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Superparamagnetic behavior in aqueously well dispersible magnetite core-shell Fe3O4@SiO2 nanoparticles is presented. The magnetic properties of core-shell nanoparticles were measured with use of the DC, AC magnetometry and EPR spectroscopy. Particles where characterized by HR-TEM and Raman spectroscopy, showing a crystalline magnetic core of 11.5 ± 0.12 nm and an amorphous silica shell of 22 ± 1.5 nm in thickness. The DC, AC magnetic measurements confirmed the superparamagnetic nature of nanoparticles, additionally the EPR studies performed at much higher frequency than DC, AC magnetometry (9 GHz) have confirmed the paramagnetic nature of the nanoparticles. Our results show the excellent magnetic behavior of the particles with a clear magnetite structure, which are desirable properties for environmental remediation and biomedical applications.

For more flexibility of environmental perception by artificial intelligence it is needed to exist the supporting software modules, which will be able to automate the creation of specific language syntax and to make a further analysis for relevant decisions based on semantic functions. According of our proposed approach, of which implementation it is possible to create the couples of formal rules of given sentences (in case of natural languages) or statements (in case of special languages) by helping of computer vision, speech recognition or editable text conversion system for further automatic improvement. In other words, we have developed an approach, by which it can be achieved to significantly improve the training process automation of artificial intelligence, which as a result will give us a higher level of self-developing skills independently from us (from users). At the base of our approach we have developed a software demo version, which includes the algorithm and software code for the entire above mentioned component's implementation (computer vision, speech recognition and editable text conversion system). The program has the ability to work in a multi - stream mode and simultaneously create a syntax based on receiving information from several sources.

The speech recognition system and creation of program Software based on it is one of the important components of natural language computer modelling. For example, the popular Google Voice system, by which the word or sentence pronounced by a person is automatically written in textual form, in Google's Search system field for given language by using already realized speech recognition systems. The trial Software program has been developed by us, which is able to solve the problems, as for the Google search system, also for YouTube, Yahoo, Bing, Yandex and Wikipedia in Georgian language. Also, it is possible to translate automatically Georgian words or sentences pronounced individually and get texts in the appropriate language by using Google Translate. Program management is performed with Georgian voice commands.

 Abstract—Machine translation from any language into another requires composition of a word-form by giving its unchanged part and morphological categories. Besides this, for distance studying Natural language and make assistant computer mean for teaching the morphology of some languages to secondary school pupils , it is necessary by using unchanged part of given word to get by the computer all grammatically right word-forms. For solving all these problems, we have developed the software, by which it is possible to solve mentioned problems for languages like Georgian. Besides this, for solving such problems of artificial intelligence, which requires composing of natural language’s word-form by using the information defining this word-form, it is convenient to use the software developed by us.