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The problem of recognizing a reference micromarking from microscopic images containing pseudo-marking element (similar to the real marking of the substrate relief elements) is considered. The scope of such marking is the identification of the studied or modified surface areas as well as the lines connecting these areas with macroscopic landmarks on the surface. The micromarking is formed using a probe microscope cantilever or a nanoindentor. Examples of images with pseudo-marking elements and the results of their recognition by low-level structural analysis methods previously used for micromarking recognition are given. In particular, a surface curvature detector is used, which has proven itself well in discrete micromarking recognition. The effect of pseudo-marking is the formation of a large number of background key points, which reduce the effectiveness of recognition. The application of the linear Hough transform for approximation and subsequent recognition of separate marking elements is described. It is also shown that to recognize the marks obtained by the probe microscope cantilever, it is advisable to use morphological erosion before the Hough transformation. The procedure for setting the parameters of this transformation, which affect the recognition of markings most significantly, is described. The range of recorded Hough transform segments and the Hough transform threshold are used as such parameters. An image processing algorithm and a recognition evaluation criterion are presented. In this case, a histogram of the distribution of the angles of mutual rotation of the segments detected by the Hough transform is used. The recognition criterion is the presence of dominant peaks with certain values in this histogram. The results showing the efficiency of the presented algorithm are presented. [ABSTRACT FROM AUTHOR]

An enhanced ratiometric fluorescence sensor was built for on-site visual detection of doxycycline (DOX) through the interaction with bovine serum albumin on the surface of red emissive copper nanoclusters. Upon the addition of weakly fluorescent DOX, the red fluorescence from copper nanoclusters gradually decreased through the inner-filter effect (IFE), while a green fluorescence appears and significantly increases, forming an interesting fluorescent isosbestic point, which was assigned to DOX due to sensitization effect of bovine serum albumin. On the basis of this ratiometric fluorescence, the system possessed good limit of detection (LOD) of 45 nM and excellent selectivity for DOX over other tetracyclines. Based on these findings, a paper-based sensor has been fabricated for distinct visual detection of trace DOX and combined with smartphone color recognizer for quantitative detection of DOX (LOD = 83 nM). This method shows broad application prospects in environmental monitoring and food safety. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we present research results on off-line Arabic handwriting recognition using structural techniques. Statistical methods have been more common in the reported research on Arabic handwriting recognition. Structural methods have remained largely unexplored in this regard. However, both statistical and structural techniques can be effectively integrated in multi-classifier based systems. This paper presents, to our knowledge, the first integrated offline Arabic handwritten text recognition system based on structural techniques. In implementing the system, several novel algorithms and techniques for structural recognition of Arabic handwriting are introduced. An Arabic text line is segmented into words/sub-words and dots are extracted. An adaptive slant correction algorithm that is able to correct the different slant angles of the different components of a text line is presented. A novel segmentation algorithm, which is integrated into the recognition phase, is designed based on the nature of Arabic writing and utilizes a polygonal approximation algorithm. This is followed by Arabic character modeling by ‘fuzzy’ polygons and later recognized using a novel fuzzy polygon matching algorithm. Dynamic programming is used to select best hypotheses of a sequence of recognized characters for each word/sub-word. In addition, several other key ideas, namely prototype selection using set-medians, lexicon reduction using dot-descriptors etc. are utilized to design a robust handwriting recognition system. Results are reported on the benchmarking IfN/ENIT database of Tunisian city names which indicate the robustness and the effectiveness of our system. The recognition rates are comparable to multi-classifier implementations and better than single classifier systems. [Copyright &y& Elsevier]

formal analysis of so-called diffusion algorithms is performed. They are frequently used in structural recognition but are rather poorly theoretically studied. These algorithms are analyzed from the viewpoint of their ability to optimize a function of many discrete variables, which is represented as the sum of many terms each of which depends on only two variables. It is proved that, under some stop condition, a diffusion algorithm approximately solves certain subclasses of optimization problems with any predefined nonzero error. The totality of problems solved by diffusion algorithms includes all so-called acyclic and supermodular optimization problems and also some other problems for which solution algorithms are unknown. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents FROSTY, a computer program for automatically extracting the high-level structural representation of a large-scale digital CMOS circuit from its transistor-level netlist and a library of subcircuit descriptions. To handle the complexity and diversity of industrial circuits, FROSTY combines traditional structural recognition and pattern matching methods into a two-step extraction process. First, logic structures based on channel-connected-components are recognized from a circuit netlist and from all library subcircuits, and are condensed into “macro devices” or called logic gates. This leads to hybrid netlists that contain the recognized logic gates and remaining transistors. Then annotated graphs representing the connectivity and properties of logic gates and remaining transistors are constructed. Compared to transistor-level netlists, these hybrid graphs are much smaller in size, more distinguishable in structure, and are thus more suitable for labeling-based pattern matching. An efficient pattern matching algorithm is then applied to extract the high-level structural representation from these condensed circuit graphs. FROSTY has demonstrated to be orders of magnitude faster than the pattern matching-based extraction program SubGemini, and can extract entire industrial designs with several hundreds of thousands of transistors in a few minutes on a modern Sun workstation. Furthermore, the FROSTY algorithm scales well with the size of a circuit. [Copyright &y& Elsevier]

The study investigated structural and shape recognition in two to three dimensions by adolescents from a historically disadvantaged neighbourhood. Data on the spatial orientation of grade eight learners in a specific school were collected using specifically adjusted and developed tests on two occasions (pre-test and post-test) and for an intervention (n=29), a control (n=30) and a placebo group (n=24). Hypotheses concerning differences between the three pre-test groups (One way ANOVA) and the three post-test groups were tested. The results indicated that with stimulation, the development of two and three dimension perception was possible at a later stage in a human's life. [ABSTRACT FROM AUTHOR]

• Structural stabilities and optical properties of Si x Ge y H z nanocrystals. • Energy bond model to determine the stable structures. • AIMD simulations for the optical properties. Based on the high-throughput first-principles calculations with structural recognition, we have ystematically investigated the structural stabilities and optical properties of Si x Ge y H z nanocrystals(H-SiGeNCs), including various sizes, shapes and compositions. The total energies of H-SiGeNCs can be simply estimated by the bond energy model in high accuracy, where the error of test set is less than 0.5 meV per atom. According to the energy difference of Si/Ge in various bonding environments, we have determined the ground state structures by the geometry analysis, as is confirmed the convex hulls of formation enthalpy from the first-principles calculations. In addition, the energy gaps of H-SiGeNCs are modulated by the atomic distributions, as well as the vibrations of Si-H and Ge-H bonds at room temperature which is revealed by ab initio molecular dynamics simulations. [ABSTRACT FROM AUTHOR]

This study focused on the structural differences of lignin after pyridine–acetic acid–water (PAW) and dioxane–acidic water (DAW) purification processes. These structural differences included the S/G ratio, condensed structure, weight-average (MW) molecular weights, β-O-4 linkages and sugar content. The chemical structure of the isolated crude lignin (CL), PAW purified lignin (PPL) and DAW purified lignin (DPL) was elucidated using quantitative 13C NMR, 2D-HSQC NMR spectra, thermogravimetric analysis (TGA), gel permeation chromatography (GPC) and Fourier transform infrared spectroscopy (FTIR). The results showed that the PPL fractions contain fewer condensed structures, higher S/G ratios, more β-O-4 linkages, higher average MW and lower thermal degradation properties compared to the CL and DPL fractions. Furthermore, the PAW process was more selective in removing condensed units and enriching S-type lignin from CL compared to the DAW process. These results provide valuable information for understanding which purification process is more suitable to be applied for lignin. [ABSTRACT FROM AUTHOR]