Hidden Signatures Research Articles

A new analysis of flow noise outside the time-frequency representation using graph-based feature extraction

Among various strategies to analyze spatiotemporal aero-hydro acoustic field, complex networks are a novel technique to deal with the acoustic pressure signals (APSs) which can fully reflect the inherent structure of the time series into complex networks. In this study first, sound generated from a low Mach number and turbulent flow around a three-dimensional circular cylinder is simulated. Then, using the complex network algorithm, APSs are transformed into natural visibility graphs (NVGs), and, their hidden signatures (macroscopic and microscopic characteristics) are unveiled using the topological metrics of the NVG. Later, spatial variations of 11 network metrics associated with 76 receiver signals distributed around the cylinder are explored and a bridge is built between these variations and their physical interpretations. The results show that all network properties corresponding to receiver signals located at a constant angular position are independent of the radial direction. Moreover, irrespective of the APSs properties, the power-law degree distribution is a feature shared by all networks, suggesting that it is a universal characteristic and highlights systems' self-organization and self-similarity characteristics in the sound field. Finally, physical interpretation of graph structures indicates that graph-based feature extraction enables identifying, distinguishing, and exploring underlying sound field dynamics in more detail.

New Names for the Old Sacristy of the Siena Hospital: Pseudo‐Scripts, Hidden Signatures, and the Ludic Self

While working on the scaffolding of Vecchietta's frescoes in the sacristy at the Santissima Annunziata, Siena (1446–49), thirteen‐year‐old Benvenuto di Giovanni and another garzone, Guasparre d'Agostino, signed together their names in Greek letters hidden among pseudo‐scripts on the hem of the cloak of a seemingly unimportant figure painted about three metres high up on a wall. Previously ignored, this signature is important in that, combined with unpublished documents, it sheds light on Benvenuto di Giovanni's youthful career and, more broadly, the first steps of a garzone on their way to becoming a master. The first known signature in Greek ever to appear in fifteenth‐century Italian painting, but enmeshed among pseudo‐scripts, Guasparre and Benvenuto's marks are not proof of antiquarian culture. Instead, this signature begs for a historicized concept of both linguistic knowledge and artistic authorship. Hidden, it betrays an interest in the signature as a locus of playful negotiation of identity, suspended between concealment and revelation.

Constructing the 2-Element AGDS Protocol based on the Discrete Logarithm Problem

It is considered a group signature scheme in frame of which different sets of signers sign electronic documents with hidden signatures and the head of the signing group generates a group signature of fixed size. A new mechanism for imbedding the information about signers into a group signature is proposed. The method provides possibilities for reducing the signature size and to construct collective signature protocols for signing groups. New group signature and collective signature protocols based on the computational difficulty of discrete logarithm are proposed.

CONSTRUCTING THE 2-ELEMENT AGDS PROTOCOL BASED ON THE DISCRETE LOGARITHM PROBLEM

It is considered a group signature scheme in frame of which different sets of signers sign electronic documents with hidden signatures and the head of the signing group generates a group signature of fixed size. A new mechanism for imbedding the information about signers into a group signature is proposed. The method provides possibilities for reducing the signature size and to construct collective signature protocols for signing groups. New group signature and collective signature protocols based on the computational difficulty of discrete logarithm are proposed.

Microscopic and Spectroscopic Characterization of Nanostructured Topographical Surface of Rattlesnake Rattle.

Rattlesnakes are easily recognized by a rattle on the tail. Despite the advances in molecular, morphological, and evolutionary studies about several aspects of rattles, there are no studies elucidating these nanoscale topographical features using high-resolution techniques. Here we propose a set of approaches to show these micro/nano surface features searching for patterns or hidden signatures. The results showed that the older rattle ring (segment 8) presented higher roughness values when compared to other segments. Cluster analysis allowed the observation of similarities/differences among some groups, which reinforced the strong discrepancy of the segment 8 when compared to the others and enable possible topographical transitions among each segment features, considering their linkages and Euclidean distances. Attractive forces and surface hardness were also significant increased on segment 8, while adhesion was significantly decreased on the segments 5, 6, and 7 compared to segment 1 (P < 0.05). Fourier transform infrared spectroscopy showed typical profiles of keratin spectra considering the amino acids present in this protein structure. Energy dispersive spectroscopy results indicated possible different molecular composition on each segment. These set of approaches applied on the present study represents an array of new possibilities towards the qualitative and quantitative analyses of this type of biomaterials enabling to address several structural, chemical and mechanical questions ongoing on scientific world.

A technique for correction of attenuations in synchronous fluorescence spectroscopy

Synchronous fluorescence spectroscopy is an efficient technique for decoupling fluorophores which are masked in fluorescence spectroscopy due to overlapping of dominant fluorophores. By choosing appropriate offsets between excitation and emission wavelengths during signal acquisition from turbid samples, responses of individual fluorophores are highlighted as sharp peaks by using this technique. Some of the peaks may, however, still be missed due to wavelength dependent absorption and scattering effects. In this study a correction technique is used to extract such hidden signatures. The technique is validated using tissue phantoms with known concentrations of fluorophores, absorbers and scatterers. On the basis of validation studies on single and combination of two fluorophores, it is found that lower offsets display better recovery due to minimal influence of absorption by blood. Among the different offsets, 55nm is found to be optimal for investigation of cervical precancers.

Hidden signatures: new reagents for developing latent fingerprints

Aldehydes substituted with a quaternised pyridinium or quinolinium ring have been investigated for the development of latent fingerprints. Two routes were developed to a novel in situ formed azacyanine dye. This dye might form in the fingerprint where reagents are concentrated but does not form appreciably in solution experiments as evidenced by the lack of an absorption band at 600 nm. N-Alkyl and N-aryl substituted benzimidazole-2-carboxaldehydes give stable fluorescent fingerprints.

Hidden signatures written in blood

Hidden signatures written in blood

Nondestructive multispectral reflectoscopy between 800 and 1900nm: An instrument for the investigation of the stratigraphy in paintings

In the present work, a powerful tool for the investigation of paintings is presented. This permits the tuneable multispectral real time imaging between 200 and 5000 nm and the simultaneous multispectral acquisition of spectroscopic data from the same region. We propose the term infrared reflectoscopy for tuneable infrared imaging in paintings (Chryssonlakis and Chassery, The Application of Physicochemical Methods of Analysis and Image Processing Techniques to Painted Works of Art, Erasmus Project ICP-88-006-6, Athens, June, 1989) for a technique that is effective especially when the spectroscopic data acquisition is performed between 800 and 1900 nm. Elements such as underdrawings, old damage that is not visible to the naked eye, later interventions or overpaintings, hidden signatures, nonvisible inscriptions, and authenticity features can thus be detected with the overlying paint layers becoming successively "transparent" due to the deep infrared penetration. The spectroscopic data are collected from each point of the studied area with a 5 nm step through grey level measurement, after adequate infrared reflectance (%R) and curve calibration. The detection limits of the infrared detector as well as the power distribution of the radiation coming out through the micrometer slit assembly of the monochromator in use are also taken into account. Inorganic pigments can thus be identified and their physicochemical properties directly compared to the corresponding infrared images at each wavelength within the optimum region. In order to check its effectiveness, this method was applied on an experimental portable icon of a known stratigraphy.

A novel bioinformatic strategy for unveiling hidden genome signatures of eukaryotes: self-organizing map of oligonucleotide frequency.

With the increasing amount of available genome sequences, novel tools are needed for comprehensive analysis of species-specific sequence characteristics for a wide variety of genomes. We used an unsupervised neural network algorithm, Kohonen's self-organizing map (SOM), to analyze di- and trinucleotide frequencies in 9 eukaryotic genomes of known sequences (a total of 1.2 Gb); S. cerevisiae, S. pombe, C. elegans, A. thaliana, D. melanogaster, Fugu, and rice, as well as P. falciparum chromosomes 2 and 3, and human chromosomes 14, 20, 21, and 22, that have been almost completely sequenced. Each genomic sequence with different window sizes was encoded as a 16- and 64-dimensional vector giving relative frequencies of di- and trinucleotides, respectively. From analysis of a total of 120,000 nonoverlapping 10-kb sequences and overlapping 100-kb sequences with a moving step size of 10 kb, derived from a total of the 1.2 Gb genomic sequences, clear species-specific separations of most sequences were obtained with the SOMs. The unsupervised algorithm could recognize, in most of the 120,000 10-kb sequences, the species-specific characteristics (key combinations of oligonucleotide frequencies) that are signature representations of each genome. Because the classification power is very high, the SOMs can provide fundamental bioinformatic strategies for extracting a wide range of genomic information that could not otherwise be obtained.