Samsung (Israel)

Robust face anti-spoofing (FAS) is essential for secure facial recognition systems. This article presents a novel hybrid sensor approach using sparsely linear polarization pixels integrated into an RGB pixel matrix to leverage both angle of linear polarization (AoLP) and degree of linear polarization (DoLP). The sparse pixel integration overcomes the vulnerabilities of conventional RGB-based methods and the complexity of multisensor solutions. By integrating polarization features into a lightweight convolutional neural network (CNN), our solution offers a cost-effective and reliable FAS under all light conditions. Experimental results show that combining AoLP and DoLP significantly boosts accuracy compared to methods relying solely on RGB or DoLP, achieving an average classification error rate (ACER) as low as 0.4%, even with an extremely sparse deployment of polarization pixels (1 per 400 RGB pixels). An ablation study quantifies the individual contributions of AoLP and DoLP. Moreover, the system sustains its efficacy in challenging low-light scenarios and delivers a 10-fold reduction in errors compared to RGB-based methods. These findings underscore the potential of this single-sensor, low-compute solution for secure, affordable deployments in mobile devices and embedded systems.

We consider a line network of nodes connected by additive white Gaussian noise channels and equipped with local feedback. We study the velocity at which information spreads over this network. For the transmission of a data packet, we derive an explicit positive lower bound on the velocity for any packet size. Furthermore, we consider streaming, that is, transmission of data packets that is generated at a given average arrival rate. We show that a positive velocity exists as long as the arrival rate is below the individual Gaussian channel capacity and provide an explicit lower bound. Our analysis involves applying pulse-amplitude modulation to the data (successively in the streaming case) and using linear mean-squared error estimation at the network nodes. Due to the analog-linear nature of the scheme, the results extend to any additive noise. For general noise, we derive exponential error-probability bounds. Moreover, for (sub-)Gaussian noise, we show doubly-exponential behavior, which reduces to the celebrated Schalkwijk-Kailath scheme when considering a single node. By viewing the constellation as an “analog source”, we also provide bounds on the exponential decay of the mean-squared error of source transmission over the network.

We consider the repair problem for Reed-Solomon (RS) codes, evaluated on an <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbb{F}_{q}$</tex> -linear subspace <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$U \subseteq \mathbb{F}_{q^{m}}$</tex> of dimension <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$d$</tex> , where <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$q$</tex> is a prime power, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$m$</tex> is a positive integer, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbb{F}_{q}$</tex> is the Galois field of size <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$q$</tex> . For <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$q &gt; 2$</tex> , we show the existence of a linear repair scheme for the RS code of length <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n=q^{d}$</tex> and codimension <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$q^{s}, s &lt; d$</tex> , evaluated on <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$U$</tex> , in which each of the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n-1$</tex> surviving nodes transmits only <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$r$</tex> symbols of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbb{F}_{q}$</tex> , provided that <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$ms\geq d(m-r)$</tex> . For the case <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$q=2$</tex> , we prove a similar result, with some restrictions on the evaluation linear subspace <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$U$</tex> . Our proof is based on a probabilistic argument, however the result is not merely an existence result; the success probability is fairly large (at least 1/3) and there is a simple criterion for checking the validity of the randomly chosen linear repair scheme.

With regard to the above paper (ibid., vol. 21, no. 2, pp. 733-741, Feb. 2012), a portion of the authors' corrections were not included before the work was finalized. These are detailed here.

Recent advances in peer to peer (P2P) search algorithms have presented viable structured and unstructured approaches for full-text search. We posit that these existing approaches are each best suited for different types of queries. We present PHIRST, the first system to facilitate effective full-text search within P2P networks. PHIRST works by effectively leveraging between the relative strengths of these approaches. Similar to structured approaches, agents first publish terms within their stored documents. However, frequent terms are quickly identified and not exhaustively stored, resulting in a significantly reduction in the system's storage requirements. During query lookup, agents use unstructured searches to compensate for the lack of fully published terms. Additionally, they explicitly weigh between the costs involved with structured and unstructured approaches, allowing for a significant reduction in query costs. We evaluated the effectiveness of our approach using both real-world and artificial queries. We found that in most situations our approach yields near perfect recall. We discuss the limitations of our system, as well as possible compensatory strategies.