Abstract: Perceptual aliasing is one of the main causes of the failure for simultaneous localization and mapping (SLAM) systems operating in the wild. Perceptual aliasing is a phenomenon where different places generate a similar visual (or, in general, perceptual) footprint. This causes spurious measurements to be fed to the SLAM estimator, which typically results in incorrect localization and mapping results. This problem is exacerbated by the fact that those outliers are highly correlated , in the sense that perceptual aliasing creates a large number of mutually consistent outliers. Another issue stems from the fact that most state-of-the-art techniques rely on a given trajectory guess (e.g., from odometry) to discern between inliers and outliers, and this makes the resulting pipeline brittle, since the accumulation of error may result in incorrect choices and recovery from failures is far from trivial. This paper provides a unified framework to model perceptual aliasing in SLAM and provides practical algorithms that can cope with outliers without relying on any initial guess. We present two main contributions. The first is a discrete–continuous graphical model ( DC-GM ) for SLAM: The continuous portion of the DC-GM captures the standard SLAM problem, while the discrete portion describes the selection of the outliers and models their correlation. The second contribution is a semidefinite relaxation to perform inference in the DC-GM that returns estimates with provable sub-optimality guarantees. Experimental results on standard benchmarking datasets show that the proposed technique compares favorably with state-of-the-art methods while not relying on an initial guess for optimization.

Abstract: We present a multi-robot system for GPS-denied search and rescue under the forest canopy. Forests are particularly challenging environments for collaborative exploration and mapping, in large part due to the existence of severe perceptual aliasing which hinders reliable loop closure detection for mutual localization and map fusion. Our proposed system features unmanned aerial vehicles (UAVs) that perform onboard sensing, estimation, and planning. When communication is available, each UAV transmits compressed tree-based submaps to a central ground station for collaborative simultaneous localization and mapping (CSLAM). To overcome high measurement noise and perceptual aliasing, we use the local configuration of a group of trees as a distinctive feature for robust loop closure detection. Furthermore, we propose a novel procedure based on cycle consistent multiway matching to recover from incorrect pairwise data associations. The returned global data association is guaranteed to be cycle consistent, and is shown to improve both precision and recall compared to the input pairwise associations. The proposed multi-UAV system is validated both in simulation and during real-world collaborative exploration missions at NASA Langley Research Center.

Abstract: Purpose To introduce a quantitative tool that enables rapid forecasting of T1 and T2 parameter map errors due to normal and aliasing noise as a function of the MR fingerprinting (MRF) sequence, which can be used in sequence optimization. Theory and methods The variances of normal noise and aliasing artifacts in the collected signal are related to the variances in T1 and T2 maps through derived quality factors. This analytical result is tested against the results of a Monte-Carlo approach for analyzing MRF sequence encoding capability in the presence of aliasing noise, and verified with phantom experiments at 3 T. To further show the utility of our approach, our quality factors are used to find efficient MRF sequences for fewer repetitions. Results Experimental results verify the ability of our quality factors to rapidly assess the efficiency of an MRF sequence in the presence of both normal and aliasing noise. Quality factor assessment of MRF sequences is in agreement with the results of a Monte-Carlo approach. Analysis of MRF parameter map errors from phantom experiments is consistent with the derived quality factors, with T1 (T2 ) data yielding goodness of fit R2 ≥ 0.92 (0.80). In phantom and in vivo experiments, the efficient pulse sequence, determined through quality factor maximization, led to comparable or improved accuracy and precision relative to a longer sequence, demonstrating quality factor utility in MRF sequence design. Conclusion The here introduced quality factor framework allows for rapid analysis and optimization of MRF sequence design through T1 and T2 error forecasting.

Abstract: The antileakage least-squares spectral analysis is a new method of regularizing irregularly spaced data series. This method mitigates the spectral leakages in the least-squares spectrum caused by non-orthogonality of the sinusoidal basis functions on irregularly spaced series, and it is robust when data series are wide-sense stationary. An appropriate windowing technique can be applied to adapt this method to non-stationary data series. When data series present mild aliasing, this method can effectively regularize the data series; however, additional information or assumption is needed when the data series is coarsely sampled. In this paper, we show how to incorporate the spatial gradients of the data series into the method to regularize data series presenting severe aliasing and show its robust performance on synthetic and marine seismic data examples.

Abstract: WaveCycleGAN has recently been proposed to bridge the gap between natural and synthesized speech waveforms in statistical parametric speech synthesis and provides fast inference with a moving average model rather than an autoregressive model and high-quality speech synthesis with the adversarial training. However, the human ear can still distinguish the processed speech waveforms from natural ones. One possible cause of this distinguishability is the aliasing observed in the processed speech waveform via down/up-sampling modules. To solve the aliasing and provide higher quality speech synthesis, we propose WaveCycleGAN2, which 1) uses generators without down/up-sampling modules and 2) combines discriminators of the waveform domain and acoustic parameter domain. The results show that the proposed method 1) alleviates the aliasing well, 2) is useful for both speech waveforms generated by analysis-and-synthesis and statistical parametric speech synthesis, and 3) achieves a mean opinion score comparable to those of natural speech and speech synthesized by WaveNet (open WaveNet) and WaveGlow while processing speech samples at a rate of more than 150 kHz on an NVIDIA Tesla P100.

Abstract: Finite-grid (or aliasing) instabilities are pervasive in particle-in-cell (PIC) plasma simulation algorithms, and force the modeler to resolve the smallest (Debye) length scale in the problem regardless of dynamical relevance. These instabilities originate in the aliasing of interpolation errors between mesh quantities and particles (which live in the space-time continuum). Recently, strictly energy-conserving PIC (EC-PIC) algorithms have been developed that promise enhanced robustness against aliasing instabilities. In this study, we confirm by analysis that EC-PIC is stable against aliasing instabilities for stationary plasmas. For drifting plasmas, we demonstrate by analysis and numerical experiments that, while EC-PIC algorithms are not free from these instabilities in principle, they feature a benign stability threshold for finite-temperature plasmas that make them usable in practice for a large class of problems (featuring ambipolarity and realistic ion-electron mass ratios) without the need to resolve Debye lengths spatially. We also demonstrate that this threshold is absent for the popular momentum-conserving PIC algorithms, which are therefore unstable for both drifting and stationary plasmas.

Abstract: Medical imaging is playing a more and more important role in clinics. However, there are several issues in different imaging modalities such as slow imaging speed in MRI, radiation injury in CT and PET. Therefore, accelerating MRI, reducing radiation dose in CT and PET have been ongoing research topics since their invention. Usually, acquiring less data is a direct but important strategy to address these issues. However, less acquisition usually results in aliasing artifacts in reconstructions. Recently, deep learning (DL) has been introduced in medical image reconstruction and shown potential on significantly speeding up MR reconstruction and reducing radiation dose. In this paper, we propose a general framework on combining the reconstruction model with deep learning to maximize the potential of deep learning and model-based reconstruction, and give the examples to demonstrate the performance and requirements of unrolling different algorithms using deep learning.

Abstract: Sequence stratigraphy remains the foremost methodology used to describe the stratigraphic record and to interpret the controls on deposition; yet, it relies on long-standing assumptions that few studies have sought to validate. Here, we present results from testing hypotheses related to the deep-water depositional sequence model by revisiting the seismic-based type locality: the Mississippi Fan, in the central Gulf of Mexico. By independently testing the relationship between cycles of relative sea-level change and those of sedimentation, we demonstrate that >98% of Neogene–Quaternary deep-water sequences do not accumulate in a manner prescribed by long-held sequence stratigraphic conventions. Instead, over the past 5.5 Myr, sequences show a temporal mismatch in frequency, phase, and amplitude with cycles of relative sea-level change, a concept we refer to as stratigraphic aliasing. Divergences are attributed to variable rates of sedimentation, which were responsible for creating cycle frequencies that were both higher and lower than those of relative sea-level change, and that resulted in two modes of Mississippi Fan accumulation: lower average sedimentation rates in older sediments, and an opposite trend in younger successions. The latter mode occurred ~2.2 Myr after the onset of North American glaciation, a period marked by significant continental drainage reorganization and salt-tectonic deformation. Based on our conclusions, we recommend that the future of sequence stratigraphy be rooted firmly in assessing the reproducibility of preexisting spatiotemporal predictions and in the rigorous use of multiple working hypotheses. INTRODUCTION For over 40 years, depositional systems have been thought to be controlled by the interaction of eustasy and subsidence (i.e., “relative sea level” of Jervey, 1988), with variability in sediment supply providing a secondary effect (see Vail et al., 1977; Posamentier et al., 1988; Van Wagoner et al., 1990). According to this view, relative sea-level change drives reciprocal sedimentation, whereby condensed sections and nearshore deposits accumulate during rises and high stands, and erosional surfaces and deepwater accumulations deposit during falls and low stands (Figs. 1A and 1B). While active debate regarding both controlling mechanisms and their stratigraphic responses has been ongoing since the late 1980s (see Haq et al., 1987; Christie-Blick et al., 1988), the community remains divided on the level of applicability of sequence stratigraphy (see Madof et al., 2016; Burgess, 2016), on its status as a workflow as opposed to a paradigm (see Burgess and Prince, 2016; Catuneanu and Zecchin, 2016), and on its ability to be treated as a set of testable hypotheses (this study). The Mississippi Fan, in the central Gulf of Mexico, serves as the type locality for the seismic-based model of the deep-water depositional sequence. In addition to Weimer (1990), other workers identified Mississippi Fan lobes from downlapping reflections at the base of gullwingshaped deposits (Garrison et al., 1982) and related accumulations to falls in relative sea level (Bouma et al., 1985). While these concepts have been applied globally to deep-water systems, few studies have sought to validate the initial findings. Here, we revisited the Mississippi Fan in an attempt to independently reproduce the relationship between relative sea-level change and sedimentation, and to test whether the latter is controlled by changes in the former. By testing long-standing conventions, we offer new insights into the time-varying interactions between purported drivers and accumulation, and into the effect of climatic and tectonic signals on modulating inherently nonstationary deposition. MISSISSIPPI FAN, GULF OF MEXICO The Neogene–Quaternary Mississippi Fan in the central Gulf of Mexico is one of the most well-studied submarine fans on Earth. Because of the abundance of subsurface data, it has been used to understand deep-water stratigraphic archi tecture and cyclicity, as well as relative sea-level change and sedimentation. Architecture and Cyclicity The Mississippi Fan is a submarine accumulation >4 km in thickness situated outboard of the Sigsbee Escarpment. Based on downlapping reflections (i.e., geometric evidence for sequence boundaries), Weimer (1990) interpreted 17 laterally compensatory deep-water sequences (Fig. 2A) and inferred each to be composed of channelized (coarse-grained) deposits flanked by levee-overbank (fine-grained) deposits. By incorporating age control, Weimer and Dixon (1994) showed that sequence duration generally decreased from 0.66 Myr (5.5–4.84 Ma; sequence number 1) to 0.023 Myr (0.23–0.0 Ma; sequence number 17) and increased in lateral extent and overall thickness through time (Figs. 2B and 2C). In addition to the duration of sequences, Weimer and Dixon (1994) interpreted two major hiatuses, from 3.0 to 1.9 Ma and from 0.45 to 0.086 Ma. While Weimer and Dixon (1994) may have incorrectly assumed that seismic reflections were laterally continuous synchronous surfaces, alternative interpretations have not yet been proposed. Sea Level and Sedimentation We calculated relative sea-level change and sedimentation rates independently for the last CITATION: Madof, A.S., et al., 2019, Stratigraphic aliasing and the transient nature of deep-water depositional sequences: Revisiting the Mississippi Fan: Geology, v. 47, p. 545–549, https:// doi .org /10 .1130 /G46159.1 Manuscript received 26 December 2018 Revised manuscript received 19 February 2019 Manuscript accepted 25 March 2019 https://doi.org/10.1130/G46159.1 © 2019 The Authors. Gold Open Access: This paper is published under the terms of the CC-BY license. Published online 16 April 2019 Downloaded from https://pubs.geoscienceworld.org/gsa/geology/article-pdf/4707771/545.pdf by guest on 31 October 2019 546 www.gsapubs.org | Volume 47 | Number 6 | GEOLOGY | Geological Society of America 5.5 Myr of growth of the Mississippi Fan (Figs. 3A and 3B). The former was constructed by adding the eustatic record of Miller et al. (2005, their fig. 3, created from the benthic foraminiferal δ18O record) to the back-stripped subsidence rate of the northern Gulf of Mexico of Diegel et al. (1995, their fig. A-3). While specific details regarding the construction of the sub sidence curve remain unclear, it serves as the most robust (if not the only) example for the area. Sedimentation rates for each Mississippi Fan sequence were calculated by dividing maximum preserved thickness (from Fig. 2A) by duration (from Fig. 2B); rates span two orders of magnitude, with older sequences displaying lower average accumulation rates (i.e., 104 cm/Myr), and younger ones showing an opposite trend (i.e., 106 cm/Myr). Based on our analysis, the bulk of long-term relative sea-level change in the Mississippi Fan was caused by subsidence related to salt withdrawal, rather than by eustatic change. Fi g u re 1. S ch e m a t i c diagram of reciprocal sedimentation and deep-water depositional sequence model. A: Two-dimensional transect along continental margin showing shelfal accumulations developing during relative sea-level high stands and rises, and slope-tobasinal sedimentation occurring during low stands and falls. B: Each deep-water sequence develops during one cycle of relative sea-level change (modified from Posamentier and Kolla, 2003), during which rate of sedimentation decreases. Sedimentation-rate curve was created by dividing facies thickness (from hypothetical well log) by duration (from relative sea-level curve) and normalizing to maximum rate. Abbreviations are as follows: RSL—relative sea level; SR—sedimentation rate; HS—high stand; LS—low stand. A

Abstract: Nonlinear systems, such as guitar distortion effects, play an important role in musical signal processing. One major problem encountered in digital nonlinear systems is aliasing distortion. Consequently, various aliasing reduction methods have been proposed in the literature. One of these is based on using the antiderivative of the nonlinearity and has proven effective, but is limited to memoryless systems. In this work, it is extended to a class of stateful systems which includes but is not limited to systems with a single one-port nonlinearity. Two examples from the realm of virtual analog modeling show its applicability to and effectiveness for commonly encountered guitar distortion effect circuits.

Abstract: The avoidance of spatial aliasing is a major challenge in the practical implementation of sound field synthesis. Such methods aim at a physically accurate reconstruction of a desired sound field inside a target region using a finite ensemble of loudspeakers. In the past, different theoretical treatises of the inherent spatial sampling process led to anti-aliasing criteria for simple loudspeaker array arrangements, e.g., lines and circles, and fundamental sound fields, e.g., plane and spherical waves. Many criteria were independent of the listener's position inside the target region. Within this paper, a geometrical framework based on ray-approximation of the underlying synthesis problem is proposed. Unlike former approaches, this model predicts spatial aliasing artefacts for arbitrary convex loudspeaker arrays and as a function of the listening position and the desired sound field. Anti-aliasing criteria for distinct listening positions and extended listening areas are formulated based on the established predictions. For validation, the model is applied to different analytical sound field synthesis approaches: The predicted spatial structure of the spatial aliasing agrees with numerical simulation of the synthesised sound fields. Moreover, it is shown within this framework, that the active prioritization of a control region using so-called local sound field synthesis approaches does indeed reduce spatial aliasing artefacts. For the scenario under investigation, a method for local wave field synthesis achieves an artefact-free synthesis up to a frequency which is between 2.9 and 17.3 times as high as for conventional wave field synthesis.

Abstract: Cycles in population dynamics are abundant in nature and are understood as emerging from the interaction among coupled species. When sampling is conducted at a slow rate compared to the population cycle period (aliasing effect), one is prone to misinterpretations. However, aliasing has been poorly addressed in coupled population dynamics. To illustrate the aliasing effect, the Lotka–Volterra model oscillatory regime is numerically sampled, creating prey–predator cycles. We show that inadequate sampling rates may produce inversions in the cause-effect relationship among other artifacts. More generally, slow acquisition rates may distort data interpretation and produce deceptive patterns and eventually leading to misinterpretations, as predators becoming preys. Experiments in coupled population dynamics should be designed that address the eventual aliasing effect.

Abstract: In the point-based method, the aliasing phenomenon in the hologram plane is usually considered as a harmful phenomenon because it will degrade the reconstructed image quality. In this paper, the advantage of the aliasing phenomenon is employed to improve the reconstructed image quality of the phase-only hologram. Through analysis of the principle of this phenomenon, we proposed a method to improve the reconstructed image quality of the phase-only hologram. By controlling the strength of the aliasing, the amplitude distribution in the hologram plane can be turned into a nearly uniform distribution. It is helpful to generate an optimized phase-only hologram, which results in higher quality of the reconstructed image because the effect of lost information caused by abandon the amplitude part can be diminished. Moreover, a holographic see-through display system is designed to demonstrate the effectiveness of the proposed method.

Abstract: Though unresolved by Argo floats, internal waves still impart an aliased signal onto their profile measurements. Recent studies have yielded nearly global characterization of several consti...

Abstract: Source location based on polarization angle information is a research hot spot in the field of shallow distributed source localization. The near-field P-wave and S-wave aliasing are severe and the polarization characteristics of the wave group are poor, making it difficult to extract the polarization angle, an important source localization parameter. To address the above difficulty, this paper proposes a method that is based on high-resolution parabolic Radon transform (HRP-Radon) and incorporates adaptive covariance matrix (ACM) to extract the polarization angle information of the wavefront. First, a data set is constructed from the data acquired by the sensor array, and this data set is morphologically corrected against the first break time information. Second, the time domain data set is converted into the Radon domain by HRP-Radon, and the direct P-wave is extracted from the aliasing information by use of the focusing characteristics of the P-wave and S-wave and the phase characteristics of the far-field P-wave. Third, a model is built using the ACM algorithm to extract the direct P-wave angle information and the angle extraction is assessed using a metric-polarization method. The numerical simulation and experimental results show that the proposed method is able to extract the wavefront angle information of the blasting near-field aliasing signal and determine the source location from the polarization angle information. This method is of practical value to the field of underground space.

Abstract: The array is a fundamental data structure that provides an efficient way to store and retrieve non-sparse data contiguous in memory. Arrays are important for the performance of many memory-intensive applications due to the design of modern memory hierarchies: contiguous storage facilitates spatial locality and predictive access patterns which enables prefetching. Operations on large arrays often lend themselves well to parallelisation, such as a fork-join style divide-and-conquer algorithm for sorting. For parallel operations on arrays to be deterministic, data-race freedom must be guaranteed. For operations on arrays of primitive data, data-race freedom is obtained by coordinating accesses so that no two threads operate on the same array indices. This is however not enough for arrays of non-primitives due to aliasing: accesses of separate array elements may return pointers to the same object, or overlapping structures. Reference capabilities have been used successfully in the past to statically guarantee the absence of data-races in object-oriented programs. This paper presents the first extension of reference capabilities -- called array capabilities -- that support concurrent and parallel operations on arrays of both primitive and non-primitive values. In addition to element access, array capabilities support the abstract manipulation of arrays, logical splitting of arrays into subarrays, and merging subarrays. These operations allow expressing a wide range of array use cases. This paper presents the array capability design space and show how it applies to a number of array use cases. The core ideas are formalised and proven sound in a simple calculus, along with a proof that shows that well-typed programs with array capabilities are free from data-races.

Abstract: Signal aliasing is an inevitable consequence of using fractional factorial designs. Unlike linear models with fixed factorial effects, for Gaussian random field models advocated in some Bayesian design and computer experiment literature, the issue of signal aliasing has not received comparable attention. In the present article, this issue is tackled for experiments with qualitative factors. The signals in a Gaussian random field can be characterized by the random effects identified from the covariance function. The aliasing severity of the signals is determined by two key elements: (i) the aliasing pattern, which depends only on the chosen design, and (ii) the effect priority, which is related to the variances of the random effects and depends on the model parameters. We first apply this framework to study the signal-aliasing problem for regular fractional factorial designs. For general factorial designs including nonregular ones, we propose an aliasing severity index to quantify the severity of signal aliasing. We also observe that the aliasing severity index is highly correlated with the prediction variance.

Abstract: Aliasing is a well-known effect in imaging which leads potentially to disturbing artefacts on structures. While the high pixel count of todays devices helps to reduce this effect, at the same time optical anti-aliasing filter are more often removed from sensor stacks to improve on system SFR and quantum efficiency. While the artefact is easy to see, an objective measurement and quantification of aliasing is not standardised or established. In this paper we show an extension to existing SFR measurement procedures described in ISO12233 which can measure and quantify the existence of aliasing in the imaging system. It utilises the harmonic Siemens star of the s-SFR method and can be included into existing systems, so does not require the capture of additional images. Introduction In dictionaries, aliasing is defined as ”the misidentification of a signal frequency, introducing distortion or error”. Aliasing in images appears as an artefact where an object with fine repeated pattern is reproduced in broader pattern. This so called Moire effect is also shown in an example in figure 1. The high spatial frequencies generated by the chair are projected onto the image sensor and result in lower spatial frequencies. So the object has a certain spatial frequency fo and the sensor can sample this with its own sampling frequency fs. The Nyquist-Shannon sampling theorem states that the sampling frequency fs needs to be at least double of the fo to be sufficient. If the sampling frequency is not sufficient, higher spatial frequencies might lead to aliasing. Figure 1. Detail of an image, showing the so called moire effect. The high spatial frequencies generated by the monochrome structures are reproduced as low frequency, coloured structures. So avoid aliasing it needs to me made sure that the object frequencies are low pass filtered before the sampling to avoid too high frequencies. In signal processing this is performed by digital filter, in sensors this is done by optical low pass filter, also called anti-aliasing filter. To maximise the performance in terms of low light sensitivity and optical resolution, many sensors in todays cameras do not feature an anti aliasing filter, so aliasing might occur in the image. While aliasing can be an annoyance for the user, it can also influence resolution measurement. Examples from a resolution measurement are shown in figure 2. The images show the center part of a sinusoidal Siemens star as used for the s-SFR measurement described in ISO12233[2]. In these images, three white circles are plotted. These represent 50%, 75% and 100% of the so called Nyquist frequency. This frequency is the theoretical highest spatial frequency that can rendered. Expressed in unit cycles/pixel the Nyquist frequency is fNyquist = 0.5 as two pixel are required to represent one cycle, which means that a single pixel can represent a half cycle. With this assumption, we can calculate the Nyquist frequency for a given Siemens star as shown in Equation 1. f = ncycles circumference = ncycles 2πr fNyquist = 0.5 cycles pixel rNyquist = ncycles π with rNyquist = radius of Nyquist frequency ncycles = cycles per full circle (here: 144) (1) It can be observed in these images, that aliasing can occur even for lower frequencies than the calculated fNyquist . The reason for this is, that the assumptions made here do not take into account that most sensors do not sample every color with every pixel, but use a color filter array and demosaicing, so the true sampling frequency is lower than the final pixel count in the image. A sensor that does not use a color filter array (like monochrome sensors) can show higher frequencies than assumed from equation 1 as we measure different orientations in a Siemens star. In diagonal orientation the sampling is different to the sampling in horizontal or vertical direction. As aliasing can lead to lower frequencies with high amplitude, this can interfere with the resolution measurement. To make the measurement more robust, we need a method to be able to tell if a measurement result is ”trustworthy” or if it is influenced by aliasing. Concept The concept to measure aliasing is an extension to the s-SFR measurement procedure described in ISO12233. The used test pattern is shown in figures 2 and 3. Figure 2. Detail of center region of a Siemens star. White circles show 50%, 75% and 100% of Nyquist frequency.Top: A D-SLR camera with typical bayer pattern senso. One can observe aliasing artefacts well below fNyquist Bottom: A Foveon Sensor without bayer pattern. One can see resolution above fNyquist in diagonal direction. To obtain the SFR from a Siemens star, the center of the star is located and digital values are read out for a single radius over angle φ . The function I(φ)1 describes the digital value I depending on the mean value a and the amplitude b which is scaled by the cosine of the frequency (2π/g) and the phase corrected angle φ −φ0. The standard document shows a fitting algorithm to obtain a and b, which is used to calculate the modulation. So the modulation is calculated for a given radius, the radius defines the spatial frequency. Calculating the modulation for all available radii will provide the s-SFR. The standard also states, that the phase is unknown and describes the method to obtain the phase by fitting a sinus and cosinus as in equation 3 and then calculate b as in equation 4. I(φ) = a+b · cos 󰀕 2π g (φ −φ0) 󰀖 (2) I(φ) = a+b1 · cos 󰀕 2π g φ 󰀖 +b2 · cos 󰀕 2π g φ 󰀖 (3) b = 󰁴 b1 +b 2 2 (4) 1Equations cited from standard document. Figure 3. The sinusoidal Siemens star for the S-SFR method described in ISO12233. So in the standard procedure the assumption is made that the frequency is known. In case of aliasing, this assumption is questionable. The core idea of this paper is to check if the assumption about the spatial frequency is correct or not. So if the real frequency differs significantly from the assumed frequency, we consider this as evidence for aliasing. The first approach was to not only get the amplitude and phase from a fitting algorithm, but to also fit the frequency. We choose to implement the Gauss-Newton algorithm to minimise the residuals while estimating all relevant parameter of the equation 5. I(φ) = A0 · sin(B0 ·φ +C0)+D0 (5) Figure 4 visualises the iterative process of this algorithm. Starting from an initial estimation, the algorithm will minimise the residual error in every step, ideally approaching an ideal solution after a reasonable amount of iterations. While this worked well if the initial guess was good, we found many cases where this unconstrained method did not lead to a solution when the initial guess was not good. So after some improvement, we finally decided not to go forward in this direction. 0 50 100 0 10 20 30 40 Estimate A 0 50 100 146.5 147 147.5 148 148.5 Estimate D 0 50 100 -1.6 -1.55 -1.5 -1.45 -1.4 -1.35 -1.3 Estimate C 0 50 100 -25 -20 -15 -10 -5 0 5 Estimate D 0 50 100 13.273 13.274 13.275 13.276 13.277 13.278 Residuals Figure 4. Iterative estimation of the parameter in equation 4 The residuals shall minimise. The now used approach is to focus on the frequency only. The standard itself describes the method to obtain amplitude and phase. In the standards approach, the frequency is taken as given. For the aliasing analysis, the same fitting approach is applied for a sequence of frequencies with the assumed frequency as highest frequency. -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 phi -150 -100 -50 0 50 100 150 D ig ita l V al ue (n or m al iz ed ) pixelvalues cosinus vector sinus vector -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 phi -150 -100 -50 0 50 100 150 D ig ita l V al ue (n or m al iz ed ) pixelvalues phase fitted Figure 5. As described in ISO12233, the amplitude and phase is fitted. Top: Fitting with sinus and cosines Bottom: The fitting with correct phase, obtained from sinus and cosines. For every frequency step (only assumed frequency and lower), the amplitude and phase is fitted and then the error between fitted function and the measured pixel values is calculated (see fig. 6). This algorithm, to check which frequency leads to the lowest error, is then applied for all radii of the Siemens star. For every radius, the frequency with the lowest error is divided by the assumed frequency. So if the aliasing value equals one, the assumed frequency and the obtained frequency in the image are identical. The lower the value, the higher the differences. 0 50 100 150 frequency (periods per circle) 0.2 0.25 0.3 0.35 0.4 0.45

Abstract: This paper extends a companion paper on compilation for target platforms with hidden deterministic hardware aliasing to generate aliasing as well as compensate for it, in so-called 'chaotic' compilation. That may be applied in encrypted computing to statistically hide any information inadvertently introduced by a human programmer. A prototype compiler implementing the technology currently covers all of ANSI C except longjmp/setjmp, and this paper sketches a proof that it protects against polynomial complexity attacks on runtime data.

Abstract: A method may include receiving an outbound communication directed to one or more recipient addresses from a communications infrastructure hosting the true address for the user. A server or similar intermediary may generate an alias address for each recipient address in an outbound communication so that each recipient may communicate with the true address using a unique reply channel. A discrete security state may be assigned as a security attribute to each such alias address. The discrete security state, which can be controlled by the user and stored, e.g., at the intermediate server, establishes rules for controlling communications from one of the recipient addresses through the communications infrastructure to the true address via one of the alias addresses. Once an alias and a security state are assigned in this manner to facilitate handling of responsive communications, the outbound communication may be forwarded to recipient addresses through the communication network.

Abstract: Hardware aliasing occurs when the same logical address can access different physical memory locations. This is a problem for software on some embedded systems and more generally when hardware becomes faulty in irretrievable locations, such as on a Mars Lander. We show how to work around the hardware problem with software logic, compiling code so it works on any platform with hardware aliasing with hidden determinism. That means: (i) a copy of an address accesses the same location, and (ii) repeating an address calculation exactly will repeat the same access again. Stuck bits can mean that even adding zero to an address can make a difference in that environment so nothing but a systematic approach could work.

Abstract: Advanced LWIR sensors have recently emerged that have all or some of the following features: large array formats, small detectors, Fλ/d over 2 (well-sampled and low in-band aliasing), and ROICs capable of using all available photons (either through deep wells, faster framerates, or digital readout). We have spent the past year studying MTF restoration techniques for these systems. Initial application of our restoration approach (called PWP for the combination of small pitch, deep electron wells, and image processing) have encountered issues with real imagery. Problems for implementing restoration may include: fixed pattern noise, aliasing, and interpolation methods. We provide an update on our findings and a path forward for successful optimization of future advanced LWIR imagers.