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The introduction of 3D bioprinting is expected to revolutionize the field of tissue engineering and regenerative medicine. The 3D bioprinter is able to dispense materials while moving in X, Y, and Z directions, which enables the engineering of complex structures from the bottom up. In this study, a bioink that combines the outstanding shear thinning properties of nanofibrillated cellulose (NFC) with the fast cross-linking ability of alginate was formulated for the 3D bioprinting of living soft tissue with cells. Printability was evaluated with concern to printer parameters and shape fidelity. The shear thinning behavior of the tested bioinks enabled printing of both 2D gridlike structures as well as 3D constructs. Furthermore, anatomically shaped cartilage structures, such as a human ear and sheep meniscus, were 3D printed using MRI and CT images as blueprints. Human chondrocytes bioprinted in the noncytotoxic, nanocellulose-based bioink exhibited a cell viability of 73% and 86% after 1 and 7 days of 3D culture, respectively. On the basis of these results, we can conclude that the nanocellulose-based bioink is a suitable hydrogel for 3D bioprinting with living cells. This study demonstrates the potential use of nanocellulose for 3D bioprinting of living tissues and organs.

Most combinations of musical tones are perceived as either consonant, “pleasing” to the human ear, or dissonant, which is “not pleasing.” Despite being largely subjective in nature, sensations of consonance and dissonance can be quantified and then compared to the judgments of human subjects. The following is a description of several simple studies that can be carried out in the classroom of a physics of music or science of sound course.

OBJECTIVES To determine whether suprathreshold measures of auditory function, such as distortion-product otoacoustic emissions (DPOAEs) and auditory brainstem responses (ABRs), are correlated with noise exposure history in normal-hearing human ears. Recent data from animal studies have revealed significant deafferentation of auditory nerve fibers after full recovery from temporary noise-induced hearing loss. Furthermore, these data report smaller ABR wave I amplitudes in noise-exposed animal ears when compared with non-noise-exposed control animals or prenoise exposure amplitudes in the same animal. It is unknown whether a similar phenomenon exists in the normal-hearing, noise-exposed human ear. DESIGN Thirty normal-hearing human subjects with a range of noise exposure backgrounds (NEBs) participated in this study. NEB was quantified by the use of a noise exposure questionnaire that extensively queried loud sound exposure during the previous 12 months. DPOAEs were collected at three f2s (1, 2, and 4 kHz) over a range of L2s. DPOAE stimulus level began at 80 dB forward-pressure level and decreased in 10 dB steps. Two-channel ABRs were collected in response to click stimuli and 4 kHz tone bursts; one channel used an ipsilateral mastoid electrode and the other an ipsilateral tympanic membrane electrode. ABR stimulus level began at 90 dB nHL and was decreased in 10 dB steps. Amplitudes of waves I and V of the ABR were analyzed. RESULTS A statistically significant relationship between ABR wave I amplitude and NEB was found for clicked-evoked ABRs recorded at a stimulus level of 90 dB nHL using a mastoid recording electrode. For this condition, ABR wave I amplitudes decreased as a function of NEB. Similar systematic trends were present for ABRs collected in response to clicks and 4 kHz tone bursts at additional suprathreshold stimulation levels (≥70 dB nHL). The relationship weakened and disappeared with decreases in stimulation level (≤60 dB nHL). Similar patterns were present for ABRs collected using a tympanic membrane electrode. However, these relationships were not statistically significant and were weaker and more variable than those collected using a mastoid electrode. In contrast to the findings for ABR wave I, wave V amplitude was not significantly related to NEB. Furthermore, there was no evidence of a systematic relationship between suprathreshold DPOAEs and NEB. CONCLUSIONS A systematic trend of smaller ABR wave I amplitudes was found in normal-hearing human ears with greater amounts of voluntary NEB in response to suprathreshold clicks and 4 kHz tone bursts. These findings are consistent with the data from previous work completed in animals, where the reduction in suprathreshold responses was a result of deafferentation of high-threshold/low-spontaneous rate auditory nerve fibers. These data suggest that a similar mechanism might be operating in human ears after exposure to high sound levels. However, evidence of this damage is only apparent when examining suprathreshold wave I amplitude of the ABR. In contrast, suprathreshold DPOAE level was not significantly related to NEB. This was expected, given noise-induced auditory damage findings in animal ears did not extend to the outer hair cells, the generator for the DPOAE response.

In mobile phones, perceived speech signal deteriorates significantly in the presence of background noise as noise reaches directly at the listener's ears. There is an inherent need to increase the intelligibility of the received speech signal in noisy environments by incorporating speech enhancement algorithm at the receiverend. This paper focus on the enhancement of selective speech samples for the intelligibility improvement, when the near-end noise dominates. Audible speech samples are selected by consideringthreshold of hearing and auditory masking properties of the human ear. Intelligibility of enhanced speech signalis measured using Speech Intelligibility Index. Experimental results show the intelligibility improvement of the speech signal in lower SNR with the proposed approach to the unprocessed far-end speech signal. This approach is efficient in overcoming the degradation of speech signals in very noisy environments.

On the basis of the dereverberation method based on TF-GSC and minimum phase decomposition, considering the insensitivity of the human ear to the speech phase information, an improved method that only use the phase of a reverberant speech to replace the phase information of the whole component is proposed. The time domain waveforms produced by all the dereverberation methods have been comprehensively compared. At the same time, all the methods are evaluated by simulation using two subjective and three objective dereverberation evaluation indices. Results show that the improved method has better performance of dereverberation and save about half of the computational complexity so that the real-time processing speed of the algorithm is greatly improved.

Automatic human ear detection has aroused great interest in biometrics community recently. Ear recognition has great potential in security application, especially it is a naturally complement to face recognition to strength identification recognition. Recent studies have shown that deep learning has achieved very good result in terms of object detection. In this article, we have proposed a practical method for human ear detection called FCNED. Firstly, we construct a human ear classifier based on convolutional neural network, and then transform it into a fully convolutional neural network. Finally, we utilize the sliding-window characteristic of the fully convolutional neural network for human ear detection. In order to improve the ear detection accuracy, the methods of multi-scale and NMS(non-maximum suppression) are also used in our paper. The results of experiment show that our method achieves a very good performance.

The human ear imparts critical form and function and remains one of the most challenging facial features to reconstruct. Over the past century, surgeons have developed numerous techniques and materials for total auricular reconstruction. Refined costal cartilage techniques have remained the gold standard for the past half-century. Recent advancements with novel materials, tissue engineering and 3D printing provide immense potential; however, prohibitive costs and regulatory steps remain as barriers to clinical translation.

This paper proposes a simple automatic 3D ear reconstruction method using a video selfie while having no knowledge about the scene. First we use the EXIF data stored within the images to estimate the intrinsic matrix. Then, standard structure from motion techniques are applied to obtain a reconstruction for every couple of images which will be merged into one reconstruction that represents the whole scene using an original procedure. Finally, the quasi-dense model is obtained by using the ASIFT and ZNCC descriptors. Our approach is simple to implement and only requires the use of a smart-phone camera. Also, the experimental results showed that this approach is very promising compared to the other methods used to solve this problem.

Ear has robust as well as reliable features, thus technique have been proposed for ear detection and recognition from 2D & 3D ear images. In the proposed work, the ring projection technique is used to convert a 2-D ear image into 1-D information. This ring projection technique requires less memory for storage, and is rotation invariant. The 1-D information, after normalization, is used for the construction of the semi-orthogonal wavelet. Using the corresponding semi-orthogonal wavelet of each ear image, 2-D ear image is decomposed to two levels; thus energy compaction ratio for each ear image is obtained. The proposed approach is tested on USTB ear image database. The database contains three images of each subject are captured (total 180 images), under different lighting conditions. They all are right ear images of the subjects. Then variations of ECR value with the various obstructions (ear-ring or partial hair occlusion) in ear illustrate the amount of useful information contained by each image after decomposition using wavelet.

This paper proposes a novel local feature approach for human verification using 2D ear imaging based on Polar Sine Transform (PST). The proposed approach consists mainly of four steps. Firstly, normalizing the training and testing images, then, combining the normalized images together. Secondly, dividing the fused image into blocks, then, PST is used to extract the invariant features from each block. Thirdly, the Approximate Nearest Neighbors (ANN) searching criterion is adopted to collect the most similar blocks by means of Locality Sensitive Hashing (LSH). Finally, some morphological operations are used to reduce the number of false matching blocks, then, the system verifies the human ear. False Reject Rate (FRR) versus False Acceptance Rate (FAR) and ROC curve are used to evaluate the performance of the proposed approach. The experiments are performed on IIT Delhi database to validate the proposed approach. The results demonstrate that the proposed approach has better performance compared with the existing methods.

Descriptor is the key of any image-based recognition algorithm. For ear recognition, conventional descriptors are either based on 2D data or 3D data. 2D images provide rich texture information and human ear is a 3D surface that could offer shape information. It also inspires us that 2D data is more robust against occlusion while 3D data shows more robustness against illumination variation and pose variation. In this paper, we introduce a novel Texture and Depth Scale Invariant Feature Transform (TDSIFT) descriptor to encode 2D and 3D local features for ear recognition. Compared to the original Scale Invariant Feature Transform (SIFT) descriptor, the proposed TDSIFT shows its superiority by fusing 2D local information and 3D local information. Firstly, keypoints are detected and described on texture images. Then, 3D information of the keypoints located on the corresponding depth images is added to form the TDSIFT descriptor. Finally, a local feature based classification algorithm is adopted to identify ear samples by TDSIFT. Experimental results on a benchmark dataset demonstrate the feasibility and effectiveness of our proposed descriptor. The rank-1 recognition rate achieved on a gallery of 415 persons is 95.9% and the time involved in the computation is satisfactory compared to state-of-the-art methods.

Data mining has a great potential in different areas of health informatics. Data mining in health industry can minimize the health cost as well as reduces the risk of life by informing a person at initial stage. An automatic classification system capable of mining pathological data may contribute in health informatics significantly. In this paper, an automatic system to differentiate between pathological and normal data is developed. The developed system mines the pathological data on the basis of an acoustic analysis. The purpose of the acoustic analysis is to estimate the auditory spectrum of a voice sample by using the principle of the human auditory system called as critical bandwidths. The estimated auditory spectrum simulates the behavior of a human ear and acts like an expert clinician who can identify a pathological voice by hearing. The pathological data used for this study is recorded from the people who are suffering from more than 100 different types of voice disorders. Voice of a disordered patient feels noisy, harsh, strain, breathy and unpleasant to ears. During the training phase of the proposed system, it takes labeled normal and pathological data to generate acoustic models by using the Gaussian mixture model. While in deployment phase, an unknown and unlabeled voice sample is given to the system to determine its type, i.e. normal or pathological. The best obtained accuracy of the system is 99.50%.

Biodegradable sponges, as a promising hemostatic biomaterial, has been clinically required over the past decades. Current hemostatic sponges are generally prepared by crosslinking and freeze-drying, but the quality control or biocompatibility is often unsatisfactory due to the freezing-caused morphological non-uniformity and the toxicity of raw materials or cross-linkers. The crosslinking often greatly retards the degradation of the sponges and thus affects the healing of the wound. In this work, we prepared a novel hemostatic sponge using human-like collagen and glutamine transaminase (non-toxic cross-linker) and optimized its morphology via “two-step” freezing instead of conventional “one-step” freezing. The resulting sponge showed a good biocompatibility in cytotoxicity and implantation tests and had a significant hemostatic effect in ear artery and liver injury models. Moreover, the sponge could be degraded high efficiently by several common enzymes in organisms (e.g. I collagenase, trypsase, and lysozyme), which means that the sponge can be easily digested by metabolism and can facilitate seamless healing. Finally, both the front and back of the sponge prepared via two-step freezing was more uniform in morphology than that prepared via one-step freezing. More importantly, two-step freezing can be used as a universal approach for preparation of diverse uniform biomaterials.

This document belongs to the implementation of a system of recognition of the bases on the Hidden Models of Markov HMM. Due to a system of recognition, we will use the techniques of parameterization which handles the mechanisms of the human ear Mel Frequency cepstral coefficient MFCC and Perceptual linear prediction PLP starting from the database TIMIT. We also used two indices Jitter and Shimmer since they show very precise information about the voice of the person.

Changes in consumer eating habits, health concerns, and convenient and practical foods have led to an increased demand for fruit and vegetable products. Food safety is essential considering that there are reports of outbreaks involving the consumption of fruits and vegetables contaminated with pathogens. Washing associated with sanitizer procedure is considered as a critical step to satisfy hygienic and sanitary requirements and maintain the sensory and nutritional characteristics of fruits and vegetables. Chemical compounds are widely applied to clean and sanitize fresh fruits and vegetables, and some of these chemicals, such as the inorganic chlorine compounds, produce by-products that are dangerous to human health. The use of ultrasound is a technology that is gaining ground in the food industry. Ultrasound is a form of energy generated by sound waves at frequencies that are too high to be detected by the human ear. In ultrasound, the removal of dirt and food residues from surfaces and the inactivation of microorganisms occur as a consequence of cavitation, which is the formation, growth and collapse of bubbles that generate a localized mechanical and chemical energy. There are indications that this technology can be used in the food industry, alone or associated with chemical sanitizers. In this paper, we discuss the principles, mechanisms and effects of ultrasound on fruits and vegetables as a sanitization technology.

Objective:To discover the anatomist who first identified the upper oesophageal sphincter.Method:The authors searched dozens of antique anatomy textbooks kept in the old section of the ‘Vincenzo Pinali’ Medical Library of Padua University, looking for descriptions of the upper oesophageal sphincter.Results:The oesophageal sphincter was drawn correctly only in 1601, by Julius Casserius, in the book De vocis auditusque organis historia anatomica… (which translates as ‘An Anatomical History on the Organs of Voice and Hearing …’), and was properly described by Antonio Maria Valsalva in 1704 in the book De aure humana tractatus… (‘Treatise on the Human Ear …’).Conclusion:Anatomists Casserius and Valsalva can be considered the discoverers of the ‘oesophageal sphincter’.

The reliability of nine measures of the stimulus level in the human ear canal was compared by measuring the sensitivity of behavioral hearing thresholds to changes in the depth of insertion of an otoacoustic emission probe. Four measures were the ear-canal pressure, the eardrum pressure estimated from it and the pressure measured in an ear simulator with and without compensation for insertion depth. The remaining five quantities were derived from the ear-canal pressure and the Thévenin-equivalent source characteristics of the probe: Forward pressure, initial forward pressure, the pressure transmitted into the middle ear, eardrum sound pressure estimated by summing the magnitudes of the forward and reverse pressure (integrated pressure) and absorbed power. Two sets of behavioral thresholds were measured in 26 subjects from 0.125 to 20 kHz, with the probe inserted at relatively deep and shallow positions in the ear canal. The greatest dependence on insertion depth was for transmitted pressure and absorbed power. The measures with the least dependence on insertion depth throughout the frequency range (best performance) included the depth-compensated simulator, eardrum, forward, and integrated pressures. Among these, forward pressure is advantageous because it quantifies stimulus phase.

Recognizing humans by their ear have recently received significant attention in the field of research. Ear is the rich in characteristics. The ear recognition does not suffer from some problems associated with other passive biometrics, such as face recognition and the ear shape very stable with respect to age. Further, the ear can be used for human recognition in surveillance videos where the face may be occluded completely or in part. This paper provides a detailed survey of research done in ear detection and recognition on 2D and 3D images respectively. This survey paper is very useful in the current state-of- art for those who are working in this area and also for those who might exploit this new approach.

Cochlear implant surgery on highly hearing impaired and deaf patients presents surgeons with major medical challenges. In advance of the operation, the surgeon must gain the necessary dexterity and topographical knowledge in the field of microsurgery. For these purposes human cadaver specimens are usually used but they are not sufficiently available. Therefore, our group from the University of Magdeburg researches and develops a manufacturing process for producing individual anatomical facsimile models (AFM) of the human ear bone, which originally simulate the cavity structure of the inner ear (cochlea, semicircular canals) by using rapid prototyping methods. For this production a variety of biomechanical data of the human ear bone are needed to recreate the later models with the same biomechanical properties. By using these obtained biomechanical data and the individual patient's CT data, stereolithography models of UV-sensitive epoxy resin can be produced. The models can be emulated to the biomechanical properties of the human bone by varying the curing process of the epoxy resin. Thus, the authentic drilling and milling properties give the surgeon the possibility to develop the skills needed in dealing with microsurgical instruments. At the same time the authenticity of the AFM promotes the study of the anatomical structure and the orientation of anatomical landmarks.

Breeders have bred canaries either for specific song characteristics (song canaries) or morphology/plumage (type canaries) for centuries. Type canaries (e.g., Border and Gloster strains) retain song characteristics that are typically quite similar to those of wild canaries. By contrast, song canaries (e.g., Belgian Waterslager and Roller strains) have been selected for song types pleasing to the human ear, resulting in songs that, in most cases, are less complex, lower pitched, and narrower in a frequency range than songs from wild canaries. We now suspect that song selection in the Belgian Waterslager song canary has either directly or indirectly resulted in high-frequency hearing loss associated with hair cell abnormalities. Here, we compare hearing in the Belgian Waterslager and several other type and song canaries including the American Singer Canary. Though bred only since the 1930s, American Singer canaries also have a high-frequency hearing loss that looks very similar to that of the Belgian Waterslager and may have similar pathologies. Illumina whole genome sequencing has preliminarily identified a number of high-impact SnpEff variants in Belgian Waterslager and American Singer Canaries, some of which are related to deafness genes in mammals.

The 3D printer is a very much discussed subject nowadays. It has many positive aspects and its purpose is to minimize costs, streamline complex processes, and shorten implementation times. From simple applications to complex systems, almost any assembly or subassembly can be reproduced using 3D printers, either based on a design or on a 3D real-world scan. Medicine is one of the domains that has turned to these devices, achieving amazing performance. 3D scanning and printing are basic elements in the development of new processes that were not possible at the moment. Thus, there are 3D models of the external ear of the human ear, applications in the repair of the epithelium affected by certain external factors, prostheses, medical models, and heart valves. In the present paper, we aim to explore, presenting advantages and disadvantages, existing systems for 3D scanning and designing of 3D models for printing in the field of orthopaedics.

Innovations in additive manufacturing [three-dimensional (3D) printing] have allowed for the fabrication of objects as complex as the human ear. The visible part of the human outer ear (pinna) serves as a funnel and a natural filter for incoming sound. Spectral cues generated by the pinna help with auditory localization and externalization. In an attempt to preserve spectral cues when using circumaural hearing devices, the present work explored the use of 3D printing to fabricate individualized pinna within custom-designed and fabricated hearing devices. Through 3D scanning, a computer aided design (CAD) model of a pinna from an anthropometric mannequin was generated to replicate human pinnae. Multiple 3D printing technologies were used to fabricate the CAD model, investigating different material options, dimensional accuracies, and overall printing costs. The fabricated pinnae were subjected to acoustic testing to assess spectral cue preservation by comparing mannequin head-related transfer functions obt...

The human ear is unique and stability and it has broad application prospects in the field of pattern recognition .In this paper, a novel ear recognition method based on differential geometry is proposed. Firstly, we get the normalization ear image through the image preprocessing. Secondly, according to the character of ear recognition, a method based on differential geometry was used to extract ear anatomy feature points. Finally, the best match is found from a database by using binary template matching. The proposed method can be performed automatically for subject recognition by using 2D ear intensity image. And it can efficiently overcome the influence of illumination and rotation change for ear recognition. Experimental results show that proposed method is simple, robust and better in accuracy and efficiency than previous methods.

An accurate finite element (FE) model of the human ear can help in understanding the physiological mechanismof human ear and facilitate the design of implantable hearing devices. In this paper,a FE modelof the human ear consisting of the external ear canal, middle ear, and cochlea was developed. The geometry of the external ear canal and middle ear model was based on a fresh specimen of human temporal boneviamicro-computer tomography imaging. A harmonic sound pressure of 90 dB SPL was applied in the ear canal and the multi-field coupled FE analysis was conductedamong the ear canal air, cochlea fluid, and middle ear and cochlea structures. The results were compared with the established physiological data. The satisfactory agreements between the model and published experimental measurementsindicate the middle ear and cochlea functions can be well simulated and further application in terms of human ear can be achieved by the model.

In our previous research, we created state-of-the-art sectioned images, color-coded images, and surface models of the human ear. Our ear data would be more beneficial and informative if they were more easily accessible. Therefore, the purpose of this study was to distribute the browsing software and the PDF file in which ear images are to be readily obtainable and freely explored. Another goal was to inform other researchers of our methods for establishing the browsing software and the PDF file. To achieve this, sectioned images and color-coded images of ear were prepared (voxel size 0.1 mm). In the color-coded images, structures related to hearing, equilibrium, and structures originated from the first and second pharyngeal arches were segmented supplementarily. The sectioned and color-coded images of right ear were added to the browsing software, which displayed the images serially along with structure names. The surface models were reconstructed to be combined into the PDF file where they could be freely manipulated. Using the browsing software and PDF file, sectional and three-dimensional shapes of ear structures could be comprehended in detail. Furthermore, using the PDF file, clinical knowledge could be identified through virtual otoscopy. Therefore, the presented educational tools will be helpful to medical students and otologists by improving their knowledge of ear anatomy. The browsing software and PDF file can be downloaded without charge and registration at our homepage (http://anatomy.dongguk.ac.kr/ear/).

The Ear Biometrics is an emerging modern human identification system, which is a passive biometrics system where the recognition of an individual is done without the knowledge of the human subject. This kind of passive biometrics system can help the image analyst to extract useful information feature for public surveillance system. The proposed article extracts structure (shape) features such as Area, Perimeter, Eccentricity, Elongation, Compactness, Horizontal Height, Vertical Height, Major Axis, Minor Axis, Circularity and Rectangularity of the human ear to construct an effective ear biometrics system.

Morphological shape of the human ear presents a rich and stable information embedded on the curved 3D surface, which has invited lot attention from the forensic and engineer scientists in order to differentiate and recognize people. However, recognizing identity from morphological shape of the human ear in unconstrained environments, with insufficient and incomplete training data, dealing with strong person-specificity, and high within-range variance, can be very challenging. In this work, we implement a simple yet effective approach which uses and exploits recent local texture-based descriptors to achieve faster and more accurate results. Support Vector Machine (SVM) is used as a classifier. We experiment with two publicly available databases, which are IIT Delhi-1 and IIT Delhi-2, consisting of several ear benchmarks of different natures under varying conditions and imaging qualities. The experiments show excellent results beyond the state-of-the-art.

New Zealand white rabbits were exposed to an environmental temperature of either 20°C (control) or 5°C (cold-exposure) for periods of from one to six weeks. Ear skin temperature was around 30°C in the control environment and fell to around 15°C in the cold environment. Compared with control arteries, ear arteries from cold-exposed animals tended to have a lower optimal temperature for responses to injected noradrenaline (NOR). At 37°C, responses of control arteries exceeded those of cold-exposed arteries; at 12°C the situation was reversed. A similar “cross-over” effect was observed with responses to electrical stimulation (ES). However, in both groups of arteries, responses to ES were better preserved than were responses to NOR at low temperatures, possibly because cooling interfered with uptake into neuronal stores of NOR released by ES, thus allowing more NOR to reach the arterial muscle at these low temperatures.

In this work, we present a low-cost and light-weight wearable sensing system that can monitor bioelectrical signals generated by electrically active tissues across the brain, the eyes, and the facial muscles from inside human ears. Our work presents two key aspects of the sensing, which include the construction of electrodes and the extraction of these biosignals using a supervised non-negative matrix factorization learning algorithm. To illustrate the usefulness of the system, we developed an autonomous sleep staging system using the output of our proposed in-ear sensing system. We prototyped the device and evaluated its sleep stage classification performance on 8 participants for a period of 1 month. With 94% accuracy on average, the evaluation results show that our wearable sensing system is promising to monitor brain, eyes, and facial muscle signals with reasonable fidelity from human ear canals.

Healthcare experts have recently turned towards the use of Biosimulation models to understand the multiple or different causative factors that cause impairment in human organs. The applications of biosimulations have been applied in different biological systems ranging from human ear, cardiovascular, to neurovascular research using Finite Element Method (FEM). FEM provide a mathematical framework to simulate these dynamic biological systems. Visualizing and analyzing huge amounts of Finite Element (FE) Biosimulation numerical data is a strenuous task. In this paper, we demonstrate a Linked Data Visualiser -- called SIFEM Visualiser -- to help domain-experts to Visualise, analyze and compare biosimulation results from heterogeneous, complex, and high volume numerical data. The SIFEM Visualiser aims to help healthcare experts in exploring and analyzing Finite Element (FE) numerical data and simulation results obtained from different aspects of inner-ear (Cochlear) model - such as biological, geometrical, mathematical, and physical models. This publication has emanated from research supported in part by the research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 and EU project SIFEM (contract Number 600933). REFERE non-peer-reviewed

An earprint is an impression of the external ear. House breakers may leave their earprints inadvertently when they listen at doors and windows to check if there is anyone inside before breaking and entering a premises. Owing to uniqueness and individualistic characteristics of the human ear, earprints can be used as evidence to link a criminal with the crime. In the recent past, many suspected thieves have been convicted and several burglaries linked due to the presence of similar earprints. This chapter explores various issues relating to earprints: ear morphology, variations, individualization, matching, and the admissibility of earprint evidence in the courts.

Infants' recognition has always been a huge challenge even in today's technology-driven world. Swapping, missing, kidnapping and mixing infants pose an exaggeration to the existing problem. While the advent of biometric tests has solved the problem of adult recognition, the similar thing for infants, could not serve an appropriate solution. The objective of this paper is to emphasize on the possibility of using human ear as an infant recognizing solution. The reason being this part of body attracted several types of research and studies to prove individuality and uniqueness. The major contributions of this paper includes (i) Implementation of seven algorithms on ear database of adult and infant, (ii) Comparison of the result of an algorithm, (iii) Preparation of infant database.

In Albanian language there are several phonemes that are similar in pronunciation like /q/ - /c/, /rr/ - /r/, /th/ - /dh/ and /gj/ - /xh/. These phonemes are difficult to distinguish by human ear even for native speaking Albanians from different regions. The task becomes more challenging for automated speech systems, recognizing and classifying Albanian words and language due to the similar sounding phonemes. This paper proposes to use Mel Frequency Cepstral Coefficients (MFCC) based features to distinguish these phonemes correctly. The three layers back propagation neural network is used for classification. The experiments are performed on speech signals that are collected from different male and female native speakers. The speaker independent tests are performed for analyzing the performance of the classification. The obtained results show that the serial MFCC features can be used to classify the very similar speech phonemes with higher accuracy.

The revenue generated from gramophone records surpassed that of ad-supported online streaming services in the United States in 2015. With the increase in popularity, a lot of old records are dug out and digitized by private audiophiles, or remastered by music labels. These old records are often scratched and damaged due to mishandling and extensive playback. This article analyses various models and algorithms than can be used to digitally refurbish the noise from gramophone records which are often perceived as crackles and pops. Different duplication approaches, trigonometric functions, polynomials, and time series models are analysed according to their signal reconstruction ability. Some novel artificial neural networks are discussed and compared to the existing models. It was found that the neural networks outperformed the other mathematical models, producing a more natural reconstruction of the audio signal with little remaining noise perceivable by the human ear.

Straipsnyje nagrinėjamas Klaipėdos garsovaizdis. Garsovaizdis suvokiamas kaip garsinė aplinka bei daugybiniai garso šaltiniai, kurie pasiekia žmogaus ausį. Gretinant skirtingus Klaipėdos garsovaizdžio kūrimo būdus, siekiama rekonstruoti ir ištirti nūdienos Klaipėdos garsinį foną. Tyrimas grindžiamas metodologine skirtimi tarp girdėjimo ir klausymo, kai pirmasis suvokiamas kaip pasyvus garso priėmimas, o antrasis – aktyvus veiksmas, apimantis tiek garsų paieškas, tiek jų interpretacijas bei analizę. Pirmame straipsnyje (Gedutis 2016) nagrinėtas miesto garsovaizdis tiek, kiek jis gali būti išgirstas. Šiame straipsnyje nagrinėjamos aktyvios pastangos išklausyti miestą. Jos apima garso teoretikų ir garso menininkų pastangas suvokti Klaipėdos miesto garsovaizdį, jo fiksavimo, konstravimo bei komunikavimo būdus. This article deals with urban soundscapes. A soundscape is a sonic environment and a multitude of sound sources that reach the human ear. By comparing different ways in which Klaipėda’s soundscape is constructed, we seek to analyze the aural background of Klaipėda. The research is based on the methodological distinction between hearing and listening. The first is a passive reception of sound, while the latter is interpreted as an activity consisting of both the search for sounds as well as their interpretation and analysis. The first article (Gedutis 2016) analyzed the Klaipėda soundscape as it can be heard. The current article concentrates on active attempts to listen to the city (or audition it), i.e., on the perception of the Klaipėda soundscape and the ways it is recorded, constructed and communicated by sound artists and theorists.

Ultrasound – Refers to sound waves with frequencies higher than 20 kHz, which is higher than the frequencies perceptible to the human ear.

To solve the multi-pose ear recognition problem under the different illumination condition, a novel method which combines phase congruency with kernel discriminant analysis (KDA) is proposed. The phase congruency of ear image is first calculated using Log-Gabor filter with 5 scales and 8 orientations, and then the phase congruency of different orientation is constructed as high dimensional vector including ample information. The high dimensional vector is mapped to kernel space to acquire discriminant feature. Experimental results show that the proposed method obtains higher recognition rate compared with the other related methods. The method of the phase congruency can eliminate the influence of illumination and phase congruency with KDA is effective to multi-pose ear recognition.

The variation of interior air pressure of high-speed train will lead to the discomfort of the human ear. In this paper, based on the four principle of modeling assumption, according to the structure of human ear and the mechanical properties of eardrum in the anatomy, the differential function model and transfer function model while the eardrum is under the action of the pressure are build in order to study the relationship between air pressure fluctuation and the comfort degree of the human ear. Under the action of the actual air pressure wave, combined with the interior air pressure comfort index, the simulation and analysis to the model are done, and then the quantitative relationship between the eardrum deformation and the comfort of human ear is built.

Spontaneous otoacoustic emissions (SOAEs) are generated by self-sustained cochlear oscillators. Properties of a computational model for a linear array of active oscillators with nearest neighbor coupling are investigated. The model can produce many experimentally well-established properties of SOAEs. (C) 2012 Acoustical Society of America. [http://dx.doi.org/10.1121/1.4730886]

The objective of this study is to explore the feasibility of using ultrasound to detect mastoid effusion (ME). In the past, ultrasound has been used to measure middle ear effusion (MEE) by injecting water into the external ear canal to measure echoes from the tympanic membrane, which is uncomfortable for the patient. It has been shown that air cells in the mastoid of patients with MEE are filled with fluid, which implies that ME could be a useful indicator of MEE. This study suggests using ultrasound to detect ME as a potentially noninvasive approach for MEE detection. In vitro experiments were performed on ten cadaver samples of the human ear. A single-element 1 MHz transducer was used to measure the mastoid of each cadaver before and after injecting water into the mastoid. The experimental results showed that the relative amplitudes of ultrasonic signals differed significantly between before (0.24 ± 0.09, mean ± standard deviation) and after (0.15 ± 0.03) the water injection (p0.05, t-test), demonstrating that the ultrasonic reflection can be used to detect ME. The location of the human mastoid under the skin behind the ear allows external measurements, and hence ultrasound-based ME detection may be an alternative, noninvasive diagnostic approach to detecting MEE in the future, providing an examination that avoids discomfort.

The design and the electric and emission characteristics of a handheld air plasma spray are presented. The plasma is generated by 60-Hz periodic discharges between two concentrically cylindrical electrodes. A ring magnet is used to rotate arc discharges, which sprays outward by an airflow. The rotation of arc discharges keeps the generated plasma in nonequilibrium state and at relatively low temperature . The plasma effluent still contains high-energy electrons which dissociate molecular oxygen into atomic oxygen. The emission spectroscopy of the plasma plume reveals that the plasma effluent, which carries abundant atomic oxygen, extends from the cap of the plasma spray about 25 mm. Using pigs as the animal model, in vivo tests of stopping wound bleeding and postoperative observation of wound healing by this air plasma spray were performed. The results show that the bleeding from a cut to an ear artery is stopped swiftly; this air plasma spray also shortens wound healing time to about half (from 14 days to 8 days) after stopping the bleeding of a cross-cut wound in the ham area.

The aim of the present research is to simulate dynamic behavior of the human auditoria peripherals during sound transmission using the equivalent six-degrees-of-freedom lumped parameter mathematical model. Transmissibility analysis was employed to get a better insight into the sound transmission from tympanic membrane to malleus, incus, stapes, and cochlea. Furthermore, transmissibility from each member to corresponding adjacent member was carried out to functional analysis of the human ear. Simulation study illustrated that the results are in agreement with the experimental results published in the literature, and the proposed model provides more information in the dynamic analysis of middle ear biomechanics.

The design and the electric and emission characteristics of two handheld air plasma spray generators are presented. The plasma is generated by 60 Hz periodic discharges between two concentrically cylindrical electrodes. A ring magnet is used to rotate arc discharges, which sprays outward by an air flow. The rotation of arc discharges keeps the generated plasma in non-equilibrium state and at relatively low temperature (

Chest percussion is a traditional technique used for the physical examination of pulmonary injuries and diseases. It is a method of tapping body parts with fingers or small instruments to evaluate the size, consistency, borders, and presence of fluid/air in the lungs and abdomen. Percussion has been successfully used for the diagnosis of such potentially lethal conditions as traumatic and tension pneumothorax. This technique, however, has certain shortcomings, including limitations of the human ear and the subjectivity of the administrator, that lead to overall low sensitivity. Automation of the method by using a standardized percussion source and computerized classification of digitized signals would remove the subjective factor and other limitations of the technique. It would also enable rapid on-site diagnostics of pulmonary traumas when thorough clinical examination is impossible. This paper lays the groundwork for an objective signal classification approach based on a general physical model of a damped harmonic oscillator. Using this concept, critical parameters that effectively subdivide percussion signals into three main groups, historically known as "tympanic," "resonant," and "dull," are identified, opening the possibility for automated diagnostics of air/liquid inclusions in the thorax and abdomen. The key role of damping in forming the character of the percussion signal is investigated using a 3D thorax phantom. The contribution of the abdominal component into the complex multimode spectrum of chest percussion signals is demonstrated.