Miracle-dz/UniFAR-FTUs huggingface dataset:
PatchSwap: Boosting the Generalizability of Face Presentation Attack Detection by Identity-aware Patch Swapping

Face presentation attack detection (PAD) is essential in mitigating spoofing attack vulnerabilities in face recognition systems. Despite the relatively good detection performance of PADs on known attacks, they tend to be challenged by unknown samples. To address this issue, we present our PatchSwap approach that aims at creating more challenging and complex bona fide, attack, and partial attack samples despite limited training resources. The PatchSwap operates by swapping intra-identity patches between training samples and correspondingly updates their pixel-wise mask label, all under a controlled strategy. The PatchSwap is deployed as an augmentation technique and can be effortlessly integrated into any model training process. The different choices towards our PatchSwap design are exhaustively investigated and proven in detailed studies. We conduct extensive experiments under intra-dataset and cross-dataset scenarios and on three different network backbones. The experimental results showed that the PatchSwap successfully induces significant gains in the PAD performance under different evaluation settings.
ON WIELANDT'S INEQUALITY AND ITS APPLICATION TO THE ASYMPTOTIC DISTRIBUTION OF THE EIGENVALUES OF A RANDOM SYMMETRIC MATRIX

A relatively obscure eigenvalue inequality due to Wielandt is used to give a simple derivation of the asymptotic distribution of the eigenvalues of a random symmetric matrix. The asymptotic distributions are obtained under a fairly general setting. An application of the general theory to the bootstrap distribution of the eigenvalues of the sample covariance matrix is given. 1. Introduction and summary. The derivation of the asymptotic distribution of the eigenvalues of a random symmetric matrix arises in many papers in multivariate analysis. Although the main idea behind most of the derivations is quite basic, i.e., the expansion of the sample roots about the population roots, the derivations themselves are often quite involved. These complications are primarily due to the mathematical rather than statistical nature of the eigenvalue problem. One of the main objectives of this paper is to introduce a simple method for obtaining the asymptotic distribution of the eigenvalue of random symmetric matrices. The method is based upon a relatively obscure eigenvalue inequality
UAV-Based Intelligent Reflecting Surface Transmission: Weighted Sum Rate Maximization of Wireless Network

Unmanned aerial vehicle (UAV) carrying intelligent reflecting surface (IRS) can serve as an aerial platform to improve the coverage area and transmission performance of traditional wireless network. In this paper, we investigate the weighted sum rate maximization problem for a UAV-assisted and IRS-based multi-user communication system. Specifically, by applying the alternating optimization approach, we propose a two-phase approach to effectively optimize the number of activated reflective elements, the precoding matrix, the phase shift, and the UAV location. Numerical results validate that the proposed approach can converge at a faster rate and improve the weighted sum rate performance.
Novel unimorph deformable mirror for ocular adaptive optics

This paper proposes a low-cost unimorph deformable mirror (DM) driven by positive voltages for ocular adaptive optics (AO). The DM consists of an inner actuators array and an outer ring actuator. The inner actuators array is used to correct aberrations, while the outer ring actuator is used to generate an overall defocus bias. The measurement results show that the maximum peak to valley defocus deformation is more than 14 μm. The DM has a satisfactory correction capability for up to the fifth order Zernike mode aberrations. Furthermore, a sample of 200 ocular wavefronts was simulated using a statistical model developed by Thibos. After correction with the developed DM, most of the simulated eyes achieved the diffraction-limited performance. These experimental and simulation results indicate that this DM is satisfactory for ocular applications.
On the Use of the SPRT in Determining the Properties of Some CUSUM Procedures

Abstract Let Y 1, Y 1,…, Y ν−1 be iid random variables with a distribution function (df) F(y, θ0) = F 0(y), and let Y ν, Y ν+1,… be iid random variables with a df F(y, θ1) = F 1(y), where ν (ν ≥ 1) is an unknown time index of a change in distribution caused by the change in parametric value. For a suitable function ψ let X j = ψ(Y j ) (j ≥ 1) denote some convenient data reduction or it is defined by certain optimality consideration such as the SPRT. Let W 0 = 0, W n = max(0, W n−1 + X n ), S 0 = 0, , n ≥ 1. For detecting a change in distribution, Page [Page, E.S. Continuous inspection schemes. Biometrika 1954, 41, 100–115] defined his famous CUSUM (cumulative sum) procedure by N = inf{n ≥ 1 : W n ≥ h}, h > 0, and noted that N is equivalent to a series of SPRT of the form M = inf{n ≥ 1 : S n ≤ 0orS n ≥ h} until there is exit at the upper boundary h. Moreover, from the inherent renewal property he noted that EN = EM/P(S M ≥ h), which is quite useful in approximating and/or evaluating EN. However, a deeper connection between N and M was noted by Khan [Khan, R.A. On cumulative sum procedures and the SPRT with applications. Journal of the Royal Statistical Society B 1984, 46, 79–85]. The purpose of this exposition paper is to further exploit such a relationship to study the properties of some more CUSUMs with several applicable examples. Exact results are attempted whenever possible otherwise suitable approximations are outlined.
Sensitivity simulations of orographic precipitation with MM5 and comparison with observations in Iceland during the Reykjanes Experiment

This paper presents a study of the sensitivity of numerically simulated precipitation across a mesoscale mountain range to horizontal resolution, cloud condensation nuclei (CCN) spectrum, initiation of cloud ice, numerical treatment of horizontal diffusion and initial and boundary conditions. The fifth generation Penn State/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model (MM5) is used in the study, in which the model is run at 8, 4 and 2 km horizontal resolutions and with a number of microphysical and numerical configurations. The model simulated precipitation is compared to the observed precipitation over the Reykjanes mountain ridge during the Reykjanes Experiment in Southwest Iceland in the autumn of 2002. Improvements in representation in topography at increasing horizontal resolutions yield large improvements in the accuracy of the simulated precipitation. At 8 km horizontal resolution the simulated maximum precipitation is too low, but the simulated precipitation upstream of the mountains is too high. The absolute values and the pattern of the precipitation field improve stepwise when going from horizontal resolutions of 8 km to 2 km, with the main contribution being when going from 8 km to 4 km. Calculations of diffusion and ice initiation do not seem to have a large impact on the simulated precipitation, which is on the other hand quite sensitive to the CCN spectrum. The simulations underestimate the precipitation over the downstream slopes of the mountain ridge by factors of 2-3. There are indications that this underestimation may be associated with a systematic overestimation of downslope winds, and possibly descending motion, by the model.
Discrimination of modulation depth of SAM noise

Difference limens (DLs) for modulation depth of sinusoidally amplitude modulated (SAM) wideband noise were measured as a function of the modulation depth of the standard, the frequency of modulation (25, 100, 400 Hz), and the spectrum level of the noise (0, 20, 40 dB SPL). Preliminary results for one subject show that psychometric functions are linear and parallel in Log d′ and 10 Log(m12 − m02), where m1 and m0 are the modulation depths of the variable and standard stimuli, respectively. In the main study, three subjects were tested using a 2IFC adaptive procedure. The DL [10 Log(m12 − m02)] is at, or slightly above, the modulation detection threshold when m0 is small. For m0 above modulation threshold, the DL is a positively accelerating function of 20 Log(m0). Weber's Law does not describe the discrimination of modulation depth over any appreciable range. Across all conditions, DLs tend to converge to values around −9 dB when the level of the standard is −5 dB (m0 = 56%) and generally cannot be measure.
Is the Earth's magnetotail balloon unstable?

The authors consider the ideal MHD stability of two-dimensional equilibrium models of the geomagnetic tail, where the magnetic field is in the xz plane and nothing depends on the coordinate y. Ballooning-type perturbations are considered for which [vert bar]k[sub y][vert bar]L[much gt]1, where L is the scale length for variation in the xz plane. They employ the energy principle to test the stability of each flux tube of the plasma sheet for a hard ionospheric boundary condition (v = 0) and present a physical argument suggesting that it is the most appropriate simple boundary condition for the Earth's plasma sheet. Numerical results are presented for compressible ballooning modes that are symmetric about the center of the current sheet. For such a hard boundary condition, they found no reasonable magnetotail configuration that was unstable to compressible symmetric ballooning but stable against interchange. Therefore compressible symmetric ideal-MHD ballooning seems incapable of substantially altering the large-scale configuration of the magnetotail.
Dark current study for CMOS fully integrated-PIN-photodiodes

PIN photodiodes are semiconductor devices widely used in a huge range of applications, such as photoconductors, charge-coupled devices and pulse oximeters for medical applications. The possibility to combine and to integrate the fabrication of the sensor with its signal conditioning circuitry in a CMOS process allows device miniaturization in addition to enhance its properties lowering the production and assembly costs. This paper presents the design and characterization of silicon based PIN photodiodes integrated in a CMOS commercial process. A high-resistivity, low impurity substrate is chosen as the start material for the PIN photodiode array fabrication in order to fabricate devices with a minimum dark current. The dark current is studied, analyzed and measured for two different starting materials and for different geometries. A model previously proposed is reviewed and compared with experimental data.
YIELDING OSCILLATOR UNDER TRIANGULAR GROUND ACCELERATION PULSE

An analytical solution is presented for the response of a bilinear inelastic simple oscillator to a symmetric triangular ground acceleration pulse. This type of motion is typical of near-fault recordings generated by source-directivity effects that may generate severe damage. Explicit closed-form expressions are derived for: (i) the inelastic response of the oscillator during the rising and decaying phases of the excitation as well as the ensuing free oscillations; (ii) the time of structural yielding; (iii) the time of peak response; (iv) the associated ductility demand. It is shown that when the duration of the pulse is long relative to the elastic period of the structure and its amplitude is of the same order as the yielding seismic coefficient, serious damage may occur if significant ductility cannot be supplied. The effect of post-yielding structural stiffness on ductility demand is also examined. Contrary to presently-used numerical algorithms, the proposed analytical solution allows many key response parameters to be evaluated in closed-form expressions and insight to be gained on the'response of inelastic structures to such motions. The model is evaluated against numerical results from actual near-field recorded motions. Illustrative examples are also presented.
MR.Brick: Designing A Remote Mixed-reality Educational Game System for Promoting Children’s Social & Collaborative Skills

Children are one of the groups most influenced by COVID-19-related social distancing, and a lack of contact with peers can limit their opportunities to develop social and collaborative skills. However, remote socialization and collaboration as an alternative approach is still a great challenge for children. This paper presents MR.Brick, a Mixed Reality (MR) educational game system that helps children adapt to remote collaboration. A controlled experimental study involving 24 children aged six to ten was conducted to compare MR.Brick with the traditional video game by measuring their social and collaborative skills and analyzing their multi-modal playing behaviours. The results showed that MR.Brick was more conducive to children’s remote collaboration experience than the traditional video game. Given the lack of training systems designed for children to collaborate remotely, this study may inspire interaction design and educational research in related fields.
Infrared Space Observatory Long Wavelength Spectrometer Observations of a Cold Giant Molecular Cloud Core near the Galactic Center

We have used the Long Wavelength Spectrometer aboard the Infrared Space Observatory in the grating mode to map the far-infrared continuum emission (45-175 μm) toward the massive giant molecular cloud core GCM 0.25+0.11 located near the Galactic center. Graybody models of the observed far-infrared spectral energy distribution indicate that the bulk of the dust in the diffuse component along the line of sight toward GCM 0.25+0.11 has a mean temperature of ~26 K and a 100 μm optical depth of ~0.17. GCM 0.25+0.11 is observed in emission at far-infrared (FIR) wavelengths (≳100 μm). However at midinfrared wavelengths (≲70 μm) the core is seen in absorption against the general Galactic center background. This indicates that GCM 0.25+0.11 is located in front of the bulk of the dust responsible for the diffuse FIR emission, most likely a few hundred parsecs from the Galactic center. By subtracting the spectrum of the diffuse component from the spectrum observed toward GCM 0.25+0.11, we have been able to extract the intrinsic spectrum of this GMC core. Graybody fits to the resulting far-infrared spectrum combined with our previous submillimeter measurements (350-800 μm) give a low temperature ~18 K for the bulk of the dust in the GCM 0.25+0.11 core. In addition, the grain emissivity is a very steep function of frequency (ν2.8). The high grain emissivity exponent is consistent with the presence of dust grains covered with thick ice mantles. We have complemented our ISO data with CO (2-1) and HCO+ (3-2) observations carried out with the Caltech Submillimeter Observatory. The molecular emission shows a large velocity gradient across the southern part of the core indicative of streaming motions of the gas or of the presence of multiple, spatially overlapping velocity components. The observed gas kinematics may indicate that GCM 0.25+0.11 is in the process of being disrupted by the strong tidal forces caused by the high mass concentration in the Galactic center region. This might explain why there is no evidence for ongoing high-mass star formation associated with this core, in spite of its large molecular mass. However, the mean H2 density of GCM 0.25+0.11 is well above the tidal stability limit for a Galactocentric distance of a few hundred parsecs implied by our observations. An alternative explanation is that we are witnessing the very early stage of a cloud-cloud collision that may result in a future star formation episode.
Calibration of the BATC Survey: Methodology and Accuracy

We describe in detail the extinction correction procedures used for the Beijing‐Arizona‐Taiwan‐Connecticut Sky Survey (BATC Survey). The survey covers the spectral range 3200–9900 Å by utilizing a set of 15 intermediate‐band filters. These filters are specifically designed to exclude most of the bright and variable night‐sky emission lines. We also present extinction coefficients for the filter passbands for typical photometric nights at the Xinglong Observing Station, Beijing Astronomical Observatory (where the observations of the survey are being carried out). Time‐dependent, low‐amplitude (∼1%), nightly extinction variation has been observed. Such variation is demonstrably independent of filter bandpass and air mass, with amplitudes ranging from ∼0.01 to ∼0.03 mag. The variation is plausibly caused by slowly varying (at ∼1%) atmospheric extinction, possibly related to changes in air pressure/temperature/humidity that occur during the night. An iterative fitting scheme has been developed to take this time‐varying component into account. We conclude that the survey can achieve its stated observational goal, namely, an absolute photometric calibration that is tied to the ABν system to an accuracy of 1% in all filters.
Adaptive Deep Neural Network Inference Optimization with EENet

Well-trained deep neural networks (DNNs) treat all test samples equally during prediction. Adaptive DNN inference with early exiting leverages the observation that some test examples can be easier to predict than others. This paper presents EENet, a novel early-exiting scheduling framework for multi-exit DNN models. Instead of having every sample go through all DNN layers during prediction, EENet learns an early exit scheduler, which can intelligently terminate the inference earlier for certain predictions, which the model has high confidence of early exit. As opposed to previous early-exiting solutions with heuristics-based methods, our EENet framework optimizes an early-exiting policy to maximize model accuracy while satisfying the given per-sample average inference budget. Extensive experiments are conducted on four computer vision datasets (CIFAR-10, CIFAR-100, ImageNet, Cityscapes) and two NLP datasets (SST-2, AgNews). The results demonstrate that the adaptive inference by EENet can outperform the representative existing early exit techniques. We also perform a detailed visualization analysis of the comparison results to interpret the benefits of EENet.
On the Dynamics of Revolving Fluids

So much of meteorology depends ultimately upon the dynamics of revolving fluid that it is desirable to formulate as clearly as possible such simple conclusions as are within our reach, in the hope that they may assist our judgment when an exact analysis seems impracticable. An important contribution to this subject is that recently published by Dr. Aitken. It formed the starting point of part of the investigation which follows, but I ought perhaps to add that I do not share Dr. Aitken’s views in all respects. His paper should be studied by all interested in these questions. As regards the present contribution to the theory it may be well to premise that the limitation to symmetry round an axis is imposed throughout.
Parameter Estimation-Based Observer for Linear Systems with Polynomial Overparameterization

An adaptive state observer is proposed for a class of overparametrized uncertain linear time-invariant systems without restrictive requirement of their representation in the observer canonical form. It evolves the method of Generalized Parameters Estimation-Based Observer design and, therefore, $(i)$ does not require to identify Luenberger correction gain parameters, $(ii)$ forms states using algebraic rather than differential equation. Additionally, the developed observer is applicable to systems with unknown output matrix and ensures exponential convergence of unmeasured state observation error under weak requirement of the regressor finite excitation. The effectiveness of the proposed solution is supported by simulation results.
Universal Neural-Cracking-Machines: Self-Configurable Password Models from Auxiliary Data

We introduce the concept of"universal password model"-- a password model that, once pre-trained, can automatically adapt its guessing strategy based on the target system. To achieve this, the model does not need to access any plaintext passwords from the target credentials. Instead, it exploits users' auxiliary information, such as email addresses, as a proxy signal to predict the underlying password distribution. Specifically, the model uses deep learning to capture the correlation between the auxiliary data of a group of users (e.g., users of a web application) and their passwords. It then exploits those patterns to create a tailored password model for the target system at inference time. No further training steps, targeted data collection, or prior knowledge of the community's password distribution is required. Besides improving over current password strength estimation techniques and attacks, the model enables any end-user (e.g., system administrators) to autonomously generate tailored password models for their systems without the often unworkable requirements of collecting suitable training data and fitting the underlying machine learning model. Ultimately, our framework enables the democratization of well-calibrated password models to the community, addressing a major challenge in the deployment of password security solutions at scale.
A rich molecular chemistry in the gas of the IC 348 star cluster of the Perseus Molecular Cloud

We present Spitzer 10–34 $\mu{\rm m}$ spectroscopic observations of the diffuse gas in the inner region of the star-forming region IC 348 of the Perseus Molecular Cloud. We find evidence for the strongest mid-IR bands of common molecules as H2, OH, H2O, CO2, and NH3 and of several carbonaceous molecules which may play an important role in the production of more complex hydrocarbons: HCN, C2H2, C4H2, HC3N, HC5N, C2H6, C6H2, C6H6. The excitation diagram of H2 reveals the presence of warm gas (270 ± 30 K) at the observed locations. Assuming this temperature, the derived abundances of CO2 and NH3 relative to H2 are 10−8 and 10−7, respectively. From the water lines we obtain an abundance of order 10−6 and higher gas temperatures. The abundances derived for HCN and C2H2, key molecules in the development of prebiotic building blocks, are of order 10−7 and 10−9, respectively. More complex molecules such as PAHs and the fullerenes C60 and C70 are also present. IC 348 appears to be very rich and diverse in molecular content. The JWST spectroscopic capabilities may provide details on the spatial distribution of all these molecules and extend the present search to more complex hydrocarbons.
COVINS-G: A Generic Back-end for Collaborative Visual-Inertial SLAM

Collaborative SLAM is at the core of perception in multi-robot systems as it enables the co-localization of the team of robots in a common reference frame, which is of vital importance for any coordination amongst them. The paradigm of a centralized architecture is well established, with the robots (i.e. agents) running Visual-Inertial Odometry (VIO) onboard while communicating relevant data, such as e.g. Keyframes (KFs), to a central back-end (i.e. server), which then merges and optimizes the joint maps of the agents. While these frameworks have proven to be successful, their capability and performance are highly dependent on the choice of the VIO front-end, thus limiting their flexibility. In this work, we present COVINSG, a generalized back-end building upon the COVINS [1] framework, enabling the compatibility of the server-back-end with any arbitrary VIO front-end, including, for example, off-the-shelf cameras with odometry capabilities, such as the Realsense T265. The COVINS-G back-end deploys a multi-camera relative pose estimation algorithm for computing the loop-closure constraints allowing the system to work purely on 2D image data. In the experimental evaluation, we show on-par accuracy with state-of-the-art multi-session and collaborative SLAM systems, while demonstrating the flexibility and generality of our approach by employing different front-ends onboard collaborating agents within the same mission. The COVINS-G codebase along with a generalized front-end wrapper to allow any existing VIO front-end to be readily used in combination with the proposed collaborative back-end is open-sourced. Video- https://youtu.be/FoJfXCfaYDw