Search results for: correlation of random variables

Authors: Ting Shen

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Whether resource matters to school has been a topic of intense debate since 1960s. Educational researchers and policy makers have been particularly interested in knowing the return or payoff of Per-Pupil Expenditure (PPE) on improving students’ achievement. However, the evidence on the effect of PPE has been mixed and the size of the effect is also unknown. With regard to the methods, it is well-known that meta-analysis study is superior to individual study and it is also preferred to vote counting method in terms of scientifically weighting the evidence by the sample size. This meta-analysis study aims to provide a synthesized evidence on the correlation between PPE and student academic achievement using recent study data from 1990s to 2010s. Meta-analytical approach of fixed- and random-effects models will be utilized in addition to a meta regression with predictors of year, location, region and school type. A preliminary result indicates that by and large there is no statistically significant relationship between per pupil expenditure and student achievement, but location seems to have a mediating effect.

Keywords: per pupil expenditure, student academic achievement, multilevel model, meta-analysis

Procedia PDF Downloads 211

Authors: Jing Jiang, Wenhuan XU, Lei Zhang, Shiyi Zhang, Tongli Wang

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Climate data quality significantly affects the reliability of ecological modeling. In the Asia Pacific (AP) region, low-quality climate data hinders ecological modeling. ClimateAP, a software developed in 2017, generates high-quality climate data for the AP region, benefiting researchers in forestry and agriculture. However, its adoption remains limited. This study aims to confirm the validity of biologically relevant variable data generated by ClimateAP during the normal climate period through comparison with the currently available gridded data. Climate data from 2,366 weather stations were used to evaluate the prediction accuracy of ClimateAP in comparison with the commonly used gridded data from WorldClim1.4. Univariate regressions were applied to 48 monthly biologically relevant variables, and the relationship between the observational data and the predictions made by ClimateAP and WorldClim was evaluated using Adjusted R-Squared and Root Mean Squared Error (RMSE). Locations were categorized into mountainous and flat landforms, considering elevation, slope, ruggedness, and Topographic Position Index. Univariate regressions were then applied to all biologically relevant variables for each landform category. Random Forest (RF) models were implemented for the climatic niche modeling of Cunninghamia lanceolata. A comparative analysis of the prediction accuracies of RF models constructed with distinct climate data sources was conducted to evaluate their relative effectiveness. Biologically relevant variables were obtained from three unpublished Chinese meteorological datasets. ClimateAPv3.0 and WorldClim predictions were obtained from weather station coordinates and WorldClim1.4 rasters, respectively, for the normal climate period of 1961-1990. Occurrence data for Cunninghamia lanceolata came from integrated biodiversity databases with 3,745 unique points. ClimateAP explains a minimum of 94.74%, 97.77%, 96.89%, and 94.40% of monthly maximum, minimum, average temperature, and precipitation variances, respectively. It outperforms WorldClim in 37 biologically relevant variables with lower RMSE values. ClimateAP achieves higher R-squared values for the 12 monthly minimum temperature variables and consistently higher Adjusted R-squared values across all landforms for precipitation. ClimateAP's temperature data yields lower Adjusted R-squared values than gridded data in high-elevation, rugged, and mountainous areas but achieves higher values in mid-slope drainages, plains, open slopes, and upper slopes. Using ClimateAP improves the prediction accuracy of tree occurrence from 77.90% to 82.77%. The biologically relevant climate data produced by ClimateAP is validated based on evaluations using observations from weather stations. The use of ClimateAP leads to an improvement in data quality, especially in non-mountainous regions. The results also suggest that using biologically relevant variables generated by ClimateAP can slightly enhance climatic niche modeling for tree species, offering a better understanding of tree species adaptation and resilience compared to using gridded data.

Keywords: climate data validation, data quality, Asia pacific climate, climatic niche modeling, random forest models, tree species

Procedia PDF Downloads 38

Authors: Samaneh Sadat Fattahi Massoom, Hossein Salimi Bajestani

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The study examines loneliness and depression in students who regularly care for themselves after school (latchkey students) in Mashhad and compares them with parent supervised students using a causal-comparative research method. The 270 participants, aged 7 -13, were selected using convenience and cluster random-assignment sampling. Independent t-test results showed significant differences between loneliness (-4.32, p ≤ 0.05) and depression (-3.02, p ≤0.05) among latchkey and non-latchkey students. Using the Pearson correlation test, significant correlation between depression and loneliness among latchkey students was also discovered (r=0.59, p ≤ 0.05). However, regarding non latchkey students, no significant difference between loneliness and depression was observed (r= 0.02. p ≥ 0.05). Multiple regression results also showed that depression variance can be determined by gender (22%) and loneliness (34%). The findings of this study, specifically the significant difference between latchkey and non-latchkey children regarding feelings of loneliness and depression, carries clear implications for parents. It can be concluded that mothers who spend most of their time working out of the house and devoid their children of their presence in the home may cause some form of mental distress like loneliness and depression. Moreover, gender differences affect the degree of these psychological disorders.

Keywords: loneliness, depression, self-care students, latchkey and non-latchkey students, gender

Procedia PDF Downloads 372

Authors: Abdelsabour G. A. Khaled, Galal A.R. El-Sherbeny, Ahmed M. Hassanein, Gameel M. G. Aly

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Classical methods of identification, based on agronomical characterization, are not always the most accurate way due to the instability of these characteristics under the influence of the different environments. In order to estimate the genetic diversity, molecular markers provided excellent tools. In this study, Genetic variation of nine Egyptian jojoba shrubs was tested using ISSR (inter simple sequences repeats), RAPD (random amplified polymorphic DNA) markers and based on the morphological characterization. The average of the percentage of polymorphism (%P) ranged between 58.17% and 74.07% for ISSR and RAPD markers, respectively. The range of genetic similarity percents among shrubs based on ISSR and RAPD markers were from 82.9 to 97.9% and from 85.5 to 97.8%, respectively. The average of PIC (polymorphism information content) values were 0.19 (ISSR) and 0.24 (RAPD). In the present study, RAPD markers were more efficient than the ISSR markers. Where the RAPD technique exhibited higher marker index (MI) average (1.26) compared to ISSR one (1.11). There was an insignificant correlation between the ISSR and RAPD data (0.076, P > 0.05). The dendrogram constructed by the combined RAPD and ISSR data gave a relatively different clustering pattern.

Keywords: correlation, molecular markers, polymorphism, marker index

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Authors: Tanzeel bin Abdul Rauf Patker, Saba Mateen

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This research investigates the impact of Brand Loyalty on the product performance and the factors those are considered more important in brand reputation. Variables selected for this research are Brand quality, Brand Equity, Brand Reputation to explore the impact of these variables on Product performance. For this purpose, primary research has been conducted. The questionnaire survey for this research study was administered among the population mainly at the shopping malls. For this research study, a sample size of 250 respondents has been taken into consideration. Customers from the shopping malls and university students constitute the sample for this research study using random sampling (non-probabilistic) used as a sampling technique for conducting the research survey. According to the results obtained from the collected data, it is interpreted that product performance shares a direct relationship with brand quality, brand quality, and brand reputation. Result also showed that brand quality and brand equity has a significant effect on product performance, whereas brand reputation has an insignificant effect on product performance.

Keywords: product performance, brand quality, brand equity, brand reputation

Procedia PDF Downloads 277

Authors: Nelson Bii, Christopher Ouma, John Odhiambo

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Non-response is a potential source of errors in sample surveys. It introduces bias and large variance in the estimation of finite population parameters. Regression models have been recognized as one of the techniques of reducing bias and variance due to random non-response using auxiliary data. In this study, it is assumed that random non-response occurs in the survey variable in the second stage of cluster sampling, assuming full auxiliary information is available throughout. Auxiliary information is used at the estimation stage via a regression model to address the problem of random non-response. In particular, the auxiliary information is used via an improved Nadaraya-Watson kernel regression technique to compensate for random non-response. The asymptotic bias and mean squared error of the estimator proposed are derived. Besides, a simulation study conducted indicates that the proposed estimator has smaller values of the bias and smaller mean squared error values compared to existing estimators of finite population mean. The proposed estimator is also shown to have tighter confidence interval lengths at a 95% coverage rate. The results obtained in this study are useful, for instance, in choosing efficient estimators of the finite population mean in demographic sample surveys.

Keywords: mean squared error, random non-response, two-stage cluster sampling, confidence interval lengths

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Authors: Obaidullah Molakhail, R. Reshmi

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Objective: This study explains the impact of talent management on employee loyalty in the IT sector in Kerala, India. Methods: A descriptive investigation was conducted within the confines of this paper to gain insight into the ramifications of talent management on enhancing employee allegiance to the organization. A quantitative study was conducted by distributing questionnaires to respondents in three IT companies. One hundred and seventy questionnaires were distributed, with `150 being utilized and the remainder being discarded. Data was collected from various departments within the companies, and the selection of respondents was conducted randomly. statistical software SPSS (version 26) was used to analyze the data and determine the outcomes. Results: The objective was examined through Pearson correlation to find the relation, and linear regression was used to find the strength of variables as talent management is independent and employee loyalty is the dependent variable. The results reveal that talent management is essential to employee loyalty. If there is a high-level implementation of talent management practices, there will be low turnover rate, it reflected employee loyalty towards the organization. Conclusion: Strategic planners ought to devote their attention to the realm of talent management due to the existence of a correlation between talent management and the loyalty exhibited by employees. The results of this study suggest that there is a favorable correlation between talent management and employee loyalty.

Keywords: talent management, employee loyalty, IT sector, quantitative study

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Authors: Sittichai Charoensettasilp, Chong Wu

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This study employs sampling of 400 Thai people who live in Bangkok and have used air transportation to travel. A random convenience sampling technique is used to collect data. The results found that at 0.05 significance level the differences of means of Thai consumers’ expectations (before) and satisfaction (after) receiving services in the service marketing mix, the results of all aspects are different both in general and for each aspect of the service marketing mix. Average levels of expectations before receiving services are higher than satisfaction after receiving services in all aspects, as well. When analyzing further to the correlation between average means, the means of expectations before receiving services are higher than those of satisfaction after receiving services in general. As in all aspects of the service marketing mix, any aspect that has a big difference between expectations before receiving services and satisfaction after receiving services has low correlation.

Keywords: domestic low-cost airlines, Thai consumers, relationship, expectation before receiving services, satisfaction after receiving services

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Authors: Yan Wang, Yasushi Asami, Yukio Sadahiro

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In urban area, several landmarks may affect housing price and rents, hedonic analysis should employ distance variables corresponding to each landmarks. Unfortunately, the effects of distances to landmarks on housing prices are generally not consistent with the true price. These distance variables may cause magnitude error in regression, pointing a problem of spatial multicollinearity. In this paper, we provided some approaches for getting the samples with less bias and method on locating the specific sampling area to avoid the multicollinerity problem in two specific landmarks case.

Keywords: landmarks, hedonic regression, distance variables, collinearity, multicollinerity

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Authors: Abiodun M. Adeola, Hannes Rautenbach, Gbenga J. Abiodun, Thabo E. Makgoale, Joel O. Botai, Omolola M. Adisa, Christina M. Botai

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There was a surge in malaria morbidity as well as mortality in 2016/2017 malaria season in malaria-endemic regions of South Africa. Rainfall is a major climatic driver of malaria transmission and has potential use for predicting malaria. Annual and seasonal trends and cross-correlation analyses were performed on time series of monthly total rainfall (derived from interpolated weather station data) and monthly malaria cases in five districts of Limpopo Province for the period of 1998 to 2017. The time series analysis indicated that an average of 629.5mm of rainfall was received over the period of study. The rainfall has an annual variation of about 0.46%. Rainfall amount varies among the five districts, with the north-eastern part receiving more rainfall. Spearman’s correlation analysis indicated that total monthly rainfall with one to two months lagged effect is significant in malaria transmission in all the five districts. The strongest correlation is noticed in Mopani (r=0.54; p-value = < 0.001), Vhembe (r=0.53; p-value = < 0.001), Waterberg (r=0.40; p-value = < 0.001), Capricorn (r=0.37; p-value = < 0.001) and lowest in Sekhukhune (r=0.36; p-value = < 0.001). More particularly, malaria morbidity showed a strong relationship with an episode of rainfall above 5-year running means of rainfall of 400 mm. Both annual and seasonal analyses showed that the effect of rainfall on malaria varied across the districts and it is seasonally dependent. Adequate understanding of climatic variables dynamics annually and seasonally is imperative in seeking answers to malaria morbidity among other factors, particularly in the wake of the sudden spike of the disease in the province.

Keywords: correlation, malaria, rainfall, seasonal, trends

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Authors: Min Jin Kwon, Seung Won Kim, Eui Yeon Kim, Haeyoung Lee

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Numerous anonymous chat apps that help people to connect with random strangers have been released in South Korea. However, they become a serious problem for young people since young people often use them for channels of prostitution or sexual violence. Although ISPs in South Korea are responsible for making inappropriate content inaccessible on their networks, they do not block traffic of random chat apps since 1) the use of random chat apps is entirely legal. 2) it is reported that they use HTTP proxy blocking so that non-HTTP traffic cannot be blocked. In this paper, we propose a service model that can block random chat apps at home routers. A service provider manages a blacklist that contains blocked apps’ information. Home routers that subscribe the service filter the traffic of the apps out using deep packet inspection. We have implemented a prototype of the proposed model, including a centralized server providing the blacklist, a Raspberry Pi-based home router that can filter traffic of the apps out, and an Android app used by the router’s administrator to locally customize the blacklist.

Keywords: deep packet inspection, internet filtering, juvenile protection, technical blocking

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Authors: Yan Wang, Yasushi Asami, Yukio Sadahiro

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In urban context, urban nodes such as amenity or hazard will certainly affect house price, while classic hedonic analysis will employ distance variables measured from each urban nodes. However, effects from distances to facilities on house prices generally do not represent the true price of the property. Distance variables measured on the same surface are suffering a problem called multicollinearity, which is usually presented as magnitude variance and mean value in regression, errors caused by instability. In this paper, we provided a theoretical framework to identify and gather the data with less bias, and also provided specific sampling method on locating the sample region to avoid the spatial multicollinerity problem in three distance variable’s case.

Keywords: hedonic regression, urban node, distance variables, multicollinerity, collinearity

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Authors: W. K. Zahra, M. A. El-Beltagy, R. R. Elkhadrawy

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So many practical problems in science and technology developed over the past decays. For instance, the mathematical boundary layer theory or the approximation of solution for different problems described by differential equations. When such problems consider large or small parameters, they become increasingly complex and therefore require the use of asymptotic methods. In this work, we consider the singularly perturbed boundary value problems which contain very small parameters. Moreover, we will consider these perturbation parameters as random variables. We propose a numerical method to solve this kind of problems. The proposed method is based on an exponential spline, Shishkin mesh discretization, and polynomial chaos expansion. The polynomial chaos expansion is used to handle the randomness exist in the perturbation parameter. Furthermore, the Monte Carlo Simulations (MCS) are used to validate the solution and the accuracy of the proposed method. Numerical results are provided to show the applicability and efficiency of the proposed method, which maintains a very remarkable high accuracy and it is ε-uniform convergence of almost second order.

Keywords: singular perturbation problem, polynomial chaos expansion, Shishkin mesh, two small parameters, exponential spline

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Authors: Kevin Worrall, Euan McGookin

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The use of optimization algorithms is common across a large number of diverse fields. This work presents the use of a hybrid optimization algorithm applied to a mobile robot tasked with carrying out a search of an unknown environment. The algorithm is then applied to the multiple robots case, which results in a reduction in the time taken to carry out the search. The hybrid algorithm is a Random Search Algorithm fused with a Tabu mechanism. The work shows that the algorithm locates the desired points in a quicker time than a brute force search. The Tabu Random algorithm is shown to work within a simulated environment using a validated mathematical model. The simulation was run using three different environments with varying numbers of targets. As an algorithm, the Tabu Random is small, clear and can be implemented with minimal resources. The power of the algorithm is the speed at which it locates points of interest and the robustness to the number of robots involved. The number of robots can vary with no changes to the algorithm resulting in a flexible algorithm.

Keywords: algorithms, control, multi-agent, search and rescue

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Authors: Surya R. Niraula, Devendra B Chhetry, Girish K. Singh, S. Nagesh, Frederick A. Connell

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Background: Although random sampling is generally considered to be the gold standard for population-based research, the majority of drug abuse research is based on non-random sampling despite the well-known limitations of this kind of sampling. Method: We compared the statistical properties of two surveys of drug abuse in the same community: one using snowball sampling of drug users who then identified “friend controls” and the other using a random sample of non-drug users (controls) who then identified “friend cases.” Models to predict drug abuse based on risk factors were developed for each data set using conditional logistic regression. We compared the precision of each model using bootstrapping method and the predictive properties of each model using receiver operating characteristics (ROC) curves. Results: Analysis of 100 random bootstrap samples drawn from the snowball-sample data set showed a wide variation in the standard errors of the beta coefficients of the predictive model, none of which achieved statistical significance. One the other hand, bootstrap analysis of the random-sample data set showed less variation, and did not change the significance of the predictors at the 5% level when compared to the non-bootstrap analysis. Comparison of the area under the ROC curves using the model derived from the random-sample data set was similar when fitted to either data set (0.93, for random-sample data vs. 0.91 for snowball-sample data, p=0.35); however, when the model derived from the snowball-sample data set was fitted to each of the data sets, the areas under the curve were significantly different (0.98 vs. 0.83, p < .001). Conclusion: The proposed method of random sampling of controls appears to be superior from a statistical perspective to snowball sampling and may represent a viable alternative to snowball sampling.

Keywords: drug abuse, matched case-control study, non-probability sampling, probability sampling

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Authors: Yuwaratu Syafira, Wahyu K. Y. Putra, Kusharisupeni Djokosujono

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Background/Objective: Body Mass Index (BMI) serves various purposes, including measuring the prevalence of obesity in a population, and also in formulating a patient’s diet at a hospital, and can be calculated with the equation = body weight (kg)/body height (m)². However, the BMI of an individual with difficulties in carrying their weight or standing up straight can not necessarily be measured. The aim of this study was to form a prediction model for the BMI of young adult students of Public Health Faculty of University of Indonesia. Subject/Method: This study used a cross sectional design, with a total sample of 132 respondents, consisted of 58 males and 74 females aged 21- 30. The dependent variable of this study was BMI, and the independent variables consisted of sex and anthropometric measurements, which included ulna length, arm length, tibia length, knee height, mid-upper arm circumference, and calf circumference. Anthropometric information was measured and recorded in a single sitting. Simple and multiple linear regression analysis were used to create the prediction equation for BMI. Results: The male respondents had an average BMI of 24.63 kg/m² and the female respondents had an average of 22.52 kg/m². A total of 17 variables were analysed for its correlation with BMI. Bivariate analysis showed the variable with the strongest correlation with BMI was Mid-Upper Arm Circumference/√Ulna Length (MUAC/√UL) (r = 0.926 for males and r = 0.886 for females). Furthermore, MUAC alone also has a very strong correlation with BMI (r = 0,913 for males and r = 0,877 for females). Prediction models formed from either MUAC/√UL or MUAC alone both produce highly accurate predictions of BMI. However, measuring MUAC/√UL is considered inconvenient, which may cause difficulties when applied on the field. Conclusion: The prediction model considered most ideal to estimate BMI is: Male BMI (kg/m²) = 1.109(MUAC (cm)) – 9.202 and Female BMI (kg/m²) = 0.236 + 0.825(MUAC (cm)), based on its high accuracy levels and the convenience of measuring MUAC on the field.

Keywords: body mass index, mid-upper arm circumference, prediction model, ulna length

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Authors: Peter M. Maurer Maurer

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DGL is a context free grammar-based tool for generating random data. Many types of simulator input data require some computation to be placed in the proper format. For example, it might be necessary to generate ordered triples in which the third element is the sum of the first two elements, or it might be necessary to generate random numbers in some sorted order. Although DGL is universal in computational power, generating these types of data is extremely difficult. To overcome this problem, we have enhanced DGL to include features that permit direct computation within the structure of a context free grammar. The features have been implemented as special types of productions, preserving the context free flavor of DGL specifications.

Keywords: DGL, Enhanced Context Free Grammars, Programming Constructs, Random Data Generation

Procedia PDF Downloads 113

Authors: Kawinphat Lertpongmanee

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The purposes of this study were (1) investigate the English language learning motivation and the attainment of their English proficiency, (2) to find out how motivation and motivational variables of the high and low proficiency subjects are related to their English proficiency. The respondents were 80 fourth-year from Faculty of Management Sciences students in Rajabhat Suansunadha University. The instruments used for data collection were questionnaires. The statistically analyzed by using the SPSS program for frequency, percentage, arithmetic mean, standard deviation (SD), t-test, one-way analysis of variance (ANOVA), and Pearson correlation coefficient. The findings of this study are summarized as there was a significant difference in overall motivation between high and low proficiency groups of subjects at .05 (p < .05), but not in overall motivational variables. Additionally, the high proficiency group had a significantly higher level of intrinsic motivation than did the low proficiency group at .05 (p < .05).

Keywords: English language proficiency, faculty of management sciences, motivation factors, proficiency subjects

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Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

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The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

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Authors: M. Seguini, D. Nedjar

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An accuracy nonlinear analysis of a deep beam resting on elastic perfectly plastic soil is carried out in this study. In fact, a nonlinear finite element modeling for large deflection and moderate rotation of Euler-Bernoulli beam resting on linear and nonlinear random soil is investigated. The geometric nonlinear analysis of the beam is based on the theory of von Kàrmàn, where the Newton-Raphson incremental iteration method is implemented in a Matlab code to solve the nonlinear equation of the soil-beam interaction system. However, two analyses (deterministic and probabilistic) are proposed to verify the accuracy and the efficiency of the proposed model where the theory of the local average based on the Monte Carlo approach is used to analyze the effect of the spatial variability of the soil properties on the nonlinear beam response. The effect of six main parameters are investigated: the external load, the length of a beam, the coefficient of subgrade reaction of the soil, the Young’s modulus of the beam, the coefficient of variation and the correlation length of the soil’s coefficient of subgrade reaction. A comparison between the beam resting on linear and nonlinear soil models is presented for different beam’s length and external load. Numerical results have been obtained for the combination of the geometric nonlinearity of beam and material nonlinearity of random soil. This comparison highlighted the need of including the material nonlinearity and spatial variability of the soil in the geometric nonlinear analysis, when the beam undergoes large deflections.

Keywords: finite element method, geometric nonlinearity, material nonlinearity, soil-structure interaction, spatial variability

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Authors: Nipawan Tharasak, Ladda Hirunyava

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The objective of the research was to study factors affecting working efficiency and the relationship between working environment, satisfaction to human resources management and operation employees’ working efficiency of Faculty of Management Science, Suan Sunandha Rajabhat University. The sample size of the research was based on 33 employees of Faculty of Management Science. The researcher had classified the support employees into 4 divisions by using Stratified Random Sampling. Individual sample was randomized by using Simple Random Sampling. Data was collected through the instrument. The Statistical Package for the Windows was utilized for data processing. Percentage, mean, standard deviation, the t-test, One-way ANOVA, and Pearson product moment correlation coefficient were applied. The result found the support employees’ satisfaction in human resources management of Faculty of Management Science in following areas: remuneration; employee recruitment & selection; manpower planning; performance evaluation; staff training & developing; and spirit & fairness were overall in good level.

Keywords: faculty of management science, operational factors, practice performance, staff working

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Authors: James Bassey Ejue, Dorn Cklaimz Enamhe, Helen Francis Ejue

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The study examined the influence of personal variables such as sex, type of school, and parental socio-economic status on secondary school students’ perception of school security. To guide the study, three null hypotheses were formulated. The research design adopted was the survey design, and a 20-item instrument was constructed and validated by the researchers through a test-retest procedure. The sample size for the study comprised 2,198 students made up of male and female students selected through a stratified random sampling technique. This was drawn from a study population of 21,988, made up of 12,635 students and 9353 students from public and private secondary schools, respectively. Data were analyzed using an independent t-test statistical tool. The findings showed that female students were more fearful in their perception of school security; the students in private schools perceived school to be more insecure than those in public schools; and the students from high parental socio-economic status are more associated with the perception of school as insecure than the ones from low parental socio-economic status. Based on these findings, it was recommended that, among others, more reassuring measures be put in place to check school security for females, for those in private schools, and for those from high parental socio-economic status. School counsellors should also be guided accordingly in designing intervention strategies.

Keywords: personal variables, students, perception, school security

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Authors: Hongmin Deng, Qionghua Wang

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A modified two dimensional (2D) logistic map based on cross feedback control is proposed. This 2D map exhibits more random chaotic dynamical properties than the classic one dimensional (1D) logistic map in the statistical characteristics analysis. So it is utilized as the pseudo-random (PN) sequence generator, where the obtained real-valued PN sequence is quantized at first, then applied to radio frequency identification (RFID) communication system in this paper. This system is experimentally validated on a cortex-M₀ development board, which shows the effectiveness in key generation, the size of key space and security. At last, further cryptanalysis is studied through the test suite in the National Institute of Standards and Technology (NIST).

Keywords: chaos encryption, logistic map, pseudo-random sequence, RFID

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Authors: Arti Devi, Parthasarthi Choudhury

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Extreme rainfall frequency analysis for Meteorological Sub-Division 4 of India was analysed using L-moments approach. Serial Correlation and Mann Kendall tests were conducted for checking serially independent and stationarity of the observations. The discordancy measure for the sites was conducted to detect the discordant sites. The regional homogeneity was tested by comparing with 500 generated homogeneous regions using a 4 parameter Kappa distribution. The best fit distribution was selected based on ZDIST statistics and L-moments ratio diagram from the five extreme value distributions GPD, GLO, GEV, P3 and LP3. The LN3 distribution was selected and regional rainfall frequency relationship was established using index-rainfall procedure. A regional mean rainfall relationship was developed using multiple linear regression with latitude and longitude of the sites as variables.

Keywords: L-moments, ZDIST statistics, serial correlation, Mann Kendall test

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Authors: Zhidong Zhang, Zhi-Chao Zhang

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This study focuses on early adolescent externalizing behavioral problems which specifically concentrate on rule breaking behavior and aggressive behavior using the instrument of Achenbach System of Empirically Based Assessment (ASEBA). The purpose was to analyze the relationships between the externalizing behavioral problems and relevant background variables such as sports activities, hobbies, chores and the number of close friends. The stratified sampling method was used to collect data from 1975 participants. The results indicated that several background variables as predictors could significantly predict rule breaking behavior and aggressive behavior. Further, a hierarchical modeling method was used to explore the causal relations among background variables, breaking behavior variables and aggressive behavior variables.

Keywords: aggressive behavior, breaking behavior, early adolescence, externalizing problem

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Authors: Halil Ibrahim Demir, Caner Erden, Abdullah Hulusi Kokcam, Mumtaz Ipek

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Process planning, scheduling, and due date assignment are three important manufacturing functions which are studied independently in literature. There are hundreds of works on IPPS and SWDDA problems but a few works on IPPSDDA problem. Integrating these three functions is very crucial due to the high relationship between them. Since the scheduling problem is in the NP-Hard problem class without any integration, an integrated problem is even harder to solve. This study focuses on the integration of these functions. Sum of weighted tardiness, earliness, and due date related costs are used as a penalty function. Random search and hybrid metaheuristics are used to solve the integrated problem. Marginal improvement in random search is very high in the early iterations and reduces enormously in later iterations. At that point directed search contribute to marginal improvement more than random search. In this study, random and genetic search methods are combined to find better solutions. Results show that overall performance becomes better as the integration level increases.

Keywords: process planning, genetic algorithm, hybrid search, random search, weighted due-date assignment, weighted scheduling

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Authors: Nabil A. A. Mohamed, Alaa A. A. Balbaa, Khaled E. Ayad

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Osteoarthritis (OA) of the knee is the most common form of arthritis and leads to more activity limitations (e.g., disability in walking and stair climbing) than any other disease, especially in the elderly. Recently, impaired proprioceptive accuracy of the knee has been proposed as a local factor in the onset and progression of radiographic knee OA (ROA). Purpose: To compare the clinical and radiological findings in healthy with that of knee OA. Also, to determine if there is a correlation between the clinical and radiological findings in patients with knee OA. Subjects: Fifty one patients diagnosed as unilateral or bilateral knee OA with age ranged between 35-70 years, from both gender without any previous history of knee trauma or surgery, and twenty one normal subjects with age ranged from 35 - 68 years. METHODS: peak torque/body weight (PT/BW) was recorded from knee extensors at isokinetic isometric mode at angle of 45 degree. Also, the Absolute Angular Error was recorded at 45O and 30O to measure joint position sense (JPS). They made anteroposterior (AP) plain X-rays from standing semiflexed knee position and their average score of Timed Up and Go test(TUG) and WOMAC were recorded as a measure of knee pain, stiffness and function. Comparison between the mean values of different variables in the two groups was performed using unpaired student t test. The P value less or equal to 0.05 was considered significant. Results: There were significant differences between the studied variables between the experimental and control groups except the values of AAE at 30O. Also, there were no significant correlation between the clinical findings (pain, function, muscle strength and proprioception) and the severity of arthritic changes in X-rays. CONCLUSION: From the finding of the current study we can conclude that there were a significant difference between the both groups in all studied parameters (the WOMAC, functional level, quadriceps muscle strength and the joint proprioception). Also this study did not support the dependency on radiological findings in management of knee OA as the radiological features did not necessarily indicate the level of structural damage of patients with knee OA and we should consider the clinical features in our treatment plan.

Keywords: joint position sense, peak torque, proprioception, radiological knee osteoarthritis

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Authors: Lucie Mrackova, Helena Kisvetrova

Abstract:

Spirituality is an integral part of human life. In a secular environment, spiritual needs are often overlooked, especially in acute nursing care. Spiritual needs assessment for patients (SNAP), which also exists in the Czech version (SNAP-CZ), can be used for objective evaluation. The aim of this study was to measure the psychometric properties of SNAP-CZ and to find correlations between SNAP-CZ and sociodemographic and clinical variables. A cross-sectional study with tools assessing spiritual needs (SNAP-CZ), anxiety (Beck Anxiety Inventory; BAI), depression (Beck Depression Inventory; BDI), pain (Visual Analogue Scale; VAS), self-sufficiency (Barthel Index; BI); cognitive function (Montreal Cognitive Test; MoCa) and selected socio-demographic data was performed. The psychometric properties of SNAP-CZ were tested using factor analysis, reliability and validity tests, and correlations between the questionnaire and sociodemographic data and clinical variables. Internal consistency was established with Cronbach’s alfa for the overall score, respective domains, and individual items. Reliability was assessed by test-retest by Interclass correlation coefficient (ICC). Data for correlation analysis were processed according to Pearson's correlation coefficient. The study included 172 trauma patients (the mean age = 40.6 ± 12.1 years) who experienced polytrauma or severe monotrauma. There were a total of 106 (61.6%) male subjects, 140 (81.4%) respondents identified themselves as non-believers. The full-scale Cronbach's alpha was 0.907. The test-retest showed the reliability of the individual domains in the range of 0.924 to 0.960 ICC. Factor analysis resulted in a three-factor solution (psychosocial needs (alfa = 0.788), spiritual needs (alfa = 0.886) and religious needs (alfa = 0.841)). Correlation analysis using Pearson's correlation coefficient showed that the domain of psychosocial needs significantly correlated only with gender (r = 0.178, p = 0.020). Males had a statistically significant lower average value in this domain (mean = 12.5) compared to females (mean = 13.8). The domain of spiritual needs significantly correlated with gender (r = 0.199, p = 0.009), social status (r = 0.156, p = 0.043), faith (r = -0.250, p = 0.001), anxiety (r = 0.194, p = 0.011) and depression (r = 0.155, p = 0.044). The domain of religious needs significantly correlated with age (r = 0,208, p = 0,007), education (r = -0,161, p = 0,035), faith (r = -0,575, p < 0,0001) and depression (r = 0,179, p = 0,019). Overall, the whole SNAP scale significantly correlated with gender (r = 0.219, p = 0.004), social status (r = 0.175, p = 0.023), faith (r = -0.334, p <0.0001), anxiety (r = 0.177, p = 0.022) and depression (r = 0.173, p = 0.025). The results of this study corroborate the reliability of the SNAP-CZ and support its future use in the nursing care of trauma patients in a secular society. Acknowledgment: The study was supported by grant nr. IGA_FZV_2020_003.

Keywords: acute nursing care, assessment of spiritual needs, patient, psychometric validation, spirituality

Procedia PDF Downloads 64

Authors: Omur F. Karakullukcu, Bilal Okudan, Yusuf Can

Abstract:

The aim of this study is to analyze sports managers’ managerial competence levels and job satisfaction’s correlation with career satisfaction. In the study, it has also been analyzed if there is any significant difference in sports managers’ managerial competence, job and career satisfaction in terms of gender, age, duty status, year of service and level of education. 256 sports managers, who work at department of sports service’s central and field organization at least as a chief in the manager position, have been chosen with random sampling method and they have voluntarily participated in the study. In the study, the managerial competence scale which was developed by Cetinkaya (2009), job satisfaction scale developed by Weiss at al.(1967) and Career Satisfaction Scale developed by Vatansever (2008) have been used as a data collection tool. The questionnaire form used as a data collection tool in the study includes a personal information form consisting of 5 questions; questioning gender, age, duty status, years of service and level of education. In the study, pearson correlation analysis has been used for defining the correlation of managerial competence levels, job satisfaction, and career satisfaction levels of sports managers. T-test analysis for binary grouping and anova analysis for more than binary groups have been used in the level of self-efficacy, collective and managerial competence in terms of the participants’ duty status, year of service and level of education. According to the research results, it has been found that there is a positive correlation between sports managers’ managerial competence levels, job satisfaction, and career satisfaction levels. Also, the results show that there is a significant difference in managerial competence levels, job satisfaction and career satisfaction of sports managers in terms of duty status, year of service and level of education; however, the results reveal that there is no significant difference in terms of age groups and gender.

Keywords: sports manager, managerial competence, job satisfaction, career satisfaction

Procedia PDF Downloads 235

Authors: Nini Johana Marín Rodríguez, William Fernando Oquendo Patino

Abstract:

In this work, we model a coupled system where we explore the effects of steady and random behavior on a linear system like an extension of the classic Strogatz model. This is exemplified by modeling a couple love dynamics as a linear system of two coupled differential equations and studying its stability for four types of lovers chosen as CC='Cautious- Cautious', OO='Only other feelings', OP='Opposites' and RR='Romeo the Robot'. We explore the effects of, first, introducing saturation, and second, adding a random variation to one of the CC-type lover, which will shape his character by trying to model how its variability influences the dynamics between love and hate in couple in a long run relationship. This work could also be useful to model other kind of systems where interactions can be modeled as linear systems with external or internal random influence. We found the final results are not easy to predict and a strong dependence on initial conditions appear, which a signature of chaos.

Keywords: differential equations, dynamical systems, linear system, love dynamics

Procedia PDF Downloads 316