Decoding Human Visual Colour EEG Information Using Machine Learning and Visual Evoked Potentials

With the rapid development of brain-computer interfaces (BCIs), human visual decoding, one of the important research directions of BCIs, has attracted a substantial amount of attention. However, most visual decoding studies have focused on graphic and image decoding. In this paper, we first demonstrate the possibility of building a new kind of task-irrelevant, simple and fast-stimulus BCI-based experimental paradigm that relies on visual evoked potentials (VEPs) during colour observation. Additionally, the features of visual colour information were found through reliable real-time decoding. We selected 9 subjects who did not have colour blindness to participate in our tests. These subjects were asked to observe red, green, and blue screens in turn with an interstimulus interval of 1 second. The machine learning results showed that the visual colour classification accuracy had a maximum of 93.73%. The latency evoked by visual colour stimuli was within the P300 range, i.e., 176.8 milliseconds for the red screen, 206.5 milliseconds for the green screen, and 225.3 milliseconds for the blue screen. The experimental results hereby show that the VEPs can be used for reliable colour real-time decoding.

A REVIEW OF MACHINE LEARNING AND ITS APPLICATIONS

Today, huge amounts of data are available everywhere. Therefore, analyzing this data is very important to derive useful information from it and develop an algorithm based on this analysis. This can be achieved through data mining and machine learning. Machine learning is an essential part of artificial intelligence used to design algorithms based on data trends and past relationships between data. Machine learning is used in a variety of areas such as bioinformatics, intrusion detection, information retrieval, games, marketing, malware detection, and image decoding. This paper shows the work of various authors in the field of machine learning in various application areas.

STUDY OF HOLOGRAPHIC PROTECTIVE ELEMENTS USED ON DRIVER'S LICENSE AND VEHICLE REGISTRATION CERTIFICATES ON PLASTIC BASIS AND AN EXAMPLE OF THEIR FORGERY

The article deals with the current situation in the study by forensic experts of holographic protective elements (hereinafter – HPE). Over the past 30 years, HPE have been actively developing and widespread, they are used both as design elements and to protect various types of documents. In its manufacture, application software and equipment are used, which provides high-resolution images and allow encoding large amounts of information. Although there are several scientific works included in the Register of methodologies for conducting forensic examinations of the Ministry of Justice of Ukraine, but it was written more than 20 years ago. Therefore, to conduct an expert study of HPE, it is necessary to update the methodological base, revise the approaches to its research and issues to be solved. The article briefly outlines the design features, techniques and methods of protecting HPE that are used by its manufacturers. It is emphasized that latent images are introduced into the structure of holograms to control its authenticity, which are checked by various detectors. There are described examples of latent image decoding. It is also described an example of detecting a fake film with holographic elements that are very similar to the original. At the same time, when examining the fake film, it was found that there are no microtext and the hidden abbreviation “MBС” (in Ukrainian). As a result of the research carried out, the author proposes to accept the results of verification of the elements of control of the authenticity of the HPE, in order to substantiate the probable conclusion about the conformity or inconsistency of the hologram. In addition, the presence of significant differences in the common features of the studied HPE and the sample, in the author's opinion, is a sufficient basis for the conclusion about the discrepancy between the holographic images and the sample. Therefore, experts of the questioned document examination can carry out such studies, with certain restrictions.

DNA Origami Model for Simple Image Decoding

DNA origami is the application of self-assembly in nanotechnology. The combination of DNA origami and hybridization chain reaction is one of the important application methods of DNA origami. In this paper, DNA origami is used to design the cipher pattern on the base of origami. The cipher chain, which is put into the reaction solution, hybridizes with the molecular beacon and the hairpin structure that form the cipher pattern to build a DNA origami model that can decode the pattern. The cipher chain consists of the starting chain and the intermediate chain. When the cipher is correct, the cipher chain can open the molecular beacon and the hairpin structure to display the cipher pattern on the origami base in the solution.