Shape descriptors and statistical classification on areal topography data for tile inspection in tessellated surfaces

Verification of conformance to design specifications in production, and identification of defects related to wear or other damage during maintenance, are key metrological aspects that must be addressed for micro-scale tessellated surfaces. A new algorithmic approach is presented that operates on topography datasets as obtained by areal topography instruments. The approach combines segmentation algorithms with a novel implementation of the angular radial transform, originally adopted by the MPEG-7 standard, to implement shape descriptors and associated similarity metrics. Applications to the inspection and verification of laser-manufactured micro-embossing topographies are illustrated. The topographies are first segmented to extract the individual tiles; the tiles are then encoded through shape descriptors. Principal component analysis and cluster analysis are used to investigate the behaviour of the angular radial transform coefficients. Finally, an algorithmic classifier based on supervised learning (k-nearest neighbours) is implemented and shown to be effective at identifying defects and at discriminating between defect types

Assessment of surface topography modifications through feature-based registration of areal topography data

Surface topography modifications due to wear or other factors are usually investigated by visual and microscopic inspection, and – when quantitative assessment is required – through the computation of surface texture parameters. However, the current state-of-the-art areal topography measuring instruments produce detailed, areal reconstructions of surface topography which, in principle, may allow accurate comparison of the individual topographic formations before and after the modification event. The main obstacle to such an approach is registration, i.e. being able to accurately relocate the two topography datasets (measured before and after modification) in the same coordinate system. The challenge is related to the measurements being performed in independent coordinate systems, and on a surface which, having undergone modifications, may not feature easily-identifiable landmarks suitable for alignment. In this work, an algorithmic registration solution is proposed, based on the automated identification and alignment of matching topographic features. A shape descriptor (adapted from the scale invariant feature transform) is used to identify landmarks. Pairs of matching landmarks are identified by similarity of shape descriptor values. Registration is implemented by resolving the absolute orientation problem to align matched landmarks. The registration method is validated and discussed through application to simulated and real topographies selected as test cases

Legal Technologies of Creation of Legal Documents

The presented article contains theoretical material examining one of major directions of practical jurisprudence, touching a legal technique. Modern legal technique is nothing more than a set of technologies for creating legal documents in the process of implementing a variety of legal activities that require documentary design. The article deals with issues related to types of legal technique, their nature, ways of implementation are analyzed

Categories “Mechanism of Legal Regulation” and “Legal Technology”

The article analyzes the legal means that are elements of both the mechanism of legal regulation and legal technology, their characteristics are given, its purpose is indicated. The legal regulation of public relations is considered not only as a static phenomenon, but also as a dynamic process, showing a phased movement from one element to another in their interaction, starting with lawmaking and ending with the achievement of the goal of legal regulation, which consists of the formation and strengthening of law and order in society. A model of the mechanism of legal regulation as a set of combined legal means at all stages of the legal regulation of public relations, including lawmaking, legal relations and the implementation of law, is proposed. The types of legal technology are considered. It is shown with the help of which techniques and means various legal technological operations and actions are carried out, forming the sum of technologies for creating legal documents and implementing legally significant acts and procedures. This is about the same legal means that are elements of a legal regulation mechanism. And here the categories of “legal technique” and “legal regulation mechanism” partially coincide. In this regard, the relationship between the categories of legal technology and the legal regulation mechanism is formulated, in which the legal regulation mechanism is general and the legal technique is private

Combined inkjet printing and infrared sintering of silver nanoparticles using a swathe-by-swathe and layer-by-layer approach for 3-dimensional structures

Despite the advancement of additive manufacturing (AM)/3-dimensional (3D) printing, single-step fabrication of multifunctional parts using AM is limited. With the view of enabling multifunctional AM (MFAM), in this study, sintering of metal nanoparticles was performed to obtain conductivity for continuous line inkjet printing of electronics. This was achieved using a bespoke three dimensional (3D) inkjet-printing machine, JETx®, capable of printing a range of materials and utilizing different post processing procedures to print multi-layered 3D structures in a single manufacturing step. Multiple layers of silver were printed from an ink containing silver nanoparticles (AgNPs) and infra-red sintered using a swathe-by-swathe (SS) and layer-by-layer sintering (LS) regime. The differences in the heat profile for the SS and LS was observed to influence the coalescence of the AgNPs. Void percentage of both SS and LS samples was higher towards the top layer than the bottom layer due to relatively less IR exposure in the top than the bottom. The results depicted a homogeneous microstructure for LS of AgNPs and showed less deformation compared to the SS. Electrical resistivity of the LS tracks (13.6 ± 1μΩ cm) was lower than the SS tracks (22.5 ± 1 μΩ cm). This study recommends the use of LS method to sinter the AgNPs to obtain a conductive track in 25% less time than SS method for MFAM

Surface characterisation with light scattering and machine learning

Light scattering technology has been intensively investigated for surface measurement [1, 2]. However, most of developments have focused on the estimation of roughness indicators via area integrating methods, while, due to the high nonlinearity of the scattering process, few have addressed the challenge of reconstructing the actual topography, which implies solving a more complex inverse problem. In this study, rather than attempting to obtain a full reconstruction of surface topography from light scattering data, a novel approach is proposed to use light scattering information combined with machine learning to discriminate amongst different topographies. This is useful not only to compare surfaces, but also to automatically detect any type of undesired variation in manufacturing, e.g. the appearance of defects, or any other type of drift. The preliminary solution presented here operates on 2D geometry (topography profiles) and 2D light scattering far fields, investigating performance and behaviour purely via simulation. First, virtual models of different classes of surface topographies are artificially generated and labelled. Then, the far field scattering signals are obtained by simulation under different conditions of incident light through a boundary element method (BEM) [3, 4]. The scattering signals are used as the training datasets for a machine learning system, based on neural networks (NNs) [5], to implement an automated multiclass classifier. With the trained classifier, new observed surfaces can be classified with high accuracy using the associated far field scattering result. Preliminary experiments have been conducted to characterise three types of grating surfaces (blaze, sinusoidal and square gratings). The NN was designed as a three-layer densely connected network. In the experiment, 3300 datasets (3000 for training, 300 for testing) were used, consisting of gratings with different spacings. For the case studies, the accuracy of classification (number of correct predictions over number of total predictions) was higher than 99%. The results demonstrate that the proposed method is effective for discrimination of surfaces classes. For future work, the proposed method will be verified with scattering measurements of real surfaces. The method will also be implemented for defect detection in different kinds of surfaces and a 3D version of BEM model will be developed and utilised for characterisation of 3D surfaces