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We have proposed n-shape elastomers for enhancing sensitivity of acoustic signal detection. The simulation results show that such n-shape elastomers with cantilever-like structure can be deformed by sound wave pressure, showing great potential of high sensitivity sensor head in distributed optical fiber sensing system.

The relevance of the work devoted to the creation of a modern displacement sensor for mechanical systems on the acousto-optic effect, which allows combining high speed and accuracy of measurements, with the possibility of using it in aggressive operating conditions, is formulated. The choice of the principle of displacement measurement based on the acousto-optic effect and non-contact measurement was made to meet the modern requirements of measuring systems. A description of the acousto-optic effect and its application for the construction of a displacement sensor are given. The structure and main parameters of the measuring circuit of the sensor, the principle of operation of the acousto-optic transducer on a standing sound wave are described. The principles of forming a standing sound wave and maintaining it in an acousto-optic element due to its design features. The analysis of the characteristics of the measuring circuit and the constructed sensor for measuring displacements and an assessment of compliance with the requirements of measuring systems has been carried out.

Ultrasound imaging is a widely used technique in medicine. It is a non-invasive medical procedure that uses sound waves to produce pictures of the inside of the human body. Ultrasound helps to diagnose conditions of soft tissues and detecting a wide range of medical diseases and pathologies. This paper presents a 3D model and a Gazebo plugin of a medical ultrasound sensor that performs ultrasound imaging of an abdomen surface. The ultrasound device is represented as an end-effector for a KUKA IIWA LBR manipulator model but can also be used for other manipulator models. We introduce an implementation of a complex abdomen 3D model that consists of fat, muscle, and intestine tissue layers. Each tissue has its unique parameters used by the Gazebo medical ultrasound plugin. The developed ultrasound sensor was successfully tested in the Gazebo simulator and was able to provide visualizing a structure of the abdomen internals for further diagnostics.

Based on the shell structure of the traditional hydrophone array, this paper studies the influence of its internal acoustic environment on the acoustic characteristics of the internal hydrophone array element under the action of sound waves. The article uses the finite element simulation method to obtain the sound pressure at the receiving position of the hydrophone changes with frequency, finds the reason for the fluctuation of the sensitivity test results of the hydrophone, and finally gives the optimization of the structure of the hydrophone array shell.

This paper aims at audience positioning using microphone array and help the high-fidelity sound system to improve the sound effect. When the audience is at different position, the sound from different speakers will not arrive at the same time. It can make the sound effect more real to adjust the delay and loudness of the sound system. Mirror source principle is proposed under near-field multi-source positioning to solve the sound wave reflection. In addition, to make it more suitable for near field indoor positioning, multiple signal classification algorithm is improved in this paper. Simulation results show that the positioning error is within 40mm, which proves that the method in the paper is effective and practical.

The vibrational waves in a one-dimensional composite system containing double-negative acoustic metamaterials were studied. The transmission of sound waves of multilayer systems was numerically clarified. A method for calculating the transmission rate in these systems was also described.

Sound waves are a form of energy produced by a vibrating object that travels through the medium that can be heard. Generally, the sound is used in human communication, music, alert, and so on. Furthermore, it also helps us to understand what are the events that occurring in the moment, and thereby, provide us hints to understand what is happening around us. This has prompt researchers to study on how humans understand what event is occurring based on the sound waves. In recent years, researchers also study on how to equip the machine with this ability, i.e. acoustic event detection. This study focuses on the acoustic event detection which leverage both frequency spectrogram technique and deep learning methods. Initially, a spectrogram image is generated from the acoustic data by using the frequency spectrogram technique. Then, the generated frequency spectrogram is fed into a pre-trained MobileNet model to extract robust features representations. In this work, 1 Dimensional Convolutional Neural Network (1D-CNN) is adopted to train a model for acoustic event detection. The feature representations are extracted from a pre-trained MobileNet. The proposed 1D-CNN consist of several alternatives of convolution and pooling layers. The last pooling layer is flattened and fed into a fully connected layer to classify the events. Dropout is employed to prevent overfitting. The proposed frequency spectrogram with pre-trained MobileNet and 1D-CNN is then evaluated with three datasets, which are Soundscapes1, Soundscapes2, and UrbanSound8k. From the experimental results, the proposed method obtained 81, 86, and 70 F1-score, for Soundscapes1, Soundscapes2, and UrbanSound8k, respectively.

The influence of acoustic field on vapor precipitation process taking place above the plating bath is analyzed in the article. Lateral exhaust hood was used to remove aerosol from open surface tank. It is shown that acoustic field generator generates sound waves with sound level of 130–140 dB at 1–4 kHz frequencies. Such acoustic field increases aerosol coagulation and its precipitation back to the liquid. This results in the reduction of aerosol concentration in the air, reduction of costs of air purification equipment and increase of its removal efficiency.

We propose a conceptually and computationally simple form of sound velocity that offers a readable view of the interference between direct and indirect sound waves. Unlike most approaches in the literature, it jointly exploits both active and reactive sound intensity measurements, as typically derived from a first order ambisonics recording. This representation has a potential both as a valuable tool for directly analyzing sound multipath propagation, as well as being a new spatial feature format for machine learning algorithms in audio and acoustics. As a showcase, we demonstrate that the Direction-of-Arrival and the range of a sound source can be estimated as a development of this approach. To the best knowledge of the authors, this is the first time that range is estimated from an ambisonics recording.

The results of theoretical and experimental studies of acoustic measurements at various angles of incidence of acoustic waves on the membrane of a condenser-type measuring microphone are presented, which have shown that, in order to minimize measurement uncertainty, technical microphones should indicate normalized frequency characteristics of sensitivity at different angles of incidence of the sound wave.

For the surveillance of isolated geographical areas, we created a sensor with a structure similar to the human head to reproduce as accurately as possible the acoustic phenomena that occur at the reception of sound waves by the ears and to obtain a transfer characteristic close to that of the human head. The four acoustic signals received simultaneously from the four microphones in the sensor structure are processed with the Audacity application using the autocorrelation function. The result is the identification of the specific sound sources for this type of area (forestry machinery, wild animals, other human activities) and the determination of the direction of arrival and of the location with sufficiently good accuracy for the purpose pursued, using a netrvork of autonomous sensors, reliable, with low energy consumption.

Imparting vibration to the contact surface of an object is a method of presenting a tactile sensation of the object surface. However, it is difficult to temporally and spatially present wide-band vibrations through the direct vibration generation of a general actuator. In this study, we focus on sound waves, and propose a method to present tactile sensations by generating vibrations via irradiating sound waves of various frequencies and amplitudes on a plate. In experiments using a parametric speaker as an acoustic device, the vibration of the plate during sound wave irradiation was measured; it was confirmed that different tactile sensations could be obtained by changing the frequency and amplitude of the irradiated sound wave.

In health care, the continuous breathing monitoring device has not been popular yet, albeit personal daily breathing monitoring is expected to be used for the diagnosis of sleep apnea syndrome, stress management, and depression prevention. With the aim to realize personal and continuous breathing monitoring, this paper proposes a lung movement detection method that uses sound waves. This method has advantages of low cost, use of a small-scale and simple device, and easiness in wearing. The proposed method can sense lung movement only by a vibration speaker and a contact microphone placed on user’s chest and use the measured parameters in the sound signal processing. In this paper, the waveform comparison of the lung movement measured by the proposed method and the displacement of the thoracic diaphragm in breathing was conducted, and it was confirmed that the proposed method could capture lung movement in breathing with a high correlation.

This paper investigates the use of radar techniques for recovering low frequency audio signals by measuring the vibration induced in objects exposed to sound pressure waves. A sound wave emitted by a speaker is recovered by measuring the small-scale displacement vibrations transmitted into a reflective surface that is being analyzed by a commercial FMCW radar at 24 GHz, bandwidth of 300 MHz and sweep time of 300 µs. Experimental validations are provided to show the effectiveness of the proposed method.

This paper investigates the design of a rotary wing unmanned aerial vehicle (UAV) and the method used for this UAV to determine its mathematical location indoors. The optimal method used for the location determination was established upon research. By reducing the signal loss caused by the indoor area and with the use of acoustic localization that measure distance by 3-dimensional vectors with velocity of ultrasonic sound wave, the determined method allowed the instantaneous observation of the UAV's mathematical location in 3-dimensional space. Furthermore, this method enabled a balanced and efficient autonomous flight indoors.

Ultrasonic sensor is one of most popular sensor type to be used in distance measurement. This sensor generates sound waves to measure the distance between itself and the measurement object by using the calculated time of the waves when the waves are reflected back to the sensor. This research is conducted to do a comparative study between 2 types of ultrasonic sensor based on their generated sound waves. The first sensor is Devantech SRF235 which uses a beam type of signal for measurement, and the second is Parallax PING))) which uses burst type of signal. The results show that SRF235 is capable to measure the distance of a small object while the burst type Parallax PING))) has an error approximately of 11.122%.

Aerodynamic noise in half space is a common problem in aviation. The reflection of sound waves on the ground should be considered in the numerical calculation. However, the effect of ground reflection is rarely considered in most current studies. In this paper, we propose a novel intelligent numerical simulation method for aerodynamic noise of propeller aircraft considering ground reflection. Aiming at the analysis of noise characteristics of a new energy two-seater light propeller aircraft and the technical requirements of improving acoustic quality, the numerical simulation of propeller aerodynamic noise is carried out in this paper. Firstly, the unsteady sliding grid method is used for modeling. Secondly, the acoustic pressure cloud map of free sound field of aerodynamic noise is obtained by using the acoustic analogy model of large eddy simulation (LES) and Ffowcs Williams and Hawkings (FW-H) acoustic model. Thirdly, the influence rule of ground reflection on propeller aerodynamic noise is obtained by establishing the ground reflection surface. Finally, the accuracy of the method is verified by the far field noise experiment on the ground. This paper focuses on the research method of intelligent numerical simulation of noise to solve practical application problems. Aiming at the problem of aerodynamic noise prediction of a certain type of propeller aircraft, we uses the intelligent numerical simulation method of noise to accurately predict the distribution law of aerodynamic noise radiated by the propeller in the far field, which solves the practical engineering problems.

In this paper, we propose a method of presenting information by manipulating granular material that are placed on two layers. In recent years, substantial displays, which are displays that present information by manipulating some form of material have been gaining traction in the research community. As these displays utilize materials found in nature, they are capable of blending in with the surrounding environment. To create a novel substantial display, we propose a substantial display that utilizes granular material and speakers. In the proposed system, two types of granular material with different colors and sizes are placed on two layers. By emitting sound waves from a speaker installed under the lower layer, the granular material on the lower layer rises to the upper layer and creates a pattern as the color of the granular material on each layer is different. To determine the optimal parameters, we examined four different granular material and varied the sound wave frequency. Finally, we implemented a system that allows users to emit sound waves at any arbitrary position on the canvas with two layers of granular material.

A compact model of an airborne capacitive acoustic MEMS transducer is generalized to perform predictive full-system simulations in the audible and ultrasonic regime. The model helps to assess and understand the interaction of the device with the surrounding air for frequencies up to 100 kHz while considering acoustic high-frequency effects and sound wave propagation. We successfully simulate transducers with varying design parameters operating under different working scenarios. The predictive power of the model and its potential for full-system design and optimization are highlighted by the very good agreement between simulations and experimental results.

We present a novel sound localization algorithm for a non-line-of-sight (NLOS) sound source in indoor environments. Our approach exploits the diffraction properties of sound waves as they bend around a barrier or an obstacle in the scene. We combine a ray tracing based sound propagation algorithm with a Uniform Theory of Diffraction (UTD) model, which simulate bending effects by placing a virtual sound source on a wedge in the environment. We precompute the wedges of a reconstructed mesh of an indoor scene and use them to generate diffraction acoustic rays to localize the 3D position of the source. Our method identifies the convergence region of those generated acoustic rays as the estimated source position based on a particle filter. We have evaluated our algorithm in multiple scenarios consisting of a static and dynamic NLOS sound source. In our tested cases, our approach can localize a source position with an average accuracy error, 0.7m, measured by the L2 distance between estimated and actual source locations in a 7m*7m*3m room. Furthermore, we observe 37% to 130% improvement in accuracy over a state-of-the-art localization method that does not model diffraction effects, especially when a sound source is not visible to the robot., Submitted to ICRA 2019. The working video is available at (https://www.youtube.com/watch?v=qqf7jM45bz4)

Speech contains sounds that delineate words of a language. Capturing speech in different real environmental circumstances may contain different mixtures of many different sound waves (i.e. the mixture of sounds, noises and other effects like reverberation). Such noisy environments make difficult to capture clear speech and hence degrade the speech quality. Due to the different nature of noise and reverberation effect, it must be necessary to remove extra noise and reverberation effect separately. This paper proposes a hybrid approach that uses various algorithms sequentially to remove noise, reverberation effect, and cocktail party problem. Non-negative matrix factorization (NMF) is representation learning method that uses basis matrix and activation coefficients to produce the basic spectral structure of speech. Deep learning use supervised mapping function to map noisy spectrum to target speech spectrum. NMF with deep learning can jointly be used to separate non-stationary noise from target speech. On other hands, the non-negative convolutive transfer function (nCTF) estimates the coefficient of reverberation. Non-negative convolutive transfer function with NMF can be used to reduce the effect of the room impulse response (RIR). Gaussian mixture model-universal background model (GMM-UBM) extracts the compact representation of speech. GMM-UBM with deep classifier used to extract target speech from cocktail party problem (the mixture of sounds of multiple speakers). The Proposed system is based on the Punjabi language that aims to enhance speech under noisy-reverberant environments and the cocktail party problem.

The relevance of the present study devoted to the development of modern optoelectronic devices based on diffraction gratings from standing elastic waves is shown. This is necessary for Russia to strengthen its defense capability and create competitive technologies in the industrial sphere. The prospectivity of research on the development of optoelectronic devices based on diffraction gratings from standing elastic waves has been established, as well as the inadequacy of due attention to the design of optoelectronic devices based on diffraction gratings from standing elastic waves. The need for research in this field has been formulated. The physics of processes in the field of acousto-optical processes is considered. It is shown that when passing through the same medium, light and sound waves interact with each other. Light is scattered on a sound wave, as on a diffraction grating. Recommendations for the design of optoelectronic devices based on diffraction gratings from standing elastic waves have been developed. The main characteristics and possible applications of optoelectronic devices based on diffraction gratings from standing elastic waves are presented. A technique for designing an acoustooptical modulator has been developed.

Human being has the capability to determine the sound source location because of sound waves difference received by the ear. The method applied to determine the humans source location in this research was Time Difference of Arrival Estimation (TDOA) at a sampling rate of 6 KHz. The results of tests found that the system can determine the human voice source location in semicircle $(0^{\mathrm{o}}\ -\ 180^{0})$, with the best angular resolution was at $10^{0}$. The results of this study can be applied to the teleconference room.

This paper aims at the development of ultrasound based thickness measurement device. A Spartan 6 FPGA from Xilinx has been used in the hardware design along with external parallel Analog to Digital and digital to Analog converter. The device is interfaced with a PC or laptop through USB cable. A measurement and control software is developed using MATLAB for conceptual level and final Graphical User Interface has been developed in. NET to transfer different user defined control parameters to the hardware and receive the captured signal. Ultrasonic probes are used to generate and receive physical sound wave in pulse-echo mode. Time of flight (ToF) based calculations are used for deriving the subject dimension.

We present a new form of game-playing that takes place among one or more participants, each in a sensory deprivation tank, wearing a waterproof VR headset, for biofeedback-based virtual interaction. Whereas conventional VR (Virtual Reality), AR (Augmented Reality), and Mediated (“XY”) reality include an axis that spans from reality to virtuality (i.e. with reality as the origin), we build upon the newer multidimensional framework of multimediated reality that has nothingness at the origin (i.e. as facilitated by total sensory deprivation). This sets the stage for a novel class of games that facilitate the suspension of disbelief for the game's players. Floating in the tank creates a new context for a heightened sense of imaginality in the world of immersive/submersive reality. Specifically, our game involves mediation while singing a steady note, using phenomenologically augmented reality (e.g. seeing sound waves with an augmented reality lock-in amplifier). A VR game that uses the binaural beat brain entrainment technique in computer-mediated/networked sensory deprivation tanks is developed.

Neurological pathologies, especially optical neuro-pathologies, can be studied by means of OCT (optical coherence tomography). Tomography generally allows to investigate inner structures of a tissue such as mass, and profiles of liquid flow. OCT is intended as an interferometry-based imaging technique that provides cross-sectional views of substrates. It allows to measure micro-scale cross-sectional imaging of biological tissue. While ultrasound uses sound waves, it acts like it but with a low coherence light. Optical nerve thickness has an impact on different neurological pathologies, and in particular as an indicator of epilepsy. We propose a dedicated technique for measuring optical nerve thickness and identifying its quality by means of processing front eye image in nanoscale. Experimental measurements have been performed, and a database of 10 teenagers has been used for that.

The purpose of this study is to train the reconstructed sound waves, which is obtained from recording holograms via digital holography, and reduce the noise from this sound wave without using noise Altering techniques. The noise reduction is achieved by approximating the reconstructed sound wave trained by YSA to the actaul recording sound wave. A network topology is created for training and the system was tested. The performance of the system is given by showing how closely the sound wave trained by YSA approaches the actual sound wave.

The parametric array can emit two parallel acoustic waves of different frequencies, and can produce high directivity sound waves due to the non-linear effect in the medium (especially in water). The maximum sampling frequency of the system DAC is 750k, that is, the minimum delay of the system is 1333ns. The minimum deflection angle of the acoustic wave emitted by the parameter array is about 5 ° and can only be transmitted to several fixed angles. In order to realize the deflection of any angle of the transmitted acoustic wave, a fractional delay method is introduced, and the minimum delay is fractionated to obtain a smaller system minimum delay, and the design of a suitable filter to approximate the characteristics of the ideal fractional delay filter to achieve the minimum deflection angle of less than 1 ° expected target. In this paper, through the Farrow structure to achieve fractional delay filter, the advantage is only need to change the delay parameter d, you can get the required delay, do not need to recalculate the filter coefficients.

When presenting a stereo sound over a pair of transducers on a bone conduction headphone, the sound wave coming from either the left or right side transducer is delivered directly to the cochlea in both ears. This mechanism is often referred to as ”cross-talk,” and it may decrease the ability to sense sound direction perceived through the bone conduction headphone. In this paper, we investigate the application of active control technique on a bone conduction headphone for estimating a cross-talk compensation filter. To reduce perceived loudness in one of the ears, transfer functions on routes from transducers to a cochlea are estimated by using a microphone placed in the outer ear canal under the assumption that otoacoustic emission (OAE) emitted by the cochlea in response to a bone-conducted sound stimulus can be recorded. By using the transfer functions, the compensation filter which produces anti-sound can be obtained as a result of the filtered-x least mean square (FXLMS) algorithm. In this study, sound stimuli with and without cancellation were presented through a bone conduction headphone where three subjects with normal hearing participated in the measurement. Experimental results show that sound reduction was achieved at the location of the microphone and all participants also reported that they could feel a decrease in the perceived loudness.

Sound wave is the only medium that can propagate effectively over long distances in the ocean. Underwater acoustic data plays an important role in the study of computational ocean acoustics. But the computation in three-dimensional underwater acoustic propagation is time-consuming, which is difficult to meet the real-time demand. In this paper, we put forward parallelization and performance optimization which is combined with the architecture of a new generation of processors from the Intel Xeon Phi family and the computing characteristics of the application to decrease the time of a parabolic equation solver in computational ocean acoustics. The results showed that the speed of computation can be greatly improved by the strategy mentioned in this paper. The method used in this paper is not only general for other similar computing model in computational ocean acoustics but also a guideline of performance enhancement for scientific and engineering application running on modern many-core computing platform.

Multiple research groups have recently innovated image recovery methods for fast pulse-echo ultrasound imaging (UI) that combine inverse scattering techniques with compressed sensing (CS). These methods alleviate the inherent tradeoff between the image quality and the image acquisition rate. The choice of the incident sound field is a crucial degree of freedom to implement the specific requirements of CS, e.g. incoherent measurements. Previous publications exclusively investigated steered plane waves (PWs). In this study, we leverage three types of random ultrasonic waves to better conform with the requirements of CS. This increases both the image quality and the speed of convergence.

The most recent cochlear Implants Naida CI Q70 and Q90 from Advanced Bionics have their external devices such as speech processor and head piece (transmitter), Communicate with the reliable connection oriented network architecture. This architecture is complex with a long cable connected between speech processor and head piece (transmitter). This structure encounter drawbacks, like maintenance of cable, expensive as any small damage requires huge money to be spent on cable. Furthermore its rare and unique structure creates a lot of nuisance with multiple enquiries from the people leading to the frustration while answering them. Hence the idea is to Design Wireless Communication system for a CI device is the thought process. The proposed Architecture uses the ‘UART to WIFI module’ and it is available in the market. We have used IEEE 802.15.4 Wi-Fi module to configure Speech Processor and Head Piece (Transmitter) of CI as Wi-Fi module that has hotspot for communication. This module provides AT commands to configure the WIFI. The Voice processing system has been configured for maximum distance between two WIFI modules as maximum 100mts (practical around 30mts of IEEE 802.15.4 capacity). In this paper we have provided sufficient results through simulation using Sound Wave audio logical software.

The ultrasound examination is a certain tool in order to diagnose some disorders at the maxillofacial region generating discomfort, disability and negative impact of life quality. In the temporomandibular joint region are different structures (tissues) that can be visualized by issuing different sound waves. The ultrasound examination applied to 103 patients complaining rheumatic symptoms of tempormandibular joint was based on a standard protocol that allowed the identification and measurement of aspects related to the alignment of the joint surfaces; mandibular condyle and temporal fossa shape; the joint space and the TMJ meniscus in static and dynamic; masticators at rest and contraction. The whole study group was found with degenerative lesions at a rate of 53.40% inflammatory lesions, a rate of 29.13% and a rate of mixed lesions of 10.67%. Conclusions: The ultrasound examination provides strong arguments demonstrating morphological and functional damage of TMJ in rheumatic disorders. The ultrasound examination is a powerful tool of diagnosis offering low cost - efficiency - time.

International audience; Micro Electro-Mechanical Systems (MEMS), applied to the field of hearing aids, offer ample possibilities for improving of performance, reliability and functional specifications, and they are also promising in terms of energy saving. In this paper, some of the major design problems relating to the use of MEMS for sound waves generation inside the ear canal are analyzed.

In the area of digital audio processing, automated music transcription stands as a major enabler in decoding of chord schema so as to facilitate re-arrangement of music. The success rates were found to be largely dependent on the complexity of supplied audio files. Many methodologies can be taken as a base of this purpose of audio transcription, namely genetic transcription algorithm, Wu Pitch Tracking System, Auto-correlation etc. This paper presents an elaborate mapping schema for sheet music transcription which can upon through user acceptance testing be used as an external library for all transcription related research. This paper introduces a new approach to transcription which is simple at its core but requires complete understanding of the nature of sound waves. In this paper fuzzy classification method is used for automated music transcription. Proposed audio processing algorithm takes a monophonic instrumental audio as an input, generates edge detection and stem detection matrices and graphs. The experimental results prove that it gives encouraging results for songs of different tempos.

Visual microphone is a technique introduced to recover the sound from a silence video. And traditional method of sound recovery involves extracting and combining subtle motion signals from the entire image. However, there are two possible drawbacks of recovering the sound using the entire image. First, motion signals extracted from plain and edge regions may contain noise due to an aperture problem. Although plain regions are penalised by their squared amplitude values, summation of all the pixels present in the image could introduce notable amount of noise. Second, it is unclear which part of the surface of an object is hit by the sound wave. Utilizing only the region hit by the sound wave is expected to lead to a better sound recovery. The proposed patch-based visual microphone framework addresses these two problems by recovering the sound from a sub-region (patch) in the image centered at a key point (corner). Since we are unable to know which sub-region in the image is good for sound recovery, speeches are recovered from patches centered at each key point (corner), and then the best speech with the least noise is selected as a recovered speech. Extensive experiment results show that utilizing motion signals from a small region in the image near a key point can improve quality of the recovered speech.

Few hundred species of mosquitoes cause disease like malaria, dengue etc. In order to eradicate these malaises, people have resorted to many remedies like chemical repellents which causes nervous breakdown, increase blood pressure and also ravage crops in the fields. In order to overcome these plight, solar energy driven autonomous smart ultrasonic mosquito repeller system has been proposed. The proposed system is driven by solar energy employing dynamic offset feed mirror parabolic dish integrated with solar panel. The proposed system is harmless to human beings as it produces ultrasonic sound waves by utilizing piezoelectric effect. The frequency range of ultrasonic sound waves is above 20 kHz which are inaudible to human beings. The ultrasonic sound waves of frequency range 38 kHz-44 kHz are audible to mosquitoes and other insects. When mosquitoes and other insects communicate, they continuously sense ultrasonic sound waves from repeller through antenna present on their body, they get irritated and are forced to repel away from that area. The microcontroller Atmega 328P-PU is used to turn on and off the repeller. The proposed system can be effectively used to repel mosquitoes from lawns, city parks, universities campus and organizations. The proposed smart mosquito repeller system is effective within 255 square meters.

Head-related transfer functions (HRTFs) reflect the interaction between human anatomical structures and sound waves, and depend on individuals due to differences in anatomical structures among individuals. This work investigates inter-individual differences of spectral cues encoded in median-plane individual HRTFs using principle component analysis (PCA). First, magnitudes of individual HRTFs from the CIPIC database are decomposed and reduced dimensions by PCA. Then, individual expansion weights of PCA are extracted. Finally, the inter-individual differences in expansion weights are analyzed using standard deviation. Results show that the inter-individual spectral difference in HRTFs decreases with increasing expansion degree of PCA, and the spatial distribution of large inter-individual difference is always at low elevations. When the expansion degree is 1 and 2, the mean of individual expansion weights mainly reflects the inter-elevation difference. The same method is also applied to a combined HRTF database including 295 subjects.

Infrasound is usually defined as sound waves below 20 Hz, the nominal limit of human hearing. Infrasound waves propagate over vast distances the Earth's atmosphere: the CTBTO (Comprehensive Nuclear-Test-Ban Treaty Organization) has 48 installed infrasound-sensing stations around the world to detect nuclear detonations and other disturbances. In February 2013, several CTBTO infrasound stations detected infrasound signals from a large bolide that exploded over Chelyabinsk, Russia. Some stations recorded signals that had circumnavigated the Earth, over a day after the original event. A balloon-borne infrasound sensor is expected to have two advantages over ground-based stations: a lack of wind noise and a concentration of infrasound energy in the “stratospheric duct” between roughly 5–50 km altitude. To test these advantages, we have built a small balloon payload with five calibrated microphones. This paper discusses the design, testing and expected sensitivity of the payload. Our current plans call for a launch in August 2016, coordinated with a ground-based explosion and a network of ground-based infrasound sensors.

Objective: To detect blockages in the seed tube using an ultrasonic sensor and reporting the same to a smartphone application. Methods/Analysis: Seeder machines in agricultural operations may face real-time problems of plugging due to stubble, stones or unusually large seeds. The ultrasonic sensor transmits sound waves and uses delay in the received echo signal to measure distance from the sensor to the obstacle (either the flowing seed or the opposite wall of the nozzle). Based on the calculated distance, the flow of seeds through the nozzle can be detected. Findings: At present, a person is employed in the field to look after the seeder machines and detect the blockages, making it more prone to human errors. Thus it is necessary to find an automated and productive solution to detect the blockages in seeder. The proposed solution monitors and report blockages in the nozzles of agricultural seeder machines by using low cost ultrasonic sensors. One such sensor will be placed on each row unit and all these sensors will continuously communicate with a central controller placed on the seeder. The sensors will report nozzle-blockage to the controller and which will then immediately notify the same to the smartphone user via a graphical real-time application. All kinds of blockages such as stones, stubble, unusually large seeds can be detected by this mechanism. These blockages will be reported to the user via a smartphone application (based on GSM) and the exact location of the blockage will be intimated to the user. Looking at the application window, the user will get real-time information about the blocked nozzle in the seeder. Applications/Improvements: The solution offered in this paper can further be improved by using other wireless technologies such as Wi-Fi (instead of GSM used here).

24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEY WOS: 000391250900528 In this study, same amplitute sounds of sinuzoidal, square and saw tooth wave in frequencies of 100 Hz, 1 kHz and 10 kHz have been generated during 1 second. These sounds have been listened 5 times by a subject. The averaged power spectrums of the EEG which gathered from the subject have been represented in the frequencies of 0-4 Hz, 4-7 Hz ve 8-12 Hz and evaluated. IEEE, Bulent Ecevit Univ, Dept Elect & Elect Engn, Bulent Ecevit Univ, Dept Biomed Engn, Bulent Ecevit Univ, Dept Comp Engn