Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-modal RGBD Attention Fusion for Dense Depth Estimation

With the development of autonomous vehicles and augmented reality devices, LiDARs and cameras are becoming the main tools for object recognition. However, fusing information from multiple data sources is a challenging task in computer vision. One of the most promising directions of fusing is self-supervised training. However, previous works in this field focused only on simple mechanisms for fusion. In this paper, a novel model architecture with improved fusion blocks with attention mechanisms is presented. A comparison of the impact of input modalities and loss functions on the model is also provided. Experiments demonstrate the ability of presented fusion block in the LiDAR and camera data fusing. The proposed Neural network architecture and learning framework show promising results in depth completion tasks.
Spatial-Temporal Context-Aware Location Prediction Based on Bidirectional Self-Attention Network

The next-location prediction tasks get much attention because it is employed in many applications. The accuracy of location prediction has become the basis of these applications. The existing approaches related rely on transition matrices according to specific probabilistic rules or recurrent neural networks that cannot be applied to complex scenarios. Other works focus on extracting extra information in trajectory. In this paper, we propose a context-aware model with a bidirectional self-attention network for location prediction, which can capture implicit spatial-temporal patterns from the time stamps and geographical distances of locations. Besides, a training mechanism, Mask Locations, is employed to improve the prediction accuracy. We conduct experiments on two large-scale datasets: a check-in dataset and a Call Detail Record (CDR) dataset. The results show that our model significantly outperforms the competitive baseline methods.
Generation and detection of terahertz pulses from biased semiconductor antennas

We propose a simple model based on the Drude–Lorentz theory of carrier transport to account for the details of the ultrashort terahertz pulses radiated from small photoconductive semiconductor antennas. The dynamics of the bias field under the influence of the space-charge field from the accelerated carriers is included in the model. We consider in detail the optical system used to image the terahertz radiation onto the terahertz detector, and we calculate the frequency-dependent response of the detector. The proposed model is compared with several different experiments, each focusing on different parameters of the model. Agreement between experiment and model is found in all cases, supporting the validity of this simple and appropriate model.
ProFace: A Cancelable Face Template Protection Approach

Biometrics are increasingly being used for authentication purposes. It calls for biometric systems with enhanced recognition performance. Further, the sensitive nature of biometric data renders great significance to biometric security because of its potential misuse. Existing biometric template protection schemes, either degrade the recognition performance of the system or have security and efficiency limitations. We propose an end-to-end deep network based face template protection scheme, ProFace, which provides template security and high recognition performance. We use a user-specific, secret key to permute the face embedding obtained from a deep network, performing a cancelable transformation. Further, an improvised centre triplet loss function is proposed to optimize the network, ensuring robustness towards both the inter-class and intra-class variations. The permuted face embeddings obtained from the optimized deep neural network represent the protected templates. The proposed approach significantly improves recognition performance (EER reduces by atleast 50%) over the existing face template protection schemes on two publicly available face datasets, namely YouTube and CFP. Additionally, we observe a reduction in training time by 7 times in our proposed approach compared to the state-of-the-art face recognition scheme based on the triplet loss function.
Global output feedback stabilization for a class of nonlinear systems subjected to both multiple time-varying delays and zero dynamics

This paper investigates the problem of global output feedback stabilization for a class of time-delay nonlinear systems simultaneously subjected to dynamic uncertainties and an unknown output function. Compared with related celebrated works, the considered systems allow the existence of parameter uncertainties in the output function and nonlinearities, dynamic uncertainties of the unmeasurable state, and continuous external disturbances. A new systematic methodology is established by revamping the double-domination technique with the utilization of a dynamic-gain strategy, an output feedback controller together with a delicate state observer is established successfully, which guarantees the convergence of the states of the closed-loop systems. Finally, a simulation example is given to demonstrate the effectiveness of the theoretical results.
Maximum-entropy closure for a Galerkin model of an incompressible periodic wake

Abstract A statistical closure is proposed for a Galerkin model of an incompressible periodic cylinder wake. This closure employs Jaynes’ maximum entropy principle to infer the probability distribution for mode amplitudes using exact statistical balance equations as side constraints. The analysis predicts mean amplitude values and modal energy levels in good agreement with direct Navier–Stokes simulation. In addition, it provides an analytical equation for the modal energy distribution.
Numerical Maximisation of Likelihood: A Neglected Alternative to EM?

There is by now a long tradition of using the EM algorithm to find maximum‐likelihood estimates (MLEs) when the data are incomplete in any of a wide range of ways, even when the observed‐data likelihood can easily be evaluated and numerical maximisation of that likelihood is available as a conceptually simple route to the MLEs. It is rare in the literature to see numerical maximisation employed if EM is possible. But with excellent general‐purpose numerical optimisers now available free, there is no longer any reason, as a matter of course, to avoid direct numerical maximisation of likelihood. In this tutorial, I present seven examples of models in which numerical maximisation of likelihood appears to have some advantages over the use of EM as a route to MLEs. The mathematical and coding effort is minimal, as there is no need to derive and code the E and M steps, only a likelihood evaluator. In all the examples, the unconstrained optimiser nlm available in R is used, and transformations are used to impose constraints on parameters.
Two Extra Components in the Brier Score Decomposition

Abstract The Brier score is widely used for the verification of probability forecasts. It also forms the basis of other frequently used probability scores such as the rank probability score. By conditioning (stratifying) on the issued forecast probabilities, the Brier score can be decomposed into the sum of three components: uncertainty, reliability, and resolution. This Brier score decomposition can provide useful information to the forecast provider about how the forecasts can be improved. Rather than stratify on all values of issued probability, it is common practice to calculate the Brier score components by first partitioning the issued probabilities into a small set of bins. This note shows that for such a procedure, an additional two within-bin components are needed in addition to the three traditional components of the Brier score. The two new components can be combined with the resolution component to make a generalized resolution component that is less sensitive to choice of bin width than is th.
Ethylene in the circumstellar envelope of IRC+10216

Abstract Ethylene (C2H4) is a symmetric molecule that is best detected using mid-infrared transitions. We report on observations of the 10.5 μm ν7 band using the cryogenic grating spectrograph TEXES. These confirm the previous ethylene detection in the IRC+10216 circumstellar shell. We detect 18 ethylene lines. The lines are both narrow and weak with depths of no more than ~2%. The ethylene lines suggest an excitation temperature of ~80 K.
AoI-Aware Spectrum and Power Allocation for High-Speed Railway Networks

This paper studies a high-speed railway (HSR) network, where train-to-infrastructure (T2I) and train-to-train (T2T) transmissions co-exist. First, we analyze the age of information (AoI) of the T2T link to capture the freshness of data. Then, with the objective to maximize the sum data rate of T2I links, we formulate a resource allocation optimization problem subject to the data rate constraint of T2I links and the average AoI constraint of T2T links. Since the formulated problem has coupled optimizing variables and non-convex structure, we propose an AoI-aware spectrum and power allocation (AoI-ASPA) scheme to address it. In the proposed scheme, the optimization problem is decomposed into a power allocation subproblem and a spectrum allocation subproblem, and solved in two steps. For the power allocation subproblem, the optimal power allocation solution for each spectrum reusing pair is derived in an algebraic method. For the spectrum allocation subproblem, we transform it into a weighted bipartite matching problem and solve it by using the Kuhn-Munkres (KM) method. Simulation results verify the effectiveness of our proposed scheme.
On Gradient Coding With Partial Recovery

We consider a generalization of the gradient coding framework where a dataset is divided across <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> workers and each worker transmits to a master node one or more linear combinations of the gradients over its assigned data subsets. Unlike the conventional framework which requires the master node to recover the sum of the gradients over all the data subsets in the presence of straggler workers, we relax the goal to computing the sum of at least some <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> fraction of the gradients. We begin by deriving a lower bound on the computation load of any scheme and also propose two strategies which achieve this lower bound, albeit at the cost of high communication load and a number of data partitions which can be polynomial in <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>. We then propose schemes based on cyclic assignment which utilize <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> data partitions and have a lower communication load. When each worker transmits a single linear combination, we prove lower bounds on the computation load of any scheme using <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> data partitions. Finally, we describe a class of schemes which achieve different intermediate operating points for the computation and communication load and provide simulation results to demonstrate the empirical performance of our schemes.
Principally Quasi-Baer skew Generalized Power Series modules

Let R be a ring and S a strictly totally ordered monoid. Let ω: S → End(R) be a monoid homomorphism. Let M R be an ω-compatible module and either R satisfies the ascending chain conditions (ACC) on left annihilator ideals or every S-indexed subset of right semicentral idempotents in R has a generalized S-indexed join. We show that M R is p.q. -Baer if and only if the generalized power series module M[[S]] R[[S, ω]] is p.q. -Baer. As a consequence, we deduce that for an ω-compatible ring R, the skew generalized power series ring R[[S, ω]] is right p.q. -Baer if and only if R is right p.q. -Baer and either R satisfies the ACC on left annihilator ideals or any S-indexed subset of right semicentral idempotents in R has a generalized S-indexed join in R. Examples to illustrate and delimit the theory are provided.
Development of Digital Society: Factors Affecting the Usage of Mobile Payment in Jakarta Metropolitan Area

This study aims to identify factors that affecting the penetration of mobile payment in Jakarta Metropolitan Area. The Technology Acceptance Model (TAM) is used as underlying theory, with the addition of trust and perceived risk. The research methodology uses a quantitative approach. Data collection was done through the online distribution of e-questionnaires created in Google Forms. The sample collection method is non-probability sampling. The respondents are mobile payment users in Jakarta Metropolitan area who are at least 17 years old. This study used Structural Equation Model (SEM) method with the SmartPLS V3.0 tool to analyze the data gathered from 202 respondents. The results showed that perceived usefulness could encourage mobile payment adoption in Jakarta Metropolitan Area. The direct impact of perceived ease of use is insignificant, but it indirectly affects the intention to use mobile payment through perceived usefulness. Trust in perceived usefulness can stimulate the use of mobile payment in Jakarta Metropolitan Area. Conversely, the perceived risk has no effect on the intention to use mobile payment in Jakarta Metropolitan Area.
The abundance distributions of Galactic bulge and disc planetary nebulae

We present an abundance analysis of a sample of Galactic bulge planetary nebulae (GBPNe). The observational data set consists of spectra of 88 nebulae obtained with the FLAIR II multiobject spectrograph on the UK Schmidt Telescope, together with spectra of 42 nebulae obtained with the RGO Spectrograph on the Anglo-Australian Telescope. After selecting those for which reliable nebular electron temperatures could be derived, collisionally excited line abundances were derived for 45 GBPNe. These were then compared with similarly derived abundances for 54 Galactic disc PNe (GDPNe), taken from the work of Kingsburgh & Barlow. We find that within the errors the abundances have the same average values, essentially the same distributions – including that for the mass-sensitive N/O ratio – and show the same relationships. The width of the nitrogen distribution exceeds that arising from errors, which could be a consequence of the range of precursor masses. The ratio of Type-I to non-Type-I PNe in the bulge and disc samples is similar, 18 and 25 per cent respectively. For the GDPNe, we find larger N/H and N/O ratios for the small number of those with He/H > 0.14, compared with those with He/H < 0.14. For neither disc nor bulge sample is there any strong evidence for a depletion of oxygen for the higher-mass precursor stars (Type I PNe). We find no correlation between O/H and N/O or He/H. On the N/O to He/H plane, the bulge and disc PNe show a distribution whereby the low N/O values only occur for low He/H values, but at N/O > 0.25 the whole range of He/H values were sampled. The theoretical tracks to which we compare our data do not explain the PNe with low He/H abundance and high N/O ratio. Realistic uncertainties in collisionally excited lines (CEL) abundances for individual PNe are quite large, of the order of 40 per cent for oxygen. Large samples are therefore required to get good statistical accuracy. This is usually achieved by combining many studies, and so we have compared the results of a number of published studies with our own, to search for any systematic differences. The average abundances are found to be the same within the errors except for cases where the abundance derivation methods are dissimilar, where systematic differences can occur. The N/O ratio is especially sensitive to the details of the abundance derivations. Our bulge PN sample shows no evidence for either very-low-metallicity objects or for super-metal-rich objects – the implied mass and age distributions of the bulge PN precursor stars are indistinguishable within the observational errors from those in the local Galactic disc.
Prediction of Student's Wellbeing from Stress and Sleep Questionnaire data using Machine Learning Approach

A sound mental health has its benefits for the overall well-being of an individual. The decline in mental health conditions has a critical impression on other vital functionalities of the human system both psychologically and physiologically. And a student's well-being is largely contributed by the level of perceived stress and overall quality of nighttime sleep which might have evolved by various external factors over a while. The main objective of this study is to understand the correlation between Perceived Stress Scale (PSS) scores and Pittsburgh Sleep Quality Index (PSQI) global scores from StudentLife, a publicly available dataset over the period, and classify the well-being factor as ‘Good’ ‘Average’ and ‘Bad’ The linear regression model significantly demonstrated the association between PSS scores and Pittsburgh Sleep Quality Index (PSQI) scores. Machine Learning techniques like Decision Trees (DT), Support Vector Machine (SVM), and K-nearest neighbors(K-NN) were implemented on both Pre-Test and Post-test questionnaire data. While SVM resulted in better accuracy for Pre-test data, the K-NN classifier resulted in best accuracy for Post-test data, and the performance was evaluated using performance metrics like accuracy Precision, recall, and F1 score.
Transmission problems for Maxwell's equations with weakly Lipschitz interfaces

We prove sufficient conditions on material constants, frequency and Lipschitz regularity of interface for well posedness of a generalized Maxwell transmission problem in finite energy norms. This is done by embedding Maxwell's equations in an elliptic Dirac equation, by constructing the natural trace space for the transmission problem and using Hodge decompositions for operators d and δ on weakly Lipschitz domains to prove stability. We also obtain results for boundary value problems and transmission problems for the Hodge–Dirac equation and prove spectral estimates for boundary singular integral operators related to double layer potentials. Copyright © 2005 John Wiley & Sons, Ltd.
Displacements due to surface temperature variation on a uniform elastic sphere with its centre of mass stationary

SUMMARY We investigate the displacement field induced by temperature variation within a spherical thermal boundary layer under an Earth-like condition of surface heating by deriving analytical solutions on a uniform elastic sphere under the constraint that its centre of mass remains stationary in space. Similar to strain solutions, our displacement solution consists of spectra of two distinctive modes: an exponential mode relating to the thermal body force and a powerlaw mode relating to the (equivalent) thermal surface loading. The exponential modes of the thermalbodyforceinoursolutionturnouttobeidenticaltothatinaclassichalf-spacesolution, whiletheeffectofthermalloadingbythepower-lawmodesinoursphericalsolutionisdifferent from the exponential modes of thermal loading in the half-space solution. The thermal surface loadingisfound,byanalyticalandnumericalanalyses,equallyimportantinorderofmagnitude as the thermal body force in producing the radial displacement at the surface throughout the entire harmonic spectrum. The transverse displacement arises mainly from the power-law modes of thermal surface loading. Numerical simulations, based on NASA’s space-borne observation of the global land surface temperature (ocean is masked out), have shown unique patterns in the annual variation of the global displacement field that fits the climatological and geographical settings. The predicted amplitude of the thermally induced surface deformation in global scale is at the millimetre level with the largest ∼2mm for radial displacement and ∼1mm for transverse displacement. Comparative analysis shows that the radial displacement field is asymptotically proportional to the surface temperature distribution, which justifies the use of the half-space solution as a good approximation for modelling the global radial displacement. The transverse displacement obtained by patched half-space solution fails to capture the long-range transverse variations on a spherical surface, and thus, is inadequate for modelling and synthesizing the global transverse displacement.
Lubricant bonding via hydrogen bond network

Lubricants having a functional end group were bonded onto thin film magnetic disks through electrostatic interaction. The resulting lubricant layer exhibited a high degree of orientation such that long alkyl molecular chains aligned themselves perpendicular to the disk surface. Furthermore, the lubricants showed strong adhesion with various disk surfaces, especially carbon overcoats pretreated with UV radiation or NH/sub 3/ plasma treatment. Friction force during CSS test was decreased by using this lubricant system even on a smooth disk surface (Ra=40 /spl Aring/), which is due to the low surface energy of the organized lubricant layers. >
EVALUATION OF CERTAIN CLASSES OF EISENSTEIN-TYPE SERIES

Abstract In this paper, we consider certain classes of Eisenstein-type series involving hyperbolic functions, and prove some formulas for them which can be regarded as relevant analogues of our previous results. We can also regard these formulas as certain generalizations of the famous formulas for the ordinary Eisenstein series given by Hurwitz.
The mechanism of synchronization in feed-forward neuronal networks

Synchronization in feed-forward subnetworks of the brain has been proposed to explain the precisely timed spike patterns observed in experiments. While the attractor dynamics of these networks is now well understood, the underlying single neuron mechanisms remain unexplained. Previous attempts have captured the effects of the highly fluctuating membrane potential by relating spike intensity f(U) to the instantaneous voltage U generated by the input. This article shows that f is high during the rise and low during the decay of U(t), demonstrating that the -dependence of f, not refractoriness, is essential for synchronization. Moreover, the bifurcation scenario is quantitatively described by a simple relationship. These findings suggest as the relevant model class for the investigation of neural synchronization phenomena in a noisy environment.
Preliminary Results of X-Band Polarization Radar Studies of Clouds and Precipitation

Abstract Combined measurements of differential reflectivity and cross-correlation coefficient between linear copolar components of weather radar returns have been obtained with a noncoherent X-band polarimetric meteorological radar. In examining these data, special attention is devoted to the problem of discrimination between liquid and solid hydrometeors and to identification of the areas of strong ground-clutter contamination. Furthermore, polarization parameters of backscattered signals are used to locate updrafts.
Superconducting properties of MgB2/Fe tape heavily doped with nanosized SiC

The critical current density (Jc), upper critical field (Hc2) and irreversibility field (Hirr) have been investigated for powder-in-tube processed MgB2 tapes heavily doped with nanosized SiC up to x = 0.6 in MgB2+xSiC. We added nanosized SiC powders to the powder mixture of MgH2 plus amorphous B and carried out Jc and resistivity measurements in magnetic fields up to 30 T at 4.2 K for tapes made from these mixtures. A maximum C substitution for B of ∼3 at. % was obtained for 0.3 SiC addition. The value of Hirr at 4.2 K rose with increasing amounts of SiC addition, and a highest Hirr of ∼25.5 T was obtained for x = 0.2–0.4 SiC-doped tapes. At 4.2 K and 8 T, the optimum addition level for obtaining the highest Jc was in the 0.1 SiC-doped sample, while at 20 T the optimum addition level shifted to a 0.4 SiC-doped material. This shift can be explained by the enhancement of Hc2 and pinning effects of nanoparticles by the SiC addition. However, the highest levels of SiC addition resulted in large amounts of impurity phases such as Mg2Si and unreacted SiC. These impurities degrade the grain connectivity of MgB2 and reduce Jc with increasing doping levels.