articles
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№ 5(101)
21 october 2022 year
Rubric: Performance management Authors: Karabtsev S., Davzit I., Gurov E., Kotov R. |
There are a number of strategic tasks in the system of higher education, the solution of which by traditional methods is not possible or very difficult. One of these tasks is the management of the contingent of students. The complexity of this process is determined by the requirement that the university fulfill various key indicators while ensuring the quality of education. The aim of the study is to improve the process of students’ contingent management of the educational institution based on data management. Universities accumulate huge number of various information, the analysis of which is able to provide the decision-making based on data but not on intuition. The analysis of large information array is not possible without the usage of modern products and technologies related to Business Intelligence. This paper sets out the task of creating a decision support system (DSS) for contingent management, a range of questions is described, to which this system will quickly give answers and help an analyst or the head of a university in making decisions. As the research methods used, the methodology for creating a DSS with a description of the main results of each stage, as well as methods of statistical data analysis, is used. The DSS introduction to the daily activities of Higher education institution allows getting the rapid response to changes in academic achievement, forecasting contingent retention and potential budget losses, assessing the number of vacancies and qualitative performance. The system allows the rector of the university to monitor the dynamics of the main indicators on a weekly basis and gives an idea of the university from the founder’s point of view. Further research is aimed at developing the information system by adding advisory functions, as well as expanding the range of questions that the system is able to give a quick answer to – evaluating the activities of the teaching staff by key indicators, estimating the costs of implementing one or another area of training, and others. Continue... |
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| The rising trend of computer technology using makes digital signal processing (DSP) techniques converted into numerical data sets particularly relevant. For the most part, they are quite complex and their use is not always justified for a wide range of applications. This determines the ongoing interest in heuristic algorithms that are based on simplified approaches and allow quickly obtaining approximation of estimates with the least work amount. This paper discusses a method of pulsed (single) aperiodic signal with a high level of noise component mathematical processing by approximating its shape by a piecewise linear function, that parameters are determined using the method of least squares. A brief justification for this method is given, based on an analysis of the stochastic nature of the noise component. A numerical analysis of the signals spectral composition before and after processing is performed, as well as a comparison with other common methods: filtering and coherent averaging. It is shown that the waveform piecewise linear approximation can effectively separate the useful signal from the noise component, does not require complex algorithmic designs, and its program code implementation is possible in any high-level languages. The developed method is applicable for all types of signals and is most effective for processing single aperiodic pulses without its repetition possibility. The proposed approach can also be used in the educational process when studying the programming basics and for solving economic problems based on the determination of trend lines by parametric methods. Continue... | |
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№ 6(102)
30 november 2022 year
Rubric: E-commerce Authors: Kondratenko N., Filimonova E., Kultygin O., Mashegov P., Nechaev A. |
This work is devoted to the study of pricing issues for obtaining maximum profit when selling consumer goods at a constant purchase price. The said goods come in from either manufacturers or warehouses where the retail companies buy the goods in order to sell them directly to the consumers. The dependence of the selling rate per unit of time on the level of the added price in relation to the purchase price of the item is established by the means of sales price variation. The object of the research is the specific case of a linear approximation of said dependence, which is usually actualized in the event of either more elastic or less elastic demand for goods, when they are sold through Internet platforms. The proposed approach to determining prices of all the goods which are being sold for maximizing the total profit from the sales of all consumer goods or maximizing the total revenue throughout the whole period of sales time, based on the search of extremum points of the profit and revenue functions for each item of goods remains valid in the case of more complex approximations by quadratic and cubic functions of demand function. The type of the function of maximum value added revenue and the type of the function of maximum profit can be both found per unit of time depending on the variable level of the added price included into the sales price of the item. The type of maximum revenue function can be found per unit of time depending on the sales price of the item. The extremum points of the found functions are being determined. The theorems have been proved, that the extremum points which are being determined appear to be the maximum points of the researched functions for each item of goods, when the maximum profit or the maximum revenues are reached by selling goods to consumers. All common variables of said functions are found by summing up these functions among the multitude of goods on the interval of the whole sales time. The received data is used for the practical implementation of an effective sales strategy that ensures maximum profits for companies specializing in direct sales to consumers of the purchased goods. An applied methodicalэф approach to the sales of goods which ensures maximum profit from the sales in the field of elastic demand approximated by a linear function and under the condition of a constant purchase price for goods is proposed and theoretically substantiated. Continue... |
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№ 6(102)
30 november 2022 year
Rubric: Performance management Authors: Gumerov E. A., Alekseeva T. V. |
In IIoT (Industrial Internet of Things) systems designed for enterprise management in real time, it is required to perform operational and intelligent processing of Big Data and issue a control signal to the actuators in a predictable time (on the order of several milliseconds). The high speeds of Big Data continuously generated by sensors of the industrial Internet of Things system make it difficult to obtain a control effect at a predictable time. The purpose of the study is to develop the architecture of a complex of IIoT systems to obtain a control effect at a predictable time in real time. The central issue of the task is the high-speed processing of structured data at the place of their occurrence to solve the contradiction between a large number of continuously generated necessary data and the need to process them at a predictable time. The decomposition of the IIoT system into separate IIoT systems according to the structures of the data used by them, followed by synthesis into a single complex of enterprise IIoT systems, is applied. The developed architecture of the IIoT system complex makes it possible to effectively implement distributed management of production processes in a predictable time, perform operational and intelligent processing of huge amounts of data of various formats continuously generated by industrial facilities. The complex of IIoT systems consists of separate systems of the industrial Internet of Things, each of which has its own structure of transmitted data and is implemented on the basis of a multi-level bus, which provides a high data transfer rate in a structured form, the ability to attach to the bus any IIoT device and any program used, including the Big Data system to identify hidden patterns in the work of the enterprise. The proposed solution of the architecture of the IIoT system complex based on intelligent sensors and touchsensors allows for effective management of enterprise equipment and technological process operations in real time with the immediate use of the new patterns found in the continuously incoming new data. The solution can be used by developers of industrial Internet of Things systems for the effective launch and implementation of projects, for the development and commissioning of IIoT systems. Continue... |
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№ 6(102)
30 november 2022 year
Rubric: Researching of processes and systems Authors: Rozhkov V., Fedotov V. |
By means of simulation computer modeling, an effective variant of constructing an identifier for the speed of an asynchronous motor of an electromechanical system of a sintering machine is analyzed. The mathematical and algorithmic basis of the adaptive speed identifier (ASI) of an induction motor with a squirrel-cage rotor (ACIM) is given. Using the developed mathematical description of ASI with a reference model and using the apparatus of Lyapunov functions, an adequate computer simulation model was created. Compared with the existing methods for constructing identifiers in sensorless asynchronous electric drives, the proposed version of the ASI allows taking into account the discrete nature of the supply voltage of the ACIM at the output of the frequency converter with pulse-width modulation (PWM) of the output voltage and changing a larger number of equivalent circuit parameters. The stability of the speed identification process is provided in a wide range, sufficient to stabilize the speed of the trolleys according to the requirements of the technological process of sintering machines. As a result, the accuracy of speed identification in static and dynamic modes of operation of the electric drive increases. Simulation confirmed the operability of the proposed version of the identifier, proposed options for setting the AIS components. Universal, important for practical application results have been obtained, which allow both to build a high-precision system for identifying the ACIM speed in general and to refine the setting of the coefficients of the proposed version of the identifier in particular. An important property of the developed version of the ASI is its operability without loss of accuracy at near-zero and zero speeds of rotation and close to the nominal load torque on the ACIM shaft. In this regard, the practical application of the developed version, in addition to the drive of the sintering machine, is also possible in high- precision positioning systems for electric drives for various purposes. Continue... |
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№ 6(102)
30 november 2022 year
Rubric: Researching of processes and systems Authors: Mezentsev A., Yasnitsky L. |
Machine learning methods are currently widely used to solve various production problems, the problems of defects diagnosing and predicting for items in mass production, in particular. One of the most important problems is defects diagnosing and predicting, basing on its solution the regulations for the technological processes parameters and raw materials used can be determined, that insures the minimum probability of defects and the highest possible quality of manufactured products. The solution of this urgent problem with the help of a neural network model is shown on the example of the technological process for manufacturing products from fine ore material. The proposed model is based on the neural network trained on the set of historical data including examples of manufacturing products with different sets of technological parameters and raw ore material. The predicted parameter is warping of the product in one of its sections. Designing and training of the proposed neural network structure allowed achieving the coefficient of determination R2 between the predicted and actual warpage values of 92%. The dependences for the warpage value on the most significant parameters of the technological process, including thermophysical and chemical power technological processes of raw materials processing were constructed by conducting computer experiments using the method of partial freezing for input parameters. Due to these dependencies, the regulations for the most significant parameters of the production process are determined, which ensures the product to be without violating the tolerance for the warpage value specified by the design documentation. Thus, a specific example shows the possibility of using neural network modeling to solve the problem of setting regulations for the production process parameters, which compliance ensures the minimum amount of rejects and, accordingly, a higher quality of a production batch. Continue... |
