The article is about the problem of storing information for a specified time. A cryptographic protocol is proposed that provides encryption of messages, the decryption of which will be possible no earlier than a specified time. The protocol is an effective combination of a distributed key generation protocol, a proactive secret sharing protocol, an asymmetric encryption algorithm, and an electronic digital signature algorithm. On the basis of such a cryptographic protocol, you can develop and implement a practical data encryption service for a specified time. This is one of the most important problems in ensuring the security of the operation of critical information systems that operate with large amounts of confidential information. In particular, as an application, the developed practical methods and protocols will allow us to develop an alternative model for the operation of the information storage service at a specified time. A simplified model of the operation of the information storage service for a specified time based on this protocol is considered.

The need for improving methods of financial investment analysis in order to reduce risks leads researchers to exploit the modern scientific advancements especially in IT domain. Financial analytics require the ability to model and forecast future value of investigated financial parameters like currency inflation. In this paper, we analyzed the monthly inflation rate of Kazakhstan currency, using historical data from 1995 to 2020 by applying wide spread statistical and machine learning methods. The results show that the proposed research approach generates a solid forecasting accuracy and can be proposed to be included into financial investment analysis methods that could reduce inflation risk.

The technological study of gold-bearing ores consists mainly of analysis and experiments necessary to determine the material composition of ores and the technology for extracting precious metals and other valuable components from them. The ultimate goal of the study is to develop a technology for the maximum recovery of all commercially valuable components from economically viable ores while meeting safety requirements. Technological study of gold ores mainly consists of analysis and experiments necessary to determine the composition of the material. ores and technology for extracting precious ores, metals and other valuable components from them [1]. The ultimate goal of the study is to develop a technology to maximize the recovery of all commercially valuable components from economically viable ores while meeting safety requirements. The object of research is the Vasilkovskoye field. The enrichment process is a single system in which the individual elements are interconnected. High results can be achieved only taking into account a systematic approach that takes into account the interaction of system elements, i.e. in this case, the whole complex of processes.

The demand for yttrium and other rare metals in many branches of technology, as well as in the chemical industry, is growing every year. The Republic of Kazakhstan possesses raw material sources of rare earths of the yttrium group. The improvement of technologies for the extraction and processing of rare earths is necessary to meet the needs of the industry for its own raw materials and, therefore, for the development of high-tech industries. To extract yttrium, an extraction method was used in this work. Organic reagents and their mixtures with low-melting organic compounds were tested as extractants. According to the results of the study, a mixture of D2EHPA-HCA(di-(2-ethylhexyl) phosphoric acid and higher carboxylic acids) was chosen as an effective extractant providing the quantitative extraction of yttrium. The extraction patterns of yttrium extraction by this extractant were studied depending on various factors (рН, Vw:Vorg, Сex, CMe, t°C). The yttrium content after extraction was determined in the aqueous phase by the photometric method with the arsenazo I reagent. The content in the organic phase was determined by calculation. In an acidic environment, the yttrium recovery rate was 97,45%. In this case, the optimal conditions for the extraction were as follows: pH = 3.0, the volumetric ratio of the aqueous and organic phases 1:10, the concentration of D2EHPA in the extractant 10%, the initial concentration of yttrium CMe = 10-4M, the temperature of the extraction 40-60°C. The results obtained show the efficiency of yttrium extraction from solutions obtained after dissolving yttrium-containing ores with the extractant D2EHPA-HCA.

Every year there is more and more evidence of an increase in terrorist activity that has spread around the world. In the light of modern technologies and a variety of threats, it is necessary to detect and prevent this with reliable methods. In this regard, the detection of explosives is an active area of research. For this purpose, many detection systems have appeared. Government agencies in various countries are equipped with devices that can detect explosives. However, they are often large in nature, and roads are also publicly visible. Therefore, it is not advisable to use them in the current conditions in public places, such as railway stations, airports, bus stations, and so on. Manual contact is another problem in traditional systems. Therefore, there is an urgent need for the detection of explosives to be integrated into a mobile network, such as the Wireless Sensor Network (BSS). Since the BSS nodes can be hidden from prying eyes, such a network is an ideal method for automatic detection of explosives in real time. The implementation of such networks can pave the way for the installation of BSSs in public places to protect the lives and property of citizens. To this end, we will review the literature on the current state of explosives, their characteristics, and detection methods, including the use of wireless sensor networks (BSS) for automatic detection of explosives in real time. This article provides an insight into the various concepts of explosives and detection methods that can help in further research on creating a defense system for detecting explosives.

This article examines the study of nanoindentation, scratch testing of a ceramic-metal nanostructured coating TiN-Cu on melted chromium-nickel-vanadium steels. The nanoindentation method, namely, the analysis of the mechanical response of the TiN-Cu coating surface to the indentation of the atomic force microscope (AFM) nanosensor, is used for direct observation of such phenomena as the appearance of dislocations, the occurrence of shear instability, phase transitions, etc. The mechanisms of destruction of the TiN-Cu coating deposited on substrates in the form of melted new EO5 samples with different copper (7%,14%) content were studied by the method of scratch testing. It is shown that the destruction of coatings begins with the formation of cracks in the tops of the piles, which are formed along the scratches due to plastic impression of the substrate material. With each increase in the load on the indenter, the nature of the destruction changes.

This article presents a mathematical modeling of the metal systems iron-titanium, titanium-silicon, titanium-aluminum. The use of low-percentage ferrotitane, which is not traditional for metal-thermal processes of ferrosilicoaluminium (FSA), as a reducing agent in the smelting process, will lead to some uncertainty about how exactly a complex alloy of Si, Al and Fe will behave during alloying. In contrast to the classical aluminothermy, where the reducing element is aluminum, in the developed technology aluminum works in combination with FSA (Si=50-60%). Since the foreign metal Si is additionally introduced into the metal system (ferrotitane), the question arises as to how it will affect the formation of the alloy in the Fe-Ti-Al system. It is likely that the introduction of Si into the medium can lead to the formation of strong heteropolar bonds in the Fe-Ti-Al triple system. According to the results of the study, from a theoretical point of view, the use of a silicon-aluminum reducing agent (FSA) in the production of low-percentage ferrotitane should not prevent the production of a product that is conditioned by impurities.

Pore-scale modeling is becoming widely applied in the oil industry. The objective of pore-scale imaging and modeling is to predict the properties of multiphase flow in porous media. Pore-network model construction of geologically realistic samples and determination of rock and two-phase fluid flow properties are described and discussed in this paper. Pore-network models were constructed using published micro-computed tomography images of different rock samples. Effective porosity, average absolute permeability, capillary pressure, tortuosity (in 3 directions), and relative permeability were calculated for 2 types of displacement (drainage and imbibition). Avizo® Software and two-phase code were used for volume rendering of rock samples and calculations of rock and two-phase fluid flow properties, since it is a valuable and reliable tool for prediction of petrophysical properties and has advances in visualization of the pore space. Created 3D models of core samples based on micro-computed tomography scan data will allow oil and oilfield service companies to create a digital core database on a computer instead of storing physical cores in warehouses, which in turn greatly facilitates access to cores for further work with them.

Zn1-xCoxO nanopowders were obtained by chemical bath deposition followed by thermal annealing. The structure and morphology of the samples were studied by X-ray diffraction analysis and scanning electron microscopy. Raman spectra were studied at room temperature using a Solver Spectrum (NT-MDT) spectrometer with laser excitation at 473 nm. Optical spectra in the range 300-800 nm were measured on a Lambda 35 PerkinElmer optical spectrophotometer. Depending on the synthesis conditions, nanopowders with an average size of 1-2 nm were obtained.

Information is data that has undergone deep analysis and systematization. Nowadays, information is the key for any company, helping to stay on the market in conditions of fierce competition and financial crisis, if any. However, it is not enough just to have information, it is important to analyze and update it correctly. In order for a person not to waste his precious time on analyzing information, various schemes and systems have been developed that can analyze large amounts of data and turn ordinary data into relevant information. This area of ​​analytics aims to improve the management of business systems using databases and the latest technologies. The main direction of this article is the use of new data analysis technology as a tool for business intelligence.