Search results for: generalized correlations

Authors: Jossitt Williams Vargas Cruz, Aura Jazmín Pérez Ríos

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The variations of solar dynamics have become a relevant topic of study due to the effects of climate changes generated on the earth. One of the most disconcerting aspects is the variability that the sun has on the climate is the role played by sunspots (extra-atmospheric variable) in the modulation of the Cosmic Rays CR (extra-atmospheric variable). CRs influence the earth's climate by affecting cloud formation (atmospheric variable), and solar cycle influence is associated with the presence of solar storms, and the magnetic activity is greater, resulting in less CR entering the earth's atmosphere. The different methods of climate prediction in Colombia do not take into account the extra-atmospheric variables. Therefore, correlations between atmospheric and extra-atmospheric variables were studied in order to implement a Python code based on neural networks to make the prediction of the extra-atmospheric variable with the highest correlation.

Keywords: correlations, cosmic rays, sun, sunspots and variations.

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Authors: Alina Zafar

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In this particular research, various morphometric characters such as total length (TL), wet weight (WW), standard length (SL), fork length (FL), head length (HL), head width (HW), body depth (BD), body girth (BG), dorsal fin length (DFL), pelvic fin length (PelFL), pectoral fin length (PecFL), anal fin length (AFL), dorsal fin base (DFB), anal fin base (AFB), caudal fin length (CFL) and caudal fin width (CFW) of wild collected Puntius sophore were studied, to know the types of growth patterns and correlations in reference to length and weight, however, high significant relationships were recorded between total length and wet weight, as the correlation coefficient (r) possessed value of 0.989. The growth pattern was observed to be positively allometric as the value of ‘b’ was 3.22 (slightly higher than the ideal value, 3) with 95% confidence intervals ranging from 3.076 to 3.372. Wet weight and total length parameters showed high significant correlations (p < 0.001) with all other morphometric characters.

Keywords: Puntius sophore, length and weight relation, morphometrics, small indigenous species

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Authors: Septimia Sarbu

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The entropy rate of a stochastic process is a fundamental concept in information theory. It provides a limit to the amount of information that can be transmitted reliably over a communication channel, as stated by Shannon's coding theorems. Recently, researchers have focused on developing new measures of information that generalize Shannon's classical theory. The aim is to design more efficient information encoding and transmission schemes. This paper continues the study of generalized entropy rates, by deriving a closed-form solution to the Sharma-Mittal entropy rate for Gaussian processes. Using the squeeze theorem, we solve the limit in the definition of the entropy rate, for different values of alpha and beta, which are the parameters of the Sharma-Mittal entropy. In the end, we compare it with Shannon and Rényi's entropy rates for Gaussian processes.

Keywords: generalized entropies, Sharma-Mittal entropy rate, Gaussian processes, eigenvalues of the covariance matrix, squeeze theorem

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Authors: Nikk Leavitt, Peter Kellett, Cheryl Currie, Richard Larouche

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Background: Masculinity has been associated with poor mental health outcomes in adult men and is colloquially referred to as toxic. Masculinity is traditionally measured using the Male Role Norms Inventory, which examines behaviors that may be common in men but that are themselves associated with poor mental health regardless of gender (e.g., aggressiveness). The purpose of this study was to examine if masculinity is associated with generalized anxiety among men using this inventory vs. a man’s personal definition of it. Method: An online survey collected data from 1,200 men aged 18-65 across Canada in July 2022. Masculinity was measured using: 1) the Male Role Norms Inventory Short Form and 2) by asking men to self-define what being masculine means. Men were then asked to rate the extent they perceived themselves to be masculine on a scale of 1 to 10 based on their definition of the construct. Generalized anxiety disorder was measured using the GAD-7. Multiple linear regression was used to examine associations between each masculinity score and anxiety score, adjusting for confounders. Results: The masculinity score measured using the inventory was positively associated with increased anxiety scores among men (β = 0.02, p < 0.01). Masculinity subscales most strongly correlated with higher anxiety were restrictive emotionality (β = 0.29, p < 0.01) and dominance (β = 0.30, p < 0.01). When traditional masculinity was replaced by a man’s self-rated masculinity score in the model, the reverse association was found, with increasing masculinity resulting in a significantly reduced anxiety score (β = -0.13, p = 0.04). Discussion: These findings highlight the need to revisit the ways in which masculinity is defined and operationalized in research to better understand its impacts on men’s mental health. The findings also highlight the importance of allowing participants to self-define gender-based constructs, given they are fluid and socially constructed.

Keywords: masculinity, generalized anxiety disorder, race, intersectionality

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Authors: Regina Tedjasulaksana, Maria Martina Nahak, A. A. Gede Agung, Ni Made Widhiasti

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Strategic effort to realize the empowerment of community in school is through the peer group approach so that it needs to choose the students who are trained as the’ little dentist’ in order to have the cognitive and skills to participate in the school dental health effort (UKGS) program, such as providing oral health education to the other students. Aim: To assessed the effectiveness of peer group approach to enhance the oral health knowledge level of schoolchildren at primary school in Klungkung, Bali. Methods: Experimental study using the pre-post test without control group design. The differences of knowledge levels, tooth brushing behavior and oral hygiene status (using PHP-M index) of 10 students before and after trained as the little dentists were analyzed using paired t-test. The correlations between knowledge level and tooth brushing behavior and correlations between tooth brushing behavior and oral hygiene before and after trained as the little dentists were analyzed using Spearman. Furthermore, the trained little dentists provide oral health education to 102 students of grade 1 to 5 at their school once a week for 3 months. The students’ knowledge level scores of each grade were taken every 21 days as many as three times The difference of it was analyzed using Repeated Measured. Result: The mean scores among all little dentists before and after training for each of knowledge level were each 63.05 + 5.62 and 85.00 + 7.81, tooth brushing behavior were each 31.00 + 14.49 and 100.00 + 0.00 and oral hygiene status using PHP-M index were each 32.80 + 10.17 and 11.40 + 8.01. The knowledge level, tooth brushing behavior and oral hygiene status of 10 students before and after trained as the little dentists were different significantly (p<0.05). Before and after trained as the little dentists it showed that significant correlations between knowledge level with tooth brushing behavior (p<0.05) and significant correlations between tooth brushing behavior and oral hygiene (p<0.05). The mean scores of knowledge level among all students before (pre-test) and after (post-test (1),(2),(3)) getting oral health education from little dentists for each, of grade 1 were 40.00 + 17.97; 67.85 + 18.88; 81.72 +26.48 and 70.00 + 22.87, grade 2 were 40.00 + 17.97; 67.85 + 18.88; 81.72 + 26.48 and 70.00 + 22.87, grade 3 were 65.83 + 23.94; 72.50 + 26.08; 80.41 + 24.93 and 83.75 + 19.74, grade 4 were 88.57 + 12.92; 90.71 + 9.97; 92.85 + 10.69 and 93.57 + 6.33 and grade 5 were 86.66 + 13.40; 93.33 + 9.16; 94.16 + 10.17 and 98.33 + 4.81. The students’ knowledge level of grade 1,2 and 3 before and after getting oral health education from little dentists showed significant different (p<0.05), meanwhile there was no significant different on grade 4 and 5 (p<0.05) although mean scores showed an increase. Conclusion: Peer group approach can be used to enhance the oral health knowledge level of schoolchildren at primary school in Klungkung, Bali.

Keywords: small dentists, oral health, peer group approach, school children

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Authors: Devinder Singh, Rajneesh Kumar, Arvind Kumar

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The present investigation deals with generalized model of the equations for a homogeneous isotropic microstretch thermoelastic half space with mass diffusion medium. Theories of generalized thermoelasticity Lord-Shulman (LS) Green-Lindsay (GL) and Coupled Theory (CT) theories are applied to investigate the problem. The stresses in the considered medium have been studied due to normal force and tangential force. The normal mode analysis technique is used to calculate the normal stress, shear stress, couple stresses and microstress. A numerical computation has been performed on the resulting quantity. The computed numerical results are shown graphically.

Keywords: microstretch, thermoelastic, normal mode analysis, normal and tangential force, microstress force

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Authors: Timothy Kayode Samson, Adedoyin Isola Lawal

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The past five years have shown a sharp increase in public interest in the crypto market, with its market capitalization growing from $100 billion in June 2017 to $2158.42 billion on April 5, 2022. Despite the outrageous nature of the volatility of cryptocurrencies, the use of skewed error innovation distributions in modelling the volatility behaviour of these digital currencies has not been given much research attention. Hence, this study models the volatility of 5 largest cryptocurrencies by market capitalization (Bitcoin, Ethereum, Tether, Binance coin, and USD Coin) using four variants of GARCH models (GJR-GARCH, sGARCH, EGARCH, and APARCH) estimated using three skewed error innovation distributions (skewed normal, skewed student- t and skewed generalized error innovation distributions). Daily closing prices of these currencies were obtained from Yahoo Finance website. Finding reveals that the Binance coin reported higher mean returns compared to other digital currencies, while the skewness indicates that the Binance coin, Tether, and USD coin increased more than they decreased in values within the period of study. For both Bitcoin and Ethereum, negative skewness was obtained, meaning that within the period of study, the returns of these currencies decreased more than they increased in value. Returns from these cryptocurrencies were found to be stationary but not normality distributed with evidence of the ARCH effect. The skewness parameters in all best forecasting models were all significant (p<.05), justifying of use of skewed error innovation distributions with a fatter tail than normal, Student-t, and generalized error innovation distributions. For Binance coin, EGARCH-sstd outperformed other volatility models, while for Bitcoin, Ethereum, Tether, and USD coin, the best forecasting models were EGARCH-sstd, APARCH-sstd, EGARCH-sged, and GJR-GARCH-sstd, respectively. This suggests the superiority of skewed Student t- distribution and skewed generalized error distribution over the skewed normal distribution.

Keywords: skewed generalized error distribution, skewed normal distribution, skewed student t- distribution, APARCH, EGARCH, sGARCH, GJR-GARCH

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Authors: Ledi Neçaj

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Objectives: The target of this paper is (1) to explain objectively physical activity model throughout three chronic cardiopulmonary conditions, and (2) to study the connection among physical activity dimensions with disease severity, self-reported physical and emotional functioning, and exercise performance. Material and Methods: This is a cross-sectional study of patients in their domestic environment. Patients with cardiopulmonary diseases were: chronic obstructive pulmonary disease (COPD), (n-63), coronary heart failure (n=60), and patients with implantable cardioverter defibrillator (n=60). Main results measures: Seven ambulatory physical activity dimensions (total steps, percentage time active, percentage time ambulating at low, medium, and hard intensity, maximum cadence for 30 non-stop minutes, and peak performance) have been measured with an accelerometer. Results: Subjects with COPD had the lowest amount of ambulatory physical activity compared with topics with coronary heart failure and cardiac dysrhythmias (all 7 interest dimensions, P<.05); total step counts have been: 5319 as opposed to 7464 as opposed to 9570, respectively. Six-minute walk distance becomes correlated (r=.44-.65, P<.01) with all physical activity dimensions inside the COPD pattern, the most powerful correlations being with total steps and peak performance. In topics with cardiac impairment, maximal oxygen intake had the most effective small to slight correlations with five of the physical activity dimensions (r=.22-.40, P<.05). In contrast, correlations among 6-minute walk test distance and physical activity have been higher (r=.48-.61, P<.01) albeit in a smaller pattern of most effective patients with coronary heart failure. For all three samples, self-reported physical and mental health functioning, age, frame mass index, airflow obstruction, and ejection fraction had both exceptionally small and no significant correlations with physical activity. Conclusions: Findings from this study present a profitable benchmark of physical activity patterns in individuals with cardiopulmonary diseases for comparison with future studies. All seven dimensions of ambulatory physical activity have disfavor between subjects with COPD, heart failure, and cardiac dysrhythmias. Depending on the research or clinical goal, the use of one dimension, such as total steps, may be sufficient. Although physical activity had high correlations with performance on a six-minute walk test relative to other variables, accelerometers-based physical activity monitoring provides unique, important information about real-world behavior in patients with cardiopulmonary not already captured with existing measures.

Keywords: ambulatory physical activity, walking, monitoring, COPD, heart failure, implantable defibrillator, exercise performance

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Authors: Rahim Ada, Mustafa Harmankaya, Sadiye Ayse Celik

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The safflower seed contains about 25-40% solvent extract and 20-33% fiber. It is well known that dietary phospholipids lower serum cholesterol levels effectively. The nutrient composition of safflower seed changes depending on region, soil and genotypes. This research was made by using of six natural selected (A22, A29, A30, C12, E1, F4, G8, G12, J27) and three commercial (Remzibey, Dincer, Black Sun1) varieties of safflower genotypes. The research was conducted on field conditions for two years (2009 and 2010) in randomized complete block design with three replications in Konya-Turkey ecological conditions. Oil contents, mineral contents and their correlations were determined in the research. According to the results, oil content was ranged from 22.38% to 34.26%, while the minerals were in between the following values: 1469, 04-2068.07 mg kg^-1 for Ca, 7.24-11.71 mg kg^-1 for B, 13.29-17.41 mg kg^-1 for Cu, 51.00-79.35 mg kg^-1 for Fe, 3988-6638.34 mg kg^-1 for K, 1418.61-2306.06 mg kg^-1 for Mg, 11.37-17.76 mg kg^-1 for Mn, 4172.33-7059.58 mg kg^-1 for P and 32.60-59.00 mg kg^-1 for Zn. Correlation analysis that was made separately for the commercial varieties and wild lines showed that high level of oil content was negatively affected by all the investigated minerals except for K and Zn in the commercial varieties.

Keywords: safflower, oil, quality, mineral content

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Authors: Muhammad Nouman Qureshi, Muhammad Hanif

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Adaptive cluster sampling (ACS) is specifically developed for the estimation of highly clumped populations and applied to a wide range of situations like animals of rare and endangered species, uneven minerals, HIV patients and drug users. In this paper, we proposed a generalized semi-exponential estimator with two auxiliary variables under the framework of ACS design. The expressions of approximate bias and mean square error (MSE) of the proposed estimator are derived. Theoretical comparisons of the proposed estimator have been made with existing estimators. A numerical study is conducted on real and artificial populations to demonstrate and compare the efficiencies of the proposed estimator. The results indicate that the proposed generalized semi-exponential estimator performed considerably better than all the adaptive and non-adaptive estimators considered in this paper.

Keywords: auxiliary information, adaptive cluster sampling, clustered populations, Hansen-Hurwitz estimation

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Authors: Riadh Zorgati, Thomas Triboulet

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In quite diverse application areas such as astronomy, medical imaging, geophysics or nondestructive evaluation, many problems related to calibration, fitting or estimation of a large number of input parameters of a model from a small amount of output noisy data, can be cast as inverse problems. Due to noisy data corruption, insufficient data and model errors, most inverse problems are ill-posed in a Hadamard sense, i.e. existence, uniqueness and stability of the solution are not guaranteed. A wide class of inverse problems in physics relates to the Fredholm equation of the first kind. The ill-posedness of such inverse problem results, after discretization, in a very ill-conditioned linear system of equations, the condition number of the associated matrix can typically range from 109 to 1018. This condition number plays the role of an amplifier of uncertainties on data during inversion and then, renders the inverse problem difficult to handle numerically. Similar problems appear in other areas such as numerical optimization when using interior points algorithms for solving linear programs leads to face ill-conditioned systems of linear equations. Devising efficient solution approaches for such system of equations is therefore of great practical interest. Efficient iterative algorithms are proposed for solving a system of linear equations. The approach is based on a preconditioning of the initial matrix of the system with an approximation of a generalized inverse leading to a stochastic preconditioned matrix. This approach, valid for non-negative matrices, is first extended to hermitian, semi-definite positive matrices and then generalized to any complex rectangular matrices. The main results obtained are as follows: 1) We are able to build a generalized inverse of any complex rectangular matrix which satisfies the convergence condition requested in iterative algorithms for solving a system of linear equations. This completes the (short) list of generalized inverse having this property, after Kaczmarz and Cimmino matrices. Theoretical results on both the characterization of the type of generalized inverse obtained and the convergence are derived. 2) Thanks to its properties, this matrix can be efficiently used in different solving schemes as Richardson-Tanabe or preconditioned conjugate gradients. 3) By using Lp norms, we propose generalized Kaczmarz’s type matrices. We also show how Cimmino's matrix can be considered as a particular case consisting in choosing the Euclidian norm in an asymmetrical structure. 4) Regarding numerical results obtained on some pathological well-known test-cases (Hilbert, Nakasaka, …), some of the proposed algorithms are empirically shown to be more efficient on ill-conditioned problems and more robust to error propagation than the known classical techniques we have tested (Gauss, Moore-Penrose inverse, minimum residue, conjugate gradients, Kaczmarz, Cimmino). We end on a very early prospective application of our approach based on stochastic matrices aiming at computing some parameters (such as the extreme values, the mean, the variance, …) of the solution of a linear system prior to its resolution. Such an approach, if it were to be efficient, would be a source of information on the solution of a system of linear equations.

Keywords: conditioning, generalized inverse, linear system, norms, stochastic matrix

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Authors: Ren Moses, Emmanuel Kidando, Eren Ozguven, Yassir Abdelrazig

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This study applied traffic speed and occupancy to develop clustering models that identify different traffic conditions. Particularly, these models are based on the Dirichlet Process Mixture of Generalized Linear regression (DML) and change-point regression (CR). The model frameworks were implemented using 2015 historical traffic data aggregated at a 15-minute interval from an Interstate 295 freeway in Jacksonville, Florida. Using the deviance information criterion (DIC) to identify the appropriate number of mixture components, three traffic states were identified as free-flow, transitional, and congested condition. Results of the DML revealed that traffic occupancy is statistically significant in influencing the reduction of traffic speed in each of the identified states. Influence on the free-flow and the congested state was estimated to be higher than the transitional flow condition in both evening and morning peak periods. Estimation of the critical speed threshold using CR revealed that 47 mph and 48 mph are speed thresholds for congested and transitional traffic condition during the morning peak hours and evening peak hours, respectively. Free-flow speed thresholds for morning and evening peak hours were estimated at 64 mph and 66 mph, respectively. The proposed approaches will facilitate accurate detection and prediction of traffic congestion for developing effective countermeasures.

Keywords: traffic congestion, multistate speed distribution, traffic occupancy, Dirichlet process mixtures of generalized linear model, Bayesian change-point detection

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Authors: Aziz Sezgin

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We consider the problem of stabilization of an unstable heat equation in a 2-D, 3-D and generally n-D domain by deriving a generalized backstepping boundary control design methodology. To stabilize the systems, we design boundary backstepping controllers inspired by the 1-D unstable heat equation stabilization procedure. We assume that one side of the boundary is hinged and the other side is controlled for each direction of the domain. Thus, controllers act on two boundaries for 2-D domain, three boundaries for 3-D domain and ”n” boundaries for n-D domain. The main idea of the design is to derive ”n” controllers for each of the dimensions by using ”n” kernel functions. Thus, we obtain ”n” controllers for the ”n” dimensional case. We use a transformation to change the system into an exponentially stable ”n” dimensional heat equation. The transformation used in this paper is a generalized Volterra/Fredholm type with ”n” kernel functions for n-D domain instead of the one kernel function of 1-D design.

Keywords: backstepping, boundary control, 2-D, 3-D, n-D heat equation, distributed parameter systems

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Authors: Habshah Midi, Mohammed A. Mohammed, Sohel Rana

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Multicollinearity occurs when two or more independent variables in a multiple linear regression model are highly correlated. The ridge regression is the commonly used method to rectify this problem. However, the ridge regression cannot handle the problem of multicollinearity which is caused by high leverage collinearity enhancing observation (HLCEO). Since high leverage points (HLPs) are responsible for inducing multicollinearity, the effect of HLPs needs to be reduced by using Generalized M estimator. The existing GM6 estimator is based on the Minimum Volume Ellipsoid (MVE) which tends to swamp some low leverage points. Hence an improvised GM (MGM) estimator is presented to improve the precision of the GM6 estimator. Numerical example and simulation study are presented to show how HLPs can cause multicollinearity. The numerical results show that our MGM estimator is the most efficient method compared to some existing methods.

Keywords: identification, high leverage points, multicollinearity, GM-estimator, DRGP, DFFITS

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Authors: Saba Riaz, Syed A. Hussain

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This paper is addressing the estimation method of the unknown population variance of the variable of interest. A new generalized class of estimators of the finite population variance has been suggested using the auxiliary information. To improve the precision of the proposed class, known population variance of the auxiliary variable has been used. Mathematical expressions for the biases and the asymptotic variances of the suggested class are derived under large sample approximation. Theoretical and numerical comparisons are made to investigate the performances of the proposed class of estimators. The empirical study reveals that the suggested class of estimators performs better than the usual estimator, classical ratio estimator, classical product estimator and classical linear regression estimator. It has also been found that the suggested class of estimators is also more efficient than some recently published estimators.

Keywords: study variable, auxiliary variable, finite population variance, bias, asymptotic variance, percent relative efficiency

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Authors: Olga I. Moskalenko, Vladislav A. Khanadeev, Anastasya D. Koloskova, Alexey A. Koronovskii, Anatoly A. Pivovarov

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Generalized synchronization is one of the most intricate phenomena in nonlinear science. It can be observed both in systems with a unidirectional and mutual type of coupling including the complex networks. Such a phenomenon has a number of practical applications, for example, for the secure information transmission through the communication channel with a high level of noise. Known methods for the secure information transmission needs in the increase of the privacy of data transmission that arises a question about the observation of such phenomenon in systems with a complex topology of chaotic attractor possessing two or more positive Lyapunov exponents. The present report is devoted to the study of such phenomenon in two unidirectionally and mutually coupled dynamical systems being in chaotic (with one positive Lyapunov exponent) and hyperchaotic (with two or more positive Lyapunov exponents) regimes, respectively. As the systems under study, we have used two mutually coupled modified Lorenz oscillators and two unidirectionally coupled time-delayed generators. We have shown that in both cases the generalized synchronization regime can be detected by means of the calculation of Lyapunov exponents and phase tube approach whereas due to the complex topology of attractor the nearest neighbor method is misleading. Moreover, the auxiliary system approaches being the standard method for the synchronous regime observation, for the mutual type of coupling results in incorrect results. To calculate the Lyapunov exponents in time-delayed systems we have proposed an approach based on the modification of Gram-Schmidt orthogonalization procedure in the context of the time-delayed system. We have studied in detail the mechanisms resulting in the generalized synchronization regime onset paying a great attention to the field where one positive Lyapunov exponent has already been become negative whereas the second one is a positive yet. We have found the intermittency here and studied its characteristics. To detect the laminar phase lengths the method based on a calculation of local Lyapunov exponents has been proposed. The efficiency of the method has been verified using the example of two unidirectionally coupled Rössler systems being in the band chaos regime. We have revealed the main characteristics of intermittency, i.e. the distribution of the laminar phase lengths and dependence of the mean length of the laminar phases on the criticality parameter, for all systems studied in the report. This work has been supported by the Russian President's Council grant for the state support of young Russian scientists (project MK-531.2018.2).

Keywords: complex topology of attractor, generalized synchronization, hyperchaos, Lyapunov exponents

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Authors: Amit Ghosh, Chanchal Kundu

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Recently, the notion of past cumulative inaccuracy (CPI) measure has been proposed in the literature as a generalization of cumulative past entropy (CPE) in univariate as well as bivariate setup. In this paper, we introduce the notion of CPI of order α (alpha) and study the proposed measure for conditionally specified models of two components failed at different time instants called generalized conditional CPI (GCCPI). We provide some bounds using usual stochastic order and investigate several properties of GCCPI. The effect of monotone transformation on this proposed measure has also been examined. Furthermore, we characterize some bivariate distributions under the assumption of conditional proportional reversed hazard rate model. Moreover, the role of GCCPI in reliability modeling has also been investigated for a real-life problem.

Keywords: cumulative past inaccuracy, marginal and conditional past lifetimes, conditional proportional reversed hazard rate model, usual stochastic order

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Authors: Mihai Rebenciuc, Simona Mihaela Bibic

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Branch of modern mathematics, graphs represent instruments for optimization and solving practical applications in various fields such as economic networks, engineering, network optimization, the geometry of social action, generally, complex systems including contemporary urban problems (path or transport efficiencies, biourbanism, & c.). In this paper is studied the interconnection of some urban network, which can lead to a simulation problem of a digraph through another digraph. The simulation is made univoc or more general multivoc. The concepts of fragment and atom are very useful in the study of connectivity in the digraph that is simulation - including an alternative evaluation of k- connectivity. Rough set approach in (bi)digraph which is proposed in premier in this paper contribute to improved significantly the evaluation of k-connectivity. This rough set approach is based on generalized rough sets - basic facts are presented in this paper.

Keywords: (bi)digraphs, rough set theory, systems of interacting agents, complex systems

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Authors: Suyeon Bae, Abimbola Asojo, Denise Guerin, Caren Martin

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Post-occupancy evaluations (POEs) have been recognized for documenting occupant well-being and responses to indoor environmental quality (IEQ) factors such as thermal, lighting, and acoustic conditions. Sustainable Post-Occupancy evaluation survey (SPOES) developed by an interdisciplinary team at a Midwest University provides an evidence-based quantitative analysis of occupants’ satisfaction in office, classroom, and residential spaces to help direct attention to successful areas and areas that need improvement in buildings. SPOES is a self-administered and Internet-based questionnaire completed by building occupants. In this study, employees in three different office buildings rated their satisfaction on a Likert-type scale about 12 IEQ criteria including thermal condition, indoor air quality, acoustic quality, daylighting, electric lighting, privacy, view conditions, furnishings, appearance, cleaning and maintenance, vibration and movement, and technology. Employees rated their level of satisfaction on a Likert-type scale from 1 (very dissatisfied) to 7 (very satisfied). They also rate the influence of their physical environment on their perception of their work performance and the impact of their primary workspaces on their health on a scale from 1 (hinders) to 7 (enhances). Building A is a three-story building that includes private and group offices, classrooms, and conference rooms and amounted to 55,000 square-feet for primary workplace (N=75). Building B, a six-story building, consisted of private offices, shared enclosed office, workstations, and open desk areas for employees and amounted to 14,193 square-feet (N=75). Building C is a three-story 56,000 square-feet building that included classrooms, therapy rooms, an outdoor playground, gym, restrooms, and training rooms for clinicians (N=76). The results indicated that 10 IEQs for Building A except acoustic quality and privacy showed statistically significant correlations on the impact of the primary workspace on health. In Building B, 11 IEQs except technology showed statistically significant correlations on the impact of the primary workspace on health. Building C had statistically significant correlations between all 12 IEQ and the employees’ perception of the impact of their primary workspace on their health in two-tailed correlations (P ≤ 0.05). Out of 33 statistically significant correlations, 25 correlations (76%) showed at least moderate relationship (r ≥ 0.35). For the three buildings, daylighting, furnishings, and indoor air quality IEQs ranked highest on the impact on health. IEQs about vibration and movement, view condition, and electric lighting ranked second, followed by IEQs about cleaning and maintenance and appearance. These results imply that 12 IEQs developed in SPOES are highly related to employees’ perception of how their primary workplaces impact their health. The IEQs in this study offer an opportunity for improving occupants’ well-being and the built environment.

Keywords: post-occupancy evaluation, built environment, sustainability, well-being, indoor air quality

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Authors: Setareh Shekarsaraei, Marjan Moridi, Nasser L. Hadipour

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In this study, nuclear magnetic resonance spectroscopy and nuclear quadrupole resonance spectroscopy parameters of 14N (Nitrogen in imidazole ring) in N–H…O hydrogen bonding for Histidine hydrochloride monohydrate were calculated via density functional theory. We considered a five-molecule model system of Histidine hydrochloride monohydrate. Also, we examined the trends of environmental effect on hydrogen bonds as well as cooperativity. The functional used in this research is M06-2X which is a good functional and the obtained results have shown good agreement with experimental data. This functional was applied to calculate the NMR and NQR parameters. Some correlations among NBO parameters, NMR, and NQR parameters have been studied which have shown the existence of strong correlations among them. Furthermore, the geometry optimization has been performed using M062X/6-31++G(d,p) method. In addition, in order to study cooperativity and changes in structural parameters, along with increase in cluster size, natural bond orbitals have been employed.

Keywords: hydrogen bonding, density functional theory (DFT), natural bond orbitals (NBO), cooperativity effect

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Authors: Jihad S. Daba, J. P. Dubois

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Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.

Keywords: Doppler shift, filtered Poisson process, generalized Clark’s model, non-isotropic scattering, partially developed scattering, Rician distribution

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Authors: S. Chee Choy, Pauline Swee Choo Goh, Yow Lin Liew

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The purpose of this study is to evaluate the English version and a Malay translation of the 21-item Learner Awareness Questionnaire for its application to assess student learning in higher education. The Learner Awareness Questionnaire, originally written in English, is a quantitative measure of how and why students learn. The questionnaire gives an indication of the process and motives to learn using four scales: survival, establishing stability, approval, and loving to learn. Data in the present study came from 680 university students enrolled in various programs in Malaysia. The Malay version of the questionnaire supported a similar four-factor structure and internal consistency to the English version. The four factors of the Malay version also showed moderate to strong correlations with those of the English versions. The results suggest that the Malay version of the questionnaire is similar to the English version. However, further refinement for the questions is needed to strengthen the correlations between the two questionnaires.

Keywords: student learning, learner awareness, questionnaire development, instrument validation

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Authors: Abdisalam Hassan Muse, Samuel Mwalili, Oscar Ngesa

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A generalized log-logistic distribution with variable shapes of the hazard rate was introduced and studied, extending the log-logistic distribution by adding an extra parameter to the classical distribution, leading to greater flexibility in analysing and modeling various data types. The proposed distribution has a large number of well-known lifetime special sub-models such as; Weibull, log-logistic, exponential, and Burr XII distributions. Its basic mathematical and statistical properties were derived. The method of maximum likelihood was adopted for estimating the unknown parameters of the proposed distribution, and a Monte Carlo simulation study is carried out to assess the behavior of the estimators. The importance of this distribution is that its tendency to model both monotone (increasing and decreasing) and non-monotone (unimodal and bathtub shape) or reversed “bathtub” shape hazard rate functions which are quite common in survival and reliability data analysis. Furthermore, the flexibility and usefulness of the proposed distribution are illustrated in a real-life data set and compared to its sub-models; Weibull, log-logistic, and BurrXII distributions and other parametric survival distributions with 3-parmaeters; like the exponentiated Weibull distribution, the 3-parameter lognormal distribution, the 3- parameter gamma distribution, the 3-parameter Weibull distribution, and the 3-parameter log-logistic (also known as shifted log-logistic) distribution. The proposed distribution provided a better fit than all of the competitive distributions based on the goodness-of-fit tests, the log-likelihood, and information criterion values. Finally, Bayesian analysis and performance of Gibbs sampling for the data set are also carried out.

Keywords: hazard rate function, log-logistic distribution, maximum likelihood estimation, generalized log-logistic distribution, survival data, Monte Carlo simulation

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Authors: A. Fettahoglu

Abstract:

Theory of viscoelasticity is used by many researchers to represent the behavior of many materials such as pavements on roads or bridges. Several researches used analytical methods and rheology to predict the material behaviors of simple models. Today, more complex engineering structures are analyzed using Finite Element Method, in which material behavior is embedded by means of three dimensional viscoelastic material laws. As a result, structures of unordinary geometry and domain can be analyzed by means of Finite Element Method and three dimensional viscoelastic equations. In the scope of this study, rheological models embedded in ANSYS, namely, generalized Maxwell model and Prony series, which are two methods used by ANSYS to represent viscoelastic material behavior, are presented explicitly. Afterwards, a guide is illustrated to ease using of viscoelasticity tool in ANSYS.

Keywords: ANSYS, generalized Maxwell model, finite element method, Prony series, viscoelasticity, viscoelastic material curve fitting

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Authors: Selin Guney, Andres Riquelme

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The traditional bio-economic method for fisheries modeling uses some estimate of the growth parameters and the system carrying capacity from a biological model for the population dynamics (usually a logistic population growth model) which is then analyzed as a traditional production function. The stock dynamic is transformed into a revenue function and then compared with the extraction costs to estimate the maximum economic yield. In this paper, the logistic population growth model for the population is combined with a forecast of the abundance and location of the stock by using a generalized additive model approach. The paper focuses on the Chilean hake population. This method allows for the incorporation of climatic variables and the interaction with other marine species, which in turn will increase the reliability of the estimates and generate better extraction paths for different conservation objectives, such as the maximum biological yield or the maximum economic yield.

Keywords: bio-economic, fisheries, GAM, production

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Authors: Yulong Wang, Yuan Yan Tang, Cuiming Zou, Lina Yang

Abstract:

This paper presents a novel sparse representation method for robust pattern classification. Generalized orthogonal matching pursuit (GOMP) is a recently proposed efficient sparse representation technique. However, GOMP adopts the mean square error (MSE) criterion and assign the same weights to all measurements, including both severely and slightly corrupted ones. To reduce the limitation, we propose an information-theoretic GOMP (ITGOMP) method by exploiting the correntropy induced metric. The results show that ITGOMP can adaptively assign small weights on severely contaminated measurements and large weights on clean ones, respectively. An ITGOMP based classifier is further developed for robust pattern classification. The experiments on public real datasets demonstrate the efficacy of the proposed approach.

Keywords: correntropy induced metric, matching pursuit, pattern classification, sparse representation

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Authors: Dale Daniel G. Bodo

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This study investigated the status of the Laboratory Tools and Equipment of the BSHRT Program of Eastern Visayas State University, Tacloban City Campus. Descriptive-correlation method was used which Variables include profile age, gender, acquired NC II, competencies in HRT and the status of the laboratory facilities, tools, and equipment of the BSHRT program. The study also identified significant correlation between the profile of the respondents and the implementation of the BSHRT Program in terms of laboratory tools and equipment. A self-structured survey questionnaire was used to gather relevant data among eighty-seven (87) BSHRT-OJT students. To test the correlations of variables, Pearson Product Moment Coefficient Correlation or Pearson r was used. As a result, the study revealed very interesting results and various significant correlations among the paired variables and as to the implementation of the BSHRT Program. Hence, this study was done to update the status of laboratory tools and equipment of the program.

Keywords: status, BSHRT Program, laboratory tools and equipment, descriptive-correlation

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Authors: Farzaneh Rajabighamchi, Stan van Hoesel, Christof Defryn

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The generalized traveling salesman problem (GTSP) is an extension of the traveling salesman problem (TSP) where the set of nodes is partitioned into clusters, and the salesman must visit exactly one node per cluster. In this research, we apply the definition of the GTSP to an order picker routing problem with multiple locations per product. As such, each product represents a cluster and its corresponding nodes are the locations at which the product can be retrieved. To pick a certain product item from the warehouse, the picker needs to visit one of these locations during its pick tour. As all products are scattered throughout the warehouse, the product clusters not separated geographically. We propose an exact LP model as well as heuristic and meta-heuristic solution algorithms for the order picking problem with multiple product locations.

Keywords: warehouse optimization, order picking problem, generalised travelling salesman problem, heuristic algorithm

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Authors: Luh Eka Suryani, Purhadi

Abstract:

Poisson regression is a non-linear regression model with response variable in the form of count data that follows Poisson distribution. Modeling for a pair of count data that show high correlation can be analyzed by Poisson Bivariate Regression. Data, the number of infant mortality and maternal mortality, are count data that can be analyzed by Poisson Bivariate Regression. The Poisson regression assumption is an equidispersion where the mean and variance values are equal. However, the actual count data has a variance value which can be greater or less than the mean value (overdispersion and underdispersion). Violations of this assumption can be overcome by applying Generalized Poisson Regression. Characteristics of each regency can affect the number of cases occurred. This issue can be overcome by spatial analysis called geographically weighted regression. This study analyzes the number of infant mortality and maternal mortality based on conditions in East Java in 2016 using Geographically Weighted Bivariate Generalized Poisson Regression (GWBGPR) method. Modeling is done with adaptive bisquare Kernel weighting which produces 3 regency groups based on infant mortality rate and 5 regency groups based on maternal mortality rate. Variables that significantly influence the number of infant and maternal mortality are the percentages of pregnant women visit health workers at least 4 times during pregnancy, pregnant women get Fe3 tablets, obstetric complication handled, clean household and healthy behavior, and married women with the first marriage age under 18 years.

Keywords: adaptive bisquare kernel, GWBGPR, infant mortality, maternal mortality, overdispersion

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Authors: Ana Ferraz, Martim Santos, M. Graça Pereira

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Distress among parents of children with acute lymphoblastic leukemia (ALL) is common during treatment and can persist several years post-diagnosis, impacting the adjustment of children and parents themselves. Current evidence is needed to examine the scope and nature of parental distress in childhood ALL. This review focused on associated variables, predictors, and outcomes of parental distress following their ALL diagnosis of their child. PubMed, Web of Science, and PsycINFO databases were searched for English and Spanish papers published from 1983 to 2021. PRISMA statement was followed, and papers were evaluated through a standardized methodological quality assessment tool (NHLBI). Of the 28 papers included, 16 were evaluated as fair, eight as good, and four as poor. Regarding results, 11 papers reported subgroup differences, and 15 found potential predictors of parental distress, including sociodemographic, psychosocial, psychological, family, health, and ALL-specific variables. Significant correlations were found between parental distress, social support, illness cognitions, and resilience, as well as contradictory results regarding the impact of sociodemographic variables on parental distress. Family cohesion and caregiver burden were associated with distress, and the use of healthy coping strategies was associated with less anxiety. Caregiver strain contributed to distress, and the overall impact of illness positively predicted anxiety in mothers and somatization in fathers. Differences in parental distress were found regarding group risk, time since diagnosis, and treatment phases. Thirteen papers explored the outcomes of parental distress on psychological, family, health, and social/education outcomes. Parental distress was the most important predictor of family strain. Significant correlations were found between parental distress at diagnosis and further psychological adjustment of parents themselves and their children. Most papers reported correlations between parental distress on children’s adjustment and quality of life, although few studies reported no association. Correlations between maternal depression and child participation in education and social life were also found. Longitudinal studies are needed to better understand parental distress and its consequences on health outcomes, in particular. Future interventions should focus mainly on parents on distress reduction and psychological adjustment, both in parents and children over time.

Keywords: childhood acute lymphoblastic leukemia, family, parental distress, psychological adjustment, quality of life

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