Usefulness of class A Pan coefficient models for computation of reference evapotranspiration for a semi-arid region

The reliability of estimates of reference evapotranspiration (ET0) using pan evaporation (Epan) depends on the accurate determination of pan coefficients (Kpan). Six ET0 models were evaluated for their usefulness using 33-year climatological dataset of a semi-arid region of the Gujarat state of India. The equations compared include Cuenca (1989), Allen and Pruitt (1991), Snyder (1992), Modified Snyder (Grismer et al., 2002), Orang (1998), and Pereira et al. (1995). The ET0 data, calculated using daily Kpan values from these equations, were compared to the Food and Agricultural Organization (FAO)-Penman-Monteith (FAO56-PM) method as a reference. Based on the visual comparison as well as from the statistical criteria, ET0 values computed using Modified Snyder and Orang model have very close agreement with the FAO56-PM method for daily, monthly, and annual estimates as compared to other approaches. The sequential performances of the explored models was found as: Modified Snyder (Eqn. 5) > Orang (Eqn. 6) > Cuenca Eqn. (2) > Allen & Pruitt (Eqn. 3) > Snyder (Eqn. 4) > Pereira et al. (Eqn. 7) model. Therefore, the Modified Snyder model (Grismer et al., 2002) could be recommended as the best model for ET0 computations under these prevailing climatic conditions for a semi arid region.

Evaluation of melt quality during polymer extrusion

Polymer materials are widely spread and used in all industry sectors. The operating properties of polymer products make them practically indispensable in various industries. They have acquired widespread popularity and their production volumes are predicted to grow every year. The extrusion of polymers is one of the main methods for their processing. The melt uniformity is one of the main factors that influence the quality of the products and is determined by the level of mixing, i.e., by the redistribution of additives in a dispersion medium when these additives are introduced into the main polymer. The influence of working conditions, geometry of working bodies and other parameters on the melt temperature uniformity was determined. Nowadays, there are a lot of methods for determining the melt uniformity. They can be used indirectly in or after the extrusion process and can be short or long lasting, which in fact determines the acceptability of each of the methods. To determine the melt uniformity, statistical evaluation methods, which have been verified by many experiments and are well known, are often used. The analysis showed that the mixing index is most sensitive among the criteria described. Although statistical criteria of evaluating the melt uniformity are widespread, it is better to use parameters that allow the state of the mixture to be analyzed directly in the work process for the extrusion of polymers, to identify those that depend on the mixing process. Methods and criteria for verifying the melt quality were analyzed and potential use of their temperature uniformity for measuring and evaluating the melt quality directly in the extrusion process, to eliminate the costly sampling process, was determined.

Method, models and information technology of decision making about the state of technical objects under non-stationary input influences

There is a significant increase in the amount of measuring information at complex and large technical objects, such as bridges. Decision making about these objects states under non-stationary input influences is a difficult task. The article proposes to make the transition from single-channel information processing to multi-channel one. Each channel processes one of the Hilbert-Huang modes, into which each realization of the nonstationary signal decomposes. It is shown that the first three modes of decomposition are often enough, which in most cases create a stationary process. If a mode is non-stationary, it is possible to decompose it into these modes. The final decision according to statistical criteria is made not on realizations as it is traditionally carried out, but on Hilbert-Huang modes.

Assessing the quality of budget risk management of the subjects of the Russian Federation

Subject. The article explores indicators for budget risk management in the subjects of the Russian Federation. Objectives. The aim is to develop a system of indicators to assess the quality of budget risk management, to create a methodology for quality management assessment and test it on the case of 85 subjects, to build a rating for the quality of budget risk management in 2020. Methods. The study rests on creating a model for assessing the quality of budget risk management on the basis of 18 mathematical and statistical criteria and their testing on budget data from 85 federal subjects for 2020, and the deductive approach. Results. I formulated and justified indicators of analysis that demonstrate the level of readiness of the budget of Russian subjects to accept budget risks. The proposed indicators are logically structured into groups and detailed by data source for evaluation. The system of indicators is incorporated into the existing methodology created by the Ministry of Finance of the Russian Federation. The results of the analysis are presented as a rating of subjects of the Russian Federation based on the aggregate assessment of the quality of budget risk management. Conclusions. The offered methodology may serve as a supplement to the methodology for assessing the quality of regional finance management created by the Ministry of Finance of the Russian Federation. It may also help evaluate decisions on proactive risk management and mitigation of consequences of risk events in regional budget utilization.

OPTIMIZATION OF DOSAGES OF NON-TRADITIONAL RAW MATERIALS IN THE FORMULATION OF PREVENTIVE ORIENTATION BREAD

Исследовано влияние сочетания нетрадиционных видов сырья – жидкого виноградного сахара и куркумы на качество хлеба из пшеничной муки. Проведена оптимизация дозировок этих рецептурных компонентов по выходным параметрам – удельному объему и формоустойчивости готового изделия. Оптимизацию рецептурного состава хлеба проводили с использованием методов математической статистики и дифференциального исчисления. Построены математические модели в виде регрессионных уравнений. Обработку экспериментальных данных выполняли по статистическим критериям Стьюдента, Кохрена и Фишера при доверительной вероятности 0,95. Дана графическая интерпретация регрессионных уравнений. Оптимизацию рецептурного состава хлеба проводили методом свертывания частных критериев в обобщенный аддитивный критерий. Определены оптимальные значения факторов: дозировка, % к массе муки, жидкого виноградного сахара – 2,50, куркумы – 2,75, обеспечивающие получение изделий с наилучшим сочетанием значений удельного объема и формоустойчивости. На основе полученных данных разработана рецептура и способ производства хлеба «Мерита» профилактической направленности (ТУ 9110–515–02068108–2019), характеризующегося улучшенным качеством и повышенной пищевой ценностью за счет дополнительного внесения биологически активных нутриентов. The influence of a combination of non-traditional raw materials – liquid grape sugar and turmeric on the quality of wheat flour bread has been studied. Optimization of the dosages of these prescription components according to the output parameters – specific volume and dimensional stability of the finished product was carried out with using methods of mathematical statistics and differential calculus. Mathematical models in the form of regression equations are constructed. The experimental data were processed according to the statistical criteria of Student, Cochran, and Fisher with a confidence probability of 0,95. Optimization of the formulation composition of bread was carried out by the method of folding partial criteria into a generalized additive criterion. The optimal values of the factors are determined: dosage, % by weight of flour, liquid grape sugar –2,50, turmeric – 2,75, ensuring the production of products with the best combination of specific volume and dimensional stability. On the basis of the obtained data, the formulation and method of production of bread «Merita» of a preventive orientation (Technical specifications 9110–515–02068108–2019) were developed. The product has improved quality and increased nutritional value due to the additional introduction of biologically active nutrients.

Synthesis of four new neuro-statistical tests for testing the hypothesis of independence of small samples of biometric data

The paper considers the analysis of small samples according to several statistical criteria to test the hypothesis of independence, since the direct calculation of the correlation coefficients using the Pearson formula gives an unacceptably high error on small biometric samples. Each of the classical statistical criteria for testing the hypothesis of independence can be replaced with an equivalent artificial neuron. Neuron training is performed based on the condition of obtaining equal probabilities of errors of the first and second kind. To improve the quality of decisions made, it is necessary to use a variety of statistical criteria, both known and new. It is necessary to form networks of artificial neurons, generalizing the number of artificial neurons that is necessary for practical use. It is shown that the classical formula for calculating the correlation coefficients can be modified with four options. This allows you to create a network of 5 artificial neurons, which is not yet able to reduce the probability of errors in comparison with the classical formula. A gain in the confidence level in the future can only be obtained when using a network of more than 23 artificial neurons, if we apply the simplest code to detect and correct errors.

Evaluating the capability of hybrid data-driven approaches to forecast monthly streamflow using hydrometric and meteorological variables

Streamflow forecasting, as one of the most important issues in hydrological studies, plays a vital role in several aspects of water resources management such as reservoir operation, water allocation, and flood forecasting. In this study, wavelet-gene expression programming (WGEP) and wavelet-M5 prime (WM5P) techniques, as two robust artificial intelligence (AI) models, were applied for forecasting the monthly streamflow in Khoshkroud and Polroud Rivers located in two basins with the same names. Results of hybrid AI techniques were compared with those achieved by two stand-alone models of GEP and M5P. Seven combinations of hydrological (H) and meteorological (M) variables were considered to investigate the effect of climatic variables on the performance of the proposed techniques. Moreover, the performance of both stand-alone and hybrid models were evaluated by statistical criteria of correlation of coefficient, root-mean-square error, index of agreement, the Nash–Sutcliffe model efficiency coefficient, and relative improvement. The statistical results revealed that there is a dependency between ‘the M5P and GEP performance’ and ‘the geometric properties of basins (e.g., area, shape, slope, and river network density)’. It was found that a preprocessed technique could increase the performance of M5P and GEP models. Compared to the stand-alone techniques, the hybrid AI models resulted in higher performance. For both basins, the performance of the WM5P model was higher than the WGEP model, especially for extreme events. Overall, the results demonstrated that the proposed hybrid AI approaches are reliable tools for forecasting the monthly streamflow, while the meteorological and hydrometric variables are taken into account.

Use GARCH Models to Build a Econometric Model to Predict Average Daily Closing Prices of the Iraqi Stock Exchange for the Period 2013-2016

This research aims to build a standard model for the analysis and prediction of the average daily closing price fluctuations for companies registered in the Iraq Stock Exchange for the period 07/01/2013 to 30/06/2016, using the conditional generalized Heteroscedasticity Generalized Autoregressive (GARCH) models. As these models deal with the fluctuations that occur in the financial time series. The results of the analysis showed that the best model for predicting the volatility of average closing prices in the Iraq Stock Exchange is the EGARCH model (3,1), depending on the statistical criteria used in the preference between the models (Akaike Information Criterion, Schwarz Criterion), and these models can provide information for investors in order to reduce the risk resulting from fluctuations in stock prices in the Iraqi financial market.

Applicability of GCMs for evaluation of agro-climatic properties of local territories

The analysis of reliability and accuracy reproduction of air temperature, precipitation, and relative humidity of the air by 18 ocean-atmosphere general circulation models (GCMs) included in CMIP6 (Coupled Model Intercomparison Project) is performed. Based on statistical criteria, the best models that most accurately reproduce empirical data are selected. On the basis of these models, an ensemble of models is compiled. The calculation of several agro-climatic indicators for the European part of Russia is performed using an ensemble approach. The comparison of agro-climatic indicators calculated on the basis of the ensemble of models and observational data is carried out for the territory of the Upper Volga including Yaroslavl, Kostroma, Vologda, Novgorod and Tver regions. The feasibility of using the ensemble of models to assess agro-climatic conditions of the region is shown.

Context-Based Testing as Assessment Tool in Chemistry Learning on University Level

Testing as an assessment technique has been widely used at all levels of education—from primary to higher school. The main purpose of the paper is to evaluate the effect of context-based testing in teaching and learning of analytical chemistry in a Russian university. The paper formulates the objectives of context-based testing, discusses its features and compares with conventional testing; proposes a model of constructing and administering context-based testing; provides examples of context-based tests. The experiment was conducted at the Ural Sate University of Economics (Russia) with bachelor’s degree students with nonscience majors. Students were assigned to one of the experimental conditions: in the control group, traditional tests were carried out, while the experimental group students experienced context-based testing. The statistical data—students’ test scores—obtained at all stages of the experiment were analyzed on the basis of statistical criteria (Shapiro–Wilk, Student’s T, Fisher). The findings of our experiment enable us to answer the guided research questions. Context-based testing may be considered as an essential component of context-based teaching and learning. In comparison with conventional testing, context-based testing could impact developing knowledge of fundamental analytical chemistry concepts and contribute to more solid knowledge.