In this paper, the fusion of four graphics into one integrated graphic is selectively observed in the visible and infrared spectrum. Each graphic represents its own information derived from the following sources: vector graphics, drawing, photograph and textual information. One graphic will be visible to the naked eye after the print. The other graphics will be observed with an NIR surveillance camera. These other graphics are nested into the selected visible graphics. All the graphics together make up a security print product with the characteristics of an individual solution with multilayered elements. Reprinting is possible only for the person in possession of the solution created according to the algorithm based on the INFRAREDESIGN^® method. When these graphics are printed on paper, it is impossible to produce an identical graphic prepress (C, M, Y, K) to produce forgery with the same dual properties in the visible and NIR spectrum.

In this paper, we publish the algorithm to create a dual image manifested in the infrared and visible spectrum. To distinguish the information in the two light spectra, twin dyes are introduced for the inkjet plotter and printing realization for garment and canvas items. The graphics, invisible to the naked eye, are designed for the near infrared (NIR) spectrum and are suitable for urban security where surveillance cameras with IR detectors are installed. The duality of dyes is presented in tables, and the analysis is a basis for programming and developing new algorithms for the application of “Infrared Dyeing” on different materials and printing technologies. Through spectroscopy, this innovative solution demonstrates twin colorants by printing in one pass through the plotter such that one image remains visible, while the other one is hidden to the bare eye. The uniform and the school bag cover presented in this paper are kept simple in design because they incorporate information hidden to the naked eye but visible with surveillance cameras and all the other infrared detectors. The article provides mathematical models of duality coloring as a basis for programming the graphic prepress that merges both of the images, the visual one and the infrared one. A topic is the fusion of two images with colors that represent two graphs, with independent contents for the visual and near-infrared spectrum.

Okosnicu istraživanja opisanom u članku čini popis germanizama formiran iz rječnika hrvatskoga jezika, rječnika stranih riječi i doktorskih disertacija koje se bave proučavanjem germanizama u hrvatskom jeziku. Pripremljeni popis germanizama omogući...

In this paper, 15-min production data from renewable energy sources (RES), aggregated by technology (onshore wind, offshore wind, solar) and by country (Germany, Austria, Hungary), are analyzed. The concept of a confidence interval is introduced as a parameter for practical use in power-system management. In probabilistic dimensioning of the FRR (Frequency Restoration Reserve; sometimes also called “secondary reserve”), it is necessary to ensure reserve sufficiency for a high percentage of time p, in the order of 99.9%. The confidence interval is specified by upper and lower deviation limits, expressed as percentages of the total installed capacity of the observed RES system, not to be exceeded with a probability greater than $1-p$. The concept of the “regulation multiplier” is also considered, which essentially indicates how many additional megawatts of RES capacity can be installed for each added megawatt of FRR capacity, ceteris paribus. Finally, a previously experimentally developed regulation-multiplier model is verified by replicating the original research on a new dataset used in this paper.

Many forensic methods have been developed for uncovering authors of threatening letters to get rid of their anonymous nature. With the development of new tools for the digital creation of threatening letters, such methods became obsolete, yet new options for their digital analysis also became available. This paper covers a method for digital analysis of threatening letters written in the Croatian language using machine learning algorithms. First the techniques for extraction of style elements of a text are covered, focusing on the most influential elements, and then transforming the extracted data into a vectorized form which can be used in machine learning models. The models are built upon the autoencoder architecture in combination with two text style vectorization methods. Multiple such models are implemented and their results are compared and analyzed, focusing on their effectiveness and the quality of their results. Finally, additional possibilities for further development of machine learning models for the analysis of threatening letters written in the Croatian language are covered and their possible effectiveness explained.