Browsing by Author "Levin, David"

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    Algorithmic handwriting analysis of Judah's military correspondence sheds light on composition of biblical texts.
    (Proceedings of the National Academy of Sciences of the United States of America, 2016-04) Faigenbaum-Golovin, Shira; Shaus, Arie; Sober, Barak; Levin, David; Na'aman, Nadav; Sass, Benjamin; Turkel, Eli; Piasetzky, Eli; Finkelstein, Israel
    The relationship between the expansion of literacy in Judah and composition of biblical texts has attracted scholarly attention for over a century. Information on this issue can be deduced from Hebrew inscriptions from the final phase of the first Temple period. We report our investigation of 16 inscriptions from the Judahite desert fortress of Arad, dated ca 600 BCE-the eve of Nebuchadnezzar's destruction of Jerusalem. The inquiry is based on new methods for image processing and document analysis, as well as machine learning algorithms. These techniques enable identification of the minimal number of authors in a given group of inscriptions. Our algorithmic analysis, complemented by the textual information, reveals a minimum of six authors within the examined inscriptions. The results indicate that in this remote fort literacy had spread throughout the military hierarchy, down to the quartermaster and probably even below that rank. This implies that an educational infrastructure that could support the composition of literary texts in Judah already existed before the destruction of the first Temple. A similar level of literacy in this area is attested again only 400 y later, ca 200 BCE.
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    Approximation of functions on manifolds in high dimension from noisy scattered data
    (Jaen Journal on Approximation) Faigenbaum-Golovin, Shira; Levin, David
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    Manifold Approximation by Moving Least-Squares Projection (MMLS)
    (Constructive Approximation) Sober, Barak; Levin, David
    In order to avoid the curse of dimensionality, frequently encountered in Big Data analysis, there was a vast development in the field of linear and nonlinear dimension reduction techniques in recent years. These techniques (sometimes referred to as manifold learning) assume that the scattered input data is lying on a lower dimensional manifold, thus the high dimensionality problem can be overcome by learning the lower dimensionality behavior. However, in real life applications, data is often very noisy. In this work, we propose a method to approximate $\mathcal{M}$ a $d$-dimensional $C^{m+1}$ smooth submanifold of $\mathbb{R}^n$ ($d \ll n$) based upon noisy scattered data points (i.e., a data cloud). We assume that the data points are located "near" the lower dimensional manifold and suggest a non-linear moving least-squares projection on an approximating $d$-dimensional manifold. Under some mild assumptions, the resulting approximant is shown to be infinitely smooth and of high approximation order (i.e., $O(h^{m+1})$, where $h$ is the fill distance and $m$ is the degree of the local polynomial approximation). The method presented here assumes no analytic knowledge of the approximated manifold and the approximation algorithm is linear in the large dimension $n$. Furthermore, the approximating manifold can serve as a framework to perform operations directly on the high dimensional data in a computationally efficient manner. This way, the preparatory step of dimension reduction, which induces distortions to the data, can be avoided altogether.
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    Multispectral imaging reveals biblical-period inscription unnoticed for half a century.
    (PloS one, 2017-01) Faigenbaum-Golovin, Shira; Mendel-Geberovich, Anat; Shaus, Arie; Sober, Barak; Cordonsky, Michael; Levin, David; Moinester, Murray; Sass, Benjamin; Turkel, Eli; Piasetzky, Eli; Finkelstein, Israel
    Most surviving biblical period Hebrew inscriptions are ostraca-ink-on-clay texts. They are poorly preserved and once unearthed, fade rapidly. Therefore, proper and timely documentation of ostraca is essential. Here we show a striking example of a hitherto invisible text on the back side of an ostracon revealed via multispectral imaging. This ostracon, found at the desert fortress of Arad and dated to ca. 600 BCE (the eve of Judah's destruction by Nebuchadnezzar), has been on display for half a century. Its front side has been thoroughly studied, while its back side was considered blank. Our research revealed three lines of text on the supposedly blank side and four "new" lines on the front side. Our results demonstrate the need for multispectral image acquisition for both sides of all ancient ink ostraca. Moreover, in certain cases we recommend employing multispectral techniques for screening newly unearthed ceramic potsherds prior to disposal.
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    Writer Characterization and Identification of Short Modern and Historical Documents
    (Proceedings of the ACM Symposium on Document Engineering 2019, 2019-09-23) Faigenbaum-Golovin, Shira; Levin, David; Piasetzky, Eli; Finkelstein, Israel