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In this paper, an enhanced approach for sound localization is proposed, which fuses automatic extraction of array signal characteristic frequencies and adaptive weighting. The method refines the autoregressive power spectral estimation algorithm and improves density-based spatial clustering of applications with noise algorithm for characteristic frequency extraction. Adaptive weighting technique is introduced to alleviate the problem of frequency mismatch in the localization process. The initial weight of narrowband signals is calculated and normalized using the frequency domain amplitude integration of narrowband signals, followed by adaptive threshold correction to eliminate invalid narrowband signal weights. The adaptive weight vector improves the localization method's accuracy and interference suppression. The effectiveness and universality of the proposed method are demonstrated with test data from dry transformers and pumps, and its applicability is shown to extend to various spatial spectrum estimation algorithms and deep learning-based sound source localization techniques.

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Electroosmotic flow (EOF) is of utmost significance due to its numerous practical uses in controlling flow at micro/nanoscales. In the present study, the time-periodic EOF of a viscoelastic fluid is statistically analyzed using a short 10:1 constriction microfluidic channel joining two reservoirs on either side. The flow is modeled using the Oldroyd-B (OB) model and the Poisson-Boltzmann model. The EOF of a highly concentrated polyacrylamide (PAA) aqueous solution is investigated under the combined effects of an alternating current (AC) electric field and a direct current (DC) electric field. Power-law degradation is visible in the energy spectra of the velocity fluctuations over a wide frequency range, pointing to the presence of elastic instabilities in the EOF. The energy-spectra curves of the velocity fluctuations under a DC electric field exhibit peaks primarily beneath 20 Hz, with the greatest peak being observed close to 6 Hz. When under both DC and AC electric fields, the energy spectra of the velocity fluctuations exhibit a peak at the same frequency as the AC electric field, and the highest peak is obtained when the frequency of the AC electric field is near 6 Hz. Additionally, the frequency of the AC electric field affects how quickly the viscoelastic EOF flows. Higher flow rates are obtained at relatively low frequencies compared to under the DC electric field, and the greatest flow rate is found close to 6 Hz. But as the frequency rises further, the flow rate falls. The flow rate falls to a level below the DC electric field when the frequency is sufficiently high.

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Rolling element bearing (REB) vibration signals under variable speed (VS) have non-stationary characteristics. Order tracking (OT) and time-frequency analysis (TFA) are two widely used methods for REB fault diagnosis under VS. However, the effect of OT methods is affected by resampling errors and close-order harmonic interference, while the accuracy of TFA methods is mainly limited by time-frequency resolution and ridge extraction algorithms. To address this issue, a novel method based on envelope spectrum fault characteristic frequency band identification (FCFBI) is proposed. Firstly, the characteristics of the bearing fault vibration signal's envelope spectrum under VS are analyzed in detail and the fault characteristic frequency band (FCFB) is introduced as a new and effective representation of faults. Then, fault templates based on FCFB are constructed as reference for fault identification. Finally, based on the calculation of the correlation coefficients between the envelope spectrum and fault templates in the extended FCFB, the bearing fault can be diagnosed automatically according to the preset correlation coefficient criterion. Two bearing VS experiments indicate that the proposed method can achieve satisfactory diagnostic accuracy. The comparison of OT and TFA methods further demonstrates the comprehensive superiority of the proposed method in the overall consideration of accuracy, diagnostic time, tachometer dependency, and automatic degree.

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Online rapid detection of a fertilizer solution's type and concentration is crucial for intelligent water and fertilizer machines to realize intellectual precision variable fertilization. In this paper, a cylindrical capacitance sensor was designed based on the dielectric properties of the fertilizer solution, and an online rapid detection method of fertilizer type and concentration was proposed based on the characteristic frequency response mode. Three fertilizer solutions, potassium chloride, calcium superphosphate, and urea, were used as test objects. Ten concentrations of each fertilizer solution in the 10~100 g/L range were taken as the test fertilizer solution. Then, under the action of a series of sine wave excitation signals from 1 kHz to 10 MHz, the sensor's amplitude-frequency/phase-frequency response data were obtained. The detection strategy of 'first type, then concentration' was adopted to realize rapid online detection of fertilizer type and concentration. Experimental results indicated that the maximum relative error of the sensor stability test was 0.72%, and the maximum error of concentration detection was 7.26%. Thus, the intelligent water and fertilizer machine can give feedback on the information of a fertilizer solution in real-time during the process of precise variable fertilization, thus improving the intelligence of water and fertilizer machines.

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Objectives: Electrocochleography (ECochG) recordings during cochlear implantation have shown promise in estimating the impact on residual hearing. The purpose of the study was (1) to determine whether a 250-Hz stimulus is superior to 500-Hz in detecting residual hearing decrement and if so; (2) to evaluate whether crossing the 500-Hz tonotopic, characteristic frequency (CF) place partly explains the problems experienced using 500-Hz. Design: Multifrequency ECochG comprising an alternating, interleaved acoustic complex of 250- and 500-Hz stimuli was used to elicit cochlear microphonics (CMs) during insertion. The largest ECochG drops (≥30% reduction in CM) were identified. After insertion, ECochG responses were measured using the individual electrodes along the array for both 250- and 500-Hz stimuli. Univariate regression was used to predict whether 250- or 500-Hz CM drops explained low-frequency pure tone average (LFPTA; 125-, 250-, and 500-Hz) shift at 1-month post-activation. Postoperative CT scans were performed to evaluate cochlear size and angular insertion depth. Results: For perimodiolar insertions (N = 34), there was a stronger linear correlation between the largest ECochG drop using 250-Hz stimulus and LFPTA shift (r = 0.58), compared to 500-Hz (r = 0.31). The 250- and 500-Hz CM insertion tracings showed an amplitude peak at two different locations, with the 500-Hz peak occurring earlier in most cases than the 250-Hz peak, consistent with tonotopicity. When using the entire array for recordings after insertion, a maximum 500-Hz response was observed 2-6 electrodes basal to the most-apical electrode in 20 cases (58.9%). For insertions where the apical insertion angle is >350 degrees and the cochlear diameter is <9.5 mm, the maximum 500-Hz ECochG response may occur at the non-apical most electrode. For lateral wall insertions (N = 14), the maximum 250- and 500-Hz CM response occurred at the most-apical electrode in all but one case. Conclusion: Using 250-Hz stimulus for ECochG feedback during implantation is more predictive of hearing preservation than 500-Hz. This is due to the electrode passing the 500-Hz CF during insertion which may be misidentified as intracochlear trauma; this is particularly important in subjects with smaller cochlear diameters and deeper insertions. Multifrequency ECochG can be used to differentiate between trauma and advancement of the apical electrode beyond the CF.

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Mass characteristic frequency (fmass) is a novel shear wave (SW) parameter that represents the ratio of the averaged minimum SW speed within the regions of interest to the largest dimension of the mass. Our study objective was to evaluate if the addition of fmass to conventional 2-D shear wave elastography (SWE) parameters would improve the differentiation of benign from malignant thyroid nodules. Our cohort comprised 107 patients with 113 thyroid nodules, of which 67 (59%) were malignant. Two-dimensional SWE data were obtained using the Supersonic Imagine Aixplorer ultrasound system equipped with a 44- to 15-MHz15-MHz linear array transducer. A receiver operating characteristic curve was generated based on a multivariable logistic regression analysis to evaluate the ability of SWE parameters with/without fmass and with/without clinical factors to discriminate benign from malignant thyroid nodules. The addition of fmass to conventional SW elasticity parameters increased the area under the curve from 0.808 to 0.871 (p = 0.02). The combination of SW elasticity parameters plus fmass plus clinical factors provided the strongest thyroid nodule malignancy probability estimate, with a sensitivity of 93.4% and specificity of 91.1% at the optimal threshold. In summary, fmass can be a valuable addition to conventional 2-D SWE parameters.

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The purpose of this study was to determine if segmental bioelectrical impedance spectroscopy characteristic frequency (fc) and phase angle (Pa) were reflective of differences in quadriceps muscle size and quality, respectively, in normal weight and obese older men, and to assess the impact of hydration status on these measurements. Forty-one healthy older men volunteered for this study and were recruited by age (65-74 years) and two body mass index groups: normal weight and obese. Participants visited the laboratory on one occasion where they underwent a hydration status assessment via urine specific gravity, a percent body fat assessment via dual-energy X-ray absorptiometry, a segmental bioelectrical impedance spectroscopy thigh assessment to determine fc and Pa, and resting ultrasonography to assess superficial quadriceps cross-sectional area and echo intensity as a proxy for muscle quality. Urine specific gravity was not different between the groups (P = 0.116); however, echo intensity, cross-sectional area, and percent body fat were greater in the obese group (P < 0.001), and both fc and Pa were greater in the normal weight group (P < 0.001). Larger muscle cross-sectional area was associated with lower fc (r = -0.597, P < 0.001), but was not associated with Pa (P = 0.469). Poorer muscle quality (higher echo intensity) was associated with lower Pa (r = -0.765, P < 0.001), but not associated with fc (P = 0.244). There was no association between fc and Pa (P = 0.449). All group differences and associations remained unchanged after controlling for urine specific gravity. Segmental bioelectrical impedance spectroscopy may offer an inexpensive, time efficient, and portable assessment of quadriceps muscle size and quality in older men.

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The amplitudes of the first Shapiro steps for an external signal with frequencies of 72 and 265 GHz are measured as function of the temperature from 20 to 80 K for a 6 µm Josephson grain boundary junction fabricated by YBaCuO film deposition on an yttria-stabilized zirconia bicrystal substrate. Non-monotonic dependences of step heights for different external signal frequencies were found in the limit of a weak driving signal, with the maxima occurring at different points as function of the temperature. The step heights are in agreement with the calculations based on the resistively-capacitively shunted junction model and Bessel theory. The emergence of the receiving optima is explained by the mutual influence of the varying critical current and the characteristic frequency.

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BACKGROUND: Lead is a nonessential heavy metal, which can inhibit heme synthesis and has significant cytotoxic effects. Nevertheless, its effect on the electrical properties of red blood cells (RBCs) remains unclear. Consequently, this study aimed to investigate the electrical properties and the electrophysiological mechanism of lead exposure in mouse blood using Electrical Impedance Spectroscopy (EIS) in 0.01-100 MHz frequency range. Data characteristic of the impedance spectrum, Bodes plot, Nyquist plot and Nichols plot, and Constant Phase Element (CPE) equivalent circuit model were used to explicitly analyze the differences in amplitude-frequency, phase-frequency, and the frequency characteristics of blood in electrical impedance properties. RESULTS: Compared with the healthy blood in control mice, the changes in blood exposed to lead were as follows: (i) the hematocrit decreased; (ii) the amplitude-frequency and phase-frequency characteristics of electrical impedance decreased; (iii) the characteristic frequencies (f0) were significantly increased; (iv) the electrical impedance of plasma, erythrocyte membrane, and hemoglobin decreased, while the conductivity increased. (v) The pseudo-capacitance of cell membrane (CPE_Tm) and the intracellular pseudo-capacitance (CPE-Ti) were decreased. CONCLUSIONS: Therefore, EIS can be used as an effective method to monitor blood and RBC abnormalities caused by lead exposure. The electrical properties of the cells can be applied as an important observation in the evaluation of the toxic effects of heavy metals.

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This purpose of this study is to correlate a new shear-wave elastography (SWE) parameter, mass characteristic frequency (fmass) and other elasticity measure with the prognostic histological factors and immunohistochemical (IHC) biomarkers for the evaluation of heterogeneous breast carcinomas. The new parameter, fmass, first introduced in this paper, is defined as the ratio of the averaged minimum shear wave speed taken spatially within regions of interest to the largest mass dimension. 264 biopsy-proven breast cancerous masses were included in this study. Mean (Emean), maximum (Emax), minimum (Emin) shear wave elasticity and standard deviation (Esd) of shear wave elasticity were found significantly correlated with tumor size, axillary lymph node (ALN) status, histological subtypes and IHC subtypes. The areas under the curve for the ALN prediction are 0.73 (95% confidence interval [CI]: 0.67-0.80) and 0.75 (95% CI: 0.69-0.81) for the combination of Emean with Breast Imaging Reporting and Data System (BI-RADS) score and Emax with BI-RADS score, respectively. fmass was significantly correlated with the presence of calcifications, ALN status, histological grade, the expressions of IHC biomarkers and IHC subtypes. To conclude, poor prognostic factors were associated with high shear wave elasticity values and low mass characteristic frequency value. Therefore, SWE provides valuable information that may help with prediction of breast cancer invasiveness.

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BACKGROUND: Early prediction of tumor response to neoadjuvant chemotherapy (NACT) is crucial for optimal treatment and improved outcome in breast cancer patients. The purpose of this study is to investigate the role of shear wave elastography (SWE) for early assessment of response to NACT in patients with invasive breast cancer. METHODS: In a prospective study, 62 patients with biopsy-proven invasive breast cancer were enrolled. Three SWE studies were conducted on each patient: before, at mid-course, and after NACT but before surgery. A new parameter, mass characteristic frequency (fmass), along with SWE measurements and mass size was obtained from each SWE study visit. The clinical biomarkers were acquired from the pre-NACT core-needle biopsy. The efficacy of different models, generated with the leave-one-out cross-validation, in predicting response to NACT was shown by the area under the receiver operating characteristic curve and the corresponding sensitivity and specificity. RESULTS: A significant difference was found for SWE parameters measured before, at mid-course, and after NACT between the responders and non-responders. The combination of Emean2 and mass size (s2) gave an AUC of 0.75 (0.95 CI 0.62-0.88). For the ER+ tumors, the combination of Emean_ratio1, s1, and Ki-67 index gave an improved AUC of 0.84 (0.95 CI 0.65-0.96). For responders, fmass was significantly higher during the third visit. CONCLUSIONS: Our study findings highlight the value of SWE estimation in the mid-course of NACT for the early prediction of treatment response. For ER+ tumors, the addition of Ki-67improves the predictive power of SWE. Moreover, fmass is presented as a new marker in predicting the endpoint of NACT in responders.

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Compared with standard-ply composites, thin-ply composites exhibit a superior mechanical performance under various operating conditions due to their positive size effects. Thin-ply laminate failure modes, including matrix initial damage (MID), matrix failure (MF), and fiber failure (FF), have been distinguished through a systematic acoustic emission (AE) signals analysis combined with scanning electron microscopy (SEM). First, the characteristic frequencies of various failure modes are identified based on unidirectional laminates ([90] 68 and [0] 68). Then, according to the identified frequencies corresponding to distinctive damage modes, four lay-up sequences (02[[90m/0m]ns]02, m = 1, 2, 4, 8, n × m = 16) with a constant total thickness are designed, and the effects of the number of identical plies in the laminate thickness on the damage evolution characteristics and the damage process under uniaxial tension loads are dynamically monitored. The obtained results indicate that the characteristic frequency ranges for MID, MF, and FF are identified as 0-85 kHz, 165-260 kHz, and 261-304 kHz, respectively. The thickness of identical plies has a significant effect on onset damage. With the decrease of the number of identical plies (i.e., m in the stacking sequences), the thin-ply laminates exhibit the initiation of damage suppression effects and crack propagation resistance.

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BACKGROUND: Citizen monitoring programs using acoustic data have been useful for detecting population and community patterns. However, they have rarely been used to study broad scale patterns of species traits. We assessed the potential of acoustic data to detect broad scale patterns in body size. We compared geographical patterns in body size with acoustic signals in the bat species Pipistrellus pipistrellus. Given the correlation between body size and acoustic characteristics, we expected to see similar results when analyzing the relationships of body size and acoustic signals with climatic variables. METHODS: We assessed body size using forearm length measurements of 1,359 bats, captured by mist nets in France. For acoustic analyses, we used an extensive dataset collected through the French citizen bat survey. We isolated each bat echolocation call (n = 4,783) and performed automatic measures of signals, including the frequency of the flattest part of the calls (characteristic frequency). We then examined the relationship between forearm length, characteristic frequencies, and two components resulting from principal component analysis for geographic (latitude, longitude) and climatic variables. RESULTS: Forearm length was positively correlated with higher precipitation, lower seasonality, and lower temperatures. Lower characteristic frequencies (i.e., larger body size) were mostly related to lower temperatures and northern latitudes. While conducted on different datasets, the two analyses provided congruent results. DISCUSSION: Acoustic data from citizen science programs can thus be useful for the detection of large-scale patterns in body size. This first analysis offers a new perspective for the use of large acoustic databases to explore biological patterns and to address both theoretical and applied questions.

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Tuning the stiffness balance is crucial to full-band common-mode rejection for a superconducting gravity gradiometer (SGG). A reliable method to do so has been proposed and experimentally tested. In the tuning scheme, the frequency response functions of the displacement of individual test mass upon common-mode accelerations were measured and thus determined a characteristic frequency for each test mass. A reduced difference in characteristic frequencies between the two test masses was utilized as the criterion for an effective tuning. Since the measurement of the characteristic frequencies does not depend on the scale factors of displacement detection, stiffness tuning can be done independently. We have tested this new method on a single-component SGG and obtained a reduction of two orders of magnitude in stiffness mismatch.

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Rotor is a widely used and easily defected mechanical component. Thus, it is significant to develop effective techniques for rotor fault diagnosis. Fault signature extraction and state classification of the extracted signatures are two key steps for diagnosing rotor faults. To complete the accurate recognition of rotor states, a novel evaluation index named characteristic frequency band energy entropy (CFBEE) was proposed to extract the defective features of rotors, and support vector machine (SVM) was employed to automatically identify the rotor fault types. Specifically, the raw vibration signal of rotor was first analyzed by a joint time-frequency method based on improved singular spectrum decomposition (ISSD) and Hilbert transform (HT) to derive its time-frequency spectrum (TFS), which is named ISSD-HT TFS in this paper. Then, the CFBEE of the ISSD-HT TFS was calculated as the fault feature vector. Finally, SVM was used to complete the automatic identification of rotor faults. Simulated processing results indicate that ISSD improves the end effects of singular spectrum decomposition (SSD) and is superior to empirical mode decomposition (EMD) in extracting the sub-components of rotor vibration signal. The ISSD-HT TFS can more accurately reflect the time-frequency information compared to the EMD-HT TFS. Experimental verification demonstrates that the proposed method can accurately identify rotor defect types and outperform some other methods.

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Presbyacusis reflects dysfunctions present along the central auditory pathway. Given that the topographic representation of the auditory directional spatial map is deteriorated in the superior colliculus of aged animals, therefore, are spectral and temporal auditory processes altered with aging in the rat's superior colliculus? Extracellular single-unit recordings were conducted in the superior colliculus of anesthetized Sprague-Dawley adult (10 months) and aged (22 months) rats. In the spectral domain, level thresholds in aged rats were significantly increased when superior colliculus auditory neurons were stimulated with pure tones or Gaussian noise bursts. The sharpness of the frequency response tuning curve at 10 dB SPL above threshold was also significantly broader among the aged rats. Furthermore, in the temporal domain, the minimal silent gap thresholds to Gaussian noises were significantly longer in aged rats. Hence, these results highlight that spectral and temporal auditory processing in the superior colliculus are impaired during aging.

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Over the last decade industrial manufacturing of viral vaccines and viral vectors for prophylactic and therapeutic applications is experiencing a remarkable growth. Currently, the quality attributes of viral derived products are assessed only at the end-point of the production process, essentially because in-process monitoring tools are not available or not implemented at industrial scale. However, to demonstrate process reproducibility and robustness, manufacturers are strongly advised by regulatory agencies to adopt more on-line process monitoring and control. Dielectric spectroscopy has been successfully used as an excellent indicator of the cell culture state in mammalian and yeast cell systems. We previously reported the use of this technique for monitoring influenza and lentiviral productions in HEK293 cell cultures. For both viruses, multi-frequency capacitance measurements allowed not only the on-line monitoring of the production kinetics, but also the identification of the viral release time from the cells. The present study demonstrates that the same approach can be successfully exploited for the on-line monitoring of different enveloped and non-enveloped virus production kinetics in cell culture processes. The on-line monitoring multi-frequency capacitance method was assessed in human HEK293 and Sf9 insect cells expression systems, with viral productions initiated by either infection or transfection. The comparative analyses of all the data acquired indicate that the characteristic capacitance signals were highly correlated with the occurrence of viral replication phases. Furthermore the evolution of the cell dielectric properties (intracellular conductivity and membrane capacitance) were indicative of each main replication steps. In conclusion, multi-frequency capacitance has a great potential for on-line monitoring, supervision and control of viral vector production in cell culture processes.

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Medial olivocochlear (MOC) neurons provide an efferent innervation to outer hair cells (OHCs) of the cochlea, but their tonotopic mapping is incompletely known. In the present study of anesthetized guinea pigs, the MOC mapping was investigated using in vivo, extracellular recording, and labeling at a site along the cochlear course of the axons. The MOC axons enter the cochlea at its base and spiral apically, successively turning out to innervate OHCs according to their characteristic frequencies (CFs). Recordings made at a site in the cochlear basal turn yielded a distribution of MOC CFs with an upper limit, or "edge," due to usually absent higher-CF axons that presumably innervate more basal locations. The CFs at the edge, normalized across preparations, were equal to the CFs of the auditory nerve fibers (ANFs) at the recording sites (near 16 kHz). Corresponding anatomical data from extracellular injections showed spiraling MOC axons giving rise to an edge of labeling at the position of a narrow band of labeled ANFs. Overall, the edges of the MOC CFs and labeling, with their correspondences to ANFs, suggest similar tonotopic mappings of these efferent and afferent fibers, at least in the cochlear basal turn. They also suggest that MOC axons miss much of the position of the more basally located cochlear amplifier appropriate for their CF; instead, the MOC innervation may be optimized for protection from damage by acoustic overstimulation.

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Because roller element bearings (REBs) failures cause unexpected machinery breakdowns, their fault diagnosis has attracted considerable research attention. Established fault feature extraction methods focus on statistical characteristics of the vibration signal, which is an approach that loses sight of the continuous waveform features. Considering this weakness, this article proposes a novel feature extraction method for frequency bands, named Window Marginal Spectrum Clustering (WMSC) to select salient features from the marginal spectrum of vibration signals by Hilbert-Huang Transform (HHT). In WMSC, a sliding window is used to divide an entire HHT marginal spectrum (HMS) into window spectrums, following which Rand Index (RI) criterion of clustering method is used to evaluate each window. The windows returning higher RI values are selected to construct characteristic frequency bands (CFBs). Next, a hybrid REBs fault diagnosis is constructed, termed by its elements, HHT-WMSC-SVM (support vector machines). The effectiveness of HHT-WMSC-SVM is validated by running series of experiments on REBs defect datasets from the Bearing Data Center of Case Western Reserve University (CWRU). The said test results evidence three major advantages of the novel method. First, the fault classification accuracy of the HHT-WMSC-SVM model is higher than that of HHT-SVM and ST-SVM, which is a method that combines statistical characteristics with SVM. Second, with Gauss white noise added to the original REBs defect dataset, the HHT-WMSC-SVM model maintains high classification accuracy, while the classification accuracy of ST-SVM and HHT-SVM models are significantly reduced. Third, fault classification accuracy by HHT-WMSC-SVM can exceed 95% under a Pmin range of 500-800 and a m range of 50-300 for REBs defect dataset, adding Gauss white noise at Signal Noise Ratio (SNR) = 5. Experimental results indicate that the proposed WMSC method yields a high REBs fault classification accuracy and a good performance in Gauss white noise reduction.

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Ultrasonic diagnosis that is convenient and nondestructive to the human body is widely used in medicine. In clinical, ultrasonic backscattered signals characteristics are utilized to acquire information of the human body tissues to perform diagnosis. In this paper, an adaptive ultrasonic backscattered signal processing technique for instantaneous characteristic frequency detection based on the marginal spectrum is presented. In the beginning, the ultrasonic backscattered signal is decomposed into a series of intrinsic mode functions (IMFs) by the Ensemble Empirical Mode Decomposition (EEMD) algorithm. Then the Hilbert spectrum is gained by the Hilbert transform on the IMFs decomposed and screened. Finally, the time-frequency information in the Hilbert spectrum is utilized to extract the instantaneous characteristic frequency based on the marginal spectrum features to detect the objective. With this technique, the spacing between tissues can be estimated for tissue characterization by processing multiple echoes even in the complicated environment. In the simulation study, comparing with the FFT, the technique presented shows its strong noise immunity and indicates its validity in instantaneous characteristic frequency detection.

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