The active sound absorption technique excels in mitigating low-frequency sound waves,yet it falls short when dealing with medium and high-frequency sound waves.To enhance the sound-absorbing effect of medium and high-...The active sound absorption technique excels in mitigating low-frequency sound waves,yet it falls short when dealing with medium and high-frequency sound waves.To enhance the sound-absorbing effect of medium and high-frequency sound waves,a novel semi-active sound absorption method has been introduced.This method modulates the surface impedance of a loudspeaker positioned behind the sound-absorbing material,thereby altering the sound absorption coefficient.The theoretical sound absorption coefficient is calculated using MATLAB and compared with the experimental one.Results show that the method can effectively modulates the absorption coefficient in response to varying incident sound wave frequencies,ensuring that it remains at its peak value.展开更多
Ultrasound computed tomography(USCT)is a noninvasive biomedical imaging modality that offers insights into acoustic properties such as the sound speed(SS)and acoustic attenuation(AA)of the human body,enhancing diagnos...Ultrasound computed tomography(USCT)is a noninvasive biomedical imaging modality that offers insights into acoustic properties such as the sound speed(SS)and acoustic attenuation(AA)of the human body,enhancing diagnostic accuracy and therapy planning.Full waveform inversion(FWI)is a promising USCT image reconstruction method that optimizes the parameter fields of a wave propagation model via gradient-based optimization.However,twodimensional FWI methods are limited by their inability to account for three-dimensional wave propagation in the elevation direction,resulting in image artifacts.To address this problem,we propose a three-dimensional time-domain full waveform inversion algorithm to reconstruct the SS and AA distributions on the basis of a fractional Laplacian wave equation,adjoint field formulation,and gradient descent optimization.Validated by two sets of simulations,the proposed algorithm has potential for generating high-resolution and quantitative SS and AA distributions.This approach holds promise for clinical USCT applications,assisting early disease detection,precise abnormality localization,and optimized treatment planning,thus contributing to better healthcare outcomes.展开更多
Objective:To explore the research landscape and hotspots of Computerized Respiratory Sound Analysis(CORSA)and provide a reference for future in-depth studies.Methods:Literature related to CORSA published up to August ...Objective:To explore the research landscape and hotspots of Computerized Respiratory Sound Analysis(CORSA)and provide a reference for future in-depth studies.Methods:Literature related to CORSA published up to August 27,2020,was retrieved from the Web of Science Core Collection.CiteSpace 5.6.R3 was used to perform co-authorship analysis,institutional collaboration analysis,keyword co-occurrence analysis,and co-citation analysis.Results:A total of 1,897 publications were included.Co-authorship analysis identified several influential contributors,including Zahra Moussavi,Kenneth Sundaraj,and H.Pasterkamp.Major research institutions included the University of Manitoba,the University of Queensland,and Aristotle University of Thessaloniki.Keyword co-occurrence analysis indicated that“respiratory sound,”“lung sound,”“asthma,”“children,”and“classification”were major research themes.The most frequently co-cited articles were published by Arati Gurung(2011),Mohammed Bahoura(2009),and H.Pasterkamp(1997).Highly cited journals included Chest,the American Journal of Respiratory and Critical Care Medicine,and IEEE Transactions on Biomedical Engineering.Conclusion:CORSA research is primarily driven by European and North American scholars and institutions,with China still in an early stage of development.Current hotspots include respiratory sound acquisition and processing,feature extraction methods such as Mel-frequency cepstral coefficients(MFCCs),and classification techniques based on machine learning and deep learning.CORSA is suitable for diverse populations and is widely applied in respiratory diseases,especially bronchial asthma.Its non-invasive nature offers particular advantages for infants and pregnant women.Although CORSA demonstrates strong clinical potential,its clinical translation remains limited.Advancing clinical applications and bridging the gap between research and practice will be key directions for future development.The prominence of top-tier respiratory and engineering journals among citations suggests that CORSA is an emerging and influential research frontier.展开更多
The emerging millimeter-wave microphones have garnered considerable attention in recent years due to their potential for sound detection in various applications,particularly in situations where traditional microphones...The emerging millimeter-wave microphones have garnered considerable attention in recent years due to their potential for sound detection in various applications,particularly in situations where traditional microphones may be impractical.However,despite their promise,there is a notable lack of evidence demonstrating high-quality sound recovery of moving sources,which remains a significant challenge in thefield.This paper addresses this critical gap by proposing a novel method for displacement alignment that improves the detection and recovery of sound signals from moving sources.The proposed method works byfirst aligning the displacement of the sound source over time,which ensures that the signals are synchronized and avoids interference from movement of sources.Subsequently,precise surface vibrations are extracted from the aligned signals,providing data for sound recovery.Afinite impulse response(FIR)filter is applied to remove low-frequency motion,which often interferes with the clarity of the detected sound.Experimental results demonstrate the method’s effectiveness in recovering high-quality sound from moving sources,offering a promising solution for advancing the emerging millimeter-wave microphone technology in real-world applications.This work could pave the way for more accurate and reliable sound detection systems,particularly in dynamic environments.展开更多
To minimize the calculation errors in the sound absorption coefficient resulting from inaccurate measurements of flow resistivity,a simple method for determining the sound absorption coefficient of soundabsorbing mate...To minimize the calculation errors in the sound absorption coefficient resulting from inaccurate measurements of flow resistivity,a simple method for determining the sound absorption coefficient of soundabsorbing materials is proposed.Firstly,the sound absorption coefficients of a fibrous sound-absorbing material are measured at two different frequencies using the impedance tube method.Secondly,utilizing the empirical formulas for the wavenumber and acoustic impedance in the fibrous material,the flow resistivity and porosity of the sound-absorbing materials are calculated using the MATLAB cycle program.Thirdly,based on the values obtained through reverse calculations,the sound absorption coefficient,the real and the imaginary parts of the acoustic impedance of the sound-absorbing material at different frequencies are theoretically computed.Finally,the accuracy of these theoretical calculations is verified through experiments.The experimental results indicate that the calculated values are basically consistent with the measured values,demonstrating the feasibility and reliability of this method.展开更多
Noise pollution is one of the common physical harmful factors in many work environments.The current study aimed to assess personal and environmental sound pressure level and project the sound-Isosonic map in one of th...Noise pollution is one of the common physical harmful factors in many work environments.The current study aimed to assess personal and environmental sound pressure level and project the sound-Isosonic map in one of the Razavi Khorasan Paste manufacture using Surfer V.14 and Noise at work V.5.0.This cross-sectional,descrip-tive study is analytical that was conducted in 2018 in the Paste factory that contains Canister,production and Brewing unit.Following ISO 9612:2009,Casella Cel-320 was used to measure personal sound pressure level,while CEL-450 sound level meter(manufactured by Casella-Cel,the UK)was employed to assess environmental sound pressure level.Statistical analyzes was done using SPSS V.18 and Linear Regression test.The sound-isosonic maps were projected using Surfer V.14 and Noise at work V.5.0.The results of assessing personal sound pressure level indicated that the highest received dose(172.21%)and personal equivalent sound level(87.36 dBA)were recorded for workers in the Canister unit.According to results of measuring of the environmental sound pressure level,out of 16 measurement stations in this unit,overall 87.5%were regarded as danger and caution areas.The lowest and highest sound pressure levels in this units were 61 dBA and 92 dBA that belong to Brewing and Canister units respectively.Results indicate Over 75%of the Canister and production units had a sound pressure level greater than 85 dBA and these two units were regarded as the most dangerous area in terms of noise pollution.It is there-fore necessary to implement noise control measures,apply hearing protection program and auditory tests among workers in these units.展开更多
Metal foams are a fascinating group of materials that possess distinct physicochEMIcal properties and interconnected strut features with high surface area-to-volume ratios, high specific strength and lightweight natur...Metal foams are a fascinating group of materials that possess distinct physicochEMIcal properties and interconnected strut features with high surface area-to-volume ratios, high specific strength and lightweight nature. These characteristics make them ideal for applications in vibration damping, heat insulation and weight reduction. In recent years, there has been increasing interest in the application of interfering energy conversion such as electromagnetic wave (EMW) and sound, where the metal foams could emerge as a solution. This paper will present a comprehensive review of the preparation methods as well as the interference energy converting mechanisms for metal foams. Typically, the progress and prospective aspects of metal foams for EMW absorption, electromagnetic interference (EMI) shielding and sound absorption have been emphasized. Through this review, we aspire to offer valuable insights for the development of multifunctional applications with metal foam materials.展开更多
The classification of respiratory sounds is crucial in diagnosing and monitoring respiratory diseases.However,auscultation is highly subjective,making it challenging to analyze respiratory sounds accurately.Although d...The classification of respiratory sounds is crucial in diagnosing and monitoring respiratory diseases.However,auscultation is highly subjective,making it challenging to analyze respiratory sounds accurately.Although deep learning has been increasingly applied to this task,most existing approaches have primarily relied on supervised learning.Since supervised learning requires large amounts of labeled data,recent studies have explored self-supervised and semi-supervised methods to overcome this limitation.However,these approaches have largely assumed a closedset setting,where the classes present in the unlabeled data are considered identical to those in the labeled data.In contrast,this study explores an open-set semi-supervised learning setting,where the unlabeled data may contain additional,unknown classes.To address this challenge,a distance-based prototype network is employed to classify respiratory sounds in an open-set setting.In the first stage,the prototype network is trained using labeled and unlabeled data to derive prototype representations of known classes.In the second stage,distances between unlabeled data and known class prototypes are computed,and samples exceeding an adaptive threshold are identified as unknown.A new prototype is then calculated for this unknown class.In the final stage,semi-supervised learning is employed to classify labeled and unlabeled data into known and unknown classes.Compared to conventional closed-set semisupervised learning approaches,the proposed method achieved an average classification accuracy improvement of 2%–5%.Additionally,in cases of data scarcity,utilizing unlabeled data further improved classification performance by 6%–8%.The findings of this study are expected to significantly enhance respiratory sound classification performance in practical clinical settings.展开更多
Passerine mimics often imitate various vocalizations from other bird species and incorporate these sounds into their song repertoires.While a few anecdotes reported that wild songbirds imitated human-associated sounds...Passerine mimics often imitate various vocalizations from other bird species and incorporate these sounds into their song repertoires.While a few anecdotes reported that wild songbirds imitated human-associated sounds,besides captive parrots and songbirds,systemic and quantitative studies on human-made sound mimicry in wild birds remain scarce.In this study,we investigated the mimetic accuracy and consistency of electric moped sounds imitated by an urban bird,the Chinese Blackbird(Turdus mandarinus).We found that:(1)Only one type of electric moped sound was imitated,i.e.,13 of 26 males mimicked the first part of the antitheft alarm,a phrase containing a series of identical notes.(2)The mimicry produced by male Chinese Blackbirds had fewer notes and lower consistency within phrases compared to the model alarms.(3)The mimicry of male Chinese Blackbirds was imperfect,i.e.,most of the acoustic parameters differed from the model alarms.Additionally,mimetic notes were lower in frequency than the models.Mimetic notes from two areas were also different in acoustic structures,suggesting Chinese Blackbirds might learn mimicry mainly from conspecific neighbors within each area respectively rather than electric mopeds,namely the secondary mimicry.Imperfect mimicry of human-made sounds could result from cost and physical constraints,associated with high consistency,frequency,and repetitions.Consequently,Chinese Blackbirds copied a simplified version of electric moped alarms.We recommend further attention to mimic species inhabiting urban ecosystems to better understand vocal mimicry's adaptation to ongoing urbanization.展开更多
A heart attack disrupts the normal flow of blood to the heart muscle,potentially causing severe damage or death if not treated promptly.It can lead to long-term health complications,reduce quality of life,and signific...A heart attack disrupts the normal flow of blood to the heart muscle,potentially causing severe damage or death if not treated promptly.It can lead to long-term health complications,reduce quality of life,and significantly impact daily activities and overall well-being.Despite the growing popularity of deep learning,several drawbacks persist,such as complexity and the limitation of single-model learning.In this paper,we introduce a residual learning-based feature fusion technique to achieve high accuracy in differentiating abnormal cardiac rhythms heart sound.Combining MobileNet with DenseNet201 for feature fusion leverages MobileNet lightweight,efficient architecture with DenseNet201,dense connections,resulting in enhanced feature extraction and improved model performance with reduced computational cost.To further enhance the fusion,we employed residual learning to optimize the hierarchical features of heart abnormal sounds during training.The experimental results demonstrate that the proposed fusion method achieved an accuracy of 95.67%on the benchmark PhysioNet-2016 Spectrogram dataset.To further validate the performance,we applied it to the BreakHis dataset with a magnification level of 100X.The results indicate that the model maintains robust performance on the second dataset,achieving an accuracy of 96.55%.it highlights its consistent performance,making it a suitable for various applications.展开更多
Large portions of the tunnel boring machine(TBM)construction cost are attributed to disc cutter consumption,and assessing the disc cutter's wear level can help determine the optimal time to replace the disc cutter...Large portions of the tunnel boring machine(TBM)construction cost are attributed to disc cutter consumption,and assessing the disc cutter's wear level can help determine the optimal time to replace the disc cutter.Therefore,the need to monitor disc cutter wear in real-time has emerged as a technical challenge for TBMs.In this study,real-time disc cutter wear monitoring is developed based on sound and vibration sensors.For this purpose,the microphone and accelerometer were used to record the sound and vibration signals of cutting three different types of rocks with varying abrasions on a laboratory scale.The relationship between disc cutter wear and the sound and vibration signal was determined by comparing the measurements of disc cutter wear with the signal plots for each sample.The features extracted from the signals showed that the sound and vibration signals are impacted by the progression of disc wear during the rock-cutting process.The signal features obtained from the rock-cutting operation were utilized to verify the machine learning techniques.The results showed that the multilayer perceptron(MLP),random subspace-based decision tree(RS-DT),DT,and random forest(RF)methods could predict the wear level of the disc cutter with an accuracy of 0.89,0.951,0.951,and 0.927,respectively.Based on the accuracy of the models and the confusion matrix,it was found that the RS-DT model has the best estimate for predicting the level of disc wear.This research has developed a method that can potentially determine when to replace a tool and assess disc wear in real-time.展开更多
Together,the heart and lung sound comprise the thoracic cavity sound,which provides informative details that reflect patient conditions,particularly heart failure(HF)patients.However,due to the limitations of human he...Together,the heart and lung sound comprise the thoracic cavity sound,which provides informative details that reflect patient conditions,particularly heart failure(HF)patients.However,due to the limitations of human hearing,a limited amount of information can be auscultated from thoracic cavity sounds.With the aid of artificial intelligence–machine learning,these features can be analyzed and aid in the care of HF patients.Machine learning of thoracic cavity sound data involves sound data pre-processing by denoising,resampling,segmentation,and normalization.Afterwards,the most crucial step is feature extraction and se-lection where relevant features are selected to train the model.The next step is classification and model performance evaluation.This review summarizes the currently available studies that utilized different machine learning models,different feature extraction and selection methods,and different classifiers to generate the desired output.Most studies have analyzed the heart sound component of thoracic cavity sound to distinguish between normal and HF patients.Additionally,some studies have aimed to classify HF patients based on thoracic cavity sounds in their entirety,while others have focused on risk strati-fication and prognostic evaluation of HF patients using thoracic cavity sounds.Overall,the results from these studies demonstrate a promisingly high level of accuracy.Therefore,future prospective studies should incorporate these machine learning models to expedite their integration into daily clinical practice for managing HF patients.展开更多
This paper delves into African America writer Octavia Butler’s Hugo-Award winning“Speech Sounds”to explore how the author uses a fictional pandemic as a metaphor to critique toxic masculinity in 1980s American cult...This paper delves into African America writer Octavia Butler’s Hugo-Award winning“Speech Sounds”to explore how the author uses a fictional pandemic as a metaphor to critique toxic masculinity in 1980s American culture.By analyzing the story,it reveals how the unnamed illness functions as a social pathogen,intensifying the negative aspects of hegemonic masculinity,leading to the breakdown of communication and the prevalence of violence.Through the character of Rye,the paper also examines how black feminist resilience offers a counter-narrative to the destructive forces of toxic masculinity.The study concludes that Butler’s work not only exposes the cultural disease of toxic masculinity but also provides a vision of healing and regeneration through communal care and the cultivation of hope,highlighting the power of speculative fiction as a tool for social critique and imagining alternative futures.展开更多
Aiming at the problem that the traditional SRP-PHAT sound source localization method performs intensive search in a 360-degree space,resulting in high computational complexity and difficulty in meeting real-time requi...Aiming at the problem that the traditional SRP-PHAT sound source localization method performs intensive search in a 360-degree space,resulting in high computational complexity and difficulty in meeting real-time requirements,an innovative high-precision sound source localization method is proposed.This method combines the selective SRP-PHAT algorithm with real-time visual analysis.Its core innovations include using face detection to dynamically determine the scanning angle range to achieve visually guided selective scanning,distinguishing face sound sources from background noise through a sound source classification mechanism,and implementing intelligent background orientation selection to ensure comprehensive monitoring of environmental noise.Experimental results show that the method achieves a positioning accuracy of±5 degrees and a processing speed of more than 10FPS in complex real environments,and its performance is significantly better than the traditional full-angle scanning method.展开更多
With the development of wireless communication,the fifth generation mobile communication technology(5G)has emerged as a hot topic in highspeed railway communication system and has moved towards industrial application....With the development of wireless communication,the fifth generation mobile communication technology(5G)has emerged as a hot topic in highspeed railway communication system and has moved towards industrial application.Investigating the radio propagation characteristics in 5G high-speed train(HST)scenarios is essential for enhancing wireless coverage and overall system performance.We propose a novel 5G passive sounding scheme to extract channel impulse responses(CIRs)using channel state information reference signals(CSI-RS)from the target 5G base station(BS).Detailed procedures for timefrequency synchronization,CSI-RS detection and extraction are presented through simulations.Through the laboratory work involving absolute power calibration,phase coherence calibration and power delay profile(PDP)validation,we validate the accuracy and performance of the developed platform.Furthermore,a measurement campaign was conducted in HST scenarios encompassing both residential and undeveloped areas.The path loss(PL)model and the channel characteristics including stationarity interval(SI),multipath components(MPCs),shadow fading(SF),Rician K-factor,root mean square(RMS)delay spread and received correlation coefficients are analyzed and fitted.The estimated channel characteristics and the statistical model presented in this paper will contribute to the research on HST radio propagation and the development of 5G railway communication systems.展开更多
As electromagnetic pollution escalates and protection demands diversify,there is an urgent requirement for versatile carbon foam materials capable of absorbing electromagnetic waves(EMWs).Furthermore,the concern about...As electromagnetic pollution escalates and protection demands diversify,there is an urgent requirement for versatile carbon foam materials capable of absorbing electromagnetic waves(EMWs).Furthermore,the concern about global warming and the depletion of petrochemical resources calls for facile and eco-friendly methods for the large-scale production of multi-functional and biodegradable carbon foams.Herein,cornstraw-derived carbon foams(CCFs)integrating EMW absorption,sound absorption,and heat insulation were prepared by a facile dual-template strategy.Benefiting from the dual-template effect of air bubbles and ice crystals,the obtained foam manifests an ultra-low density of 31 mg/cm^(3),large poros-ity of 0.85 and also super-broad absorption with an effective absorption bandwidth(EAB)of 7.18 GHz at 3.6 mm,even beyond most carbon-based composite foams.Moreover,abundant pores also endow the foam with good thermal insulation performance(as low as 0.041 W/(m K))and high sound absorp-tion coefficient(0.8 at 1250-6000 Hz),which are equivalent to commercial foams.The excellent EMW absorption performance originates from conduction loss produced by the three-dimensional(3D)inter-connected network structure and also interfacial polarization and multiple scattering induced by porous structure.Additionally,the abundant closed pores in foam prevent thermal convection and thus provide good thermal-insulation performance,yet the opening pores proffer excellent sound absorption through resonance and friction absorption.This study provides new insights into the green synthesis of multi-functional microwave absorbing foam and also supplies a new thermal-insulation material for exterior walls of buildings exposed to electromagnetic environment.展开更多
Spatio-temporal variation of sound speed,in seafloor geodetic precise positioning,can always be attributed to the time error.Firstly,this paper analyzes the existing error compensation model,i.e.,the time ratio model,...Spatio-temporal variation of sound speed,in seafloor geodetic precise positioning,can always be attributed to the time error.Firstly,this paper analyzes the existing error compensation model,i.e.,the time ratio model,which is expressed by the recorded time multiplying a ratio coefficient.And then a time split model is proposed by expressing the acoustic ray traveling time as the recorded time pluses a perturbation time error.The theoretical differences between the proposed time bias compensation model and the time ratio model are analyzed.Under the new framework,sound speed perturbation models with optimal single-layer spatial gradient and multi-layer spatial gradients are developed to compensate for sound speed error in the complex cases.Numerical computation shows that the simple time split model keeps the same accuracy as some complicated models while considering the distribution of random error.Furthermore,multi-layer model can improve the positioning accuracy without putting the pressure on parametrization.展开更多
BackgroundIt's crucial to study the effect of changes in thresholds(T)and most comfortable levels(M)on behavioral measurements in young children using cochlear implants.This would help the clinician with the optim...BackgroundIt's crucial to study the effect of changes in thresholds(T)and most comfortable levels(M)on behavioral measurements in young children using cochlear implants.This would help the clinician with the optimization and validation of programming parameters.ObjectiveThe study has attempted to describe the changes in behavioral responses with modification of T and M levels.MethodsTwenty-five participants in the age range 5 to 12 years using HR90K/HiFocus1J or HR90KAdvantage/HiFocus1J with Harmony speech processors participated in the study.A decrease in T levels,a rise in T levels,or a decrease in M levels in the everyday program were used to create experimental programs.Sound field thresholds and speech perception were measured at 50 dBHL for three experimental and everyday programs.ConclusionThe results indicated that only reductions of M levels resulted in significantly(p<0.01)poor aided thresholds and speech perception.On the other hand,variation in T levels did not have significant changes in either sound field thresholds or speech perception.The results highlight that M levels must be correctly established in order to prevent decreased speech perception and audibility.展开更多
基金National Natural Science Foundation of China(No.51705545)。
文摘The active sound absorption technique excels in mitigating low-frequency sound waves,yet it falls short when dealing with medium and high-frequency sound waves.To enhance the sound-absorbing effect of medium and high-frequency sound waves,a novel semi-active sound absorption method has been introduced.This method modulates the surface impedance of a loudspeaker positioned behind the sound-absorbing material,thereby altering the sound absorption coefficient.The theoretical sound absorption coefficient is calculated using MATLAB and compared with the experimental one.Results show that the method can effectively modulates the absorption coefficient in response to varying incident sound wave frequencies,ensuring that it remains at its peak value.
基金supported by the National Key Research and Development Program of China(2022YFA1404400)the National Natural Science Foundation of China(62122072,12174368,61705216,62405306)+4 种基金Anhui Provincial Department of Science and Technology(202203a07020020,18030801138)Anhui Provincial Natural Science Foundation(2308085QA21,2408085QF187)the USTC Research Funds of the Double First-Class Initiative(YD2090002015)the Institute of Artificial Intelligence at Hefei Comprehensive National Science Center(23YGXT005)the Fundamental Research Funds for the Central Universities(WK2090000083).
文摘Ultrasound computed tomography(USCT)is a noninvasive biomedical imaging modality that offers insights into acoustic properties such as the sound speed(SS)and acoustic attenuation(AA)of the human body,enhancing diagnostic accuracy and therapy planning.Full waveform inversion(FWI)is a promising USCT image reconstruction method that optimizes the parameter fields of a wave propagation model via gradient-based optimization.However,twodimensional FWI methods are limited by their inability to account for three-dimensional wave propagation in the elevation direction,resulting in image artifacts.To address this problem,we propose a three-dimensional time-domain full waveform inversion algorithm to reconstruct the SS and AA distributions on the basis of a fractional Laplacian wave equation,adjoint field formulation,and gradient descent optimization.Validated by two sets of simulations,the proposed algorithm has potential for generating high-resolution and quantitative SS and AA distributions.This approach holds promise for clinical USCT applications,assisting early disease detection,precise abnormality localization,and optimized treatment planning,thus contributing to better healthcare outcomes.
基金Beijing Hospitals Authority Clinical Medicine Development of Special Funding Support,Code(Project No.:YGLX202514)。
文摘Objective:To explore the research landscape and hotspots of Computerized Respiratory Sound Analysis(CORSA)and provide a reference for future in-depth studies.Methods:Literature related to CORSA published up to August 27,2020,was retrieved from the Web of Science Core Collection.CiteSpace 5.6.R3 was used to perform co-authorship analysis,institutional collaboration analysis,keyword co-occurrence analysis,and co-citation analysis.Results:A total of 1,897 publications were included.Co-authorship analysis identified several influential contributors,including Zahra Moussavi,Kenneth Sundaraj,and H.Pasterkamp.Major research institutions included the University of Manitoba,the University of Queensland,and Aristotle University of Thessaloniki.Keyword co-occurrence analysis indicated that“respiratory sound,”“lung sound,”“asthma,”“children,”and“classification”were major research themes.The most frequently co-cited articles were published by Arati Gurung(2011),Mohammed Bahoura(2009),and H.Pasterkamp(1997).Highly cited journals included Chest,the American Journal of Respiratory and Critical Care Medicine,and IEEE Transactions on Biomedical Engineering.Conclusion:CORSA research is primarily driven by European and North American scholars and institutions,with China still in an early stage of development.Current hotspots include respiratory sound acquisition and processing,feature extraction methods such as Mel-frequency cepstral coefficients(MFCCs),and classification techniques based on machine learning and deep learning.CORSA is suitable for diverse populations and is widely applied in respiratory diseases,especially bronchial asthma.Its non-invasive nature offers particular advantages for infants and pregnant women.Although CORSA demonstrates strong clinical potential,its clinical translation remains limited.Advancing clinical applications and bridging the gap between research and practice will be key directions for future development.The prominence of top-tier respiratory and engineering journals among citations suggests that CORSA is an emerging and influential research frontier.
基金supported by the National Natural Science Foundation of China under Grant No.51905341the Natural Science Foundation of Shanghai under Grant 22ZR1433900.
文摘The emerging millimeter-wave microphones have garnered considerable attention in recent years due to their potential for sound detection in various applications,particularly in situations where traditional microphones may be impractical.However,despite their promise,there is a notable lack of evidence demonstrating high-quality sound recovery of moving sources,which remains a significant challenge in thefield.This paper addresses this critical gap by proposing a novel method for displacement alignment that improves the detection and recovery of sound signals from moving sources.The proposed method works byfirst aligning the displacement of the sound source over time,which ensures that the signals are synchronized and avoids interference from movement of sources.Subsequently,precise surface vibrations are extracted from the aligned signals,providing data for sound recovery.Afinite impulse response(FIR)filter is applied to remove low-frequency motion,which often interferes with the clarity of the detected sound.Experimental results demonstrate the method’s effectiveness in recovering high-quality sound from moving sources,offering a promising solution for advancing the emerging millimeter-wave microphone technology in real-world applications.This work could pave the way for more accurate and reliable sound detection systems,particularly in dynamic environments.
基金National Natural Science Foundation of China(No.51705545)。
文摘To minimize the calculation errors in the sound absorption coefficient resulting from inaccurate measurements of flow resistivity,a simple method for determining the sound absorption coefficient of soundabsorbing materials is proposed.Firstly,the sound absorption coefficients of a fibrous sound-absorbing material are measured at two different frequencies using the impedance tube method.Secondly,utilizing the empirical formulas for the wavenumber and acoustic impedance in the fibrous material,the flow resistivity and porosity of the sound-absorbing materials are calculated using the MATLAB cycle program.Thirdly,based on the values obtained through reverse calculations,the sound absorption coefficient,the real and the imaginary parts of the acoustic impedance of the sound-absorbing material at different frequencies are theoretically computed.Finally,the accuracy of these theoretical calculations is verified through experiments.The experimental results indicate that the calculated values are basically consistent with the measured values,demonstrating the feasibility and reliability of this method.
文摘Noise pollution is one of the common physical harmful factors in many work environments.The current study aimed to assess personal and environmental sound pressure level and project the sound-Isosonic map in one of the Razavi Khorasan Paste manufacture using Surfer V.14 and Noise at work V.5.0.This cross-sectional,descrip-tive study is analytical that was conducted in 2018 in the Paste factory that contains Canister,production and Brewing unit.Following ISO 9612:2009,Casella Cel-320 was used to measure personal sound pressure level,while CEL-450 sound level meter(manufactured by Casella-Cel,the UK)was employed to assess environmental sound pressure level.Statistical analyzes was done using SPSS V.18 and Linear Regression test.The sound-isosonic maps were projected using Surfer V.14 and Noise at work V.5.0.The results of assessing personal sound pressure level indicated that the highest received dose(172.21%)and personal equivalent sound level(87.36 dBA)were recorded for workers in the Canister unit.According to results of measuring of the environmental sound pressure level,out of 16 measurement stations in this unit,overall 87.5%were regarded as danger and caution areas.The lowest and highest sound pressure levels in this units were 61 dBA and 92 dBA that belong to Brewing and Canister units respectively.Results indicate Over 75%of the Canister and production units had a sound pressure level greater than 85 dBA and these two units were regarded as the most dangerous area in terms of noise pollution.It is there-fore necessary to implement noise control measures,apply hearing protection program and auditory tests among workers in these units.
基金supported by the National Natural Science Foundation of China(No.52271180)the Leading Goose R&D Program of Zhejiang Province(2022C01110).
文摘Metal foams are a fascinating group of materials that possess distinct physicochEMIcal properties and interconnected strut features with high surface area-to-volume ratios, high specific strength and lightweight nature. These characteristics make them ideal for applications in vibration damping, heat insulation and weight reduction. In recent years, there has been increasing interest in the application of interfering energy conversion such as electromagnetic wave (EMW) and sound, where the metal foams could emerge as a solution. This paper will present a comprehensive review of the preparation methods as well as the interference energy converting mechanisms for metal foams. Typically, the progress and prospective aspects of metal foams for EMW absorption, electromagnetic interference (EMI) shielding and sound absorption have been emphasized. Through this review, we aspire to offer valuable insights for the development of multifunctional applications with metal foam materials.
基金supported by Innovative Human Resource Development for Local Intellectualization Programthrough the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(IITP-2025-RS-2022-00156360).
文摘The classification of respiratory sounds is crucial in diagnosing and monitoring respiratory diseases.However,auscultation is highly subjective,making it challenging to analyze respiratory sounds accurately.Although deep learning has been increasingly applied to this task,most existing approaches have primarily relied on supervised learning.Since supervised learning requires large amounts of labeled data,recent studies have explored self-supervised and semi-supervised methods to overcome this limitation.However,these approaches have largely assumed a closedset setting,where the classes present in the unlabeled data are considered identical to those in the labeled data.In contrast,this study explores an open-set semi-supervised learning setting,where the unlabeled data may contain additional,unknown classes.To address this challenge,a distance-based prototype network is employed to classify respiratory sounds in an open-set setting.In the first stage,the prototype network is trained using labeled and unlabeled data to derive prototype representations of known classes.In the second stage,distances between unlabeled data and known class prototypes are computed,and samples exceeding an adaptive threshold are identified as unknown.A new prototype is then calculated for this unknown class.In the final stage,semi-supervised learning is employed to classify labeled and unlabeled data into known and unknown classes.Compared to conventional closed-set semisupervised learning approaches,the proposed method achieved an average classification accuracy improvement of 2%–5%.Additionally,in cases of data scarcity,utilizing unlabeled data further improved classification performance by 6%–8%.The findings of this study are expected to significantly enhance respiratory sound classification performance in practical clinical settings.
基金supported by the National Key Research and Development Program of China(2022YFC3202104)the Western LightKey Laboratory Cooperative Research Cross-Team Project of Chinese Academy of Sciences(xbzg-zdsys-202207)。
文摘Passerine mimics often imitate various vocalizations from other bird species and incorporate these sounds into their song repertoires.While a few anecdotes reported that wild songbirds imitated human-associated sounds,besides captive parrots and songbirds,systemic and quantitative studies on human-made sound mimicry in wild birds remain scarce.In this study,we investigated the mimetic accuracy and consistency of electric moped sounds imitated by an urban bird,the Chinese Blackbird(Turdus mandarinus).We found that:(1)Only one type of electric moped sound was imitated,i.e.,13 of 26 males mimicked the first part of the antitheft alarm,a phrase containing a series of identical notes.(2)The mimicry produced by male Chinese Blackbirds had fewer notes and lower consistency within phrases compared to the model alarms.(3)The mimicry of male Chinese Blackbirds was imperfect,i.e.,most of the acoustic parameters differed from the model alarms.Additionally,mimetic notes were lower in frequency than the models.Mimetic notes from two areas were also different in acoustic structures,suggesting Chinese Blackbirds might learn mimicry mainly from conspecific neighbors within each area respectively rather than electric mopeds,namely the secondary mimicry.Imperfect mimicry of human-made sounds could result from cost and physical constraints,associated with high consistency,frequency,and repetitions.Consequently,Chinese Blackbirds copied a simplified version of electric moped alarms.We recommend further attention to mimic species inhabiting urban ecosystems to better understand vocal mimicry's adaptation to ongoing urbanization.
文摘A heart attack disrupts the normal flow of blood to the heart muscle,potentially causing severe damage or death if not treated promptly.It can lead to long-term health complications,reduce quality of life,and significantly impact daily activities and overall well-being.Despite the growing popularity of deep learning,several drawbacks persist,such as complexity and the limitation of single-model learning.In this paper,we introduce a residual learning-based feature fusion technique to achieve high accuracy in differentiating abnormal cardiac rhythms heart sound.Combining MobileNet with DenseNet201 for feature fusion leverages MobileNet lightweight,efficient architecture with DenseNet201,dense connections,resulting in enhanced feature extraction and improved model performance with reduced computational cost.To further enhance the fusion,we employed residual learning to optimize the hierarchical features of heart abnormal sounds during training.The experimental results demonstrate that the proposed fusion method achieved an accuracy of 95.67%on the benchmark PhysioNet-2016 Spectrogram dataset.To further validate the performance,we applied it to the BreakHis dataset with a magnification level of 100X.The results indicate that the model maintains robust performance on the second dataset,achieving an accuracy of 96.55%.it highlights its consistent performance,making it a suitable for various applications.
文摘Large portions of the tunnel boring machine(TBM)construction cost are attributed to disc cutter consumption,and assessing the disc cutter's wear level can help determine the optimal time to replace the disc cutter.Therefore,the need to monitor disc cutter wear in real-time has emerged as a technical challenge for TBMs.In this study,real-time disc cutter wear monitoring is developed based on sound and vibration sensors.For this purpose,the microphone and accelerometer were used to record the sound and vibration signals of cutting three different types of rocks with varying abrasions on a laboratory scale.The relationship between disc cutter wear and the sound and vibration signal was determined by comparing the measurements of disc cutter wear with the signal plots for each sample.The features extracted from the signals showed that the sound and vibration signals are impacted by the progression of disc wear during the rock-cutting process.The signal features obtained from the rock-cutting operation were utilized to verify the machine learning techniques.The results showed that the multilayer perceptron(MLP),random subspace-based decision tree(RS-DT),DT,and random forest(RF)methods could predict the wear level of the disc cutter with an accuracy of 0.89,0.951,0.951,and 0.927,respectively.Based on the accuracy of the models and the confusion matrix,it was found that the RS-DT model has the best estimate for predicting the level of disc wear.This research has developed a method that can potentially determine when to replace a tool and assess disc wear in real-time.
文摘Together,the heart and lung sound comprise the thoracic cavity sound,which provides informative details that reflect patient conditions,particularly heart failure(HF)patients.However,due to the limitations of human hearing,a limited amount of information can be auscultated from thoracic cavity sounds.With the aid of artificial intelligence–machine learning,these features can be analyzed and aid in the care of HF patients.Machine learning of thoracic cavity sound data involves sound data pre-processing by denoising,resampling,segmentation,and normalization.Afterwards,the most crucial step is feature extraction and se-lection where relevant features are selected to train the model.The next step is classification and model performance evaluation.This review summarizes the currently available studies that utilized different machine learning models,different feature extraction and selection methods,and different classifiers to generate the desired output.Most studies have analyzed the heart sound component of thoracic cavity sound to distinguish between normal and HF patients.Additionally,some studies have aimed to classify HF patients based on thoracic cavity sounds in their entirety,while others have focused on risk strati-fication and prognostic evaluation of HF patients using thoracic cavity sounds.Overall,the results from these studies demonstrate a promisingly high level of accuracy.Therefore,future prospective studies should incorporate these machine learning models to expedite their integration into daily clinical practice for managing HF patients.
基金supported by the Ministry of Education Humanities and Social Science Project,Project Title:“A Study of the Writing of Futures in Contemporary Science Fiction by African American Women”(Grant No.22YJC752010)。
文摘This paper delves into African America writer Octavia Butler’s Hugo-Award winning“Speech Sounds”to explore how the author uses a fictional pandemic as a metaphor to critique toxic masculinity in 1980s American culture.By analyzing the story,it reveals how the unnamed illness functions as a social pathogen,intensifying the negative aspects of hegemonic masculinity,leading to the breakdown of communication and the prevalence of violence.Through the character of Rye,the paper also examines how black feminist resilience offers a counter-narrative to the destructive forces of toxic masculinity.The study concludes that Butler’s work not only exposes the cultural disease of toxic masculinity but also provides a vision of healing and regeneration through communal care and the cultivation of hope,highlighting the power of speculative fiction as a tool for social critique and imagining alternative futures.
基金the research result of the 2024 Guangxi Higher Education Undergraduate Teaching Reform Project“OBE-Guided,Digitally Empowered‘Hadoop Big Data Development Technology’Course Ideological and Political Construction Innovation Exploration and Practice”(Project No.:2024JGA396).
文摘Aiming at the problem that the traditional SRP-PHAT sound source localization method performs intensive search in a 360-degree space,resulting in high computational complexity and difficulty in meeting real-time requirements,an innovative high-precision sound source localization method is proposed.This method combines the selective SRP-PHAT algorithm with real-time visual analysis.Its core innovations include using face detection to dynamically determine the scanning angle range to achieve visually guided selective scanning,distinguishing face sound sources from background noise through a sound source classification mechanism,and implementing intelligent background orientation selection to ensure comprehensive monitoring of environmental noise.Experimental results show that the method achieves a positioning accuracy of±5 degrees and a processing speed of more than 10FPS in complex real environments,and its performance is significantly better than the traditional full-angle scanning method.
基金supported by Fundamental Research Funds for the Central Universities(No.2024YJS078)the National Natural Science Foundation of China(No.62341127,62221001 and 62171021)+1 种基金the Fundamental Research Funds for the Natural Science Foundation of Jiangsu Province,Major Project(No.BK2021200)the Key Research and Development Program of Zhejiang Province(No.2023C01003)。
文摘With the development of wireless communication,the fifth generation mobile communication technology(5G)has emerged as a hot topic in highspeed railway communication system and has moved towards industrial application.Investigating the radio propagation characteristics in 5G high-speed train(HST)scenarios is essential for enhancing wireless coverage and overall system performance.We propose a novel 5G passive sounding scheme to extract channel impulse responses(CIRs)using channel state information reference signals(CSI-RS)from the target 5G base station(BS).Detailed procedures for timefrequency synchronization,CSI-RS detection and extraction are presented through simulations.Through the laboratory work involving absolute power calibration,phase coherence calibration and power delay profile(PDP)validation,we validate the accuracy and performance of the developed platform.Furthermore,a measurement campaign was conducted in HST scenarios encompassing both residential and undeveloped areas.The path loss(PL)model and the channel characteristics including stationarity interval(SI),multipath components(MPCs),shadow fading(SF),Rician K-factor,root mean square(RMS)delay spread and received correlation coefficients are analyzed and fitted.The estimated channel characteristics and the statistical model presented in this paper will contribute to the research on HST radio propagation and the development of 5G railway communication systems.
基金financially supported by the National Science Foundation of China(Nos.52362024,22004106,51872238 and 21806129)the Fundamental Research Funds for the Central Universities(Nos.3102018zy045 and 3102019AX11)+1 种基金the Shaanxi Excellent Young Talents Support Program for Universities(No.202120006)the Key Laboratory of Icing and Anti/Deicing of CARDC(IADL20220401).
文摘As electromagnetic pollution escalates and protection demands diversify,there is an urgent requirement for versatile carbon foam materials capable of absorbing electromagnetic waves(EMWs).Furthermore,the concern about global warming and the depletion of petrochemical resources calls for facile and eco-friendly methods for the large-scale production of multi-functional and biodegradable carbon foams.Herein,cornstraw-derived carbon foams(CCFs)integrating EMW absorption,sound absorption,and heat insulation were prepared by a facile dual-template strategy.Benefiting from the dual-template effect of air bubbles and ice crystals,the obtained foam manifests an ultra-low density of 31 mg/cm^(3),large poros-ity of 0.85 and also super-broad absorption with an effective absorption bandwidth(EAB)of 7.18 GHz at 3.6 mm,even beyond most carbon-based composite foams.Moreover,abundant pores also endow the foam with good thermal insulation performance(as low as 0.041 W/(m K))and high sound absorp-tion coefficient(0.8 at 1250-6000 Hz),which are equivalent to commercial foams.The excellent EMW absorption performance originates from conduction loss produced by the three-dimensional(3D)inter-connected network structure and also interfacial polarization and multiple scattering induced by porous structure.Additionally,the abundant closed pores in foam prevent thermal convection and thus provide good thermal-insulation performance,yet the opening pores proffer excellent sound absorption through resonance and friction absorption.This study provides new insights into the green synthesis of multi-functional microwave absorbing foam and also supplies a new thermal-insulation material for exterior walls of buildings exposed to electromagnetic environment.
基金The National Natural Science Foundation of China under contract No.41931076the National Center for Basic Sciences Project under contract No.42388102the Laoshan Laboratory under contract No.LSKJ202205100.
文摘Spatio-temporal variation of sound speed,in seafloor geodetic precise positioning,can always be attributed to the time error.Firstly,this paper analyzes the existing error compensation model,i.e.,the time ratio model,which is expressed by the recorded time multiplying a ratio coefficient.And then a time split model is proposed by expressing the acoustic ray traveling time as the recorded time pluses a perturbation time error.The theoretical differences between the proposed time bias compensation model and the time ratio model are analyzed.Under the new framework,sound speed perturbation models with optimal single-layer spatial gradient and multi-layer spatial gradients are developed to compensate for sound speed error in the complex cases.Numerical computation shows that the simple time split model keeps the same accuracy as some complicated models while considering the distribution of random error.Furthermore,multi-layer model can improve the positioning accuracy without putting the pressure on parametrization.
文摘BackgroundIt's crucial to study the effect of changes in thresholds(T)and most comfortable levels(M)on behavioral measurements in young children using cochlear implants.This would help the clinician with the optimization and validation of programming parameters.ObjectiveThe study has attempted to describe the changes in behavioral responses with modification of T and M levels.MethodsTwenty-five participants in the age range 5 to 12 years using HR90K/HiFocus1J or HR90KAdvantage/HiFocus1J with Harmony speech processors participated in the study.A decrease in T levels,a rise in T levels,or a decrease in M levels in the everyday program were used to create experimental programs.Sound field thresholds and speech perception were measured at 50 dBHL for three experimental and everyday programs.ConclusionThe results indicated that only reductions of M levels resulted in significantly(p<0.01)poor aided thresholds and speech perception.On the other hand,variation in T levels did not have significant changes in either sound field thresholds or speech perception.The results highlight that M levels must be correctly established in order to prevent decreased speech perception and audibility.
