scholarly journals Analysis of predictive capabilities of metacognitive strategies in the expression of professional thinking of military personnel

2021 ◽  
Vol 15 (4) ◽  
pp. 638-647
Author(s):  
I. O. Smolentsev ◽  
J. M. Perevozkina ◽  
M. I. Fedorishin
Keyword(s):  
Time Management ◽  
Information Acquisition ◽  
Regression Models ◽  
Metacognitive Strategies ◽  
Variable Response ◽  
Problem Situations ◽  
Multiple Stepwise Regression Analysis ◽  
Metacognitive Activity ◽  
Military Activity

The article examines professional thinking in relation to the conditions of military activity. The goal is to identify a model of cadets’ metacognitive competence, contributing to the successful formation of professional thinking in the conditions of military activity. The construction of two regression models is carried out by means of multiple stepwise regression analysis with inclusion. In the first model, the variable response was the over-situational style of thinking of servicemen, determined by the questionnaire «Determination of the dominant level of problematicity in solving service-professional problem situations.» In the second model of the variable, the response was the type of professional thinking determined on the basis of the case method. Cadets’ metacognitive strategies were used as variable predictors. It was possible to establish that both regression models are statistically significant, the level of error probability is less than 0.01% and explain more than 40% of the variability of the variable responses. All metacognitive strategies (six variable predictors) in the first model have a statistically significant relationship with variable responses (p≤0.05). The predictive influence on the dominance of a certain type of professional thinking among cadets has the character of structural interaction. Metacognitive strategies such as information acquisition, concentration, time management and the level of reflection are facilitators for the formation of a supra-situational level of cadets’ professional thinking. Whereas metacognitive knowledge and metacognitive activity act as inhibitors.

scholarly journals A NON-DESTRUCTIVE METHOD FOR ESTIMATING LEAF AREA OF Ceiba glaziovii (Kuntze) K. Schum.

FLORESTA ◽  
2019 ◽  
Vol 50 (1) ◽  
pp. 1063
Author(s):  
João Everthon da Silva Ribeiro ◽  
Francisco Romário Andrade Figueiredo ◽  
Ester Dos Santos Coêlho ◽  
Walter Esfrain Pereira ◽  
Manoel Bandeira de Albuquerque
Keyword(s):  
Leaf Area ◽  
Regression Models ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Linear Measurements ◽  
Maximum Width ◽  
Bias Index ◽  
Different Shapes ◽  
Non Destructive

The determination of leaf area is of fundamental importance in studies involving ecological and ecophysiological aspects of forest species. The objective of this research was to adjust an equation to determine the leaf area of Ceiba glaziovii as a function of linear measurements of leaves. Six hundred healthy leaf limbs were collected in different matrices, with different shapes and sizes, in the Mata do Pau-Ferro State Park, Areia, Paraíba state, Northeast Brazil. The maximum length (L), maximum width (W), product between length and width (L.W), and leaf area of the leaf limbs were calculated. The regression models used to construct equations were: linear, linear without intercept, quadratic, cubic, power and exponential. The criteria for choosing the best equation were based on the coefficient of determination (R²), Akaike information criterion (AIC), root mean square error (RMSE), Willmott concordance index (d) and BIAS index. All the proposed equations satisfactorily estimate the leaf area of C. glaziovii, due to their high determination coefficients (R² ≥ 0.851). The linear model without intercept, using the product between length and width (L.W), presented the best criteria to estimate the leaf area of the species, using the equation 0.4549*LW.

scholarly journals Determination of collected porcini and chanterelle quantities depending on different climate change scenarios

2016 ◽  
pp. 77-98
Author(s):  
Nenad Rankovic ◽  
Jelena Nedeljkovic ◽  
Zoran Poduska ◽  
Dragan Nonic
Keyword(s):  
Climate Change ◽  
Growth Rate ◽  
Regression Models ◽  
The Other ◽  
Climate Change Scenarios ◽  
Exponential Growth Rate ◽  
Scientific Methods ◽  
Exponential Regression ◽  
Modelling Methods

This study examines the influence of some climate elements on the collected quantities of two commercially most significant types of mushrooms in Serbia (porcini and chanterelle). The main objective of the research is to determine the extent of the collected quantity of porcini and chanterelle, which can be expected in different scenarios of climate change (?1Bmin, ?1Bmax, A2min ? A2max), based on forecasts of temperature and rainfall changes. The general (dialectical) and specific (modelling methods) are used in the research, as well as the classical scientific methods of reasoning. The calculation of the average annual exponential growth rate (IS) was carried out by forming exponential regression models of the trend of porcini and chanterelle collected quantities. In the research it was found that, according to the data related to the period up to 2014, one can expect a decrease in the movement of both porcini and chanterelle IS, and thus a decrease in the collected quantities. On the other hand, according to the data related to the period up to 2040, in both cases one can expect some fluctuation (increase and decrease) in the movement of IS. According to the data related to periods after 2041 (especially for the period until 2100), in both cases, one can expect a decrease in the collected quantities, as a result of changes in T and P, caused by the assumed climate change.

scholarly journals Pengaruh Kompetensi dan Kegiatan Komite Audit terhadap Kualitas Audit

2019 ◽  
Vol 14 (1) ◽  
pp. 25-36
Author(s):  
Dayu Swispa Pamantau
Keyword(s):  
Regression Models ◽  
Audit Committee ◽  
Audit Quality ◽  
Analysis Method ◽  
Linear Regression Models ◽  
High Competence ◽  
The City ◽  
A Company

The accuracy of the determination of policies within a company is determined by the quality of the resulting audit by the auditor. Audit quality will be higher when the auditor assigned to have high competence in the field of audit, in addition to the quality of the audit will be better if the activities of the audit committee to provide oversight of internal party activities. Therefore, this study purpose to determine the effect of the competence and activities of the audit committee on audit quality. The study was conducted at the KAP region of the city of Padang and Pekanbaru. The sample used was 43 respondents. The analysis method used is to use multiple linear regression models. Based on the results of hypothesis testing results found that the competence and activities of the audit committee have a significant effect on audit quality auditors working in KAP of Padang and Pekanbaru city.

scholarly journals Star Positions from Overlapping Plates in the Cape Zone −40° to −52°

1974 ◽  
Vol 61 ◽  
pp. 305-306
Author(s):  
S. V. M. Clube
Keyword(s):  
Regression Models ◽  
Preliminary Results ◽  
Normal Regression

A modification of the normal regression models used for the determination of star positions is described. Some preliminary results relating to accuracy are given.

SEQUENTIAL EXTRACTION OF FUZZY REGRESSION MODELS: LEAST SQUARES AND LEAST ABSOLUTE DEVIATIONS

2011 ◽  
Vol 19 (supp01) ◽  
pp. 53-63 ◽  
Author(s):  
HENGJIN TANG ◽  
SADAAKI MIYAMOTO
Keyword(s):  
Least Squares ◽  
Regression Models ◽  
Fuzzy Regression ◽  
Noise Detection ◽  
Automatic Determination ◽  
Number Of Clusters ◽  
Least Absolute Deviations ◽  
Input And Output ◽  
Scalar Input

Fuzzy c-regression models are known to be useful in real applications, but there are two drawbacks: strong dependency on the predefined number of clusters and sensitiveness against outliers or noises. To avoid these drawbacks, we propose sequential fuzzy regression models based on least absolute deviations which we call SFCRMLAD. This algorithm sequentially extracts one cluster at a time using a method of noise-detection, enabling the automatic determination of clusters and having robustness to noises. We compare this method with the ordinary fuzzy c-regression models based on least squares, fuzzy c-regression models based on least absolute deviations, and moreover sequential fuzzy regression models based on least squares. For this purpose we use a two-dimensional illustrative example whereby characteristics of the four methods are made clear. Moreover a simpler and more efficient algorithm of SFCRMLAD can be used for scalar input and output variables, while a general algorithm of SFCRMLAD uses linear programming solutions for multivariable input. By using the above example, we compare efficiency of different algorithms.

Twelve different types of data normalization for the proposition of classification, univariate and multivariate regression models for the direct analyses of alloys by laser-induced breakdown spectroscopy (LIBS)

2016 ◽  
Vol 31 (10) ◽  
pp. 2005-2014 ◽  
Author(s):  
Jeyne Pricylla Castro ◽  
Edenir Rodrigues Pereira-Filho
Keyword(s):  
Multivariate Regression ◽  
Regression Models ◽  
Direct Analysis ◽  
Laser Induced Breakdown Spectroscopy ◽  
Emission Signal ◽  
Breakdown Spectroscopy ◽  
Different Types ◽  
Laser Induced Breakdown ◽  
Signal Normalization

Emission signal normalization in LIBS for the direct analysis of metal samples aiming at the determination of 10 analytes (Al, Cr, Cu, Fe, Mn, Mo, Ni, Ti, V and Zn).

Far Eastern Commission

1949 ◽  
Vol 3 (1) ◽  
pp. 180-182 ◽  
Keyword(s):  
Policy Decision ◽  
Policy Decisions ◽  
Military Equipment ◽  
First Category ◽  
Japanese Military ◽  
Military Activity ◽  
Far Eastern

During the period from July 10, 1947 to December 23, 1948, thirteen policy decisions were adopted by the Far Eastern Commission. These fell primarily into three categories–disarmament, democratization, and the determination of a self-sustaining economy for Japan. In the first category the Commission adopted a policy decision on February 12, 1948, entitled “Prohibition of Military Activity in Japan and Disposition of Japanese Military Equipment”. Under the terms of this decision a ministry of war was forbidden, and possession by Japanese of arms, ammunition and implements of war and the development, manufacture or importation of these articles was prohibited

scholarly journals Sewing Thread Consumption for Chain Stitches of Class 400 Using Geometrical and Multilinear Regression Models

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Sarah Malek ◽  
Faouzi Khedher ◽  
Dominique C. Adolphe ◽  
Boubaker Jaouachi
Keyword(s):  
Regression Models ◽  
Geometrical Method ◽  
Multilinear Regression ◽  
Consumption Behavior ◽  
Fabric Thickness ◽  
Sewing Thread ◽  
Stitch Density ◽  
Statistical Results ◽  
Consumption Value

Abstract This work deals with determination of rapid and precise methods to predict the amount of sewing thread needed to sew a garment using different chain stitches of the class 400 (from 401 to 407 chain stitches). At first, to avoid unused stocks, sewing consumption value was determined using a geometrical method (based on different chain stitch shapes). The prediction of the sewing thread consumption was proposed as a function of the studied input parameters, which are fabric thickness, stitch density, yarn linear density, and stitch width. Then, a statistical method based on the multilinear regression was studied. Geometrical and statistical results were discussed. Based on the R2 range, we concluded that the geometrical method is more accurate than the statistical one (from 98.16 to 99.19% and from 97.30 to 98.51%, respectively). Thus, this result encourages industrialists to use geometrical models to predict thread consumption. Also, all studied parameters, contributing to the sewing thread consumption behavior, were investigated and analyzed. The result shows that the most important parameters affecting thread consumption are stitch density followed by stitch width and fabric thickness. The yarn density has a low contribution on the thread consumption value.

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