Elastic Rhythm in Signal-Synchronised Sequencing Objects for Pure Data

This paper presents a family of objects for manipulating polyrhythmic sequences and isorhythmic relationships, in both the signal and event domains. These work together and are tightly synchronised to an audio phase signal, so that relative temporal relationships can be tempo-manipulated in a linear fashion. Many permutations of polyrhythmic sequences including incomplete tuplets, scrambled elements, interleaved tuplets and any complex franctional relation can be realised. Similarly, these many be driven with controllable isorhythmic generators derived from a single driver, so that sequences of different fractionally related lengths may be combined and synchronised. It is possible to use signals to drive audio playback that are directly generated, so that disparate sound files may be combined into sequences. A set of sequenced parameters are included to facilitate this process.

Hepatobiliary phase signal intensity: A potential method of diagnosing HCC with atypical imaging features among LR-M observations

Herein, we assessed whether hepatobiliary phase (HBP) signal intensity (SI) can be used to differentiate HCC and non-HCC malignancies within LR-M observations. 106 LR-M patients based on LI-RADS v2018 who underwent gadoxetate-disodium magnetic resonance imaging and surgery from January 2009 to December 2018 were included. SI of LR-M observation on HBP was analyzed by two radiologists and categorized into dark, low and iso-to-high groups. Tumor was classified as dark when more than 50% of tumor showed hypointensity compared to spleen, as low when more than 50% of tumor showed hyperintensity compared to spleen but hypointensity compared to liver parenchyma, and as iso-to-high if there was even a focal iso-intensity or hyperintensity compared to liver parenchyma. Analysis of clinicopathological factors and association between imaging and histology was performed. Out of 106 LR-M, 42 (40%) were showed dark, 61 (58%) showed low, and 3 (3%) showed iso-to-high SI in HBP. Three iso-to-high SI LR-M were HCCs (P = 0.060) and their major histologic differentiation was Edmondson grade 1 (P = 0.001). 43 out of 61 (71%) low SI LR-M were iCCA or cHCC-CCA (P = 0.002). Inter-reader agreement of HBP SI classification was excellent, with a kappa coefficient of 0.872. LR-M with iso-to-high SI in HBP is prone to being HCC while LR-M with low SI in HBP is prone to being tumor with fibrous stroma such as iCCA and cHCC-CCA. Classification of LR-M based on HBP SI may be a helpful method of differentiating HCC from non-HCC malignancies.

Digital controller for active power filter based on P-Q theory under non-ideal main voltages

<span>This paper proposes a control strategy active power filter under non-ideal main voltages. The P-Q Theory is used to generate three-phase active power filter reference currents, but the P-Q Theory has a weakness when implemented under non ideal main voltages. This paper proposes a reference current generation method using modified P-Q Theory under non-ideal main voltages conditions. Before calculating the P-Q Theory, the non-ideal voltage at the source is normalized by using PLL to determine the phase angle which is then carried out by generating an ideal three-phase signal. The proposed method is simulated and implemented in a three-phase active power filter controller. The test results show the improvement in the performance of the P-Q Theory under non ideal main voltages with THD 7.21% to THD 3.29%.</span>

Receiver phase alignment using fitted SVD derived sensitivities from routine prescans

Magnetic resonance imaging radio frequency arrays are composed of multiple receive coils that have their signals combined to form an image. Combination requires an estimate of the radio frequency coil sensitivities to align signal phases and prevent destructive interference. At lower fields this can be accomplished using a uniform physical reference coil. However, at higher fields, uniform volume coils are lacking and, when available, suffer from regions of low receive sensitivity that result in poor sensitivity estimation and combination. Several approaches exist that do not require a physical reference coil but require manual intervention, specific prescans, or must be completed post-acquisition. This makes these methods impractical for large multi-volume datasets such as those collected for novel types of functional MRI or quantitative susceptibility mapping, where magnitude and phase are important. This pilot study proposes a fitted SVD method which utilizes existing combination methods to create a phase sensitive combination method targeted at large multi-volume datasets. This method uses any multi-image prescan to calculate the relative receive sensitivities using voxel-wise singular value decomposition. These relative sensitivities are fitted to the solid harmonics using an iterative least squares fitting algorithm. Fits of the relative sensitivities are used to align the phases of the receive coils and improve combination in subsequent acquisitions during the imaging session. This method is compared against existing approaches in the human brain at 7 Tesla by examining the combined data for the presence of singularities and changes in phase signal-to-noise ratio. Two additional applications of the method are also explored, using the fitted SVD method in an asymmetrical coil and in a case with subject motion. The fitted SVD method produces singularity-free images and recovers between 95–100% of the phase signal-to-noise ratio depending on the prescan data resolution. Using solid harmonic fitting to interpolate singular value decomposition derived receive sensitivities from existing prescans allows the fitted SVD method to be used on all acquisitions within a session without increasing exam duration. Our fitted SVD method is able to combine imaging datasets accurately without supervision during online reconstruction.

Vibration Signal Parameter Estimation in Variable Speed: Algorithms and performance bounds

Vibration signal parameter estimation for rotating machinery diagnostics operating under variable speedconditions is considered. At first, we provide a brief survey of existing methods for Quadratic Phase Signal (QPS)parameter estimation. Then, we introduce improved solutions for the general QPS case and the Order QPS (O-QPS)case, respectively. For all considered cases (namely the QPS, O-QPS with tachometer and O-QPS without tachometer),we develop the Cramer Rao Bounds to assess and compare the estimation performance limits for each model. Finally, wecompare the performance of all considered methods and highlight, in particular, the gain of the proposed solutions.