W}$ . It also achieves state-of-the-art energy efficiency, as demonstrated by a Schreier FoM of 186.4 dB and an SNDR FoM of 183.6 dB.

With the popularization of audio-visual entertainment equipment, the application of pre-stage power amplifiers is becoming more and more extensive. The use of a high-quality pre-stage amplifier will often bring people a better sound quality experience. The system uses STM32F103C8T6 as the main control chip, controls the multi-channel audio selector NJW1110 through the IIC bus, and can select the input audio signal corresponding to the output channel and the gain of the output audio signal. The output signal distortion is small, and HMI is used for human-computer interaction control The serial port screen greatly facilitates the user’s operation and use.

In this paper, an automated controller for an integrated, reconfigurable dc-dc converter for plugin electric vehicles (EVs) is presented. The integrated converter combines both an interleaved boost converter and dual active bridge (DAB) converter, sharing magnetics and switching devices. The converter switches between operating modes using the existing battery management system (BMS) contactors. The integrated converter operates in isolated DAB mode during battery charging operation. During traction operation, the integrated converter is operated in interleaved boost mode for heavy load and DAB mode during light load, high voltage operation. An online transition algorithm is used to transition from interleaved boost mode to DAB mode with minimal bus distortion. The automated controller selects the operating mode and inverter bus voltage at different torque-speed conditions to get maximum overall traction drive efficiency. An experimental prototype of the integrated converter demonstrates the automated controller functionality.

Hearing loss is often associated with poor performance and incident dementia that leads to reduced social engagements, loneliness, and depression. Hearing aids are a solution for hearing loss. Traditional Hearing aids are an electroacoustic device that blocks noise and enhances target sound out of a multi-source mixture. In some cases when the source objects are devices such as mobiles, laptops, or television a higher distortion happens when the traditional hearing aid amplifies the multi-source mixture which leads the wearer unable to extract the exact information conveyed. This paper proposes a smart internet of things based hearing aid which is cost-effective, reliable, and secured. The smart hearing aid compounds the properties of system on- chip property of micro-controllers which allows the user to connect the internet of things based device directly to the hearing aid, therefore, limiting the multi-source mixture. The micro-controller is equipped with an advance digital signal processor that helps in the separation of acoustic sounds and functions more enhanced compared to the traditional ear aids commercially produced.

An average power tracking (APT) power amplifier (PA) using a multilevel supply voltage DC-DC converter is presented for IEEE Wi-Fi applications. The PA operates in high, middle, and low average output power regions by setting the DCDC converter output to 4 V, 3 V and 2 V, respectively. Power added efficiency (PAE) of the APT PA is significantly improved by reducing DC power consumption in low and middle output power regions. The APT PA aided by predistortion can further improve PAE when the PA operates in less back-off from 1-dB compression point (PldB) without causing significant nonlinearity distortion. For a 5 GHz 64-QAM OFDM signal with 20 MHz bandwidth and 9. SdB PAPR, the APT PA with a 2.0 V voltage supply delivers a PAE of 25% at an average output power of about 10 dBm, which is 15% higher than that of the conventional PA with a fixed voltage supply of 4 V at the same average output power.

The topics of visual and audio quality assessment (QA) have been widely researched for decades, yet nearly all of this prior work has focused only on single-mode visual or audio signals. However, visual signals rarely are presented without accompanying audio, including heavy-bandwidth video streaming applications. Moreover, the distortions that may separately (or conjointly) afflict the visual and audio signals collectively shape user-perceived quality of experience (QoE). This motivated us to conduct a subjective study of audio and video (A/V) quality, which we then used to compare and develop A/V quality measurement models and algorithms. The new LIVE-SJTU Audio and Video Quality Assessment (A/V-QA) Database includes 336 A/V sequences that were generated from 14 original source contents by applying 24 different A/V distortion combinations on them. We then conducted a subjective A/V quality perception study on the database towards attaining a better understanding of how humans perceive the overall combined quality of A/V signals. We also designed four different families of objective A/V quality prediction models, using a multimodal fusion strategy. The different types of A/V quality models differ in both the unimodal audio and video quality prediction models comprising the direct signal measurements and in the way that the two perceptual signal modes are combined. The objective models are built using both existing state-of-the-art audio and video quality prediction models and some new prediction models, as well as quality-predictive features delivered by a deep neural network. The methods of fusing audio and video quality predictions that are considered include simple product combinations as well as learned mappings. Using the new subjective A/V database as a tool, we validated and tested all of the objective A/V quality prediction models. We will make the database publicly available to facilitate further research.

This article investigates the use of deep neural networks for black-box modelling of audio distortion circuits, such as guitar amplifiers and distortion pedals. Both a feedforward network, based on the WaveNet model, and a recurrent neural network model are compared. To determine a suitable hyperparameter configuration for the WaveNet, models of three popular audio distortion pedals were created: the Ibanez Tube Screamer, the Boss DS-1, and the Electro-Harmonix Big Muff Pi. It is also shown that three minutes of audio data is sufficient for training the neural network models. Real-time implementations of the neural networks were used to measure their computational load. To further validate the results, models of two valve amplifiers, the Blackstar HT-5 Metal and the Mesa Boogie 5:50 Plus, were created, and subjective tests were conducted. The listening test results show that the models of the first amplifier could be identified as different from the reference, but the sound quality of the best models was judged to be excellent. In the case of the second guitar amplifier, many listeners were unable to hear the difference between the reference signal and the signals produced with the two largest neural network models. This study demonstrates that the neural network models can convincingly emulate highly nonlinear audio distortion circuits, whilst running in real-time, with some models requiring only a relatively small amount of processing power to run on a modern desktop computer.

Compared with traditional two-stage class-D audio amplifier, audio amplifier based on cycloconverter-type single-stage inverter (CSSI) has advantages of high efficiency and no bus voltage pumping (BVP). However, CSSI requires complex active clamp circuits for the current commutation of cycloconverter, especially for multichannel amplification. In this letter, a 2.1-channel switching amplifier with dc/high-frequency-ac (HFAC) mixed power supply is proposed, where CSSI is used as low-frequency audio channel amplifier and two class-D amplifiers are used as high-frequency audio channel amplifiers. With dc/HFAC mixed power supply, the proposed 2.1-channel switching amplifier does not require additional active clamp circuits for current commutation of cycloconverter. Besides, wide range soft switching of cycloconverter switches can be achieved. Benefiting from single-stage power conversion of low-frequency audio channel and wide range soft switching of cycloconverter switches, high efficiency of the proposed 2.1-channel amplifier is achieved. Without BVP, low voltage stress of switches and low distortion of low-frequency audio signal are realized in the proposed 2.1-channel amplifier. A 200-W prototype is presented to verify the analysis results.

An ac/dc + dual active bridge (DAB) circuit was found as one solution for the high-efficiency and high-power-density electric vehicle charger. One control option is to let the ac/dc part only convert the grid voltage to a double-line-frequency folded sine wave and let the DAB stage handle both the power factor (PF) and power delivery. While conventional single-phase-shift tends to lose zero-voltage switching (ZVS) at light load and the variable-switching-frequency dual-phase-shift (DPS) sacrifices the light-load performance, this letter proposes a multiple-phase-shift control, which allows for a fixed-switching-frequency triple-phase-shift (TPS) control at the light load to enhance the grid power quality. At medium- and heavy-load conditions, a phase-shift jump from TPS to DPS is performed to reduce the circulating current and improve efficiency. The proposed control strategy secures ZVS, realizes unity PF accurately and minimizes the control complexity. Experimental results on a SiC-based 7.2-kW charger validated its effectiveness and the smooth transition between the heavy load and light load.

In metal music studies, “heaviness” has been acknowledged an essential element of the genre. Commonly associated with the distorted guitar, most work on heaviness has concentrated on the instrument’s sound. If respective research considered structural aspects of the guitar riff, then with a special focus on tempo, rhythm, tonality and form. This article analyses the interaction between distortion and harmonic structures on the electric guitar. Operationalising heaviness with a psychoacoustic model of sensory consonance, an acoustic experiment explores how guitar distortion affects acoustic features of harmonic structures. Since acoustic studies are limited in predicting perception, a listening test investigates distortion’s influence on listener perception. The findings indicate that both increasing distortion level and harmonic complexity reduce sensory consonance, especially when acting together. Acoustically, distortion shows a slightly stronger effect strength than structure; perceptually, the ratio is dependent on person-specific characteristics. Metalheads seem to be only little affected by sensory dissonance.

Guitar distortion used in rock music modifies a chord so that new frequencies appear in its harmonic structure. A distorted dyad (power chord) has a special role in heavy metal music due to its harmonics that create a major third interval, making it similar to a major chord. We investigated how distortion affects cortical auditory processing of chords in musicians and nonmusicians. Electric guitar chords with or without distortion and with or without the interval of the major third (i.e., triads or dyads) were presented in an oddball design where one of them served as a repeating standard stimulus and others served as occasional deviants. This enabled the recording of event-related potentials (ERPs) of the electroencephalogram (EEG) related to deviance processing (the mismatch negativity MMN and the attention-related P3a component) in an ignore condition. MMN and P3a responses were elicited in most paradigms. Distorted chords in a nondistorted context only elicited early P3a responses. However, the power chord did not demonstrate a special role in the level of the ERPs. Earlier and larger MMN and P3a responses were elicited when distortion was modified compared to when only harmony (triad vs. dyad) was modified between standards and deviants. The MMN responses were largest when distortion and harmony deviated simultaneously. Musicians demonstrated larger P3a responses than nonmusicians. The results suggest mostly independent cortical auditory processing of distortion and harmony in Western individuals, and facilitated chord change processing in musicians compared to nonmusicians. While distortion has been used in heavy rock music for decades, this study is among the first ones to shed light on its cortical basis.

This paper presents the design and implementation of a miniaturized high-voltage power supply with power factor correction (PFC) for atmospheric-pressure plasma jet (APPJ) applications. The sinusoidal output frequency and voltage of the power supply can be controlled independently from 16 to 24 kHz and from 1 to 10 kVpeak, respectively. A helium APPJ load is used to assess the performance of the developed power supply. It is shown that the developed high-voltage power supply operates effectively, and the designed PFC converter improves the input current distortion of the power supply. Not only the power factor of the power supply is increased from 0.41 to 0.95, but it also provides a low-ripple DC voltage, which reduces the high-voltage ripple of the output from 730 to 50 Vp-p. In this paper, the proposed design integrates the PFC converter into the high-voltage power supply so that the developed power supply has better electrical characteristics and the overall power supply can be significantly miniaturized.

In this paper, it is proposed to put forward musical sound effects processing system based on virtual analog modeling and digital signal processing techniques. The effects used most commonly by musicians such as, fuzz, phaser, distortion reverb, echo, flanger tremolo, vibrato, etc., are generated by analog circuits. Here, we propose to generate these effects by using the concept of digital signal processing filters. The proposed system works on wave files and also on the buffered audio which is fed from the microphone input of computer. The proposed system is built around by using the codes in Scilab/Octave and the sequences of effects are sequenced depending on the musicians/artists choice. The various concepts of filtering in digital signal processing are used. The results obtained are compared with the commercially available systems.

DRS has developed a Variable-Frequency Drive (VFD) and Permanent Magnet (PM) Electric Propulsion Motor (EPM) for a 1.7MW Hybrid Electric Drive system currently commissioned on the Frigate FFX-II of the Republic of Korean Navy. The EPM utilizes a “bearingless” design, allowing for more compact equipment and shafting arrangements. The machine is mounted directly on the shaft, permitting operation of the HED system without main gear engagement. The VFD employs a modular, power-dense, 3-Level Neutral Point Clamped, Power Electronics Module used as an Active Front End and Inverter that enables superior current distortion performance, thereby enabling input electrical interface compliance to MIL-STD-1399 Sec. 300B and output performance that enables compliance of the motor to MIL-STD- 740–2 structureborne noise, which supports Anti-Submarine Warfare vessel operations. The HED system provides superior fuel economy, offering significant life-cycle cost savings over the life of the ship from fuel savings and reduced maintenance costs.

This paper presents a continuous-time (CT) zoom ADC for use in audio applications. Compared to previous zoom ADCs, its input impedance is mainly resistive, making it much easier to drive while still maintaining high energy efficiency. The prototype is fabricated in a 0.16 ×m CMOS process, occupies 0.27 m m2 and achieves 108.5 dB DR, 108.1 dB SNR, 106.4 dB SNDR in a 20 kHz BW, while consuming 618 ×W. This results in a state-of-the-art Schreier FoM of 183.6 dB.

Valve amplifiers have been modulated recently by digital signal processing techniques, using the Wiener-Hammerstein cell. The key of this approach is to identify the non-linear static transfer function. In the present contribution we model audio distortion pedal effects and propose a transfer function model derived from a modification of the Shockley equation. Six limiter circuits with different types of diodes (silicon, germanium and LED) were evaluated using a voltage sine wave of 10 Hz and amplitude such as to provide a 10 mA input current. Ten seconds of input and output signals were sampled (100 kSamples/s) and the model was fitted to the data using the Levenberg-Marquardt non-linear least square method. The model worked well, providing a root mean square standard error between the data and best fit less than 10−4, except for the LED limiter circuit. The present approach resulted in an analytical representation of the non-linear transfer function, which can generate directly from a discretised input signal the corresponding output signal according to a desired response of a chosen limiter model.

In today's world, transmission of secret and important data has various security issues. Information security has become a major issue in the field of data communication. One of the many techniques used to resolve these security issues is Audio Steganography. Audio Steganography means hiding some data in an audio file so that the intruder cannot know about the data. In this paper, we present an improved and new approach for hiding secret messages in audio clips. We use a security key and a Genetic Algorithm to embed the message bits into cover audio samples. One or two message bits are embedded in different Least Significant Bit (LSB) layers of each sample. We have successfully tested proposed technique on several audio sequences. The experimental results show clear demonstration that the proposed technique has higher message embedding capacity and provides less distortion to the output sequences.

Sometimes, the input-port of A/D converter always needs a S/H switch. In Sample state, the S/H switch should always be opening, now voltages between input-port and output-port in S/H switch are always the same. In Hold state, the S/H switch should always be closing, now the voltage of output-port in S/H switch will keep a fixed value, and it will not be changed with the voltage of input-port in S/H switch. For A/D converter, the conversion linearity is the most important parameter. For getting the best performance of conversion linearity, it is very important to design a high linear S/H switch. In sample stage, the voltage of output-port in S/H switch should be always changed with the voltage of input-port at any time. It is very easy to S/H switch design under the normal condition. Next for getting the higher linear performance in A/D converter, the fixed value in Hold state should be keeping linear performance of input voltage at the most, it is very hard in high resolution A/D converter. Through this paper's design, it makes the distortion leading by Sample switch become linear distortion. So it can get a high performance S/H bootstrapped switch, which can apply to 16-bit or much higher resolution ADC.

Multimedia services play an important role in modern human communication. Understanding the impact of multisensory input (audio and video) on perceived quality is important for optimizing the delivery of these services. This work explores the impact of audio degradations on audio-visual quality. With this goal, we present a new dataset that contains audio-visual sequences with distortions only in the audio component (Im-AV-Exp2). The degradations in this new dataset correspond to commonly encountered streaming degradations, matching those found in the audio-only TCD-VoIP dataset. Using the Immersive Methodology, we perform a subjective experiment with the Im-AV-Exp2 dataset. We analyze the experimental data and compared the quality scores of the Im-AV-Exp2 and TCD-VoIP datasets. Results show that the video component act as a masking factor for certain classes of audio degradations (e.g. echo), showing that there is an interaction of video and audio quality that may depend on content.

Auditory feedbacks are becoming increasingly popular in sports providing opportunities for monitoring and gait (re)training in ecological environments. We present the design process of a sonification strategy for modification of running parameters. The sonification provides real-time feedback of the performance through introduction of distortion of a baseline music track. The music BPM is continuously matched to the runners' cadence. The noise-based continuous feedback was able to significantly alter the mean running cadence in a non-instructed and non-disturbing way and performed better than standard verbal instructions. Although some of the participants did not respond effectively to the feedback, a large majority of the participants positively rated the feedback system in terms of pleasantness and motivation.

Power efficiency of multi-source integrated energy harvesting (EH), storage, and delivery is a fundamental requirement of emerging energy autonomous internet-of-thing (IoT) and internet-of-everything (IoE) devices. To make these energy autonomous devices practical, an enhanced, universal power management integrated circuit (PMIC) needs to be developed for efficiently controlling power on-chip. Currently, there exists no universal power manager (UPM) that seamlessly interfaces to DC and/or AC EH sources. The state of the art viable PMICs delivered by industry rely primarily on the following approach: for an unregulated DC source a DC/DC power manager is adopted whereas for an AC source, a front-end rectifier is inserted. This reduces efficiency and enhances distortion, requiring additional filtering.

We construct targeted audio adversarial examples on automatic speech recognition. Given any audio waveform, we can produce another that is over 99.9% similar, but transcribes as any phrase we choose (recognizing up to 50 characters per second of audio). We apply our white-box iterative optimization-based attack to Mozilla's implementation DeepSpeech end-to-end, and show it has a 100% success rate. The feasibility of this attack introduce a new domain to study adversarial examples.

In a previous paper the authors use a recurrent network in the form of a NARX architecture to model the nonlinear behavior of a vacuum-tube guitar amplifier and its effects as applied to an electric guitar signal. The use of recurrent networks is important in the vacuum-tube modeling effort as the nonlinear dynamic responses are thought to be an important component in achieving the distortion that creates the sound treasured by rock guitarists and the fans of rock music. In this paper, we report on our current experiments evaluating the use of long/short-term memory (LSTM) units for modeling the dynamic nonlinear characteristics of a vacuum-tube guitar amplifier. It is our view that since LSTM units incorporate information from both recent and distant changes in state, they are useful for modeling the amplifier characteristics that produce the desired musical timbre. Our experiments involve investigating differing combinations of the hyperparameters of a deep learning network including the number of hidden layers, the number of units within each layer, and the type of unit within each layer. Model performance is evaluated using mean-square error and aural comparisons. Once the best architecture is determined, efforts will be put forth to minimize the hardware requirements for the implementation of the feedforward network.

The electric guitar is an ubiquitous part of contemporary consumer culture. In this Marketplace Icons contribution, we illuminate the iconicity of the electric guitar and what lies behind its thick layers of distorted riffs, mad soloing escapades and eccentric onstage performances, specifically within the rock genre. The genesis of electric guitar playing involves a series of technological alterations of the guitar that freed it from a mere background instrument allowing for new musical roles. It quickly became apparent that all the technical solutions designed to get rid of what was defined as unwanted noise could be turned “against” the clean tone and instead be used to create a unique sound. The control of these noise elements, such as feedback and distortion, became a core element of mastering the modern electric guitar. Rather than just being a marketplace icon, we argue that the electric guitar is fetishized because both its audio quality – the loudness and the potential roughness of the sound – and...

This paper describes the theory and implementation of audio effects such as echo, distortion and pitch-shift in Field Programmable Gate Array (FPGA). At first the mathematical formulation for generation of such effects is explained and then the algorithm is described for its implementation in FPGA using Very high speed integrated circuit hardware descriptive language (VHDL). The digital system being designed, which is synthesizable and reconfigurable, offers a great flexibility and scalability in designing and prototyping in FPGAs. The system is divided into three HDL blocks, each for echo, distortion, and pitch-shift effect generation, which are multiplexed in order to share the common ADC and DAC. The audio effect generator designed in this paper was successfully implemented in Spartan-3E FPGA utilizing the resources available effectively. There has been tremendous research being carried out in the field of IP core. Efficient IP cores designed to carry out digital signal processing are implemented in every modern device using configurable logics. This trend hasn’t yet been realized in Nepal. Through the design and implementation of audio effect generator, this paper also aims at bringing the field of IP core development to limelight among scholars of Nepal.DOI: http://dx.doi.org/10.3126/njst.v15i1.12022 Nepal Journal of Science and TechnologyVol. 15, No.1 (2014) 89-98

There are serious distortion problems in the history audio and video data. In view of the characteristics of audio data repair, the intelligent technology of audio evaluation is explored. As the traditional audio subjective evaluation method requires a large number of personal to audition and evaluation, the tester’s subjective sense of hearing deviation and sample space data limited the impact of the accuracy of the experiment. Based on the deep learning network, this paper designs an objective quality evaluation system for historical audio and video data and evaluates the performance of the system and the audio signal quality from the perspective of feature extraction and network parameter selection. Experiments show that the system has good performance in this experiment; the predictive results and subjective evaluation of the correlation and dispersion indicators are good, up to 0.91 and 0.19.

Probability and Statistics, Allan White and Hagbae Kim Electronic Hardware Reliability, Michael Pecht and Iuliana Bordelon Software Reliability, Carol Smidts Thermal Properties, David F. Besch Heat Management, Zbigniew J. Staszak Shielding and EMI Considerations, Don White Resistors and Resistive Materials, Jerry C. Whitaker Capacitance and Capacitors, Jerry C. Whitaker Inductors and Magnetic Properties, Jerry C. Whitaker Printed Wiring Boards, Ravindanath Kollipara and Vijai Tripathi Hybrid Microelectronics Technology, Jerry E. Sergent Surface Mount Technology, Glenn R. Blackwell Semiconductor Failure Modes, Jerry c. Whitaker Power System Protection Alternatives, Jerry C. Whitaker Facility Grounding, Jerry C. Whitaker Network Switching Concepts, Tsong-Ho Wu Network Communication, James E. Goldman Data Acquisition, Edward McConnell and Dave Jernigan Computer-Based Circuit Simulation, Bashir Al-Hashimi Audio Frequency Distortion Mechanisms and Analysis, Jerry C. Whitaker Video Display Distortion Mechanisms and Analysis, Jerry C. Whitaker Radio Frequency Distortion Mechanisms and Analysis, Samuel O. Agbo Digital Test Equipment and Measurement Systems, Jerry C. Whitaker Fourier Waveform Analysis, Jerry C. Hamann and John W. Pierre Computer Based Signal Analysis, Rodger E. Ziemer Systems Engineering Concepts, Gene DeSantis Disaster Planning and Recovery, Richard Rudman Safety and Protection Systems, Jerry C. Whitaker Conversion Tables, Jerry C. Whitaker Index

Around View Monitoring (AVM) system is a computer vision application in advanced driver-assistance systems (ADASs). When using full high-definition (HD) camera, it brings significant challenge to system design. Multi-channel HD cameras bring great pressure to video processing system, especially the communication between the processing circuit and memory. To address these issues, this paper proposes a software-hardware co- designed AVM system. In particular, we present and implement a computational efficient composing algorithm for high quality bird's-eye view image and a cost efficient hardware architecture for low memory bandwidth. The performance of the proposed full HD AVM system can reach up to 30 frames per second.

This paper presents approximating non-linear behavior of distortion guitar effect such as Fuzz and Overdrive by Bernstein polynomial with low orders in the form of electrical signal. The Bernstein method can be adjusted parameters by manual, in order to designing a new sound of distortion effect. The method was confirmed effectively by a ratio of harmonics. Original effects were generated by electronic circuit, which couldn't be adjusted. In the other hand, the Bernstein method can be identified a dominant feature sound and developed on other devices such as software or application not the same as distortion effect circuit.

This paper presents approximating non-linear behavior of distortion guitar effect such as Fuzz and Overdrive by Bernstein polynomial with low orders in the form of electrical signal. The Bernstein method can be adjusted parameters by manual, in order to designing a new sound of distortion effect. The method was confirmed effectively by a ratio of harmonics. Original effects were generated by electronic circuit, which couldn't be adjusted. In the other hand, Bernstein can be identified a dominant feature sound and developed on other devices such as software or application not the same as distortion effect circuit.

All IoT(internet of things) devices can establish the relationship by connecting the network between other things. Also things can catch human behaviors and analyze them to predict a person's next action from data based on the cumulative behavior patterns of people. After analyzing, things can provide services to people derived from their analysis of individualized peoples behavior patterns. The proposed research will present the initial effort of the things-server interaction between IoT devices to provide user intent service using acoustic signal event detection. Acoustic signal events can be detected whenever people touch things. By collecting and sharing events between things and things, users patterns will be created server side and provide user intent event to people. In the experiments, the piezo transducers are used to detect users touch events by vibrating on the things surface using acoustic waves. Wireless connection, specifically based TCP/IP connection, is used to implement things-server interaction. Through data calculation perspective, thing-things interaction is implemented for pre-process pattern analysis to reduce the calculation amount. With these interactions, users can be provided with their intended services for individualized pattern analysis with cumulated event data at server side.

this paper presents the implementation in simulation of two control techniques for a drive system in electric motorcycle. The controls proposed are field-oriented control (FOC) and direct torque control (DTC). The analysis consists of comparing the two controls and analyze the advantages and disadvantages of each technique. The aim is validate the best technique that provides greater efficiency, easy of implement and most cost effective for a future implementation in a prototype electric motorcycle. The paper contributes to the implementation of means of transportation powered with electricity for student mobility in the city of Cuenca Ecuador and reducing of problems of environment pollution and traffic saturation.

The sound of the distorted electric guitar is particularly important for many metal music genres. It contributes to the music’s perception of heaviness, serves as a distinguishing marker, and is crucial for the power of productions. This article aims at extending the research on the distorted metal guitar and on metal music production by combining both fields of interest. By the means of isolated guitar tracks of original metal recordings, ten tracks in each of the last five decades served as sample for a historical analysis of metal guitar aesthetics including the aspects tuning, loudness, layering and spectral composition. Building upon this insight, an experimental analysis of 287 guitar recordings explored the effectiveness and effect of metal guitar production techniques. The article attempts to provide an empirical ground of the acoustics of metal guitar production in order to extend the still rare practice-based research and metal-oriented production manuals.

Nonlinear systems, such as guitar distortion effects, play an important role in musical signal processing. One major problem encountered in digital nonlinear systems is aliasing distortion. Consequently, various aliasing reduction methods have been proposed in the literature. One of these is based on using the antiderivative of the nonlinearity and has proven effective, but is limited to memoryless systems. In this work, it is extended to a class of stateful systems which includes but is not limited to systems with a single one-port nonlinearity. Two examples from the realm of virtual analog modeling show its applicability to and effectiveness for commonly encountered guitar distortion effect circuits.

Smartphone technology provides new opportunities for recording standardized voice samples of patients and sending the files by e-mail to the voice laboratory. This drastically improves the collection of baseline data, as used in research on efficiency of voice treatments. However, the basic requirement is the suitability of smartphones for recording and digitizing pathologic voices (mainly characterized by period perturbations and noise) without significant distortion. In this experiment, two smartphones (a very inexpensive one and a high-level one) were tested and compared with direct microphone recordings in a soundproof room. The voice stimuli consisted in synthesized deviant voice samples (median of fundamental frequency: 120 and 200 Hz) with three levels of jitter and three levels of added noise. All voice samples were analyzed using PRAAT software. The results show high correlations between jitter, shimmer, and noise-to-harmonics ratio measured on the recordings via both smartphones, the microphone, and measured directly on the sound files from the synthesizer. Smartphones thus appear adequate for reliable recording and digitizing of pathologic voices.

In this work an intelligent projection framework system (IPS) is proposed, which empowers uncovered finger touch association on normal planar surfaces (e.g., dividers, tables), with one and only standard camera and one projector. The test of uncovered finger touch recognition is recouping the touching data just from the 2-D picture caught by the camera. In our system, the graphical client interface (GUI) catch is anticipated at first glance and is twisted by the finger when clicking it, and there is a huge positive relationship between the button’s distortion and the finger’s stature to the surface. Hence, we propose a novel, quick, and strong calculation, which exploits the catch’s mutilation to identify the touch activity. The current consoles utilized keys construct console for writing in light of the PC. These consoles are chipping away at the mechanical push standard. In any case, for the little gadgets like cellular telephones and tablets it is difficult to convey enormous console with them. The touch screen based consoles accessible in such gadgets are extremely badly designed to compose in light of the fact that the measure of individual’s finger is enormous and the extent of the keys on the touch screen is little. So writing chip away at the little gadgets is not helpful and on PC our fingers get torment in the wake of doing long time writing work as a result of mechanical vibration of the keys.

Nowadays, people pay more and more attention to logistics management. However, due to the global e-commerce supply chain information transfer is not timely; information distortion and system error, hundreds of billions of dollars every year have lost. In order to improve the efficiency of logistics management system and reduce the error rate, people put forward RFID logistics management system. At the same time, because the embedded technology has the advantages of flexibility, high integration and low price, the use of embedded technology to realize RFID becomes the mainstream. This paper, combining the two, designs a RFID logistics management system based on Nios II. The system consists of a Nios II embedded soft core, a FPGA, a LCD screen, a matrix keyboard etc. After test, it can read the information of goods in a certain range and show them on a LCD screen and users can use a keyboard to manage the warehouse. It also helps to improve the efficiency of logistics management and reduce the error rate.

Serie: Lecture notes in electrical engineering, vol. 402, This paper presents an evaluation of the introduction of electric vehi-cles (EVs) in an electrical power grid. The main contribution is the control analysis of the power quality considering simultaneous battery charging pro-cesses. The methodology used can be applied to any known power grid; howev-er, it was considered the case of the island of Maio, in Cape Verde, in continua-tion of previous works concerning that power grid. Two commercial different types of battery chargers were considered: a traditional model with highly dis-torted current consumption (that causes distortion in the power grid voltage), and another with almost sinusoidal current consumption. Considering simulta-neous battery charging processes, it can be concluded that the power grid struc-ture (composed by three medium voltage branches) with the current power de-mands of the consumers of the island of Maio have a potential integration for 300 EVs if battery chargers with almost sinusoidal current consumption are used, i.e., 152 for the first medium voltage branch, 35 for the second branch, and 113 for the third branch. Moreover, the results show that the first medium voltage branch of the distribution system, which has the capability to support the integration of 152 EVs if the battery chargers have sinusoidal current con-sumption (presenting a maximum value of THDv% in the power grid voltage of 1.8%), only can support 27 EVs if are used traditional battery chargers, with highly distorted current consumption (considering a maximum THDv% of 5%)., COMPETE: POCI-01-0145-FEDER-007043, Fundação para a Ciência e Tecnologia (FCT) - UID/CEC/00319/2013, Fundação para a Ciência e Tecnologia (FCT) - SFRH/BD/80155/2011