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Journal articles on the topic 'Waveform similarity analysis'
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Havrlík, Matouš, Martin Libra, Vladislav Poulek, and Pavel Kouřím. "Analysis of Output Signal Distortion of Galvanic Isolation Circuits for Monitoring the Mains Voltage Waveform." Sensors 22, no. 20 (October 13, 2022): 7769. http://dx.doi.org/10.3390/s22207769.
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Different methods for galvanically isolated monitoring of the mains voltage waveform were evaluated. The aim was to determine the level of distortion of the output signal relative to the input signal and the suitability of each method for calculating active power values. Six fixtures were tested: two voltage transformers, an electronic circuit with a current transformer, a standalone current transformer, a simple circuit with optocouplers, and a circuit with an A/D-D/A converter with capacitive coupling. The input and output waveforms were mathematically analyzed by three methods: (1) calculating the spectral components of waveforms and the relative changes in their THD (total harmonic distortion) values, (2) determining the similarity of waveforms according to the size of the area bounded by the input and output waveform curves, and (3) determining the accuracy of the active power calculation based on the output waveform. The time difference in the zero crossing of the input and output signals was measured, and further calculations for the second and third method were performed on the zero-crossing time shift-corrected waveforms. Other aspects of selecting the appropriate type of monitoring element, such as power consumption or overall circuit complexity, were also evaluated.
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LIU, Tong-tong, Min DAI, and Zhong-yi LI. "ECG waveform similarity analysis based on window-slope representation." Journal of Computer Applications 32, no. 10 (May 23, 2013): 2969–72. http://dx.doi.org/10.3724/sp.j.1087.2012.02969.
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Iosa, M., A. Cereatti, A. Merlo, I. Campanini, S. Paolucci, and A. Cappozzo. "Assessment of Waveform Similarity in Clinical Gait Data: The Linear Fit Method." BioMed Research International 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/214156.
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The assessment of waveform similarity is a crucial issue in gait analysis for the comparison of kinematic or kinetic patterns with reference data. A typical scenario is in fact the comparison of a patient’s gait pattern with a relevant physiological pattern. This study aims to propose and validate a simple method for the assessment of waveform similarity in terms of shape, amplitude, and offset. The method relies on the interpretation of these three parameters, obtained through a linear fit applied to the two data sets under comparison plotted one against the other after time normalization. The validity of this linear fit method was tested in terms of appropriateness (comparing real gait data of 34 patients with cerebrovascular accident with those of 15 healthy subjects), reliability, sensitivity, and specificity (applying a cluster analysis on the real data). Results showed for this method good appropriateness, 94.1% of sensitivity, 93.3% of specificity, and good reliability. The LFM resulted in a simple method suitable for analysing the waveform similarity in clinical gait analysis.
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A. Khalil, Mohamed. "Groundwater Classification by Using Fourier Analysis." Global Journal of Earth Science and Engineering 9 (August 22, 2022): 65–73. http://dx.doi.org/10.15377/2409-5710.2022.09.5.
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The article illustrates a statistical technique for the visual representation of geochemical data. Quaternary and Pre-Quaternary groundwater samples from Northern Sinai Peninsula, Egypt, were interpreted statistically using Andrews plots, which use Fourier analysis to transform and represent a set of multivariate data by a waveform pattern. The resulting waveform patterns were classified into low, middle, and high amplitudes, following up the increase in the total dissolved solids of the samples. Comparison with the traditional hydrochemical polygonal Stiff diagrams resulted in a complete matching. The proposed mixing between the Quaternary and Pre-Quaternary aquifers has been proved via the similarity of waveform patterns of the mixed water. The application of Andrews plots is investigated by comparison with the Stiff conventional diagrams. The correlation between different amplitudes and the TDS value of every sample indicates that the amplitude increases with the increase in the salinity.
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Zheng, Tao, Xinhui Yang, Xingchao Guo, Xingguo Wang, and Chengqi Zhang. "Zero-Sequence Differential Current Protection Scheme for Converter Transformer Based on Waveform Correlation Analysis." Energies 13, no. 7 (April 9, 2020): 1814. http://dx.doi.org/10.3390/en13071814.
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Through the analysis of the recovery inrush current generated by the external fault removal of the converter transformer, it is pointed out that the zero-sequence current caused by the recovery inrush may result in the saturation of the neutral current transformer (CT), whose measurement distortion contributes to the mis-operation of zero-sequence differential current protection. In this paper, a new scheme of zero-sequence differential current protection based on waveform correlation is proposed. By analyzing the characteristics of zero-sequence current under internal fault, external fault and external fault removal, the waveform correlation of the zero-sequence current measured at the terminal of the transformer and the zero-sequence current measured at the neutral point of the transformer is used for identification. The polarity of the CT is selected to guarantee the zero-sequence currents at the terminal and neutral point of the transformer exhibit a "ride through" characteristic under external fault, then the waveform similarity is high, and the correlation coefficient is positive. On the other hand, when internal fault occurs, zero-sequence current waveforms on both sides differ from each other largely, and the correlation coefficient is negative. Through a large number of simulations verified by PSCAD/EMTDC, this criterion can accurately identify internal and external faults, exempt from effects of the recovery inrush. Moreover, it presents certain ability for CT anti-saturation.
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Lukovenkova, Olga, and Alexandra Solodchuk. "Analysis of geoacoustic emission and electromagnetic radiation signals accompanying earthquake with magnitude Mw = 7.5." E3S Web of Conferences 196 (2020): 03001. http://dx.doi.org/10.1051/e3sconf/202019603001.
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The paper is devoted to the analysis of frequency spectra and pulse waveform variety of the geoacoustic and electromagnetic signals recorded on Kamchatka Peninsula at “Karymshina” site during seismically calm and active periods. Signal pre-processing includes pulse detection and their waveforms reconstruction. A frequency spectrum is analyzed using the Adaptive Matching Pursuit algorithm. To study a variety of waveforms, each pulse is encoded by a special descriptive matrix. Then pulse classification based on similarity of the descriptive matrices is performed. Thus, a signal alphabet is formed. The authors analyzed the geophysical signals recorded before, during and after the earthquake with the magnitude Mw = 7.5 dated March 25, 2020. The obtained estimates of frequency spectra and signal alphabets are compared with the analysis results of signal recoded during the seismically calm period of March 22, 2020.
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Petersen, G. M., P. Niemz, S. Cesca, V. Mouslopoulou, and G. M. Bocchini. "Clusty, the waveform-based network similarity clustering toolbox: concept and application to image complex faulting offshore Zakynthos (Greece)." Geophysical Journal International 224, no. 3 (November 25, 2020): 2044–59. http://dx.doi.org/10.1093/gji/ggaa568.
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SUMMARY Clusty is a new open source toolbox dedicated to earthquake clustering based on waveforms recorded across a network of seismic stations. Its main application is the study of active faults and the detection and characterization of faults and fault networks. By using a density-based clustering approach, earthquakes pertaining to a common fault can be recognized even over long fault segments, and the first-order geometry and extent of active faults can be inferred. Clusty implements multiple techniques to compute a waveform based network similarity from maximum cross-correlation coefficients at multiple stations. The clustering procedure is designed to be transparent and parameters can be easily tuned. It is supported by a number of analysis visualization tools which help to assess the homogeneity within each cluster and the differences among distinct clusters. The toolbox returns graphical representations of the results. A list of representative events and stacked waveforms facilitate further analyses like moment tensor inversion. Results obtained in various frequency bands can be combined to account for large magnitude ranges. Thanks to the simple configuration, the toolbox is easily adaptable to new data sets and to large magnitude ranges. To show the potential of our new toolbox, we apply Clusty to the aftershock sequence of the Mw 6.9 25 October 2018 Zakynthos (Greece) Earthquake. Thanks to the complex tectonic setting at the western termination of the Hellenic Subduction System where multiple faults and faulting styles operate simultaneously, the Zakynthos data set provides an ideal case-study for our clustering analysis toolbox. Our results support the activation of several faults and provide insight into the geometry of faults or fault segments. We identify two large thrust faulting clusters in the vicinity of the main shock and multiple strike-slip clusters to the east, west and south of these clusters. Despite its location within the largest thrust cluster, the main shock does not show a high waveform similarity to any of the clusters. This is consistent with the results of other studies suggesting a complex failure mechanism for the main shock. We propose the existence of conjugated strike-slip faults in the south of the study area. Our waveform similarity based clustering toolbox is able to reveal distinct event clusters which cannot be discriminated based on locations and/or timing only. Additionally, the clustering results allows distinction between fault and auxiliary planes of focal mechanisms and to associate them to known active faults.
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Tang, Junlei, Junyang Li, Hu Wang, Yingying Wang, and Geng Chen. "In-Situ Monitoring and Analysis of the Pitting Corrosion of Carbon Steel by Acoustic Emission." Applied Sciences 9, no. 4 (February 18, 2019): 706. http://dx.doi.org/10.3390/app9040706.
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The acoustic emission (AE) technique was applied to monitor the pitting corrosion of carbon steel in NaHCO3 + NaCl solutions. The open circuit potential (OCP) measurement and corrosion morphology in-situ capturing using an optical microscope were conducted during AE monitoring. The corrosion micromorphology was characterized with a scanning electron microscope (SEM). The propagation behavior and AE features of natural pitting on carbon steel were investigated. After completion of the signal processing, including pre-treatment, shape preserving interpolation, and denoising, for raw AE waveforms, three types of AE signals were classified in the correlation diagrams of the new waveform parameters. Finally, a 2D pattern recognition method was established to calculate the similarity of different continuous AE graphics, which is quite effective to distinguish the localized corrosion from uniform corrosion.
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Jeon, Jeong Woo, and Jiheon Hong. "Comparison of screw-home mechanism in the unloaded living knee subjected to active and passive movements." Journal of Back and Musculoskeletal Rehabilitation 34, no. 4 (July 13, 2021): 589–95. http://dx.doi.org/10.3233/bmr-200110.
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BACKGROUND: The screw-home mechanism (SHM) plays an important role in the stability of the knee. Accordingly, the analysis of tibial rotation patterns can be used to elucidate the effect of SHM-related factors. OBJECTIVE: The purpose of this study was to compare the magnitude of the angle and the pattern of SHM between passive and active movements. METHODS: We studied twenty healthy males, of which the angle of knee flexion-extension and tibial longitudinal rotation (TLR) during active and passive movements were measured using the inertial measurement unit. Student’s t-tests were used to compare the magnitude of TLR. The waveform similarity was quantified using a coefficient of multiple correlation (CMC). RESULTS: Significant differences were found in the TLR between the active and passive movements (p< 0.05). The knee flexion-extension waveform similarity was excellent (CMC = 0.956). However, the waveform similarity of TLR was weak (CMC = 0.629). CONCLUSION: The SHM increased abruptly during the last 20∘ of the active (extension) movement compared with passive extension. The SHM occurred mainly owing to the geometry and shape of the articular surfaces of the knee joint. In addition, muscle contraction was considered to be an important factor in the articulation movement.
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Grund, Michael, Jörn C. Groos, and Joachim R. R. Ritter. "Fault Reactivation Analysis Using Microearthquake Clustering Based on Signal-to-Noise Weighted Waveform Similarity." Pure and Applied Geophysics 173, no. 7 (April 2, 2016): 2325–55. http://dx.doi.org/10.1007/s00024-016-1281-4.
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Feng, Shang, Haifeng Li, Lin Ma, and Zhongliang Xu. "An EEG Feature Extraction Method Based on Sparse Dictionary Self-Organizing Map for Event-Related Potential Recognition." Algorithms 13, no. 10 (October 13, 2020): 259. http://dx.doi.org/10.3390/a13100259.
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In the application of the brain-computer interface, feature extraction is an important part of Electroencephalography (EEG) signal classification. Using sparse modeling to extract EEG signal features is a common approach. However, the features extracted by common sparse decomposition methods are only of analytical meaning, and cannot relate to actual EEG waveforms, especially event-related potential waveforms. In this article, we propose a feature extraction method based on a self-organizing map of sparse dictionary atoms, which can aggregate event-related potential waveforms scattered inside an over-complete sparse dictionary into the code book of neurons in the self-organizing map network. Then, the cosine similarity between the EEG signal sample and the code vector is used as the classification feature. Compared with traditional feature extraction methods based on sparse decomposition, the classification features obtained by this method have more intuitive electrophysiological meaning. The experiment conducted on a public auditory event-related potential (ERP) brain-computer interface dataset showed that, after the self-organized mapping of dictionary atoms, the neurons’ code vectors in the self-organized mapping network were remarkably similar to the ERP waveform obtained after superposition and averaging. The feature extracted by the proposed method used a smaller amount of data to obtain classification accuracy comparable to the traditional method.
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Bermúdez-Barrios, Juan Carlos, and Hiroyuki Kumagai. "Repeating Earthquakes Along the Colombian Subduction Zone." Journal of Disaster Research 15, no. 5 (August 1, 2020): 645–54. http://dx.doi.org/10.20965/jdr.2020.p0645.
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Colombia is tectonically active, and several large earthquakes have ruptured the Colombia-Ecuador subduction zone (CESZ) during the last century. Among them, the Colombia-Ecuador earthquake in 1906 (Mw 8.4) and the Tumaco earthquake in 1979 (Mw 8.3) generated destructive tsunamis. Therefore, it is important to characterize the seismic rupture processes and their relation with interplate coupling along the CESZ. We searched for repeating earthquakes by performing waveform similarity analysis. Cross correlation (CC) values were computed between earthquake pairs with hypocenter differences of less than 50 km that were located in the northern CESZ (1°–4°N) and that occurred from June 1993 to February 2018. We used broadband and short-period seismic waveform data from the Servicio Geológico Colombiano (SGC) seismic network. A CC threshold value of 0.90 was used to identify the waveform similarity and select repeating earthquakes. We found repeating earthquakes distributed near the trench and the coast. Our estimated repeating earthquakes near the trench suggest that the interplate coupling in this region is low. This is in clear constrast to the occurrence of a large slip in the 1906 Colombia-Ecuador earthquake along the trench in the southern part of the CESZ, and suggests that rupture modes are different between the northern and southern parts of CESZ near the trench.
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Massa, M., G. Ferretti, D. Spallarossa, and C. Eva. "Improving automatic location procedure by waveform similarity analysis: An application in the South Western Alps (Italy)." Physics of the Earth and Planetary Interiors 154, no. 1 (January 2006): 18–29. http://dx.doi.org/10.1016/j.pepi.2005.07.003.
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ADJI, A., K. HIRATA, S. HOEGLER, and M. OROURKE. "Noninvasive Pulse Waveform Analysis in Clinical Trials: Similarity of Two Methods for Calculating Aortic Systolic Pressure." American Journal of Hypertension 20, no. 8 (August 2007): 917–22. http://dx.doi.org/10.1016/j.amjhyper.2007.03.006.
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Smugala, Dariusz, Pawel Ptak, and Michal Bonk. "Simulation Analysis of LED Stripes Drivers’ Influence on Electric Energy Quality." Energies 15, no. 10 (May 19, 2022): 3733. http://dx.doi.org/10.3390/en15103733.
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This paper presents a comparative simulation study of the operation of various types of drivers dedicated for use in light-emitting diode (LED)-based light stripes. The study comprises an experimentally verified simulation in view of their influence on harmonic content generation and impact on electric energy quality. The simulation models were optimized in order to precisely reflect the currents and voltage waveforms recorded in the frame of laboratory measurements. The simulation parameters were adjusted in view of harmonic generation analysis and high-frequency (HF) transient presence resulting from circuit principles of operation. Two driver circuit types were analyzed in the framework of the study—a voltage stabilization circuit based on a Zener diode, and a current stabilization integrated circuit (IC) based on an AL8806 chip. The study results entail an analysis executed for light stripes comprising various numbers of LEDs connected to each driver and various numbers of each of the tested drivers equipped with the same number of LEDs used as load. Based on the simulation, THD factors, harmonic components spectrum, waveform factors, power factors analysis and HF transient parameters were determined. The obtained simulations results are characterized by a high level of similarity in relation to results gained by means of measurements.
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Zhang, Xinmei. "Music Waveform Analysis Based on SOM Neural Network and Big Data." Computational Intelligence and Neuroscience 2021 (September 3, 2021): 1–11. http://dx.doi.org/10.1155/2021/9714988.
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Music is an indispensable part of our life and study and is one of the most important forms of multimedia applications. With the development of deep learning and neural network in recent years, how to use cutting-edge technology to study and apply music has become a research hotspot. Music waveform is not only the main form of music frequency but also the basis of music feature extraction. This paper first designs a method of note extraction based on the fast Fourier transform principle of the audio signal packet route under the self-organizing map (SOM neural network) which can accurately extract the musical features of the note, such as amplitude, loudness, period, and so on. Secondly, the audio segments are divided into summary by adding window moving matching method, and the music features such as amplitude, loudness, and period of each bar are obtained according to the performance of audio signal in each bar. Finally, according to the similarity of the audio music theory of the adjacent summary of each bar, the audio segments are divided, and the music features of each segment are obtained. The traditional recurrent neural network (RNN) is improved, and the SOM neural network is used to recognize the audio emotion features. The final experimental results show that the proposed method based on SOM neural network and big data can effectively extract and analyze music waveform features. Compared with previous studies, this paper creatively proposed a new algorithm, which can more accurately and quickly extract and analyze the data sound waveform, and used SOM neural network to analyze the emotion model contained in music for the first time.
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Potas, Jason Robert, Newton Gonçalves de Castro, Ted Maddess, and Marcio Nogueira de Souza. "Waveform Similarity Analysis: A Simple Template Comparing Approach for Detecting and Quantifying Noisy Evoked Compound Action Potentials." PLOS ONE 10, no. 9 (September 1, 2015): e0136992. http://dx.doi.org/10.1371/journal.pone.0136992.
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Bai, Tong, Ilya Tsvankin, and Xinming Wu. "Waveform inversion for attenuation estimation in anisotropic media." GEOPHYSICS 82, no. 4 (July 1, 2017): WA83—WA93. http://dx.doi.org/10.1190/geo2016-0596.1.
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Robust estimation of attenuation coefficients remains a challenging problem, especially for heterogeneous anisotropic media. Here, we apply waveform inversion (WI) to perform attenuation analysis in heterogeneous VTI (transversely isotropic with a vertical symmetry axis) media. A time-domain finite-difference algorithm based on the standard linear solid model simulates nearly constant quality-factor values in a specified frequency band. We employ the adjoint-state method to derive the gradients of the objective function based on the Born approximation. Four parameters describing the attenuation coefficients of P- and SV-waves are updated simultaneously with a quasi-Newton optimization algorithm. To remove the time shifts between the modeled and observed data caused by velocity errors, we apply a local similarity technique. The inversion still requires a sufficiently accurate velocity model to minimize the trade-off between the contributions of velocity and attenuation to amplitudes. The inversion algorithm is tested on homogeneous background models with a Gaussian anomaly in one of the attenuation parameters and on a realistic heterogeneous VTI medium.
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IHRKE, MATTHIAS, HECKE SCHROBSDORFF, and J. MICHAEL HERRMANN. "RECURRENCE-BASED ESTIMATION OF TIME-DISTORTION FUNCTIONS FOR ERP WAVEFORM RECONSTRUCTION." International Journal of Neural Systems 21, no. 01 (February 2011): 65–78. http://dx.doi.org/10.1142/s0129065711002651.
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We introduce an approach to compensate for temporal distortions of repeated measurements in event-related potential research. The algorithm uses a combination of methods from nonlinear time-series analysis and is based on the construction of pairwise registration functions from cross-recurrence plots of the phase-space representations of ERP signals. The globally optimal multiple-alignment path is approximated by hierarchical cluster analysis, i.e. by iteratively combining pairs of trials according to similarity. By the inclusion of context information in form of externally acquired time markers (e.g. reaction time) into a regularization scheme, the extracted warping functions can be guided near paths that are implied by the experimental procedure. All parameters occurring in the algorithm can be optimized based on the properties of the data and there is a broad regime of parameter configurations where the algorithm produces good results. Simulations on artificial data and the analysis of ERPs from a psychophysical study demonstrate the robustness and applicability of the algorithm.
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Shuai, Zhenyu, Anqi Dong, Haoyang Liu, and Yixiong Cui. "Reliability and Validity of an Inertial Measurement System to Quantify Lower Extremity Joint Angle in Functional Movements." Sensors 22, no. 3 (January 23, 2022): 863. http://dx.doi.org/10.3390/s22030863.
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The purpose of this research was to determine if the commercially available Perception Neuron motion capture system was valid and reliable in clinically relevant lower limb functional tasks. Twenty healthy participants performed two sessions on different days: gait, squat, single-leg squat, side lunge, forward lunge, and counter-movement jump. Seven IMUs and an OptiTrack system were used to record the three-dimensional joint kinematics of the lower extremity. To evaluate the performance, the multiple correlation coefficient (CMC) and the root mean square error (RMSE) of the waveforms as well as the difference and intraclass correlation coefficient (ICC) of discrete parameters were calculated. In all tasks, the CMC revealed fair to excellent waveform similarity (0.47–0.99) and the RMSE was between 3.57° and 13.14°. The difference between discrete parameters was lower than 14.54°. The repeatability analysis of waveforms showed that the CMC was between 0.54 and 0.95 and the RMSE was less than 5° in the frontal and transverse planes. The ICC of all joint angles in the IMU was general to excellent (0.57–1). Our findings showed that the IMU system might be utilized to evaluate lower extremity 3D joint kinematics in functional motions.
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Sinclair, Jonathan, Paul John Taylor, and Sarah Jane Hobbs. "Digital Filtering of Three-Dimensional Lower Extremity Kinematics: an Assessment." Journal of Human Kinetics 39, no. 1 (December 1, 2013): 25–36. http://dx.doi.org/10.2478/hukin-2013-0065.
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Abstract Errors in kinematic data are referred to as noise and are an undesirable portion of any waveform. Noise is typically removed using a low-pass filter which removes the high frequency components of the signal. The selection of an optimal frequency cut-off is very important when processing kinematic information and a number of techniques exists for the determination of an optimal frequency cut-off. Despite the importance of cut-off frequency to the efficacy of kinematic analyses there is currently a paucity of research examining the influence of different cut-off frequencies on the resultant 3-D kinematic waveforms and discrete parameters. Twenty participants ran at 4.0 m•s-1 as lower extremity kinematics in the sagittal, coronal and transverse planes were measured using an eight camera motion analysis system. The data were filtered at a range of cut-off frequencies and the discrete kinematic parameters were examined using repeated measures ANOVA’s. The similarity between the raw and filtered waveforms were examined using intra-class correlations. The results show that the cut-off frequency has a significant influence on the discrete kinematic measure across displacement and derivative information in all three planes of rotation. Furthermore, it was also revealed that as the cut-off frequency decreased the attenuation of the kinematic waveforms became more pronounced, particularly in the coronal and transverse planes at the second derivative. In conclusion, this investigation provides new information regarding the influence of digital filtering on lower extremity kinematics and re-emphasizes the importance of selecting the correct cut-off frequency.
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Wen, Cheng, Chih-Hung Huang, and Ming-Feng Yeh. "GRAY RELATIONAL ALGORITHM FOR ECG PATTERN RECOGNITION." Biomedical Engineering: Applications, Basis and Communications 19, no. 05 (October 2007): 313–21. http://dx.doi.org/10.4015/s1016237207000410.
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The paper proposes a gray relational analysis based learning algorithm, called gray relational algorithm, for the recognition of ECG beats. Without analyzing relations between the input ECG beat and every beat in the database for the recognition, several training beats are chosen for learning from an ECG waveform database with patient diagnosis information, and then the learning result is used to analyze the test ECGs. The resulting similarity measurement is further identified as the diagnosis of the test ECG. This algorithm is capable of reducing the computational procedure of gray relational analysis as it is directly used for the analysis. The experiment shows that the proposed method can achieve a good classification result.
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Massa, M. "Selection of Empirical Green's Functions by Waveform Similarity Analysis: An Approach to Predict Ground Motion in Areas with Saturated Records." Bulletin of the Seismological Society of America 100, no. 4 (July 27, 2010): 1513–27. http://dx.doi.org/10.1785/0120090296.
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Fischer, T., and J. Michálek. "Post 2000-swarm microearthquake activity in the principal focal zone of West Bohemia/Vogtland: Space-time distribution and waveform similarity analysis." Studia Geophysica et Geodaetica 52, no. 4 (October 2008): 493–512. http://dx.doi.org/10.1007/s11200-008-0034-y.
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Figueiredo, Joana, Simão P. Carvalho, João Paulo Vilas-Boas, Luís M. Gonçalves, Juan C. Moreno, and Cristina P. Santos. "Wearable Inertial Sensor System towards Daily Human Kinematic Gait Analysis: Benchmarking Analysis to MVN BIOMECH." Sensors 20, no. 8 (April 12, 2020): 2185. http://dx.doi.org/10.3390/s20082185.
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This paper presents a cost- and time-effective wearable inertial sensor system, the InertialLAB. It includes gyroscopes and accelerometers for the real-time monitoring of 3D-angular velocity and 3D-acceleration of up to six lower limbs and trunk segment and sagittal joint angle up to six joints. InertialLAB followed an open architecture with a low computational load to be executed by wearable processing units up to 200 Hz for fostering kinematic gait data to third-party systems, advancing similar commercial systems. For joint angle estimation, we developed a trigonometric method based on the segments’ orientation previously computed by fusion-based methods. The validation covered healthy gait patterns in varying speed and terrain (flat, ramp, and stairs) and including turns, extending the experiments approached in the literature. The benchmarking analysis to MVN BIOMECH reported that InertialLAB provides more reliable measures in stairs than in flat terrain and ramp. The joint angle time-series of InertialLAB showed good waveform similarity (>0.898) with MVN BIOMECH, resulting in high reliability and excellent validity. User-independent neural network regression models successfully minimized the drift errors observed in InertialLAB’s joint angles (NRMSE < 0.092). Further, users ranked InertialLAB as good in terms of usability. InertialLAB shows promise for daily kinematic gait analysis and real-time kinematic feedback for wearable third-party systems.
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Fang, Lei, Min Fang, and Min-min Guo. "Study on Force Mechanism for Therapeutic Effect of Pushing Manipulation with One-Finger Meditation Base on Similarity Analysis of Force and Waveform." Chinese Journal of Integrative Medicine 24, no. 7 (December 27, 2016): 531–36. http://dx.doi.org/10.1007/s11655-016-2275-x.
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Zakharov, S. M. "SPECTRAL ESTIMATES OF CORRELATIONS OF ELECTROCARDIOGRAM SIGNALS, ARTERIAL PRESSURE AND PLETHYSMOGRAMS." Issues of radio electronics, no. 1 (January 20, 2019): 64–71. http://dx.doi.org/10.21778/2218-5453-2019-1-64-71.
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Spectral analysis of simultaneously recorded signals of electrocardiograms, arterial pressure and plethysmograms is considered. Spectrograms are analyzed for ten-second and minute time records. There is a similarity of data, which allows us to talk about the temporal correlation of the initial characteristics. The same applies to the spectral representation of all signals. Correlation of spectra looks better for signals of blood pressure (BP) and PG than for ECG and BP (ECG and PG), while the phenomenon of ordering (disordering) of the spectrum as a whole plays an important role. The initial data was taken from the international database Mimic 2.3 Waveform Database Part 1/31 of the PhisioBank ATM system, and all calculations were performed using the Maple package.
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Gao, Dengliang. "Wavelet spectral probe for seismic structure interpretation and fracture characterization: A workflow with case studies." GEOPHYSICS 78, no. 5 (September 1, 2013): O57—O67. http://dx.doi.org/10.1190/geo2012-0427.1.
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Conventional amplitude images are routinely and often exclusively used to interpret subsurface structures; however, the amplitude images are composite seismic response to various geologic features at different scales. The interference makes it difficult to investigate structural details that are not visually discernible in the amplitude images. This paper presents a new algorithmic workflow to unravel seismic structural details by differentiating waveform characteristics at varying scales. Using a wavelet model as a spectral probe, the algorithm performs a least-squares linear regression between the model and data at each sample location to calculate the absolute correlation coefficient. The resulting absolute correlation coefficient attribute, which is indicative of instantaneous waveform similarity relative to the wavelet spectral probe, provides a superior image with enhanced precision and resolution of the structural grain. Two case studies in the Powder River and the Appalachian Basins demonstrate that the new algorithm helps investigate kinematic relationships among structural elements and differentiate between structural styles. In particular, the algorithm helps better define the along-strike structural variation and segmentation associated with cross-strike lineaments in the foreland basins. Comparative analysis indicates that the wavelet spectral probe algorithm helps shed new light on subtle but critical structural fabrics not easily discernible from conventional amplitude images. Revealing such information has important implications for better defining basin structural complexities and reservoir heterogeneity, detecting faults and fractures at different scales, and modeling fractured reservoirs.
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Hu, Yong, Liguo Han, Rushan Wu, and Yongzhong Xu. "Multi-scale time-frequency domain full waveform inversion with a weighted local correlation-phase misfit function." Journal of Geophysics and Engineering 16, no. 6 (September 9, 2019): 1017–31. http://dx.doi.org/10.1093/jge/gxz062.
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Abstract Full Waveform Inversion (FWI) is based on the least squares algorithm to minimize the difference between the synthetic and observed data, which is a promising technique for high-resolution velocity inversion. However, the FWI method is characterized by strong model dependence, because the ultra-low-frequency components in the field seismic data are usually not available. In this work, to reduce the model dependence of the FWI method, we introduce a Weighted Local Correlation-phase based FWI method (WLCFWI), which emphasizes the correlation phase between the synthetic and observed data in the time-frequency domain. The local correlation-phase misfit function combines the advantages of phase and normalized correlation function, and has an enormous potential for reducing the model dependence and improving FWI results. Besides, in the correlation-phase misfit function, the amplitude information is treated as a weighting factor, which emphasizes the phase similarity between synthetic and observed data. Numerical examples and the analysis of the misfit function show that the WLCFWI method has a strong ability to reduce model dependence, even if the seismic data are devoid of low-frequency components and contain strong Gaussian noise.
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Zhao, Xiaoming, Qiang Tuo, Ruosi Guo, and Tengteng Kong. "Research on Music Signal Processing Based on a Blind Source Separation Algorithm." Annals of Emerging Technologies in Computing 6, no. 4 (October 1, 2022): 24–30. http://dx.doi.org/10.33166/aetic.2022.04.003.
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The isolation of mixed music signals is beneficial to the extraction and identification of music signal features and to enhance music signal quality. This paper briefly introduced the mathematical model for separating blind source from mixed music signals and the traditional Independent Component Analysis (ICA) algorithm. The separation algorithm was optimized by the complex neural network. The traditional and optimized ICA algorithms were simulated in MATLAB software. It was found that the time-domain waveform of the signal isolated by the improved ICA-based separation algorithm was closer to the source signal. The similarity coefficient matrix, signal-to-interference ratio, performance index, and iteration time of the improved ICA-based algorithm was 62.3, 0.0011, and 0.87 s, respectively, which were all superior to the traditional ICA algorithm. The novelty of this paper is setting the initial iterative matrix of the ICA algorithm with the complex neural network.
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Taylor, Steven R., John T. Rambo, and Robert P. Swift. "Near-source effects on regional seismograms: An analysis of the NTS explosions PERA and QUESO." Bulletin of the Seismological Society of America 81, no. 6 (December 1, 1991): 2371–94. http://dx.doi.org/10.1785/bssa0810062371.
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Abstract A comparative analysis of two closely spaced Nevada Test Site explosions, PERA and QUESO, is made to study the effects of near-source phenomena on regional-wave excitation. Although the two explosions were of similar size, burial depth, and only separated by 4 km, the 1 to 2 and 6 to 8 Hz regional-wave spectral ratio for QUESO is anomalously low (a factor of 10 smaller than that of PERA). Examination of the regional and close-in spectra for each event shows a remarkable similarity and suggests that QUESO has less low-frequency and more high-frequency energy than PERA. These observations may be caused by a 564 m3, funnel-shaped region filled with unconsolidated sand and a possible void directly above the QUESO detonation point. Close-in observations suggest that this region may have partially decoupled the up-going energy from QUESO, resulting in a reduction of the low-frequency energy. The high-frequency enhancement for QUESO may be due to the rapid loss of energy to nonlinear effects such as greater pore collapse and fracturing in the anomalous region. This resulted in the radiation of more impulsive, shorter-duration waveforms producing a higher corner frequency and less-rapid high-frequency spectral decay for QUESO. For PERA, the loss of energy to a two-wave system occurred more slowly and over a larger volume, resulting in a broader source pulse typical of explosions in porous materials. Comparison of shock radius versus time data suggests that the shock wave was strongly affected in the anomalous zone a few meters above the QUESO device. One-dimensional finite-difference calculations with and without a partial decoupling region within 8 m of the device are consistent with the observations. Although spallation was reduced for QUESO, simulations using a finite spall model indicate that the spall spectral peak should be centered at about 3 to 7 Hz and probably did not significantly contribute to the reduced spectral ratio. The remarkable similarity of the PERA/QUESO spectral ratios taken at distances of 90 m and 400 km suggests that the spectral characteristics of explosions are established in close proximity to the source. Although depth-dependent effects of attenuation acting at small strains may enhance the differences in spectral ratios between NTS explosions and western U.S. earthquakes, these effects are probably secondary to the high-pressure, high strain-rate dynamic material response to the radiated explosion shock wave. These observations point out the importance of up-going energy on the generation of regional phases from explosions. Because of reduced overburden pressures above the detonation point, large nonlinear deformations predominate in this region and appear to affect all of the signals except perhaps the very initial part of the Pn waveform.
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Shearer, Peter M. "Evidence from a cluster of small earthquakes for a fault at 18 km depth beneath Oak Ridge, southern California." Bulletin of the Seismological Society of America 88, no. 6 (December 1, 1998): 1327–36. http://dx.doi.org/10.1785/bssa0880061327.
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Abstract A swarm of about 50 small earthquakes (M ∼ 1.5) occurred for a month during 1989 beneath Oak Ridge, southern California. Location accuracy using conventional analysis of arrival-time picks is limited for these events by the weak, emergent nature of arrivals on the available seismograms. However, waveform cross-correlation techniques are found to provide precise relative event locations due to the similarity of the waveforms recorded at individual stations. The relocated events form a small cluster about 1 km across at a depth of ∼ 18 km and are aligned along a plane that dips 35° to the northwest. Estimated standard errors for the locations are generally less than 50 m. The time evolution of the sequence shows a gradual migration of activity away from its initiation point. Three additional events occurred several months later; these align along the same plane but are displaced about 500 m to the southeast from the main swarm. Reliable fault-plane solutions are difficult to obtain for these events due to the small number of station records available, the limited range of takeoff angles, and the weak initial arrivals on many of the seismograms. Stacking the records at each station over the different events greatly reduces prearrival noise levels and assists in resolving the average P first motions. Analysis of these first-motion data indicates that the slip planes of probable focal mechanisms are not in agreement with the plane defined by the seismicity. The seismicity alignment may represent the extension of the Simi fault, in which case some shallowing of the fault dip would be required to match the observed 35° dip at 18 km.
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Vlasic, František, Josef Volák, Libor Nohál, Pavel Mazal, and Filip Hort. "Study of Initial Stages of Fatigue Process Using Non-Destructive Testing Methods." Key Engineering Materials 592-593 (November 2013): 553–56. http://dx.doi.org/10.4028/www.scientific.net/kem.592-593.553.
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This paper deals with the basic research of cyclic damage during the initial stages of fatigue process using the non-destructive testing methods. The acoustic emission method was used for monitoring of the microstructure changes during fatigue loading. The electrical potential measurements of specimen and microscopic observation were used mainly to detect the first short cracks and their propagation. The fatigue tests at room temperature were conducted on titanium alloy and creep-resistant steel specimens under bending and tension loading. The aim of the study was to compare the acoustic emission signal at different types of loading until fracture and to analyze in detail the signal changes in initial stages of fatigue process. This analysis was primarily based on the waveform similarity and division into classes. The results show the high sensitivity of the acoustic emission technology in the transition from the stage of surface relief evolution to the stage of crack nucleation and propagation.
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Moriya, Hirokazu. "Phase-only correlation of time-varying spectral representations of microseismic data for identification of similar seismic events." GEOPHYSICS 76, no. 6 (November 2011): WC37—WC45. http://dx.doi.org/10.1190/geo2011-0021.1.
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Identification of similar seismic events is important for precise estimation of source locations and for evaluation of subsurface structure. Phase-only correlation is well known as a real-time image-matching method for fingerprint identification. I applied the phase-only correlation in a geophysical context to identify similar waveforms among microseismic events. The waveforms were first transformed into time-varying spectral representations to express frequency content in the time-frequency domain. The phase-only correlation function is calculated between two time-varying spectral representations and similarity is evaluated using the peak value of the phase-only correlation function. This method was applied to arbitrarily selected waveforms from aftershocks of an earthquake in Japan to assess its ability to identify similar waveforms perturbed by white noise. The detection of similarity of the proposed algorithm was compared to the similarity as detected by a 2D crosscorrelation function of the time-varying spectral representation and a 1D crosscorrelation of the raw waveform. This showed that the phase-only correlation function exhibits a sharp peak that quantifies similarity and dissimilarity over a wide range of signal-to-noise ratio (S/N) and remained unaffected by the length of the time window used to estimate time-varying spectral representations. Phase-only correlation may also have applications in other geophysical analyses and interpretations that are based on waveform and seismic image data.
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Lythgoe, Karen, Aidan Loasby, Dannie Hidayat, and Shengji Wei. "Seismic event detection in urban Singapore using a nodal array and frequency domain array detector: earthquakes, blasts and thunderquakes." Geophysical Journal International 226, no. 3 (April 6, 2021): 1542–57. http://dx.doi.org/10.1093/gji/ggab135.
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SUMMARY Detection of seismic events at or below the noise level is enabled by the use of dense arrays of receivers and corresponding advances in data analysis methods. It is not only important to detect tectonic events, but also events from man-made, non-earthquake sources and events that originate from coupling between the solid Earth and the atmosphere. In urban environments with high ambient noise levels the effectiveness of event detection methods is unclear, particularly when deployment restrictions result in an irregular receiver array geometry. Here, we deploy a dense nodal array for 1 month in the highly populated city state of Singapore. We develop a new detection method based on image processing that we call spectrogram stacking, which detects anomalous, coherent spectral energy across the array. It simultaneously detects multiple classes of signal with differing spectral content and aids event classification, so it is particularly useful for signal exploration when signal characteristics are unknown. Our approach detects more local events compared to the traditional short-term average over long-term average and waveform similarity methods, while all methods detect similar numbers of teleseismic and regional earthquakes. Local events are principally man-made non-earthquake sources, with several events from the same location exhibiting repeating waveforms. The closest earthquake occurs in peninsular Malaysia, in an area where no earthquakes have previously been detected. We also detect ground motion over a wide frequency range from discrete thunder events that show complex coupling between acoustic and elastic wavefield propagation. We suggest that care should be taken deciphering local high-frequency tectonic events in areas prone to thunder storms.
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Zhou, Guang-Quan, Yi Zhang, Ruo-Li Wang, Ping Zhou, Yong-Ping Zheng, Olga Tarassova, Anton Arndt, and Qiang Chen. "Automatic Myotendinous Junction Tracking in Ultrasound Images with Phase-Based Segmentation." BioMed Research International 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/3697835.
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Displacement of the myotendinous junction (MTJ) obtained by ultrasound imaging is crucial to quantify the interactive length changes of muscles and tendons for understanding the mechanics and pathological conditions of the muscle-tendon unit during motion. However, the lack of a reliable automatic measurement method restricts its application in human motion analysis. This paper presents an automated measurement of MTJ displacement using prior knowledge on tendinous tissues and MTJ, precluding the influence of nontendinous components on the estimation of MTJ displacement. It is based on the perception of tendinous features from musculoskeletal ultrasound images using Radon transform and thresholding methods, with information about the symmetric measures obtained from phase congruency. The displacement of MTJ is achieved by tracking manually marked points on tendinous tissues with the Lucas-Kanade optical flow algorithm applied over the segmented MTJ region. The performance of this method was evaluated on ultrasound images of the gastrocnemius obtained from 10 healthy subjects (26.0±2.9 years of age). Waveform similarity between the manual and automatic measurements was assessed by calculating the overall similarity with the coefficient of multiple correlation (CMC). In vivo experiments demonstrated that MTJ tracking with the proposed method (CMC = 0.97±0.02) was more consistent with the manual measurements than existing optical flow tracking methods (CMC = 0.79±0.11). This study demonstrated that the proposed method was robust to the interference of nontendinous components, resulting in a more reliable measurement of MTJ displacement, which may facilitate further research and applications related to the architectural change of muscles and tendons.
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Cornilleau-Wehrlin, N., H. St Alleyne, K. H. Yearby, B. de la Porte de Vaux, A. Meyer, O. Santolík, M. Parrot, et al. "The STAFF-DWP wave instrument on the DSP equatorial spacecraft: description and first results." Annales Geophysicae 23, no. 8 (November 8, 2005): 2785–801. http://dx.doi.org/10.5194/angeo-23-2785-2005.
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Abstract. The STAFF-DWP wave instrument on board the equatorial spacecraft (TC1) of the Double Star Project consists of a combination of 2 instruments which are a heritage of the Cluster mission: the Spatio-Temporal Analysis of Field Fluctuations (STAFF) experiment and the Digital Wave-Processing experiment (DWP). On DSP-TC1 STAFF consists of a three-axis search coil magnetometer, used to measure magnetic fluctuations at frequencies up to 4 kHz and a waveform unit, up to 10 Hz, plus snapshots up to 180 Hz. DWP provides several onboard analysis tools: a complex FFT to fully characterise electromagnetic waves in the frequency range 10 Hz-4 kHz, a particle correlator linked to the PEACE electron experiment, and compression of the STAFF waveform data. The complementary Cluster and TC1 orbits, together with the similarity of the instruments, permits new multi-point studies. The first results show the capabilities of the experiment, with examples in the different regions of the magnetosphere-solar wind system that have been encountered by DSP-TC1 at the beginning of its operational phase. An overview of the different kinds of electromagnetic waves observed on the dayside from perigee to apogee is given, including the different whistler mode waves (hiss, chorus, lion roars) and broad-band ULF emissions. The polarisation and propagation characteristics of intense waves in the vicinity of a bow shock crossing are analysed using the dedicated PRASSADCO tool, giving results compatible with previous studies: the broad-band ULF waves consist of a superimposition of different wave modes, whereas the magnetosheath lion roars are right-handed and propagate close to the magnetic field. An example of a combined Cluster DSP-TC1 magnetopause crossing is given. This first case study shows that the ULF wave power intensity is higher at low latitude (DSP) than at high latitude (Cluster). On the nightside in the tail, a first wave event comparison - in a rather quiet time interval - is shown. It opens the doors to future studies, such as event timing during substorms, to possibly determine their onset location.
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Mancuso, Marco, Valerio Sveva, Alessandro Cruciani, Katlyn Brown, Jaime Ibáñez, Vishal Rawji, Elias Casula, et al. "Transcranial Evoked Potentials Can Be Reliably Recorded with Active Electrodes." Brain Sciences 11, no. 2 (January 22, 2021): 145. http://dx.doi.org/10.3390/brainsci11020145.
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Electroencephalographic (EEG) signals evoked by transcranial magnetic stimulation (TMS) are usually recorded with passive electrodes (PE). Active electrode (AE) systems have recently become widely available; compared to PE, they allow for easier electrode preparation and a higher-quality signal, due to the preamplification at the electrode stage, which reduces electrical line noise. The performance between the AE and PE can differ, especially with fast EEG voltage changes, which can easily occur with TMS-EEG; however, a systematic comparison in the TMS-EEG setting has not been made. Therefore, we recorded TMS-evoked EEG potentials (TEPs) in a group of healthy subjects in two sessions, one using PE and the other using AE. We stimulated the left primary motor cortex and right medial prefrontal cortex and used two different approaches to remove early TMS artefacts, Independent Component Analysis and Signal Space Projection—Source Informed Recovery. We assessed statistical differences in amplitude and topography of TEPs, and their similarity, by means of the concordance correlation coefficient (CCC). We also tested the capability of each system to approximate the final TEP waveform with a reduced number of trials. The results showed that TEPs recorded with AE and PE do not differ in amplitude and topography, and only few electrodes showed a lower-than-expected CCC between the two methods of amplification. We conclude that AE are a viable solution for TMS-EEG recording.
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King, S. M., and R. S. Patel-King. "Identification of a Ca(2+)-binding light chain within Chlamydomonas outer arm dynein." Journal of Cell Science 108, no. 12 (December 1, 1995): 3757–64. http://dx.doi.org/10.1242/jcs.108.12.3757.
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We describe here the molecular cloning of the M(r) 18,000 dynein light chain from the outer arm of Chlamydomonas flagella. In vivo, this molecule is directly associated with the gamma dynein heavy chain. Sequence analysis indicates that this light chain is a novel member of the calmodulin superfamily of Ca2+ binding regulatory proteins; this molecule is 42, 37 and 36% identical to calmodulin, centrin/caltractin and troponin C, respectively, and also shows significant similarity to myosin light chains. Although four helix-loop-helix elements are evident, only two conform precisely to the EF hand consensus and are therefore predicted to bind Ca2+ in vivo. In vitro Ca2+ binding studies indicate that this dynein light chain (expressed as a C-terminal fusion with maltose binding protein) has at least one functional Ca2+ binding site with an apparent affinity for Ca2+ of approximately 3 × 10(−5) M. Within the Chlamydomonas flagellum, the transition from an assymmetric to a symmetric waveform (which implies an alteration in dynein activity) is mediated by an increase in intraflagellar Ca2+ from 10(−6) to 10(−1) M; this transition is altered in mutants that lack the outer arm. The data presented here suggest that a Ca(2+)-dependent alteration in the interaction of this dynein light chain with the motor containing heavy chain may affect outer arm function during flagellar reversal.
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Li, Zheng, Wei Feng, Ze Wang, and He Chen. "Non-intrusive Load Identification Method based on SAGOA-GMM Algorithm." Electrotehnica, Electronica, Automatica 69, no. 4 (November 15, 2021): 59–65. http://dx.doi.org/10.46904/eea.21.69.4.1108007.
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Non-intrusive Load Identification play an important role in daily life. It can monitor and predict grid load while statistics and analysis of user electricity information. Aiming at the problems of low non-intrusive load decomposition ability and low precision when two electrical appliances are started and stopped at the same time, a new type of clustering and decomposition algorithm is proposed. The algorithm first analyses the measured power and use DBSCAN to filter out the noise of the collected data. Secondly, the remaining power points are clustered using the Adaptive Gaussian Mixture Model (AGMM) to obtain the cluster centres of the electrical appliances, and finally correlate the corresponding current waveform to establish a load characteristic database. In terms of load decomposition, a mathematical model was established for the magnitude of the changing power and current. The Grasshopper optimization algorithm (GOA) is optimized by introducing simulated annealing (SA) to identify and decompose electrical appliances that start and stop at the same time. The result of the decomposition is checked by the current similarity test to determine whether the result of the decomposition is correct, thereby improving the recognition accuracy. Experimental data shows that the combination of DBSCAN and GMM can can identify similar power characteristics. The introduction of SA makes up for the weakness of GOA and gives full play to the advantages of GOA's high identification efficiency. Finally, the test is carried out through the load detection data of the simultaneous start and stop of the two equipment. The test results show that the proposed method can effectively identify the simultaneous start and stop of two loads and can solve the problem of low recognition rate caused by the similar load power, which lays the foundation for the development of non-intrusive load identification in the future.
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Osborn, C. E., and R. E. Poppele. "Parallel distributed network characteristics of the DSCT." Journal of Neurophysiology 68, no. 4 (October 1, 1992): 1100–1112. http://dx.doi.org/10.1152/jn.1992.68.4.1100.
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1. We examined the functional organization of the dorsal spinocerebellar tract (DSCT) and found that it is similar to that of a parallel distributed network having widespread connectivity among parallel elements. The prevailing view is that the DSCT provides receptor-specific information to the cerebellum regarding muscle and cutaneous inputs from the hindlimbs, but that view does not consider the convergent inputs to DSCT neurons from multimodal polysynaptic pathways. 2. Spontaneously active DSCT neurons respond to peripheral stimulation with changes in their firing probability. We characterized the temporal patterns of poststimulus excitability changes for a large number of neurons using principal component analysis. The response of each neuron was represented by a response vector in three-dimensional principal component space, in which similar vectors represent responses having a similar waveform for their poststimulus activity patterns. 3. We compared the responses of large populations of DSCT units to two types of stimuli: small (3-8 deg) passive rotations of the foot at the ankle of an intact limb (234 cells) and stretch or contraction of an isolated muscle group (gastrocnemius-soleus, 168 cells). Most of the cells tested had significant responses (P < 0.05) to both types of stimuli (40-78% responded to muscle stimulation and 88% to foot rotation), and they exhibited similar patterns of poststimulus activity. Long-lasting inhibitory responses and excitatory responses with a range of peak times (< 10- > 60 ms) were prevalent in all cases. The population response to each stimulus was characterized by the relative incidence of response types among the units in a representative sample of the population. 4. The time course of excitability changes induced in DSCT cells by the stimuli could have been determined primarily by the presynaptic circuitry or by postsynaptic factors intrinsic to the DSCT cells. The evidence presented suggests that the selection of response waveforms and their distribution among the DSCT cells was determined presynaptically. We found that individual cells were capable of diverse responses to different stimuli. 5. Sample groups of 7-30 cells were selected at random and also on the basis of the similarity of their responses to one type of stimulus. The distributions of response types among the cells of the sample groups were compared to the distributions for the entire population recorded for each stimulus.(ABSTRACT TRUNCATED AT 400 WORDS)
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Gao, Jiyong, Na Dai, Zhigang Liu, Dehong Chen, Junqing Zhen, and Jin Wang. "Electroencephalogram Image under Complex Domain Analysis Algorithm to Analyze Neurological Status Epilepticus and Poor Prognostic Factors of Children." Journal of Healthcare Engineering 2021 (December 15, 2021): 1–11. http://dx.doi.org/10.1155/2021/3109061.
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This study was to adopt the electroencephalogram (EEG) image to analyze the neurological status epilepticus (SE) and adverse prognostic factors of children using the complex domain analysis algorithm, aiming at providing a theoretical basis for the clinical treatment of children with SE. 24-hour EEG was adopted to diagnose 197 children with SE. The patients were divided into an experimental group (100 cases) and a control group (97 cases) using a random number table method. The EEGs of children in the experimental group were analyzed using the compound domain analysis algorithm, and those in the control group were diagnosed by a professional doctor. The indicators of children in two groups were compared to analyze the effect of the compound domain analysis algorithm in diagnosing diseases through EEG. The prognostic scores of 197 children were scored one month after they were diagnosed, treated, and discharged, and the adverse prognostic factors were analyzed. As a result, EEG can accurately and effectively analyze the brain diseases in children. The sensitivity and specificity of the complex domain analysis algorithm for the detection of epilepsy EEG were much higher than those of the EEG automatic detection algorithm based on time-domain waveform similarity and the EEG automatic detection algorithm based on convolutional neural network (CNN), and the average running time was opposite, showing obvious difference ( P < 0.05 ).The average accuracy, sensitivity, and specificity of children in the experimental group were 96.11%, 97.10%, and 95.19%, respectively; and those in the control group were 88.83%, 90.14%, and 87.82%, respectively, so there was an obvious difference in accuracy between two groups ( P < 0.05 ). There were 57 cases with good prognosis and 140 cases with poor prognosis; there were 70 males with good prognosis and 19 poor prognoses and 69 women with good prognosis and 19 poor prognoses. Among 121 patients with infections, 84 cases had good prognosis and 37 cases had poor prognosis; 39 cases of irregular medication had good prognosis in 31 cases and a poor prognosis in 8 cases; and 37 cases had no obvious cause, including 25 cases with good prognosis and 12 cases with poor prognosis. In short, the EEG diagnosis and treatment effect of the compound domain analysis algorithm were better than those of professional doctors; the gender of the patient had no effect on the poor prognosis, and the pathogenic factors had an impact on the poor prognosis of the patient.
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Piana Agostinetti, Nicola, and Giulia Sgattoni. "Changepoint detection in seismic double-difference data: application of a trans-dimensional algorithm to data-space exploration." Solid Earth 12, no. 12 (December 14, 2021): 2717–33. http://dx.doi.org/10.5194/se-12-2717-2021.
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Abstract. Double-difference (DD) seismic data are widely used to define elasticity distribution in the Earth's interior and its variation in time. DD data are often pre-processed from earthquake recordings through expert opinion, whereby pairs of earthquakes are selected based on some user-defined criteria and DD data are computed from the selected pairs. We develop a novel methodology for preparing DD seismic data based on a trans-dimensional algorithm, without imposing pre-defined criteria on the selection of event pairs. We apply it to a seismic database recorded on the flank of Katla volcano (Iceland), where elasticity variations in time have been indicated. Our approach quantitatively defines the presence of changepoints that separate the seismic events in time windows. Within each time window, the DD data are consistent with the hypothesis of time-invariant elasticity in the subsurface, and DD data can be safely used in subsequent analysis. Due to the parsimonious behaviour of the trans-dimensional algorithm, only changepoints supported by the data are retrieved. Our results indicate the following: (a) retrieved changepoints are consistent with first-order variations in the data (i.e. most striking changes in the amplitude of DD data are correctly reproduced in the changepoint distribution in time); (b) changepoint locations in time correlate neither with changes in seismicity rate nor with changes in waveform similarity (measured through the cross-correlation coefficients); and (c) the changepoint distribution in time seems to be insensitive to variations in the seismic network geometry during the experiment. Our results demonstrate that trans-dimensional algorithms can be effectively applied to pre-processing of geophysical data before the application of standard routines (e.g. before using them to solve standard geophysical inverse problems).
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Winiwarter, L., K. Anders, D. Wujanz, and B. Höfle. "INFLUENCE OF RANGING UNCERTAINTY OF TERRESTRIAL LASER SCANNING ON CHANGE DETECTION IN TOPOGRAPHIC 3D POINT CLOUDS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2020 (August 3, 2020): 789–96. http://dx.doi.org/10.5194/isprs-annals-v-2-2020-789-2020.
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Abstract. Terrestrial laser scanners are commonly used for remotely sensing natural surfaces into 3D point clouds. Time series of such 3D point clouds can be analysed to gain information of surface changes that are induced by Earth surface shaping processes. The atomic unit in time series analysis is a bitemporal change detection and quantification. This should involve an estimation of the minimum quantifiable change, the Level of Detection, to separate signal from noise, e.g. stemming from the measurement. To enable such an estimation through error propagation, a model of the sensing instrument’s measurement uncertainty is required. In this work, we present an investigation on the ranging component of terrestrial laser scanning on this uncertainty and its influence on 3D distances between point clouds of two epochs. Specifically, we analyse the effects of incidence angle, intensity and range for different object materials, and make additional considerations with respect to waveform information returned by the sensor. We estimate a model for the rangefinder uncertainty of a terrestrial laser scanner and apply it on experimental data. The results show that using a sensor-specific model of ranging uncertainty allows an appropriate estimation of the Level of Detection. At a range of 60 m and a rotational displacement of 10°, this Level of Detection ranges between 0.1 mm to 1 mm for a white and a grey surface and up to 5 mm for a black surface. The completeness of the detection of significant change ranges from 60.2 % (black) to 89.8 % (grey) for the proposed method and from 65.5 % to 88.9 % for the baseline, when compared to tachymeter measurements. The similarity between the results is expected and suggests the validity of error propagation for the derivation of the Level of Detection.
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Gischig, Valentin Samuel, Joseph Doetsch, Hansruedi Maurer, Hannes Krietsch, Florian Amann, Keith Frederick Evans, Morteza Nejati, et al. "On the link between stress field and small-scale hydraulic fracture growth in anisotropic rock derived from microseismicity." Solid Earth 9, no. 1 (January 25, 2018): 39–61. http://dx.doi.org/10.5194/se-9-39-2018.
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Abstract. To characterize the stress field at the Grimsel Test Site (GTS) underground rock laboratory, a series of hydrofracturing and overcoring tests were performed. Hydrofracturing was accompanied by seismic monitoring using a network of highly sensitive piezosensors and accelerometers that were able to record small seismic events associated with metre-sized fractures. Due to potential discrepancies between the hydrofracture orientation and stress field estimates from overcoring, it was essential to obtain high-precision hypocentre locations that reliably illuminate fracture growth. Absolute locations were improved using a transverse isotropic P-wave velocity model and by applying joint hypocentre determination that allowed for the computation of station corrections. We further exploited the high degree of waveform similarity of events by applying cluster analysis and relative relocation. Resulting clouds of absolute and relative located seismicity showed a consistent east–west strike and 70° dip for all hydrofractures. The fracture growth direction from microseismicity is consistent with the principal stress orientations from the overcoring stress tests, provided that an anisotropic elastic model for the rock mass is used in the data inversions. The σ1 stress is significantly larger than the other two principal stresses and has a reasonably well-defined orientation that is subparallel to the fracture plane; σ2 and σ3 are almost equal in magnitude and thus lie on a circle defined by the standard errors of the solutions. The poles of the microseismicity planes also lie on this circle towards the north. Analysis of P-wave polarizations suggested double-couple focal mechanisms with both thrust and normal faulting mechanisms present, whereas strike-slip and thrust mechanisms would be expected from the overcoring-derived stress solution. The reasons for these discrepancies can be explained by pressure leak-off, but possibly may also involve stress field rotation around the propagating hydrofracture. Our study demonstrates that microseismicity monitoring along with high-resolution event locations provides valuable information for interpreting stress characterization measurements.
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Sakai, Hiroko M., Hildred Machuca, Michael J. Korenberg, and Ken-Ichi Naka. "Processing of Color- and Noncolor-Coded Signals in the Gourami Retina. III. Ganglion Cells." Journal of Neurophysiology 78, no. 4 (October 1, 1997): 2034–47. http://dx.doi.org/10.1152/jn.1997.78.4.2034.
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Sakai, Hiroko M., Hildred Machuca, Michael J. Korenberg, and Ken-Ichi Naka. Processing of color- and noncolor-coded signals in the gourami retina. III. Ganglion cells. J. Neurophysiol. 78: 2034–2047, 1997. The dynamics of intracellular responses from ganglion cells, as well as that of spike discharges, were studied with the stimulus regimens and analytic procedures identical to those used to study the dynamics of the responses from horizontal and amacrine cells ( Sakai et al. 1997a , b ). The stimuli used were large fields of red and green light given as a pulsatile input or modulation about a mean luminance by a white-noise signal. Spike discharges evoked by a white-noise stimulus were analyzed in exactly the same manner as that used for analysis of analog responses. The canonical nature of kernels allowed us to correlate the first- and second-order components in a spike train with those of the intracellular responses from horizontal, amacrine, and ganglion cells. Both red and green stimuli given alone in darkness produced noncolor-coded responses from all ganglion cells. In the case of some cells, steady red illumination changed the polarity or waveform of the response to green light. Color-coded ganglions responded only to simultaneous color contrast. Nonlinearities recovered from intracellular responses, and spike discharges were similar to those found in responses from amacrine cells and were of two types, one characteristic of the C amacrine cells and the other characteristic of the N amacrine cells. The first-order kernels of most ganglion cells could be divided into two basic types, biphasic and triphasic. The combination of kernels of these two basic types with different polarities can produce a wide range of responses. Addition of two types of second-order nonlinearity could render color coding in this relatively simple retina as an extremely complex process. Color information appeared to be represented by the polarity, as well as the waveform, of the first-order kernel. The response dynamics is a means of transmission of color-coded information. Second-order components carry information about changes around a mean luminance regardless of the color of an input. Some spike discharges produced a well-defined cross-kernel between red and green inputs to show that a particular time sequence of red and green stimuli was detected by the retinal neuron network. The similarity between signatures of second-order kernels for both amacrine and ganglion cells indicates that signals undergo a minimal transformation in the temporal domain when they are transmitted from amacrine to ganglion cells and then transformed into a spike train. Under our experimental conditions, a single spike train carried simultaneously information about red and green inputs, as well as about linear and nonlinear components. In addition, the spike train also carries a cross-talk component. A spike train is a carrier of multiple signals. Conversely, many types of information in a stimulus are independently encoded into a spike train.
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Liu, Zhining, Chengyun Song, Hanpeng Cai, Xingmiao Yao, and Guangmin Hu. "Enhanced coherence using principal component analysis." Interpretation 5, no. 3 (August 31, 2017): T351—T359. http://dx.doi.org/10.1190/int-2016-0194.1.
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Coherence is a measure of similarity between seismic waveforms. It gives a quantitative description of lateral reflection changes and highlights variations of the geologic features within a seismic image. However, subtle changes in waveforms are often difficult to capture using traditional coherence measures because of the high similarity among the remaining parts in the vertical analysis window. We have developed an attribute called enhanced coherence based on principal component analysis (PCA) with the goal of reducing redundancy within the vertical analysis window, which is often composed of the parts with a high similarity between neighboring traces, and highlighting subtle lateral changes. In computing such a coherence image, we first extract seismic data within a specified time window along a picked horizon. Then, we calculate the enhanced coherence from reduced data obtained using a dimension-reduction technique. Because seismic data typically consist of large volumes, PCA is chosen for dimension reduction due to its insensitivity to the amount of data. We also find that reduced data based on PCA is equivalent to applying texture model regression with multiple models obtained from the data. We have evaluated the enhanced coherence by applying it to poststack data and prestack data acquired over the Sichuan Basin in southwestern China. We determined that the enhanced coherence has a higher resolution for delineating subtle lateral changes. Additionally, enhanced coherence calculated from prestack data is proven to be able to capture anisotropic features.
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Rojas, Emilio L., and Rodrigo F. Cádiz. "A Physically Inspired Implementation of Xenakis's Stochastic Synthesis: Diffusion Dynamic Stochastic Synthesis." Computer Music Journal 45, no. 2 (2021): 48–66. http://dx.doi.org/10.1162/comj_a_00606.
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Abstract This article presents an extension of Iannis Xenakis's Dynamic Stochastic Synthesis (DSS) called Diffusion Dynamic Stochastic Synthesis (DDSS). This extension solves a diffusion equation whose solutions can be used to map particle positions to amplitude values of several breakpoints in a waveform, following traditional concepts of DSS by directly shaping the waveform of a sound. One significant difference between DSS and DDSS is that the latter includes a drift in the Brownian trajectories that each breakpoint experiences through time. Diffusion Dynamic Stochastic Synthesis can also be used in other ways, such as to control the amplitude values of an oscillator bank using additive synthesis, shaping in this case the spectrum, not the waveform. This second modality goes against Xenakis's original desire to depart from classical Fourier synthesis. The results of spectral analyses of the DDSS waveform approach, implemented using the software environment Max, are discussed and compared with the results of a simplified version of DSS to which, despite the similarity in the overall form of the frequency spectrum, noticeable differences are found. In addition to the Max implementation of the basic DDSS algorithm, a MIDI-controlled synthesizer is also presented here. With DDSS we introduce a real physical process, in this case diffusion, into traditional stochastic synthesis. This sort of sonification can suggest models of sound synthesis that are more complex and grounded in physical concepts.
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Xia, Sen. "An Time Domain Analysis Approach to Measurement of Three Dimensional Shape Distortion." Applied Mechanics and Materials 235 (November 2012): 135–40. http://dx.doi.org/10.4028/www.scientific.net/amm.235.135.
Full textAbstract:
Autocorrelation function and cross-correlation function can be used to illustrate the dependency relation of random processes. The degree of mini-transmutation is often too small to detect. A new approach via utilization of correlation coefficient between two different signals in time domain was proposed to measure the tiny distortion of three dimensional objects. The correlation analysis and deduction on transformation from 3-D surface distribution to 1-D time series signal were made rationally. Numeric simulation experiments of discrete digital signal generated from triangular function composite generator were done and six groups of correlation coefficient curves were given deliberately with different signal length. The correlation and similarity degree among different similar waveforms were analyzed in detail. It shows that the approach is valid to detect the degree of distortion between the original standard one and the practical one.
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Li, Ma, and Pengyuan Dong. "Identification of voltage sag source based on Improved GRA." Journal of Physics: Conference Series 2258, no. 1 (April 1, 2022): 012075. http://dx.doi.org/10.1088/1742-6596/2258/1/012075.
Full textAbstract:
Abstract Accurate identification of fault source causing voltage sag is of great significance to the governance and further research of voltage sag. In this paper, a voltage sag source identification method based on improved grey correlation analysis (GRA) is proposed. In view of the deficiency that the traditional GRA only considers the similarity, the proposed method considers the geometric area and slope of sequence into the calculation of correlation coefficient, so that the improved GRA has attributes of both sequence similarity and data closeness. Eight features are extracted from six common types of sag waveforms to form standard and test sequence; The improved GRA is used to calculate the correlation degree between the test and standard sequences, then the identification of sag source can be realized. Simulation model is built in MATLAB. Results show that this proposed method can effectively identify the voltage sag source. Compared with the traditional GRA, this method has higher identification accuracy and stronger identification ability.