Search results for: linear correlation

Authors: Ghazal Doostmohammadi, Susan Rahimzadeh

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Aim: This research aimed to investigate the relationship between empathy and interpersonal trust and recognize the mediating role of loneliness between them in both genders. Methods: With a correlational descriptive design, 192 university students (130 female and 62 male) responded to the questionnaires on “empathy quotient,” “loneliness,” and “interpersonal trust” tests. These tests were designed and validated by experts in the field. Data were analysed using Pearson correlation and path analysis, which is a statistical technique that uses standard linear regression equations to determine the degree of conformity of a theoretical causal model with reality. Results: The data analysis showed that there was no significant correlation between interpersonal trust, both with loneliness (t=0.169) and empathy (t=0.186), while there was a significant negative correlation (t=0.359) between empathy and loneliness. This means that there is an inverse correlation between empathy and loneliness. The path analysis confirmed the hypothesis of the research about the mediating role of loneliness between empathy and interpersonal trust. But gender did not play a role in this relationship. Conclusion: As an outcome, clinical professionals and education trainers should pay more attention to interpersonal trust as a basic need and try to recreate and shape it to prevent people's social breakdown, and on the other hand, self-disclosure training (especially in Men), expression of feelings and courage should be given double importance to prevent the consequences of loneliness.

Keywords: empathy, loneliness, interpersonal trust, gender

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Authors: G. I. Onwuka, A. Danbaba, S. U. Gulumbe

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This study investigated of Infant Mortality Rate as observed at a general hospital in Kaduna-South, Kaduna State, North West Nigeria. The causes of infant Mortality were examined. The data used for this analysis were collected at the statistics unit of the Hospital. The analysis was carried out on the data using Multiple Linear regression Technique and this showed that there is linear relationship between the dependent variable (death) and the independent variables (malaria, measles, anaemia, and coronary heart disease). The resultant model also revealed that a unit increment in each of these diseases would result to a unit increment in death recorded, 98.7% of the total variation in mortality is explained by the given model. The highest number of mortality was recorded in July, 2005 and the lowest mortality recorded in October, 2009.Recommendations were however made based on the results of the study.

Keywords: infant mortality rate, multiple linear regression, diseases, serial correlation

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Authors: Ahmed Abdelghany, Bernard Uguen, Christophe Moy, Dominique Lemur

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The Internet of Things (IoT) is developed to ensure monitoring and connectivity within different applications. Thus, it is critical to study the channel propagation characteristics in Low Power Wide Area Network (LPWAN), especially Long Range Wide Area Network (LoRaWAN). In this paper, an in-depth investigation of the reciprocity between the uplink and downlink Channel State Information (CSI) is done by performing an outdoor measurement campaign in the area of Campus Beaulieu in Rennes. At each different location, the CSI reciprocity is quantified using the Pearson Correlation Coefficient (PCC) which shows a very high linear correlation between the uplink and downlink CSI. This reciprocity feature could be utilized for the physical layer security between the node and the gateway. On the other hand, most of the CSI shapes from different locations are highly uncorrelated from each other. Hence, it can be anticipated that this could achieve significant localization gain by utilizing the frequency hopping in the LoRa systems by getting access to a wider band.

Keywords: IoT, LPWAN, LoRa, effective signal power, onsite measurement

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Authors: B. Güney, Ç. Teke

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In recent years, rapid and correct decision making is crucial for both people and enterprises. However, uncertainty makes decision-making difficult. Fuzzy logic is used for coping with this situation. Thus, fuzzy linear programming models are developed in order to handle uncertainty in objective function and the constraints. In this study, a problem of a factory in food industry is investigated, required data is obtained and the problem is figured out as a fuzzy linear programming model. The model is solved using Zimmerman approach which is one of the approaches for fuzzy linear programming. As a result, the solution gives the amount of production for each product type in order to gain maximum profit.

Keywords: food industry, fuzzy linear programming, fuzzy logic, linear programming

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Authors: Hazem Al-Mofleh, John Daniels, Joseph McKean

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Within geostatistics research, effective estimation of the variogram points has been examined, particularly in developing robust alternatives. The parametric fit of these variogram points which eventually defines the kriging weights, however, has not received the same attention from a robust perspective. This paper proposes the use of the non-linear Wilcoxon norm over weighted non-linear least squares as a robust variogram fitting alternative. First, we introduce the concept of variogram estimation and fitting. Then, as an alternative to non-linear weighted least squares, we discuss the non-linear Wilcoxon estimator. Next, the robustness properties of the non-linear Wilcoxon are demonstrated using a contaminated spatial data set. Finally, under simulated conditions, increasing levels of contaminated spatial processes have their variograms points estimated and fit. In the fitting of these variogram points, both non-linear Weighted Least Squares and non-linear Wilcoxon fits are examined for efficiency. At all levels of contamination (including 0%), using a robust estimation and robust fitting procedure, the non-weighted Wilcoxon outperforms weighted Least Squares.

Keywords: non-linear wilcoxon, robust estimation, variogram estimation, wilcoxon norm

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Authors: John Kabuba

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The study investigated the implementation of the Neural Network (NN) techniques for prediction of the loading of Cu ions onto clinoptilolite. The experimental design using analysis of variance (ANOVA) was chosen for testing the adequacy of the Neural Network and for optimizing of the effective input parameters (pH, temperature and initial concentration). Feed forward, multi-layer perceptron (MLP) NN successfully tracked the non-linear behavior of the adsorption process versus the input parameters with mean squared error (MSE), correlation coefficient (R) and minimum squared error (MSRE) of 0.102, 0.998 and 0.004 respectively. The results showed that NN modeling techniques could effectively predict and simulate the highly complex system and non-linear process such as ion-exchange.

Keywords: clinoptilolite, loading, modeling, neural network

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Authors: Altayeb Abdalla Ahmed

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Skeletal phenotype is a product of a balanced interaction between genetics and environmental factors throughout different life stages. Therefore, interlimb proportions are variable between populations. Although interlimb proportion indices have been used in anthropology in assessing the influence of various environmental factors on limbs, an extensive literature review revealed that there is a paucity of published research assessing interlimb part correlations and possibility of reconstruction. Hence, this study aims to assess the relationships between upper and lower limb parts and develop regression formulae to reconstruct the parts from one another. The left upper arm length, ulnar length, wrist breadth, hand length, hand breadth, tibial length, bimalleolar breadth, foot length, and foot breadth of 376 right-handed subjects, comprising 187 males and 189 females (aged 25-35 years), were measured. Initially, the data were analyzed using basic univariate analysis and independent t-tests; then sex-specific simple and multiple linear regression models were used to estimate upper limb parts from lower limb parts and vice-versa. The results of this study indicated significant sexual dimorphism for all variables. The results indicated a significant correlation between the upper and lower limbs parts (p < 0.01). Linear and multiple (stepwise) regression equations were developed to reconstruct the limb parts in the presence of a single or multiple dimension(s) from the other limb. Multiple stepwise regression equations generated better reconstructions than simple equations. These results are significant in forensics as it can aid in identification of multiple isolated limb parts particularly during mass disasters and criminal dismemberment. Although a DNA analysis is the most reliable tool for identification, its usage has multiple limitations in undeveloped countries, e.g., cost, facility availability, and trained personnel. Furthermore, it has important implication in plastic and orthopedic reconstructive surgeries. This study is the only reported study assessing the correlation and prediction capabilities between many of the upper and lower dimensions. The present study demonstrates a significant correlation between the interlimb parts in both sexes, which indicates a possibility to reconstruction using regression equations.

Keywords: anthropometry, correlation, limb, Sudanese

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Authors: Mehdi Jafari Matehkolaee

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In this paper, we have obtained the adjoint of an arbitrary operator (linear and nonlinear) in Hilbert space by introducing an n-dimensional Riemannian manifold. This general formalism covers every linear operator (non – differential) in Hilbert space. In fact, our approach shows that instead of using the adjoint definition of an operator directly, it can be obtained directly by relying on a suitable generalized space according to the action of the operator in question. For the case of nonlinear operators, we have to change the definition of the linear operator adjoint. But here, we have obtained an adjoint of these operators with respect to the definition of the derivative of the operator. As a matter of fact, we have shown one of the straight applications of the ''Frechet derivative'' in the algebra of the operators.

Keywords: adjoint operator, non-linear operator, differentiable operator, manifold

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Authors: Mishu Gupta, Rama Gupta

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It has been elucidated here that non- autonomous discrete non-linear Schrödinger equation is associated with saturable non-linearity through photo-refractive media. We have investigated the localized solution of non-autonomous saturable discrete non-linear Schrödinger equations. The similarity transformation has been involved in converting non-autonomous saturable discrete non-linear Schrödinger equation to constant-coefficient saturable discrete non-linear Schrödinger equation (SDNLSE), whose exact solution is already known. By back substitution, the solution of the non-autonomous version has been obtained. We have analysed our solution for the hyperbolic and periodic form of gain/loss term, and interesting results have been obtained. The most important characteristic role is that it helps us to analyse the propagation of electromagnetic waves in glass fibres and other optical wave mediums. Also, the usage of SDNLSE has been seen in tight binding for Bose-Einstein condensates in optical mediums. Even the solutions are interrelated, and its properties are prominently used in various physical aspects like optical waveguides, Bose-Einstein (B-E) condensates in optical mediums, Non-linear optics in photonic crystals, and non-linear kerr–type non-linearity effect and photo refracting medium.

Keywords: B-E-Bose-Einstein, DNLSE-Discrete non linear schrodinger equation, NLSE-non linear schrodinger equation, SDNLSE - saturable discrete non linear Schrodinger equation

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Authors: Rabia Khan, Nargis Munir, Suriya Gharib, Syeda Roshana Ali

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In this paper linear equations are discussed in detail along with elimination method. Gaussian elimination and Gauss Jordan schemes are carried out to solve the linear system of equation. This paper comprises of matrix introduction, and the direct methods for linear equations. The goal of this research was to analyze different elimination techniques of linear equations and measure the performance of Gaussian elimination and Gauss Jordan method, in order to find their relative importance and advantage in the field of symbolic and numeric computation. The purpose of this research is to revise an introductory concept of linear equations, matrix theory and forms of Gaussian elimination through which the performance of Gauss Jordan and Gaussian elimination can be measured.

Keywords: direct, indirect, backward stage, forward stage

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Authors: Qasim M. Kriri

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Few Saudi Arabia production companies face financial profit issues until this moment. This work presents a linear integer programming model that solves a production problem of a Saudi Food Company in Saudi Arabia. An optimal solution to the above-mentioned problem is a Linear Programming solution. In this regard, the main purpose of this project is to maximize profit. Linear Programming Technique has been used to derive the maximum profit from production of natural juice at Saudi Food Co. The operations of production of the company were formulated and optimal results are found out by using Lindo Software that employed Sensitivity Analysis and Parametric linear programming in order develop Linear Programming. In addition, the parameter values are increased, then the values of the objective function will be increased.

Keywords: parameter linear programming, objective function, sensitivity analysis, optimize profit

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Authors: Chico Horacio Jose Sambo

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Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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Authors: A. Benhamena, L. Aminallah, A. Aid, M. Benguediab, A. Amrouche

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The goal of this work is to analyze the severity of interfacial stress distribution in the single lap adhesive joint under tensile loading. The three-dimensional and non-linear finite element method based on the computation of the peel and shear stresses was used to analyze the fracture behaviour of single lap adhesive joint. The effect of the loading magnitude and the overlap length on the distribution of peel and shear stresses was highlighted. A good correlation was found between the FEM simulations and the analytical results.

Keywords: aluminum 2024-T3 alloy, single-lap adhesive joints, Interface stress distributions, material nonlinear analysis, adhesive, bending moment, finite element method

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Authors: Ningning Liu, Gaoding Jia, Yinshan Wang, Haimei Li, Xinian Zuo, Yufeng Wang, Lu Liu, Qiujin Qian

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Background: There has been speculation that a high IQ may not necessarily provide protection against attention deficit hyperactivity disorder (ADHD), and there may be a U-shaped correlation between IQ and ADHD symptoms. However, this speculation has not been validated in the ADHD population in any study so far. Method: We conducted a study with 5,138 children who have been professionally diagnosed with ADHD and have a wide range of IQ levels. General Linear Models were used to determine the optimal model between IQ and ADHD core symptoms with sex and age as covariates. The ADHD symptoms we looked at included the total scores (TO), inattention (IA) and hyperactivity/impulsivity (HI). Wechsler Intelligence scale were used to assess IQ [Full-Scale IQ (FSIQ), Verbal IQ (VIQ), and Performance IQ (PIQ)]. Furthermore, we examined the correlation between IQ and the execution function [Behavior Rating Inventory of Executive Function (BRIEF)], as well as between IQ and brain surface area, to determine if the associations between IQ and ADHD symptoms are reflected in executive functions and brain structure. Results: Consistent with previous research, the results indicated that FSIQ and VIQ both showed a linear negative correlation with the TO and IA scores of ADHD. However, PIQ showed an inverted U-shaped relationship with the TO and HI scores of ADHD, with 103 as the peak point. These findings were also partially reflected in the relationship between IQ and executive functions, as well as IQ and brain surface area. Conclusion: To sum up, the relationship between IQ and ADHD symptoms is not straightforward. Our study confirms long-standing academic hypotheses and finds that PIQ exhibits an inverted U-shaped relationship with ADHD symptoms. This study enhances our understanding of symptoms and behaviors of ADHD with varying IQ characteristics and provides some evidence for targeted clinical intervention.

Keywords: ADHD, IQ, execution function, brain imaging

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Authors: Yu-Chien Huang, Shu-Chen Yang

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Introduction: Parenting style, non-attachment, and inferiority are important topics in psychology, but the related research on nonattachment is still lacking. Therefore, the purposes of this study were to explore the relationship between parenting style, nonattachment, and inferiority. Methods: We conducted a correlational study, and three instruments were utilized to collect data: parenting style scale, nonattachment scale, and inferiority scale. The inter-reliability Cronbach's α used in this research indicated good inter item reliability and the test-retest reliability that showed a good consistency. The data were analyzed using the descriptive statistics, Chi-square test, one way ANOVA, Pearson’s correlation, and regression analysis. Results: A total of 200 participators were tested in this research. As a result of the study, inferiority had a positive correlation with authoritarian parenting style; nonattachment had a negative correlation with authoritarian parenting style; and with inferiority, the hypothesis was supported. In the linear mediation models, nonattachment was found to be partially mediated the relationship between authoritarian parenting style and inferiority. Conclusion: These findings imply that interventions aimed at enhancing nonattachment as a way to improve inferiority are a good strategy.

Keywords: inferiority, nonattachment, parenting style, psychology

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Authors: Suparman

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Piecewise linear regression models are very flexible models for modeling the data. If the piecewise linear regression models are matched against the data, then the parameters are generally not known. This paper studies the problem of parameter estimation of piecewise linear regression models. The method used to estimate the parameters of picewise linear regression models is Bayesian method. But the Bayes estimator can not be found analytically. To overcome these problems, the reversible jump MCMC algorithm is proposed. Reversible jump MCMC algorithm generates the Markov chain converges to the limit distribution of the posterior distribution of the parameters of picewise linear regression models. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of picewise linear regression models.

Keywords: regression, piecewise, Bayesian, reversible Jump MCMC

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Authors: Wenpeng You, Maciej Henneberg

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Background: Sugar consumption has been overwhelmingly advocated as a major dietary offender to obesity prevalence. Meat intake has been hypothesized as an obesity contributor in previous publications, but a moderate amount of meat to be included in our daily diet still has been suggested in many dietary guidelines. Comparable sugar and meat exposure data were obtained to assess the difference in relationships between the two major food groups and obesity prevalence at population level. Methods: Population level estimates of obesity and overweight rates, per capita per day exposure of major food groups (meat, sugar, starch crops, fibers, fats and fruits) and total calories, per capita per year GDP, urbanization and physical inactivity prevalence rate were extracted and matched for statistical analysis. Correlation coefficient (Pearson and partial) comparisons with Fisher’s r-to-z transformation and β range (β ± 2 SE) and overlapping in multiple linear regression (Enter and Stepwise) were used to examine potential differences in the relationships between obesity prevalence and sugar exposure and meat exposure respectively. Results: Pearson and partial correlations (controlled for total calories, physical inactivity prevalence, GDP and urbanization) analyses revealed that sugar and meat exposures correlated to obesity and overweight prevalence significantly. Fisher's r-to-z transformation did not show statistically significant difference in Pearson correlation coefficients (z=-0.53, p=0.5961) or partial correlation coefficients (z=-0.04, p=0.9681) between obesity prevalence and both sugar exposure and meat exposure. Both Enter and Stepwise models in multiple linear regression analysis showed that sugar and meat exposure were most significant predictors of obesity prevalence. Great β range overlapping in the Enter (0.289-0.573) and Stepwise (0.294-0.582) models indicated statistically sugar and meat exposure correlated to obesity without significant difference. Conclusion: Worldwide sugar and meat exposure correlated to obesity prevalence at the same extent. Like sugar, minimal meat exposure should also be suggested in the dietary guidelines.

Keywords: meat, sugar, obesity, energy surplus, meat protein, fats, insulin resistance

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Authors: Sie Long Kek, Wah June Leong, Kok Lay Teo

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Linear quadratic Gaussian model is a standard mathematical model for the stochastic optimal control problem. The combination of the linear quadratic estimation and the linear quadratic regulator allows the state estimation and the optimal control policy to be designed separately. This is known as the separation principle. In this paper, an efficient computational method is proposed to solve the linear quadratic Gaussian problem. In our approach, the Hamiltonian function is defined, and the necessary conditions are derived. In addition to this, the output error is defined and the least-square optimization problem is introduced. By determining the first-order necessary condition, the gradient of the sum squares of output error is established. On this point of view, the stochastic approximation approach is employed such that the optimal control policy is updated. Within a given tolerance, the iteration procedure would be stopped and the optimal solution of the linear-quadratic Gaussian problem is obtained. For illustration, an example of the linear-quadratic Gaussian problem is studied. The result shows the efficiency of the approach proposed. In conclusion, the applicability of the approach proposed for solving the linear quadratic Gaussian problem is highly demonstrated.

Keywords: iteration procedure, least squares solution, linear quadratic Gaussian, output error, stochastic approximation

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Authors: Raya Al Khayari, Rasha Al Jassim, Muna Al Balushi, Fatma Al Moqbali, Said El Hajjar

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This study utilizes linear regression analysis to investigate the correlation between user account passwords and the probability of civil ID exposure, offering statistical insights into civil ID security. The study employs multiple linear regression (MLR) analysis to further investigate the elements that influence consumers’ views of civil ID security. This aims to increase awareness and improve preventive measures. The results obtained from the MLR analysis provide a thorough comprehension and can guide specific educational and awareness campaigns aimed at promoting improved security procedures. In summary, the study’s results offer significant insights for improving existing security measures and developing more efficient tactics to reduce risks related to civil ID security in Oman. By identifying key factors that impact consumers’ perceptions, organizations can tailor their strategies to address vulnerabilities effectively. Additionally, the findings can inform policymakers on potential regulatory changes to enhance civil ID security in the country.

Keywords: civil-id disclosure, awareness, linear regression, multiple regression

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Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

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Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

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Authors: M. Berrehail, F. Benamira

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We study the quantum motion of a particle in the presence of a time- dependent linear potential using an operator invariant that is quadratic in p and linear in q within the framework of the Lewis-Riesenfeld invariant, The special invariant operator proposed in this work is demonstrated to be an Hermitian operator which has an Airy wave packet as its Eigenfunction

Keywords: airy wave packet, ivariant, time-dependent linear potential, unitary transformation

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Authors: Kaushalendra K. Khadanga, Lee Hee Hyol

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Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.

Keywords: active suspension, bending vibration, railway vehicle, vibration control

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Authors: Sujeet Kumar Singh, Shiv Prasad Yadav

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This paper develops an approach for solving intuitionistic fuzzy linear fractional programming (IFLFP) problem where the cost of the objective function, the resources, and the technological coefficients are triangular intuitionistic fuzzy numbers. Here, the IFLFP problem is transformed into an equivalent crisp multi-objective linear fractional programming (MOLFP) problem. By using fuzzy mathematical programming approach the transformed MOLFP problem is reduced into a single objective linear programming (LP) problem. The proposed procedure is illustrated through a numerical example.

Keywords: triangular intuitionistic fuzzy number, linear programming problem, multi objective linear programming problem, fuzzy mathematical programming, membership function

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Authors: Fauzi Jarushi, Sinan Mohsin AlKaabi

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The Standard Penetration Test (SPT) is the most common insitu test for soil investigations. On the other hand, the Cone Penetration Test (CPT) is considered one of the best investigation tools. Due to the fast and accurate results that can be obtained it complaints the SPT in many applications like field explorations, design parameters, and quality control assessments. Many soil index and engineering properties have been correlated to both of SPT and CPT. Various foundation design methods were developed based on the outcome of these tests. Therefore it is vital to correlate these tests to each other so that either one of the tests can be used in the absence of the other, especially for preliminary evaluation and design purposes. The primary purpose of this study was to investigate the relationships between the SPT and CPT for different types of soil in Florida. Data for this research were collected from number of projects sponsored by the Florida Department of Transportation (FDOT), six sites served as the subject of SPT-CPT correlations. The correlations were established between the cone resistance (qc) and the SPT blows (i.e., N) for various soils. A positive linear relationship was found between fs and N for various soils. In general, qc versus N showed higher correlation coefficients than fs versus N. qc/N ratios were developed for different soil types and compared to literature values, the results of this research revealed higher ratios than literature values.

Keywords: in situ tests, correlation, SPT, CPT

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Authors: Tulin Coskun

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We investigate the approximation of analytic functions of several variables in polydisc by the sequences of linear k-positive operators in Gadjiev sence. The approximation of analytic functions of complex variable by linear k-positive operators was tackled, and k-positive operators and formulated theorems of Korovkin's type for these operators in the space of analytic functions on the unit disc were introduced in the past. Recently, very general results on convergence of the sequences of linear k-positive operators on a simply connected bounded domain within the space of analytic functions were proved. In this presentation, we extend some of these results to the approximation of analytic functions of several complex variables by sequences of linear k-positive operators.

Keywords: analytic functions, approximation of analytic functions, Linear k-positive operators, Korovkin type theorems

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Authors: Milena Serzante, Viktoriia Stankevich, Yousre Badir

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Companies have a significant impact on the environment and society, and sustainability is important not only for ethical concerns but also for financial and economic reasons. The aim of the study is to analyze how the sustainable performance of the company impacts the economy and the business's economic performance. To achieve this goal, such methods as the Pearson correlation, Multiple Linear Regression, Cook's distance method, K-nearest neighbor and COPRAS technique were implemented. The results revealed that there is no significant correlation between different indicators of sustainable development of the company and both GDP and Return on Equity. It indicates that the methodology of evaluating sustainability causes the difference in ranking companies based on sustainable performance.

Keywords: economic impact, sustainability evaluation, sustainable companies, economic indicators, sustainability, GDP, return on equity

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Authors: Peyman Sindareh Esfahani, Jeffery Kurt Pieper

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In this paper, the problem of robust model predictive control (MPC) for discrete-time linear systems in linear fractional transformation form with structured uncertainty and norm-bounded disturbance is investigated. The problem of minimization of the cost function for MPC design is converted to minimization of the worst case of the cost function. Then, this problem is reduced to minimization of an upper bound of the cost function subject to a terminal inequality satisfying the l₂-norm of the closed loop system. The characteristic of the linear fractional transformation system is taken into account, and by using some mathematical tools, the robust predictive controller design problem is turned into a linear matrix inequality minimization problem. Afterwards, a formulation which includes an integrator to improve the performance of the proposed robust model predictive controller in steady state condition is studied. The validity of the approaches is illustrated through a robust control benchmark problem.

Keywords: linear fractional transformation, linear matrix inequality, robust model predictive control, state feedback control

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Authors: Branka Milicic Stanic, Romana Mijovic

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In primary hyperparathyroidism, an increased risk of developing cardiovascular disease may exist due to increased activity of the renin-angiotensin-aldosterone system (RAAS). In adenomatous altered tissue of parathyroid gland, compared to normal tissue, there are two to fourfold increase in the expression of type 1 angiotensin II receptors. As there is a clear evidence of the independent role of aldosterone on the cardiovascular system, the aim of this study was to evaluate the existence of an association between aldosterone secretion and parathyroid hormone in patients with primary hyperparathyroidism. This study included 48 patients with elevated parathyroid hormone who had come to the Departement of Nuclear Medicine, Clinical Center of Vojvodina, for Parathyroid Scintigraphy. The control group consisted of 30 healthy subjects who matched age and gender to the study group. All the results were statistically processed by statistical package STATISTICA 14 (Statsoft Inc,Tulsa, OK, USA). The survey was conducted between February 2017 and April 2018 at the Departement of Nuclear Medicine and at the Departement for Endocinology Diagnoistics, in Clinical Center of Vojvodina, Novi Sad. Compared to the control group, the study group had statistically significantly higher values of aldosterone (p=0.028), total calcium (p=0.01), ionized calcium (p=0.003) and parathyroid hormone (N-TACT PTH) (p=0.00), while statistically a significant lower levels in the study group were for phosphorus (p=0.003) and vitamin D (p=0.04). A linear correlation analysis in the study group revealed a statistically significant degree of positive correlation between renin and N-TACT PTH (r=0.688, p<0.05); renin and calcium (r=0.673, p<0.05) and renin and ionized calcium (r=0.641, p<0.05). Serum aldosterone and parathyroid hormone levels (N-TACT) were correlated positively in patients with primary hyperparathyroidism (r=0.509, p<0.05). According to the linear correlation analysis in the control group, aldosterone showed no positive correlation with N-TACT PTH (r=-0.285, p>0.05), as well as total and ionized calcium (r=-0.200, p>0.05; r=-0.313, p>0.05). In multivariate regression analysis of the study group, the strongest predictive variable of aldosterone secretion was N-TACT PTH (p=0.011). Aldosterone correlated positively to PTH levels in patients with primary hyperparathyroidism, and the fact is that in these patients aldosterone might be a key mediator of cardiovascular symptoms. All this knowledge should help to find new treatments to prevent cardiovascular disease.

Keywords: aldosterone, hyperparathyroidism, parathyroid hormone, parathyroid gland

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Authors: S. Abbsi, M. R. Hadian, M. Abdolvahab, M. Jalili, S. Khafri

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Background: According to physical effects of cardiovascular accident (CVA) which is the most common disabilities in adulthood. It seems attention to treatment and rehabilitation of this patient has importance. Hemiplegic patients have been experienced of wild functional disabilities. Numerous patients have been suffered from upper limb disabilities. Aim of this study correlation of pinch and grip strength with dexterity in adult hemiplegic. Methods: 34 adult hemiplegic in range of 50-70 years participate in this study. After introduce and take a satisfaction patient, pinch and grip strength have evaluated by dynamometer and dexterity have evaluated by Minnesota manual dexterity test and correlation effects of them have studied. Result: According to result of present investigation, patients with hemiplegia have shown significant correlation between dexterity with pinch and grip strength. Conclusion: Dexterity has correlation with pinch and grip strength, but it seems, not have correlation with age and duration of CVA.

Keywords: pinch strength, grip strength, dexterity, hemiplegia

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

Abstract:

In this paper, quantitative structure-retention relationships (QSRR) analysis was applied in order to correlate in silico biological and lipophilicity molecular descriptors with retention values for the set of selected s-triazine herbicides. In silico generated biological and lipophilicity descriptors were discriminated using generalized pair correlation method (GPCM). According to this method, the significant difference between independent variables can be noticed regardless almost equal correlation with dependent variable. Using established multiple linear regression (MLR) models some biological characteristics could be predicted. Established MLR models were evaluated statistically and the most suitable models were selected and ranked using sum of ranking differences (SRD) method. In this method, as reference values, average experimentally obtained values are used. Additionally, using SRD method, similarities among investigated s-triazine herbicides can be noticed. These analysis were conducted in order to characterize selected s-triazine herbicides for future investigations regarding their biodegradability. This study is financially supported by COST action TD1305.

Keywords: descriptors, generalized pair correlation method, pesticides, sum of ranking differences

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