Frequency-based Analysis Research Articles

Frequency-based characterization of liquid–solid fluidized bed hydrodynamics using the analysis of vibration signature and pressure fluctuations

This work is mainly focused on the frequency-based analyses of non-invasive vibration and pressure fluctuations signals to characterize main hydrodynamic events inside a liquid–solid fluidized bed. The power spectra of bed shell vibration and local pressure fluctuations in a frequency domain were calculated over a wide range of liquid velocities to cover the pathway of bed behavior in between three main hydrodynamic events, namely: minimum fluidization, cluster-circulating-to-individual particle motion (termed as the solid regime transition), and solid entrainment points. First rise in the mean power spectral density function (PSDF m ) of vibration fluctuations predicted the minimum fluidization accurately while a sharp level off in pressure signals showed the minimum fluidization velocity. Global maxima in the PSDF m of vibrations as well as second minima in the PSDF m of pressure fluctuations corresponded to the solid regime transition points. Finally, a plateau in the PSDF m of vibration signatures indicated a complete solid entrainment. Moreover, energy-based wavelet transform coupled with Hurst exponent analysis provided a detailed pathway of bed structure evolution, which led to the successful and accurate predictions of minimum fluidization as well as the solid regime transition inside the bed. The frequency-based analysis of non-invasive vibration and pressure fluctuations signals allows the main hydrodynamic parameters inside a liquid–solid fluidized bed (i.e., minimum U mf , solid regime transition velocity U c , and solid entrainment velocity U t ) to be determined. ► Hydrodynamic parameters of a liquid-solid two-phase fluidized bed are determined using non-intrusive vibration and pressure fluctuations. ► Wavelet transform furnishes minimum fluidization and regime transition points. ► The results can be used in the operation of multiphase reactors at severe conditions.

Fault Detection of Governor Systems Using Discrete Wavelet Transform Analysis

This study introduces a condition diagnosis technique for a turbine governor system. The governor system is an important control system to handle turbine speed in a nuclear power plant. The turbine governor system includes turbine valves and stop valves which have their own functions in the system. Because a turbine governor system is operated by high oil pressure, it is very difficult to maintain under stable operating conditions. Turbine valves supply oil pressure to the governor system for proper operation. Using the pressure variation of turbine and governor valves, operating conditions of the turbine governor control system are detected and identified. To achieve automatic detection of valve status, time-based and frequency-based analysis is employed. In this study, a new approach, wavelet decomposition, was used to extract specific features from the pressure signals of the governor and stop valves. The extracted features, which represent the operating conditions of the turbine governor system, include important information to control and diagnose the valves. After extracting the specific features, decision rules were used to classify the valve conditions. The rules were generated by a decision tree algorithm (a typical simple method for data-based rule generation). The results given by the wavelet-based analysis were compared to detection results using time- and frequency-based approaches. Compared with the several related studies, the wavelet transform-based analysis, the proposed in this study has the advantage of easier application without auxiliary features.

Advanced Methodology for Frequency Description of Biomechanical Systems

After basic frequency-based analysis and segmentation for high speed videosequences containing motion information, it is necessary to remove some of the motion artifacts distorting the results for accurate analysis. In the paper we are describing construction of amplitude and phase maps based on FFT and projecting 3D image information (videosequence) to relevant 2D arrays. Synthesis of these maps with basical frequency ones brings more accurate information about regions with useful information (regions with normal motion of objects). Last part of the paper offers solutions on the basis of separate region morphology.

Genetic identification of two putative world record Michigan salmonids resolves stakeholder and manager questions

The ability of fishery managers to quickly and effectively answer stakeholder questions using the best available science is crucial for successful management. The 2009 capture of a potential world record brown trout (Salmo trutta) and the 2010 capture of a potential world record land-locked Atlantic salmon (S. salar) in Michigan required managers to acquire genetic verification of the species identity. Given the variety of hatchery strains used to maintain Great Lakes fisheries for brown trout and in the absence of physical markings, managers also were interested to determine the strain of origin for information on assessing performance. DNA barcoding techniques using sequences from the mitochondrial (mt) DNA cytochrome c oxidase I (COI) gene and frequency-based analysis of species-specific microsatellite genotypes provided data to establish the species of both fish. The putative brown trout was confirmed to be a new world record specimen. Using individual assignment tests based on maximum likelihood estimators informed by multi-locus microsatellite genotypes, we determined the fish to be from the Seeforellen hatchery strain (p<0.01). Analysis of the COI gene in the putative Atlantic salmon resulted in assignment as a brown trout. The presence of only brown trout alleles at all six microsatellite loci examined revealed that the individual was not an inter-specific hybrid. Given sufficient genetic divergence exists among species, populations, or hatchery strains, the combination of mtDNA barcoding and microsatellite genetic analysis can provide accurate and rapid identification to address stakeholder and management questions.

Transcranial magnetic stimulation and peristimulus frequencygram

ObjectiveThe aim of our study was to use peristimulus frequencygram (PSF) constructed from single motor unit recordings to further characterise the responses evoked by low intensity TMS. MethodsTwelve healthy subjects (age 32±11 years) received single-pulse TMS over the first dorsal interosseus (FDI) motor area during weak isometric index finger abduction. Several hundred stimuli were delivered at a frequency of ∼0.3Hz and at an intensity of 79–110% of active motor threshold. FDI electromyogram (EMG) was recorded with surface and intramuscular fine wire electrodes. For single motor units, data analysis involved construction of a peristimulus time histogram (PSTH) and PSF. Surface EMG analysis involved signal averaging. Cumulative sums (CUSUMs) were calculated for SEMG, PSTH, and PSF data. ResultsForty-five single motor units were identified. The average number of stimuli per unit was 201±112. Characterisation of the response evoked by TMS differed with the use of SEMG, PSTH, and PSF CUSUMs. ConclusionsThe duration of the EMG silence that follows the MEP during voluntary contraction was longer in the PSF than SEMG and PSTH. SignificanceThese findings highlight the importance of using both probability and frequency-based analysis when determining the duration of inhibitory events in peripheral recordings.

Spatial Frequency-Based Analysis of Mean Red Blood Cell Speed in Single Microvessels: Investigation of Microvascular Perfusion in Rat Cerebral Cortex

BackgroundOur previous study has shown that prenatal exposure to X-ray irradiation causes cerebral hypo-perfusion during the postnatal development of central nervous system (CNS). However, the source of the hypo-perfusion and its impact on the CNS development remains unclear. The present study developed an automatic analysis method to determine the mean red blood cell (RBC) speed through single microvessels imaged with two-photon microscopy in the cerebral cortex of rats prenatally exposed to X-ray irradiation (1.5 Gy).Methodology/Principal FindingsWe obtained a mean RBC speed (0.9±0.6 mm/sec) that ranged from 0.2 to 4.4 mm/sec from 121 vessels in the radiation-exposed rats, which was about 40% lower than that of normal rats that were not exposed. These results were then compared with the conventional method for monitoring microvascular perfusion using the arteriovenous transit time (AVTT) determined by tracking fluorescent markers. A significant increase in the AVTT was observed in the exposed rats (1.9±0.6 sec) as compared to the age-matched non-exposed rats (1.2±0.3 sec). The results indicate that parenchyma capillary blood velocity in the exposed rats was approximately 37% lower than in non-exposed rats.Conclusions/SignificanceThe algorithm presented is simple and robust relative to monitoring individual RBC speeds, which is superior in terms of noise tolerance and computation time. The demonstrative results show that the method developed in this study for determining the mean RBC speed in the spatial frequency domain was consistent with the conventional transit time method.

A Frequency-based Analysis of the Norms for Spanish Noun Gender

A Frequency-based Analysis of the Norms for Spanish Noun Gender

Megacusps on rip channel bathymetry: Observations and modeling

The formation of beach megacusps along the shoreline of southern Monterey Bay, CA, is investigated using time-averaged video and simulated with XBeach, a recently developed coastal sediment transport model. Investigations focus on the hydrodynamic role played by the bay's ever-present rip channels. A review of four years of video and wave data from Sand City, CA, indicates that megacusps most often form shoreward of rip channels under larger waves (significant wave height ( H s ) = 1.5–2.0 m). However, they also occasionally appear shoreward of shoals when waves are smaller ( H s ~ 1 m) and the mean water level is higher on the beach. After calibration to the Sand City site, XBeach is shown to hindcast measured shoreline change moderately well (skill = 0.41) but to overpredict the erosion of the swash region and beach face. Simulations with small to moderate waves ( H s = 0.5–1.2 m) suggest, similar to field data, that megacusps will form shoreward of either rip channels or shoals, depending on mean daily water level and pre-existing beach shape. A frequency-based analysis of sediment transport forcing is performed, decomposing transport processes to the mean, infragravity, and very-low-frequency (VLF) contributions for two highlighted cases. Results indicate that the mean flow plays the dominant role in both types of megacusp formation, but that VLF oscillations in sediment concentration and advective flow are also significant.

Non-invasive Electrophysiology I

Non-invasive Electrophysiology I

Anomalous video event detection using spatiotemporal context

Compared to other anomalous video event detection approaches that analyze object trajectories only, we propose a context-aware method to detect anomalies. By tracking all moving objects in the video, three different levels of spatiotemporal contexts are considered, i.e., point anomaly of a video object, sequential anomaly of an object trajectory, and co-occurrence anomaly of multiple video objects. A hierarchical data mining approach is proposed. At each level, frequency-based analysis is performed to automatically discover regular rules of normal events. Events deviating from these rules are identified as anomalies. The proposed method is computationally efficient and can infer complex rules. Experiments on real traffic video validate that the detected video anomalies are hazardous or illegal according to traffic regulations.

Cutaneous silent period in human FDI motor units

In this study, we aimed to use both the probability-based and the frequency-based analyses methods simultaneously to examine cutaneous silent period (CSP) induced by strong electrical currents. Subjects were asked to contract their first dorsal interosseus muscles so that one motor unit monitored via intramuscular wire electrodes discharged at a rate of approximately 8 Hz. Strong electrical stimuli were delivered to the back of the hand that created a subjective discomfort level of between 4 and 7 [0-10 visual analogue scale] and induced cutaneous silent period in all units. It was found that the duration of the CSP was significantly longer when the same data were analysed using frequency-based analysis method compared with the probability-based methods. Frequency-based analysis indicated that the strong electrical stimuli induce longer lasting inhibitory currents than what was indicated using the probability-based analyses such as surface electromyogram and peristimulus time histogram. Usage of frequency-based analysis for bringing out the synaptic activity underlying CSP seems essential as its characteristics have been subject to a large number of studies in experimental and clinical settings.

A commentary to ‘Asynchronous Little Ice Age glacial maximum extent in southeast Iceland’ by Chenet et al. (Geomorphology 114 (2010) 253–260); a case of Fláajökull

The validity of the generalized extreme value method and the Bayesian approach, used by Chenet et al. (2010) in lichenometric dating of the outermost LIA Fláajökull moraines in SE Iceland, is questioned. The technique produced the date of A.D. 1821 for the abandonment of the moraine which does not agree with historical data nor does it correlate with the hypsometry (size, equilibrium line altitude and slope) of the glacier. On the other hand, a simple technique based on the five largest thalli or the size–frequency-based analysis agree well with the historical data and show that the Little Ice Age glacier maximum occurred in the late nineteenth century.

Reliability analysis of time series force plate data of community dwelling older adults

Frequency-based analysis of body sway has been used to distinguish between healthy young, healthy elderly adults and elderly adults with Huntingtons disease. Our aim was to assess the reliability of spectral-based outcomes of the centre of pressure (CoP) kinematics in order to determine if these outcomes could be tested for their capability to distinguish between elderly fallers and non-fallers in a future study. We have studied balance for 30 community dwelling healthy older adults 60 years or older. Four test conditions were used. Three successive trials were performed for each condition. CoP kinematics were estimated with a force platform with three strain gauges set in a triangular position. The frequency content of these signals was estimated. Intrasession correlation coefficients (ICC's) were then calculated for all test conditions. The reliability of the selected parameters varied between low and high (ICC 0.652–0.939). The ICC's for the narrow stance tests were higher compared to tests with normal standing conditions (0.771–0.94) to (0.652–0.865). The highest value was obtained in the high frequency band (0.939). These measures should be viewed with caution when screening geriatric patients because their reliability cannot always be assumed.

Frequency-based analysis of weld pool dynamics and keyhole oscillations at laser beam welding of galvanized steel sheets

The movements of the keyhole and the weld pool at deep penetration solid-state laser welding can be analyzed by observing either the optical process emissions, or directly the work piece surface using camera systems in the visual range. In this paper, the welding process of zinc-coated steel sheets is monitored. The geometry and behaviour of weld pool and capillary are calculated from the acquired camera images, they are compared with the onedimensional optical process emissions, and analyzed in the time- and frequency-domain. This helps to better understand the uncontrolled process behaviour, especially regarding the destructive influence of the evaporating zinc-layer.

EMPLOYING STN ANAVIST TO FORECAST CONVERGING INDUSTRIES

Converging industries are characterized by the blurring of boundaries between technologies, markets and industry sectors. As such they can enable firms to access new markets or threaten them with an array of new competitors and a lack of knowledge. This makes an early identification of convergence trends highly important. In the present paper we focus on the application of a frequency-based analysis and visualization software (STN AnaVist) for the forecasting of converging industries. Scrutinizing 3,836 patent and scientific publication references on phytosterols in the areas of nutraceuticals and cosmeceuticals, we employ research landscape, co-authorship and International Patent Classification (IPC) co-classification analyses. The results demonstrate partial convergence between the pharmaceutical, the chemical, the nutrition and the cosmetics industries and the suitability of the employed approach. According to this study, scientific as well as technology convergence have taken place in this segment, with a time-lag of roughly 25 years.

Analysis of Genetic Diversity in the North Eastern Himalayan Maize Landraces using Microsatellite Markers

Population DNA fingerprinting of 48 selected North Eastern Himalayan (NEH) landrace accessions was undertaken using 41 polymorphic fluorescent dye-labelled microsatellite/Simple Sequence Repeat (SSR) markers, using a DNA Sequencer. The analysis revealed a large number of SSR alleles (576), with high mean number of alleles per locus (13.8), and Polymorphism Information Content (PIC) of 0.63, reflecting the level of diversity in the NEH accessions and the informativeness of the SSR markers. The study also led to identification of 135 unique alleles, differentiating 44 out of the 48 accessions. Five highly frequent (major) SSR alleles (umc154580bp, phi062162bp, umc1367159bp, umc2250152bp and phi112152bp) were detected indicating that chromosomal regions harbouring these S SR alleles might not be selectively neutral. Analysis of population genetic parameters, including Wright’s F statistics, revealed high level of genetic differentiation, very low levels of inbreeding, and restricted gene flow between the NEH landraces. AMOVA (Analysis of Molecular Variance) showed that 67 per cent of the total variation in the accessions could be attributed to within-population diversity, and the rest between the accessions. Cluster analysis of SSR data using Rogers’ genetic distance and UPGMA, showed significant genetic diversity among the landraces from Sikkim. This is the first detailed study of SSR allele frequency-based analysis of genetic diversity in the NEH maize landraces of India.

Automated processing of electrochemical current noise in the time domain: I. Simulated signal

The concept of automated processing of electrochemical current noise in the time domain is presented. The methodology is based on the identification of “run-ups”, which are representative of every single rising feature (transient) in a signal. Selected transients are then subjected to the analysis in terms of their characteristic parameters. Functionality is first demonstrated on a simulated signal with a predefined sample of pitting nucleation events and then in application to processing current signatures from potentiostatic tests on Alloy C22. The results from the analysis of the simulated signal are compared with those of a frequency-based analysis, and it is demonstrated that analysis in the time domain provides direct quantitative information on electrochemical processes that cannot be obtained from frequency-domain analysis.

To what extent do native and non-native writers make use of collocations?

Usage-based models claim that first language learning is based on the frequency-based analysis of memorised phrases. It is not clear though, whether adult second language learning works in the same way. It has been claimed that non-native language lacks idiomatic formulas, suggesting that learners neglect phrases, focusing instead on orthographic words. While a number of studies challenge the claim that non-native language lacks formulaicity, these studies have two important shortcomings: they fail to take account of appropriate frequency information and they pool the writing of different learners in ways that may mask individual differences. Using methodologies which avoid these problems, this study found that non-native writers rely heavily on high-frequency collocations, but that they underuse less frequent, strongly associated collocations (items which are probably highly salient for native speakers). These findings are consistent with usage-based models of acquisition while accounting for the impression that non-native writing lacks idiomatic phraseology.

Contact force regulation in wire-actuated pantographs via variable structure control and frequency-domain techniques

One of the main problems in high-speed-train transportation systems is related to the current collection quality, that can dramatically decrease because of oscillations of the pantograph-catenary system. This problem has been addressed by means of active pantographs. In this paper we present some results about the possible implementation of variable structure control (VSC) techniques on a wire actuated symmetric pantograph. Such an actuator was suggested in the literature as a viable solution to building an active pantograph by modifying a passive pantograph currently used by Italian Railways. The use of VSC with sliding modes was considered in order to cope with the system uncertainties due to the overhead suspended catenary. Recent results about the frequency-based analysis of VSC systems featuring second-order sliding modes are exploited to avoid the performance-destroying effect of the resonant wire actuator and to get a continuous control force without using observers. We show by simulations that the contact force results are very close to the desired set-point also in the presence of measurement noise.

Single-ensemble-based eigen-processing methods for color flow imaging - Part I. The Hankel-SVD filter

Because of their adaptability to the slow-time signal contents, eigen-based filters have shown potential in improving the flow detection performance of color flow images. This paper proposes a new eigen-based filter called the Hankel-SVD filter that is intended to process each slowtime ensemble individually. The new filter is derived using the notion of principal Hankel component analysis, and it achieves clutter suppression by retaining only the principal components whose order is greater than the clutter eigen-space dimension estimated from a frequency based analysis algorithm. To assess its efficacy, the Hankel-SVD filter was first applied to synthetic slow-time data (ensemble size: 10) simulated from two different sets of flow parameters that model: 1) arterial imaging (blood velocity: 0 to 38.5 cm/s, tissue motion: up to 2 mm/s, transmit frequency: 5 MHz, pulse repetition period: 0.4 ms) and 2) deep vessel imaging (blood velocity: 0 to 19.2 cm/s, tissue motion: up to 2 cm/s, transmit frequency: 2 MHz, pulse repetition period: 2.0 ms). In the simulation analysis, the post-filter clutter-to- blood signal ratio (CBR) was computed as a function of blood velocity. Results show that for the same effective stopband size (50 Hz), the Hankel-SVD filter has a narrower transition region in the post-filter CBR curve than that of another type of adaptive filter called the clutter-downmixing filter. The practical efficacy of the proposed filter was tested by application to in vivo color flow data obtained from the human carotid arteries (transmit frequency: 4 MHz, pulse repetition period: 0.333 ms, ensemble size: 10). The resulting power images show that the Hankel-SVD filter can better distinguish between blood and moving-tissue regions (about 9 dB separation in power) than the clutter-downmixing filter and a fixed-rank multi ensemble-based eigen-filter (which showed a 2 to 3 dB separation).