In the process of self-assessment and accreditation examination, assessment is carried out according to a scale that covers four levels of compliance with the quality criteria of the educational program and educational activities. Assessing the quality of education is complicated by the fact that the value of quality criteria is due to a large number of factors, possibly with an unknown nature of influence, as well as the fact that when conducting pedagogical measurements it is necessary to work with non-numerical information. To solve these problems, the authors proposed a method for assessing the quality of educational programs and educational activities based on the adaptive neuro-fuzzy input system (ANFIS), implemented in the package Fuzzy Logic Toolbox system MATLAB and artificial neural network direct propagation with one output and multiple inputs. As input variables of the system ANFIS used criteria for evaluating the educational program. The initial variable of the system formed a total indicator of the quality of the curriculum and educational activities according to a certain criterion or group of criteria. The article considers a neural network that can provide a forecast for assessing the quality of educational programs and educational activities by experts. The training of the artificial neural network was carried out based on survey data of students and graduates of higher education institutions. Before the accreditation examination, students were offered questionnaires with a proposal to assess the quality of the educational program and educational activities of the specialty on an assessment scale covering four levels. Student assessments were used to form the vector of artificial neural network inputs. It was assumed that if the assessments of students and graduates are sorted by increasing the rating based on determining the average grade point average, the artificial neural network, which was taught based on this organized data set, can provide effective forecasts of accreditation examinations. As a result of comparing the initial data of the neural network with the estimates of experts, it was found that the neural network does make predictions quite close to reality.
The development and efficient application of Fog Computing technologies necessitate complex tasks associated with the management and processing of large data sets, including the creation of low-level networks that guarantee the functioning of end devices within the Internet of Things (IoT) concept. This article presents the utilization of graph theory techniques to address these issues. The proposed graph model enables the determination of fundamental characteristics of systems, networks, and network devices in Fog Computing, including optimal features and methods to maintain them in a functioning condition. This work demonstrates how to create and personalize graph displays by adding labels or highlighting to the graph nodes and edges of pseudo-random task graphs. The task graphs, described and visualized in Matlab code, represent the computational work to perform and data transfer between tasks, expressed in Megacycles per second and kilobits/kilobytes of data, respectively. The task graphs can be applied in both single-user systems, where one mobile device accesses a remote server, and multi-user systems, where many users access a remote server through a wireless channel. This set can be utilized by researchers to evaluate cloud/fog/edge computing systems and computational offloading algorithms.
The rapid development of information technology, robotics, nanotechnology, and biotechnology requires modern education to train highly qualified specialists who can support it, preparing students and students for producing creative work. The need to reform education to modern challenges is an urgent problem today. It is predicted that the most popular professions soon will be programmers, engineers, roboticists, nanotechnologists, biotechnologists, IT specialists, etc. STEM education can combine these areas into a complex, which can be implemented in different age groups. One example of the use of STEM technologies is the development and implementation of scientific and technical projects using the Arduino hardware and software complex. With the help of STEM technologies, a method for calibrating an NTC thermistor in the operating temperature range is proposed and a working model of an electronic thermometer is presented using the example of an NTC thermistor and an Arduino microcontroller.
The article deals with the problem of calculation of errors of improvised devices and installations for physical training experiment in the construction of which digital and analog sensors are used, which are intended for measuring various physical quantities. The general requirements for educational devices are considered: scientific and pedagogical, technical, ergonomic, aesthetic, economic. In the article special attention is paid to the technical requirements of improvised devices and installations. It is noted that it is necessary to ensure their reliability and durability, perfection and simplicity of construction, high metrological indicators. The basic stages of calculation of errors of measurement of physical quantities, features of measurements with use of digital measuring devices are given. The measurement process using digital measuring instruments and automatic measurement methods remove the measurement from subjective errors and have a number of other advantages. It is convenient to make computers and sensors in combination with hardware platforms Arduino, STM32, Raspberry, etc. for the output of home-made appliances. Analog sensors are connected to the analog inputs of the hardware and software platforms that perform analog-to-digital conversion. Digital sensors are easier to use and capable of providing high metrological performance in the design of self-made physical devices. Most sensors have errors in the instructions. The cases of calculation of errors, when the home-made installation uses optical steam as the main measuring tool, are considered. Optical pairs are used in many homemade physics installations - studies of body motion on an inclined plane, studies of rotational motion using Oberbeck pendulum, studies of mathematical pendulum, etc. Examples and schemes of installations and description of experiments with methods of calculation of measurement errors using optical pairs are given. As a result, it is noted that homemade devices using digital sensors, hardware platforms Arduino, STM32, Raspberry and others meet the general requirements for training devices, in particular, have high metrological indicators, are easy to manufacture and require little financial cost.
The article deals with the problem of developing a modern computer Interface to traditional installations for laboratory work on physics and search for new, active forms, methods and learning tools that would fit modern trends in the development of education and facilitate training highly professional physics teachers. Modern facilities for research isoprocesses in gases consist of a vessel, the volume of which can be changed, pressure and temperature sensors, device for processing signal from sensors. But the price for such installation is too high for educational institutions. The results of implementation of the method of use of the platform Arduino in a laboratory workshop on molecular physics as a simple and, at the same time, an effective alternative to factory equipment for the study of gas laws are given in the article. Arduino is a hardware computer platform for amateur design, basic components of which is a microcontroller board with I / O elements and Processing development environment. The article contains a description of the hardware platform Arduino Nano and pressure and temperature sensors BMP180, MS5611-01BA03, DS18B20, which are used in the installation for the study of gas laws. An important methodological aspect of laboratory work with the use of Computer and Arduino is the data processing of the experiment. Need experimentally establish a functional relationship between independent measured gas parameters: pressure, volume and temperature. In the laboratory works on the study of gas laws is proposed to use methods of statistical analysis: direct selection method functions and the method of linearization. The isochoric or isochloric process is thermodynamic process, which occurs at a constant volume. In its gases to carry out simply - it is enough to heat (cool) substance in a vessel that does not change its volume. The article describes how to explore isochoric process with the help of the developed device. The given software is a code for working with pressure and temperature sensor. Proposed methodology proved the feasibility of practical use of hardware and computer platform Arduino at the Laboratory for Molecular Physics.
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