Phase Correlation Research Articles

A chaos-based word-wise stream cipher using keyed strong S-Box

Stream ciphers are crucial in the realm of information security. However, many existing stream ciphers suffer from several vulnerabilities, including insufficient security levels and the use of S-boxes with low non-linearity, fixed points, reverse fixed points and short cycles. To address these issues, a robust word-wise stream cipher was proposed that incorporates a keyed strong S-box and a two-dimensional (2D) chaotic map, significantly enhancing overall security. A 2D non-degenerate quadratic map (2D-NDQM) was constructed and evaluated using bifurcation and phase diagrams, Lyapunov exponent, Kolmogorov entropy, sample entropy, correlation dimension, and TestU01. The 2D-NDQM is then utilized to design a keyed strong S-box construction algorithm. Based on this, a word-wise stream cipher leveraging both the 2D-NDQM and the keyed strong S-box was developed. A series of tests were conducted to evaluate the proposed stream cipher's performance. The results were promising, showing a key space of 2179, an average number of bits change rate of 50.0229 %, a unified average changing intensity of 33.4402 %, and a number of pixels change rate of 99.6671 %. Additional metrics such as Hamming distance, linear complexity, and Shannon entropy also closely aligned with ideal values, confirming the security and feasibility of the proposed algorithm.

Uniaxial Compressive Failure Characteristics and Fractal Analysis of Mud–Sand Composite Rock Samples Based on Acoustic Emission Tests

In order to study the influence of rock combination types on their mechanical properties and failure characteristics, uniaxial compression tests of single rock samples and combined rock samples were conducted. Acoustic emission (AE) signals during the test process were collected, and the differences in AE signals of single rock samples and combined rock samples were studied based on the fractal theory. The results showed that the peak strength, elastic modulus, peak strain, and failure degree of the combined rock samples are all between those of the two single rock samples. The AE ringing count gradually increases with the loading process and suddenly increases to the maximum when the rock sample fails. During this process, the phase trajectory volume corresponding to the ringing count shows an evolution law of first decreasing and then increasing, while the correlation dimension corresponding to the ringing count signal shows an overall evolution law of first increasing and then decreasing. The results indicate that the phase trajectory volume, correlation dimension, and crack changes have a consistent dynamic change. Therefore, the phase trajectory and correlation dimension are effective tools to describe the pore change characteristics of rock combinations.

An efficient single-shot global localization method for indoor mobile robots usingphase correlation

Purpose The purposes of this paper are to solve the low-efficiency problem caused by large search space in global localization and develop an efficient global localization method requiring only one 2D-LiDAR scan to match against the prior map for indoor mobile robots. Design/methodology/approach This paper solves the global localization problem using phase correlation as the underlying registration method. To obtain accurate rotation parameter, this paper exhaustively pre-rotates the prior map by a certain angle stride in advance. Then the input scan is matched against the pre-rotated maps one by one using phase correlation to determine translation parameters, and this paper constructs an orientation histogram by the correlation coefficients. The map rotation angle and corresponding translation parameters of the maximal peak value in the orientation histogram constitute the global pose. This paper applies a divide-and-conquer method to reduce the time consumption of single phase correlation and determines promising angle ranges where the maximal peak value may appear based on the periodicity of 90º in the orientation histogram with the signal-to-noise ratio (SNR) to reduce execution times of phase correlation. Findings Both simulated and real experimental results reveal that the proposed method achieves a high enough success rate and efficient (processing time in a second) global localization. Originality/value The proposed method constructs an orientation histogram to improve the global localization success rate and applies a divide-and-conquer method with SNR to improve efficiency, which will benefit the indoor mobile robots equipped with 2D-LiDAR.

Constructing keyed strong S-box with optimized nonlinearity using nondegenerate 2D hyper chaotic map

Abstract In the realm of information security, the nonlinearity of an S-Box is a pivotal attribute for ensuring its effectiveness. S-Boxes randomly generated with chaotic maps, however, often exhibit insufficient nonlinearity. To construct a robust S-Box with enhanced nonlinearity, we have developed a nondegenerate two-dimensional hyper chaotic map (2D-NDHCM). We rigorously evaluated its dynamic properties through bifurcation and phase diagrams, Lyapunov exponents, Kolmogorov entropy, correlation dimension, and randomness tests to assess the map's resilience. Subsequently, we employed the 2D-NDHCM to devise a novel algorithm for constructing and optimizing a keyed strong S-Box, leveraging simulated annealing technique to achieve superior nonlinearity. Finally, We conducted performance analyses of the optimized S-Box using the classic six criteria, and the results confirmed the algorithm's practicality and effectiveness.

Nonlinear time series analysis of state-wise COVID-19 in Malaysia using wavelet and persistent homology

The nonlinear progression of COVID-19 positive cases, their fluctuations, the correlations in amplitudes and phases across different regions, along with seasonality or periodicity, pose challenges to thoroughly examining the data for revealing similarities or detecting anomalous trajectories. To address this, we conducted a nonlinear time series analysis combining wavelet and persistent homology to detect the qualitative properties underlying COVID-19 daily infection numbers at the state level from the pandemic’s onset to June 2024 in Malaysia. The first phase involved investigating the evolution of daily confirmed cases by state in the time-frequency domain using wavelets. Subsequently, a topological feature-based time series clustering is performed by reconstructing a higher-dimensional phase space through a delay embedding method. Our findings reveal a prominent 7-day periodicity in case numbers from mid-2021 to the end of 2022. The state-wise daily cases are moderately correlated in both amplitudes and phases during the Delta and Omicron waves. Biweekly averaged data significantly enhances the detection of topological loops associated with these waves. Selangor demonstrates unique case trajectories, while Pahang shows the highest similarity with other states. This methodological framework provides a more detailed understanding of epidemiological time series data, offering valuable insights for preparing for future public health crises.

Removing atmospheric noise from InSAR interferograms in mountainous regions with a convolutional neural network

Atmospheric noise in interferometric synthetic aperture radar (InSAR)-derived estimates of surface deformation often obscures real displacement signals, especially in mountainous regions. As climate change disproportionately impacts the mountain cryosphere, a reliable technique for atmospheric correction in high-relief terrain is increasingly important. We developed and implemented a statistical machine learning atmospheric correction approach that relies on the differing spatial and topographic characteristics of slow-moving periglacial features and atmospheric noise. Our correction is applied at the native spatial and temporal resolution of the InSAR data, does not require external atmospheric reanalysis data, and can correct both stratified and turbulent atmospheric noise.Using Sentinel-1 data from 2017 to 2022, we trained a convolutional neural network (CNN) on observed atmospheric noise from 330 short-baseline interferograms and observed displacement signals from time series inversion of 1322 interferograms. We applied our trained CNN to correct 251 additional interferograms over an out-of-region application area, which were inverted to create displacement time series. We used the Rocky Mountains in New Mexico, Colorado, and Wyoming as our training, validation, testing, and application areas. When applied to our testing dataset, our correction offered performance improvements of 131%, 208%, and 68% in structural similarity index measure over corrections using atmospheric reanalysis data, phase correlation with topography, and high-pass filtering, respectively. The CNN-corrected time series reveals previously obscured kinematic behavior of rock glaciers and other features in the application dataset. Our flexible, robust approach can be used to correct arbitrary InSAR data to analyze subtle surface deformation signals for a range of science and engineering applications.

Robust Multimodal Image Matching Based on Radiation Invariant Phase Correlation

Abstract. Due to the influence of nonlinear radiation distortion and geometric deformation, achieving multimodal image matching remains a challenging task. To address these issues, this paper proposes a method called radiation invariant phase correlation (RIPC) to simultaneously estimate the rotation, scale, and displacement changes of multimodal image pairs. Firstly, based on the local structure characteristics of the image itself, we harness the nonlinear invariance of kernel canonical correlation analysis to devise the multimodal local self-correlation (MLSC) descriptor. This descriptor is resilient to nonlinear radiative differences, as well as local rotation and scale variations. Subsequently, we incorporate the log-polar coordinate transformation to capture the overall rotation and scale changes in the image, enabling independent representation of these factors on the Cartesian coordinate system. Finally, drawing upon the continuity of displacement estimation, as well as rotation and scale estimation, we construct a five-dimensional descriptor tailored for phase correlation. Extensive experiments conducted on five open-source datasets demonstrate that our proposed method surpasses state-of-the-art (SOTA) techniques in matching performance. Furthermore, our RIPC method achieves matching accuracy within 2-pixel threshold, which underscores its effectiveness in multimodal remote sensing image matching.

The impact of EEG electrode density on the mapping of cortical activity networks in infants

ObjectiveElectroencephalography (EEG) is widely used for assessing infant's brain activity, and multi-channel recordings support studies on functional cortical networks. Here, we aimed to assess how the number of recording electrodes affects the quality and level of details accessible in studying infant's cortical networks. MethodsDense array EEG recordings with 124 channels from N=20 infants were used as the reference, and lower electrode numbers were subsampled to simulate recording setups with 63, 31, and 19 electrodes, respectively. Cortical activity networks were computed for each recording setup and different frequencies using amplitude and phase correlation measures. The effects of the recording setup were systematically assessed on global, nodal, and edge levels. ResultsCompared to the reference 124-channel recording setup, lowering electrode density affected network measures in a modality- and frequency-specific manner. The global network features were essentially comparable with 63 or 31 channels. However, the analytic reliability of the local network measures, both at nodal and edge levels, was proportional to the electrode density. The low-frequency amplitude correlations were most robust to the number of recording electrodes, whereas higher frequency phase correlation networks were most sensitive to the density of recording electrodes. ConclusionsOur findings suggest strong and predictable effects of recording setup on the network analyses. Higher electrode number supports studies on networks with phase correlations, higher frequency, and finer spatial details. SignificanceThe relationship between the recording setup and reliability of network analyses is essential for the prospective design of research data collection, as well as for guiding analytic strategies when using already collected EEG data from infants.

Influence of mixotrophy on cell cycle phase duration and correlation of karlotoxin synthesis with light and G1 phase in Karlodinium veneficum

Karlodinium veneficum forms fish killing blooms in estuaries worldwide. The toxicity of these blooms is variable and thought to be connected to bloom stage and in situ growth rates. Methods for measuring in situ growth rates rely on the assumption that cell cycle progression is phased to the diel photocycle, which is true for phototrophically-growing K. veneficum cultures where G1 phase occurs during light and S and G2 + M phases occur during darkness. However, K. veneficum is a facultative mixotroph that also phagocytizes microalgal prey, and the effects of this mixotrophy on its cell cycle synchrony are unknown. Furthermore, toxicity in laboratory cultures is inversely related to growth rate and is light dependent, suggesting synchrony between the cell cycle (G1 phase) and karlotoxin synthesis. To test this, the cell cycle phase distribution and cellular toxin content for phototrophic and mixotrophic cultures of K. veneficum were monitored hourly for a full diel cycle. The results demonstrated that mixotrophic cultures maintained a synchronized cell cycle, despite increased growth rates. The faster growth rates were attributed to a shortened duration of G1 phase in mixotrophic cultures compared to phototrophic cultures (30.8 ± 9.2 h vs 69.4 ± 21.5 h, respectively). Meanwhile, toxin production was observed only during light hours, consistent with synthesis initiating with the photorespiratory byproduct glycolate. Cellular toxin content had a significant positive correlation with the percentage of G1 phase cells and a significant negative correlation with the percentage of S phase cells. These results indicate a clear role in mixotrophy increasing growth rates of K. veneficum and of the diel photocycle in synchronizing the cell and karlotoxin synthetic cycles.

A TDLAS gas detection method based on digital signal modulation

This research presents a novel TDLAS gas concentration detection method based on digital modulation. The method inherits the advantage of a simple system structure from Direct Absorption Spectroscopy, as well as the excellent sensitivity of Wavelength Modulation Spectroscopy. A low-frequency sawtooth wave is employed to drive the laser, resulting in a digital direct absorption spectrum signal. By constructing a cosine modulation sequence in the time domain and performing linear interpolation on the direct absorption spectrum, it successfully converts to a wavelength-modulated absorption spectrum and simultaneously generates a digital reference signal at double the frequency. Ultimately, phase-locked amplification technology can be used to calculate the amplitude of the second harmonic. Since both the modulation and reference signals are generated digitally, they ensure a strict frequency-doubling relationship and phase correlation, which not only reduces the complexity of the hardware system but also effectively minimizes system errors. Because digital technology generates both the modulation and reference signals, it ensures that they have the same phase and a strict frequency-doubling relationship. Experimental results demonstrate that, when fitted by a cubic polynomial, the second harmonic amplitude and the gas concentration have a correlation coefficient (R2) as high as 0.99999 and a root mean square error as low as 0.0011. This proves the method's great accuracy and reliability in practical applications.

Optimization and Application Analysis of Phase Correction Method Based on Improved Image Registration in Ultrasonic Image Detection

ABSTRACTIn order to prevent and detect a wide range of disorders, including those of the brain, thoracic, digestive, urogenital, and cardiovascular systems, ultrasound technology is essential for assessing physiological data and tissue morphology. Its capacity to deliver real‐time, high‐frequency scans makes it a handy and non‐invasive diagnostic tool. However, issues like patient movements and probe jitter from human error can provide a large amount of interference, resulting in inaccurate test findings. Techniques for image registration can assist in locating and eliminating unwanted interference while maintaining crucial data. Even though there has been research on improving these techniques in Matlab, there are no specialized systems for interference removal, and the procedure is still time‐consuming, particularly when working with huge quantities of ultrasound images. The phase correlation technique, which converts images into the frequency domain and makes noise suppression easier, is one of the most efficient algorithms now in use since it can tolerate noise with resilience. Nevertheless, little research has been done on using this technique to identify displacement in blood vessel wall ultrasound images. To address these gaps, this work presents an image registration system that uses the phase correlation algorithm. The system provides rotation, zoom registration, picture translation, and displacement detection of the vessel wall in addition to interference removal. Furthermore, batch processing is included to increase the effectiveness of registering multiple ultrasound pictures. Through efficient interference management and streamlined registration, this method offers a workable way to improve the precision and efficacy of ultrasonic diagnostics.

Phase volume correlation approach for overcoming decorrelation in three-dimensional phase-sensitive optical coherence elastography.

The dynamic measurement range in phase-sensitive optical coherence elastography (PhS-OCE) is limited for the phase decorrelation induced by pixel-level displacements in precision measurement, where the consideration of the time-resolved incremental method and in-plane pixels tracking method is insufficient to recover the phase holistically. This work presented a phase volume correlation (PVC) approach to handle the phase decorrelation in three-dimensional PhS-OCE. By utilizing the ability of the discontinuous source diagram to quantify voxel phase correlation levels, the PVC establishes a wrapped phase-matching equation aimed at optimizing the number of volumetric source distributions. The three-dimensional pixel-level motions in the deformed phase space can be evaluated by solving the optimization model for phase matching, thereby enabling the reconstruction of the volumetric phase variation corrupted by decorrelation. The large deformations experiments including diffident loadings, i.e., stretching, three-point bending, and light-cured, verified the proposed PPVC approach's of feasibility, reliability, and stability. The contribution of this work can dramatically enhance the dynamic measuring range in three-dimensional PhS-OCE.

Multiband topological acoustic waveguide with multistage toroidal resonant cavities

In recent years, there has been significant development in acoustic waveguides through the introduction of topological phase correlation concepts in acoustics. Many studies have shown the properties of acoustic unidirectional transmission. This paper presents a new ring-shaped acoustic topological insulator that is multi-band, unlike previous structures. The structure improves internal space utilization with the same dimensions, reducing acoustic wave conduction frequency in air environments. Additionally, the introduction of a multistage ring-shaped resonant cavity enables the conduction of acoustic waves in multiple frequency bands. This paper employs the rotational scattering mechanism to invert the topological phase of the lattice. This allows for the construction of two crystals with opposite phases, which can be used to create a topological channel for the transmission of acoustic waves. At the topological interface, the acoustic transmission losses within the four bands are small. Furthermore, this paper verifies by simulation that the defects have little effect on acoustic transmission. The paper's research offers potential for multiband acoustic control.

Acoustic near field effects in distribution transformer noise measurement

This paper examines the near field effect, including the active and reactive acoustic field around a liquid-filled distribution transformer with heat-dissipating corrugated fins on the tank walls. The analysis was carried out on the basis of measurements of sound pressure and sound intensity levels along with acoustic maps including the phase correlation of acoustic waves. The acoustic field around the transformer was evaluated in the measurement planes showing normal direction radiation of up to 1,0 m distance. Discrete point measurements made with the PU (pressure - velocity) probe was used to obtain parameters such as particle velocity, active and reactive sound intensity as well as the transfer function associated with the reference microphone. The last parameter, the transfer function, allows to show the phase correlation between acoustic wave propagation, which contributes to a better understanding of acoustic near-field effects where energy circulates, creating a sound field that can have overestimated sound pressure and intensity levels.

Realizing multiorbital Hubbard model with commensurate fillings in the paramagnetic phase of triangular magnets (X = Mn, Co, Ni)

The multiorbital Hubbard model is renowned for its rich phase diagram, characterized by various filling-dependent Mott transitions. However, controlling electron filling to explore the complete phase diagram within a single material remains challenging. In this study, we investigate three members of a correlated magnet family: Na2BaX(PO4)2 (where X = Mn, Co, Ni). Our focus is on revealing their unusual electronic structure related to the different electron fillings. Despite differences in their effective angular momentum, our first-principles calculations reveal a strikingly similar flat-band electronic structure across all three systems. Remarkably, we found that their distinct valence configurations lead to a similar response to electronic correlations in the high-temperature paramagnetic phases, which nicely realizes Mott states with different electron concentrations. Thus, these systems can be conceptualized as multiorbital Hubbard models with differing electron fillings. Our work unifies the understanding of these structurally similar systems and opens new avenues for exploring correlated electronic structures with distinct fillings.

Probing early phase coarsening in a rapidly quenched Bose gas using off-resonant matter-wave interferometry

We experimentally investigate the evolution of spatial phase correlations in a rapidly quenched inhomogeneous Bose gas of rubidium using off-resonant matter-wave interferometry. We measure the phase coherence length ℓ of the sample and directly probe its increase during the early stage of condensate growth before vortices are formed. Once the vortices are formed stably in the quenched condensate, the measured value of ℓ is shown to be linearly proportional to the mean distance between the vortex. These results confirm the presence of phase coarsening prior to vortex formation, which is crucial for a quantitative understanding of the resultant defect density in samples undergoing critical phase transitions. Published by the American Physical Society 2024

Comparison of the accumulation manner of a macromolecular drug between two mouse tumour models: study with magnetic resonance imaging and the model macromolecular drug, gadolinium-conjugated dextran

A knowledge of the difference of spatio-temporal behaviour of nanomedicine in different type of tumour models is important to develop well-targeted nanomedicine for tumour. In this study, intratumoral accumulation of the model nanomedicine, gadolinium-conjugated dextran (Gd-Dex), was examined with magnetic resonance imaging in two tumour models; mouse sarcoma S180 and radiation-induced mouse fibrosarcoma RIF-1. From time-course of the distribution images, the plasma-to-tumour interstitial tissue transfer constant (Ktrans ) and fractional plasma volume (Vp ) were calculated and mapped. Gd-Dex preferentially distributed to the marginal region of S180 tumours immediately after its injection, and then started to accumulate in some parts of the central region. Ktrans and Vp values were large in the marginal region, while only Ktrans was large in some parts of the central region. In contrast, the distribution of Gd-Dex in RIF-1 tumours was fairly homogeneous, and may have resulted from the homogeneous distributions of Ktrans and Vp . The amounts of Gd-Dex that accumulated in entire tumours in both tumour models correlated with the volume of tumours; however, accumulation in large S180 tumours deviated from the correlation in the early phase. The differences in the manner and pharmacokinetics of nanomedicine among tumour models may affect the accumulation of the medicine.

Correlation of deglutitive striated esophagus motor function and pharyngeal phase swallowing biomechanical events.

The functional relationship of striated esophagus (St.Eso) motor function with pharyngeal deglutitive biomechanical events has not been systematically studied. The aim of this study was to determine the spatio-temporal characteristics of St.Eso function and its correlation with pharyngeal biomechanics and bolus transport. We studied 50 healthy volunteer subjects (age range: 21-82 years, 31 female) by digital videofluoroscopy. All subjects were studied in a seated, upright position. Thirteen of these 50 volunteers also underwent high-resolution manometry (HRM) concurrent with fluoroscopy. We used laryngeal excursion as a surrogate for St.Eso excursion. Median duration of St.Eso excursion was 2.35 [1.93,2.85, 5th and 95th percentile] seconds. Mean maximum extent of St.Eso excursion was 2.84 ± 0.72 cm. We identified four distinct periods in deglutitive St.Eso motor function: P1. Anterosuperior ascent without bolus or peristaltic activity, P2. Non-peristaltic bolus receiving at the apogee of St.Eso excursion concurrent with UES opening and pharyngeal peristalsis P3. Peristaltic bolus transport as St.Eso descends and P4. Continued peristalsis in resting position. 1. St.Eso motor function spans both pharyngeal and esophageal phases of swallowing for receiving and transporting the bolus, 2. Pressure signatures in HRM recordings currently attributed to St.Eso deglutitive motor activity does not represent the entirety of St.Eso peristalsis, only the part that occurs in its resting position. St.Eso peristalsis that occurs during its descent is recorded by pressure sensors initially in the pharynx. This finding needs to be considered when interpreting HRM recordings of the pharynx and proximal esophagus.

Tensor-network-based variational Monte Carlo approach to the non-equilibrium steady state of open quantum systems

We introduce a novel method of efficiently simulating the non-equilibrium steady state of large many-body open quantum systems with highly non-local interactions, based on a variational Monte Carlo optimization of a matrix product operator ansatz. Our approach outperforms and offers several advantages over comparable algorithms, such as an improved scaling of the computational cost with respect to the bond dimension for periodic systems. We showcase the versatility of our approach by studying the phase diagrams and correlation functions of the dissipative quantum Ising model with collective dephasing and long-ranged power law interactions for spin chains of up to N=100 spins.

Elevated effect of hydrothermal treatment on phosphorus transition between solid-liquid phase in swine manure

The morphology and composition of phosphorus in biomass wastes are key factors in determining its potential for utilization. However, the morphological distribution and evolutionary mechanism of phosphorus during the hydrothermal conversion of biomass wastes are still unclear. In this study, swine manure was investigated as the research subject, and the changes in its solid-phase organic components, such as lignocellulose, and inorganic constituents, including metals and phosphorus, during the hydrothermal carbonization (HTC) processes were analyzed in relation to hydrothermal reaction severity (LnR0). A significant linear correlation in Phase II was observed between the solid-phase yield of swine manure and the LnR0. The rapid decline in the solid-phase yield during the initial phase (LnR0 < 9.72) was primarily attributed to the hydrolysis of hemicellulose and similar components. Similarly, solid phase phosphorus showed a very significant phase II with the decrease of solid phase yield. In the first stage, inorganic phosphorus and metal ions (calcium ions, magnesium ions) transferred to the liquid phase (LnR0<9.41). When LnR0 > 9.41, and the driving force of inorganic phosphorus and metal ions into solid phase is enhanced. As the LnR0 was further increased, the HTC could fix over 90 % of the total phosphorus content. XANES analysis indicated that hydroxyapatite emerged as the predominant phosphorus fraction in the solid-phase products, comprising more than 60 %, while magnesium ammonium phosphate components also appeared. This research elucidates the underlying mechanisms of component interaction and phosphorus transformation, providing a solid foundation for enhancing the reuse efficiency of phosphorus in wastes.