Search results for: regression analysis (RA)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 29375

Search results for: regression analysis (RA)

28715 Impact Assessment of Information Communication, Network Providers, Teledensity, and Consumer Complaints on Gross Domestic Products

Authors: Essang Anwana Onuntuei, Chinyere Blessing Azunwoke

Abstract:

The study used secondary data from foreign and local organizations to explore major challenges and opportunities abound in Information Communication. The study aimed at exploring the tie between tele density (network coverage area) and the number of network subscriptions, probing if the degree of consumer complaints varies significantly among network providers, and assessing if network subscriptions do significantly influence the sector’s GDP contribution. Methods used for data analysis include Pearson product-moment correlation and regression analysis, and the Analysis of Variance (ANOVA) as well. At a two-tailed test of 0.05 confidence level, the results of findings established about 85.6% of network subscriptions were explained by tele density (network coverage area), and the number of network subscriptions; Consumer Complaints’ degree varied significantly among network providers as 80.158291 (F calculated) > 3.490295 (F critical) with very high confidence associated p-value = 0.000000 which is < 0.05; and finally, 65% of the nation’s GDP was explained by network subscription to show a high association.

Keywords: tele density, subscription, network coverage, information communication, consumer

Procedia PDF Downloads 55
28714 Similar Correlation of Meat and Sugar to Global Obesity Prevalence

Authors: Wenpeng You, Maciej Henneberg

Abstract:

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

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

Procedia PDF Downloads 309
28713 Financial Literacy Testing: Results of Conducted Research and Introduction of a Project

Authors: J. Nesleha, H. Florianova

Abstract:

The goal of the study is to provide results of a conducted study devoted to financial literacy in the Czech Republic and to introduce a project related to financial education in the Czech Republic. Financial education has become an important part of education in the country, yet it is still neglected on the lowest level of formal education–primary schools. The project is based on investigation of financial literacy on primary schools in the Czech Republic. Consequently, the authors aim to formulate possible amendments related to this type of education. The gained dataset is intended to be used for analysis concerning financial education in the Czech Republic. With regard to used methods, the most important one is regression analysis for disclosure of predictors causing different levels of financial literacy. Furthermore, comparison of different groups is planned, for which t-tests are intended to be used. The study also employs descriptive statistics to introduce basic relationship in the data file.

Keywords: Czech Republic, financial education, financial literacy, primary school

Procedia PDF Downloads 349
28712 Sero-Prevalence of Hepatitis B Surface Antigen and Associated Factors among Pregnant Mothers Attending Antenatal Care Service, Mekelle, Ethiopia: Evidence from Institutional Based Quantitative Cross-Sectional Study

Authors: Semaw A., Awet H., Yohannes M.

Abstract:

Background: Hepatitis B Virus (HBV) is a major global public health problem. Individuals living in Sub-Sahara Africa have 60% lifetime risk of acquiring HBV infection. Evidences showed that 80-90% of those born from infected mothers developed chronic HBV. Perinatal HBV transmission is a major determinant of HBV carrier status, its chronic squeal and maintains HBV transmission across generations. Method: Institution based cross-sectional study was conducted among 406 pregnant mothers attending Antenatal clinics at Mekelle and Ayder referral hospital from January 30 to April 1/2014. Epidata version 3.1 was used for data entry and SPSS version 21 statistical software was used for data cleaning, management and finally determine associated factors of hepatitis B surface antigen adjusting important confounders using multivariable logistic regression analysis at 5% level of significance. Result: The overall prevalence of hepatitis B surface antigen among pregnant women was 33 (8.1%). The socio-demographic characteristic of the study population showed that there is high positivity among secondary school 189 (46.6%). In the multivariable logistic regression analysis, history of a contact with individuals who had history of hepatitis B infection or jaundice and lifetime number of multiple sexual partners were found to be significantly associated with HBsAg positivity at AOR = 3.73 95%C.I (1.373-10.182) and AOR = 2.57 95%C.I (1.173-5.654), respectively. Moreover, Human Immunodeficiency Virus (HIV) and HBV confection rate was found 3.6%. Conclusion: This study has shown that HBV prevalence in pregnant women is highly prevalent (8.1%) in the study area. Contact with individuals who had a history of hepatitis or have jaundice and report of multiple lifetime sexual partnership were associated with hepatitis B infection. Education about HBV transmission and prevention as well as screening all pregnant mothers shall be sought to reduce the serious public health crisis of HBV.

Keywords: HBsAg, hepatitis B, pregnant women, prevalence

Procedia PDF Downloads 346
28711 Effect of Genuine Missing Data Imputation on Prediction of Urinary Incontinence

Authors: Suzan Arslanturk, Mohammad-Reza Siadat, Theophilus Ogunyemi, Ananias Diokno

Abstract:

Missing data is a common challenge in statistical analyses of most clinical survey datasets. A variety of methods have been developed to enable analysis of survey data to deal with missing values. Imputation is the most commonly used among the above methods. However, in order to minimize the bias introduced due to imputation, one must choose the right imputation technique and apply it to the correct type of missing data. In this paper, we have identified different types of missing values: missing data due to skip pattern (SPMD), undetermined missing data (UMD), and genuine missing data (GMD) and applied rough set imputation on only the GMD portion of the missing data. We have used rough set imputation to evaluate the effect of such imputation on prediction by generating several simulation datasets based on an existing epidemiological dataset (MESA). To measure how well each dataset lends itself to the prediction model (logistic regression), we have used p-values from the Wald test. To evaluate the accuracy of the prediction, we have considered the width of 95% confidence interval for the probability of incontinence. Both imputed and non-imputed simulation datasets were fit to the prediction model, and they both turned out to be significant (p-value < 0.05). However, the Wald score shows a better fit for the imputed compared to non-imputed datasets (28.7 vs. 23.4). The average confidence interval width was decreased by 10.4% when the imputed dataset was used, meaning higher precision. The results show that using the rough set method for missing data imputation on GMD data improve the predictive capability of the logistic regression. Further studies are required to generalize this conclusion to other clinical survey datasets.

Keywords: rough set, imputation, clinical survey data simulation, genuine missing data, predictive index

Procedia PDF Downloads 171
28710 Banks Profitability Indicators in CEE Countries

Authors: I. Erins, J. Erina

Abstract:

The aim of the present article is to determine the impact of the external and internal factors of bank performance on the profitability indicators of the CEE countries banks in the period from 2006 to 2012. On the basis of research conducted abroad on bank and macroeconomic profitability indicators, in order to obtain research results, the authors evaluated return on average assets (ROAA) and return on average equity (ROAE) indicators of the CEE countries banks. The authors analyzed profitability indicators of banks using descriptive methods, SPSS data analysis methods as well as data correlation and linear regression analysis. The authors concluded that most internal and external indicators of bank performance have no direct effect on the profitability of the banks in the CEE countries. The only exceptions are credit risk and bank size which affect one of the measures of bank profitability–return on average equity.

Keywords: banks, CEE countries, profitability ROAA, ROAE

Procedia PDF Downloads 371
28709 Exploring the Relationship among Job Stress, Travel Constraints, and Job Satisfaction of the Employees in Casino Hotels: The Case of Macau

Authors: Tao Zhang

Abstract:

Job stress appears nearly everywhere especially in the hospitality industry because employees in this industry usually have to work long time and try to meet conflicting demands of their customers, managers, and company. To reduce job stress, employees of casino hotels try to perform leisure activities or tourism. However, casino employees often meet many obstacles or constraints when they plan to travel. Until now, there is little understanding as to why casino hotel employees often face many travel constraints or leisure barriers. What is more, few studies explore the relationship between travel constraints and job stress of casino employees. Therefore, this study is to explore the construct of casino hotel employees' travel constraints and the relationship among job stress, travel constraints, and job satisfaction. Using convenient sampling method, this study planned to investigate 500 front line employees and managers of ten casino hotels in Macau. A total of 500 questionnaires were distributed, and 414 valid questionnaires were received. The return rate of valid questionnaires is 82.8%. Several statistical techniques such as factor analysis, t-test, one-way ANOVA, and regression analysis were applied to analyze the collected data. The findings of this study are as follows. Firstly, by using factor analysis, this study found the travel constraints of casino employees include intrapersonal constraints, interpersonal constraints, and structural constraints. Secondly, by using regression analysis, the study found travel constraints are positively related with job stress while negatively related with job satisfaction. This means reducing travel constraints may create a chance for casino employees to travel so that they could reduce job stress, therefore raise their job satisfaction. Thirdly, this research divided the research samples into three groups by the degree of job stress. The three groups are low satisfaction group, medium satisfaction group, and high satisfaction group. The means values of these groups were compared by t-test. Results showed that there are significant differences of the means values of interpersonal constraints between low satisfaction group and high satisfaction group. This suggests positive interpersonal relationship especially good family member relationship reduce not only job stress but also travel constraints of casino employees. Interestingly, results of t-test showed there is not a significant difference of the means values of structural constraints between low satisfaction group and high satisfaction group. This suggests structural constraints are outside variables which may be related with tourism destination marketing. Destination marketing organizations (DMO) need use all kinds of tools and techniques to promote their tourism destinations so as to reduce structural constraints of casino employees. This research is significant for both theoretical and practical fields. From the theoretical perspective, the study found the internal relationship between travel constraints, job stress, and job satisfaction and the different roles of three dimensions of travel constraints. From the practical perspective, the study provides useful methods to reduce travel constraints and job stress, therefore, raise job satisfaction of casino employees.

Keywords: hotel, job satisfaction, job stress, travel constraints

Procedia PDF Downloads 254
28708 Enhancement in Digester Efficiency and Numerical Analysis for Optimal Design Parameters of Biogas Plant Using Design of Experiment Approach

Authors: Rajneesh, Priyanka Singh

Abstract:

Biomass resources have been one of the main energy sources for mankind since the dawn of civilization. There is a vast scope to convert these energy sources into biogas which is a clean, low carbon technology for efficient management and conversion of fermentable organic wastes into a cheap and versatile fuel and bio/organic manure. Thus, in order to enhance the performance of anaerobic digester, an optimizing analysis of resultant parameters (organic dry matter (oDM) content, methane percentage, and biogas yield) has been done for a plug flow anaerobic digester having mesophilic conditions (20-40°C) with the wet fermentation process. Based on the analysis, correlations for oDM, methane percentage, and biogas yield are derived using multiple regression analysis. A statistical model is developed to correlate the operating variables using the design of experiment approach by selecting central composite design (CCD) of a response surface methodology. Results shown in the paper indicates that as the operating temperature increases the efficiency of digester gets improved provided that the pH and hydraulic retention time (HRT) remains constant. Working in an optimized range of carbon-nitrogen ratio for the plug flow digester, the output parameters show a positive change with the variation of dry matter content (DM).

Keywords: biogas, digester efficiency, design of experiment, plug flow digester

Procedia PDF Downloads 382
28707 Exploring the Factors Affecting the Presence of Farmers’ Markets in Rural British Columbia

Authors: Amirmohsen Behjat, Aleck Ostry, Christina Miewald, Bernie Pauly

Abstract:

Farmers’ Markets have become one of the important healthy food suppliers in both rural communities and urban settings. Farmers’ markets are evolving and their number has rapidly increased in the past decade. Despite this drastic increase, the distribution of the farmers’ markets is not even across different areas. The main goal of this study is to explore the socioeconomic, geographic, and demographic variables which affect the establishment of farmers’ market in rural communities in British Columbia (BC). Thus, the data on available farmers’ markets in rural areas were collected from BC Association of Farmers’ Markets and spatially joined to BC map at Dissemination Area (DA) level using ArcGIS software to link the farmers’ market to the respective communities that they serve. Then, in order to investigate this issue and understand which rural communities farmer’ markets tend to operate, a binary logistic regression analysis was performed with the availability of farmer’ markets at DA-level as dependent variable and Deprivation Index (DI), Metro Influence Zone (MIZ) and population as independent variables. The results indicated that DI and MIZ variables are not statistically significant whereas the population is the only which had a significant contribution in predicting the availability of farmers’ markets in rural BC. Moreover, this study found that farmers’ markets usually do not operate in rural food deserts where other healthy food providers such as supermarkets and grocery stores are non-existent. In conclusion, the presence of farmers markets is not associated with socioeconomic and geographic characteristics of rural communities in BC, but farmers’ markets tend to operate in more populated rural communities in BC.

Keywords: farmers’ markets, socioeconomic and demographic variables, metro influence zone, logistic regression, ArcGIS

Procedia PDF Downloads 192
28706 Derivation of Bathymetry from High-Resolution Satellite Images: Comparison of Empirical Methods through Geographical Error Analysis

Authors: Anusha P. Wijesundara, Dulap I. Rathnayake, Nihal D. Perera

Abstract:

Bathymetric information is fundamental importance to coastal and marine planning and management, nautical navigation, and scientific studies of marine environments. Satellite-derived bathymetry data provide detailed information in areas where conventional sounding data is lacking and conventional surveys are inaccessible. The two empirical approaches of log-linear bathymetric inversion model and non-linear bathymetric inversion model are applied for deriving bathymetry from high-resolution multispectral satellite imagery. This study compares these two approaches by means of geographical error analysis for the site Kankesanturai using WorldView-2 satellite imagery. Based on the Levenberg-Marquardt method calibrated the parameters of non-linear inversion model and the multiple-linear regression model was applied to calibrate the log-linear inversion model. In order to calibrate both models, Single Beam Echo Sounding (SBES) data in this study area were used as reference points. Residuals were calculated as the difference between the derived depth values and the validation echo sounder bathymetry data and the geographical distribution of model residuals was mapped. The spatial autocorrelation was calculated by comparing the performance of the bathymetric models and the results showing the geographic errors for both models. A spatial error model was constructed from the initial bathymetry estimates and the estimates of autocorrelation. This spatial error model is used to generate more reliable estimates of bathymetry by quantifying autocorrelation of model error and incorporating this into an improved regression model. Log-linear model (R²=0.846) performs better than the non- linear model (R²=0.692). Finally, the spatial error models improved bathymetric estimates derived from linear and non-linear models up to R²=0.854 and R²=0.704 respectively. The Root Mean Square Error (RMSE) was calculated for all reference points in various depth ranges. The magnitude of the prediction error increases with depth for both the log-linear and the non-linear inversion models. Overall RMSE for log-linear and the non-linear inversion models were ±1.532 m and ±2.089 m, respectively.

Keywords: log-linear model, multi spectral, residuals, spatial error model

Procedia PDF Downloads 300
28705 New Approach for Load Modeling

Authors: Slim Chokri

Abstract:

Load forecasting is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.

Keywords: neural network, load forecasting, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression

Procedia PDF Downloads 439
28704 Using Linear Logistic Regression to Evaluation the Patient and System Delay and Effective Factors in Mortality of Patients with Acute Myocardial Infarction

Authors: Firouz Amani, Adalat Hoseinian, Sajjad Hakimian

Abstract:

Background: The mortality due to Myocardial Infarction (MI) is often occur during the first hours after onset of symptom. So, for taking the necessary treatment and decreasing the mortality rate, timely visited of the hospital could be effective in this regard. The aim of this study was to investigate the impact of effective factors in mortality of MI patients by using Linear Logistic Regression. Materials and Methods: In this case-control study, all patients with Acute MI who referred to the Ardabil city hospital were studied. All of died patients were considered as the case group (n=27) and we select 27 matched patients without Acute MI as a control group. Data collected for all patients in two groups by a same checklist and then analyzed by SPSS version 24 software using statistical methods. We used the linear logistic regression model to determine the effective factors on mortality of MI patients. Results: The mean age of patients in case group was significantly higher than control group (75.1±11.7 vs. 63.1±11.6, p=0.001).The history of non-cardinal diseases in case group with 44.4% significantly higher than control group with 7.4% (p=0.002).The number of performed PCIs in case group with 40.7% significantly lower than control group with 74.1% (P=0.013). The time distance between hospital admission and performed PCI in case group with 110.9 min was significantly upper than control group with 56 min (P=0.001). The mean of delay time from Onset of symptom to hospital admission (patient delay) and the mean of delay time from hospital admissions to receive treatment (system delay) was similar between two groups. By using logistic regression model we revealed that history of non-cardinal diseases (OR=283) and the number of performed PCIs (OR=24.5) had significant impact on mortality of MI patients in compare to other factors. Conclusion: Results of this study showed that of all studied factors, the number of performed PCIs, history of non-cardinal illness and the interval between onset of symptoms and performed PCI have significant relation with morality of MI patients and other factors were not meaningful. So, doing more studies with a large sample and investigated other involved factors such as smoking, weather and etc. is recommended in future.

Keywords: acute MI, mortality, heart failure, arrhythmia

Procedia PDF Downloads 125
28703 Determination of the Bank's Customer Risk Profile: Data Mining Applications

Authors: Taner Ersoz, Filiz Ersoz, Seyma Ozbilge

Abstract:

In this study, the clients who applied to a bank branch for loan were analyzed through data mining. The study was composed of the information such as amounts of loans received by personal and SME clients working with the bank branch, installment numbers, number of delays in loan installments, payments available in other banks and number of banks to which they are in debt between 2010 and 2013. The client risk profile was examined through Classification and Regression Tree (CART) analysis, one of the decision tree classification methods. At the end of the study, 5 different types of customers have been determined on the decision tree. The classification of these types of customers has been created with the rating of those posing a risk for the bank branch and the customers have been classified according to the risk ratings.

Keywords: client classification, loan suitability, risk rating, CART analysis

Procedia PDF Downloads 338
28702 Islamic Equity Markets Response to Volatility of Bitcoin

Authors: Zakaria S. G. Hegazy, Walid M. A. Ahmed

Abstract:

This paper examines the dependence structure of Islamic stock markets on Bitcoin’s realized volatility components in bear, normal, and bull market periods. A quantile regression approach is employed, after adjusting raw returns with respect to a broad set of relevant global factors and accounting for structural breaks in the data. The results reveal that upside volatility tends to exert negative influences on Islamic developed-market returns more in bear than in bull market conditions, while downside volatility positively affects returns during bear and bull conditions. For emerging markets, we find that the upside (downside) component exerts lagged negative (positive) effects on returns in bear (all) market regimes. By and large, the dependence structures turn out to be asymmetric. Our evidence provides essential implications for investors.

Keywords: cryptocurrency markets, bitcoin, realized volatility measures, asymmetry, quantile regression

Procedia PDF Downloads 191
28701 Estimation of Dynamic Characteristics of a Middle Rise Steel Reinforced Concrete Building Using Long-Term

Authors: Fumiya Sugino, Naohiro Nakamura, Yuji Miyazu

Abstract:

In earthquake resistant design of buildings, evaluation of vibration characteristics is important. In recent years, due to the increment of super high-rise buildings, the evaluation of response is important for not only the first mode but also higher modes. The knowledge of vibration characteristics in buildings is mostly limited to the first mode and the knowledge of higher modes is still insufficient. In this paper, using earthquake observation records of a SRC building by applying frequency filter to ARX model, characteristics of first and second modes were studied. First, we studied the change of the eigen frequency and the damping ratio during the 3.11 earthquake. The eigen frequency gradually decreases from the time of earthquake occurrence, and it is almost stable after about 150 seconds have passed. At this time, the decreasing rates of the 1st and 2nd eigen frequencies are both about 0.7. Although the damping ratio has more large error than the eigen frequency, both the 1st and 2nd damping ratio are 3 to 5%. Also, there is a strong correlation between the 1st and 2nd eigen frequency, and the regression line is y=3.17x. In the damping ratio, the regression line is y=0.90x. Therefore 1st and 2nd damping ratios are approximately the same degree. Next, we study the eigen frequency and damping ratio from 1998 after 3.11 earthquakes, the final year is 2014. In all the considered earthquakes, they are connected in order of occurrence respectively. The eigen frequency slowly declined from immediately after completion, and tend to stabilize after several years. Although it has declined greatly after the 3.11 earthquake. Both the decresing rate of the 1st and 2nd eigen frequencies until about 7 years later are about 0.8. For the damping ratio, both the 1st and 2nd are about 1 to 6%. After the 3.11 earthquake, the 1st increases by about 1% and the 2nd increases by less than 1%. For the eigen frequency, there is a strong correlation between the 1st and 2nd, and the regression line is y=3.17x. For the damping ratio, the regression line is y=1.01x. Therefore, it can be said that the 1st and 2nd damping ratio is approximately the same degree. Based on the above results, changes in eigen frequency and damping ratio are summarized as follows. In the long-term study of the eigen frequency, both the 1st and 2nd gradually declined from immediately after completion, and tended to stabilize after a few years. Further it declined after the 3.11 earthquake. In addition, there is a strong correlation between the 1st and 2nd, and the declining time and the decreasing rate are the same degree. In the long-term study of the damping ratio, both the 1st and 2nd are about 1 to 6%. After the 3.11 earthquake, the 1st increases by about 1%, the 2nd increases by less than 1%. Also, the 1st and 2nd are approximately the same degree.

Keywords: eigenfrequency, damping ratio, ARX model, earthquake observation records

Procedia PDF Downloads 219
28700 Negative Perceptions of Ageing Predicts Greater Dysfunctional Sleep Related Cognition Among Adults Aged 60+

Authors: Serena Salvi

Abstract:

Ageistic stereotypes and practices have become a normal and therefore pervasive phenomenon in various aspects of everyday life. Over the past years, renewed awareness towards self-directed age stereotyping in older adults has given rise to a line of research focused on the potential role of attitudes towards ageing on seniors’ health and functioning. This set of studies has showed how a negative internalisation of ageistic stereotypes would discourage older adults in seeking medical advice, in addition to be associated to negative subjective health evaluation. An important dimension of mental health that is often affected in older adults is represented by sleep quality. Self-reported sleep quality among older adults has shown to be often unreliable when compared to their objective sleep measures. Investigations focused on self-reported sleep quality among older adults have suggested how this portion of the population would tend to accept disrupted sleep if believed to be up to standard for their age. On the other hand, unrealistic expectations, and dysfunctional beliefs towards sleep in ageing, might prompt older adults to report sleep disruption even in the absence of objective disrupted sleep. Objective of this study is to examine an association between personal attitudes towards ageing in adults aged 60+ and dysfunctional sleep related cognition. More in detail, this study aims to investigate a potential association between personal attitudes towards ageing, sleep locus of control and dysfunctional beliefs towards sleep among this portion of the population. Data in this study were statistically analysed in SPSS software. Participants were recruited through the online participants recruitment system Prolific. Inclusion of attention check questions throughout the questionnaire and consistency of responses were looked at. Prior to the commencement of this study, Ethical Approval was granted (ref. 39396). Descriptive statistics were used to determine the frequency, mean, and SDs of the variables. Pearson coefficient was used for interval variables, independent T-test for comparing means between two independent groups, analysis of variance (ANOVA) test for comparing the means in several independent groups, and hierarchical linear regression models for predicting criterion variables based on predictor variables. In this study self-perceptions of ageing were assessed using APQ-B’s subscales, while dysfunctional sleep related cognition was operationalised using the SLOC and the DBAS16 scales. Of the final subscales taken in consideration in the brief version of the APQ questionnaire, Emotional Representations (ER), Control Positive (PC) and Control and Consequences Negative (NC) have shown to be of particularly relevance for the remits of this study. Regression analysis show how an increase in the APQ-B subscale Emotional Representations (ER) predicts an increase in dysfunctional beliefs and attitudes towards sleep in this sample, after controlling for subjective sleep quality, level of depression and chronological age. A second regression analysis showed that APQ-B subscales Control Positive (PC) and Control and Consequences Negative (NC) were significant predictors in the change of variance of SLOC, after controlling for subjective sleep quality, level of depression and dysfunctional beliefs about sleep.

Keywords: sleep-related cognition, perceptions of aging, older adults, sleep quality

Procedia PDF Downloads 106
28699 Predicting College Students’ Happiness During COVID-19 Pandemic; Be optimistic and Well in College!

Authors: Michiko Iwasaki, Jane M. Endres, Julia Y. Richards, Andrew Futterman

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The present study aimed to examine college students’ happiness during COVID19-pandemic. Using the online survey data from 96 college students in the U.S., a regression analysis was conducted to predict college students’ happiness. The results indicated that a four-predictor model (optimism, college students’ subjective wellbeing, coronavirus stress, and spirituality) explained 57.9% of the variance in student’s subjective happiness, F(4,77)=26.428, p<.001, R2=.579, 95% CI [.41,.66]. The study suggests the importance of learned optimism among college students.

Keywords: COVID-19, optimism, spirituality, well-being

Procedia PDF Downloads 230
28698 Surface Roughness Prediction Using Numerical Scheme and Adaptive Control

Authors: Michael K.O. Ayomoh, Khaled A. Abou-El-Hossein., Sameh F.M. Ghobashy

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This paper proposes a numerical modelling scheme for surface roughness prediction. The approach is premised on the use of 3D difference analysis method enhanced with the use of feedback control loop where a set of adaptive weights are generated. The surface roughness values utilized in this paper were adapted from [1]. Their experiments were carried out using S55C high carbon steel. A comparison was further carried out between the proposed technique and those utilized in [1]. The experimental design has three cutting parameters namely: depth of cut, feed rate and cutting speed with twenty-seven experimental sample-space. The simulation trials conducted using Matlab software is of two sub-classes namely: prediction of the surface roughness readings for the non-boundary cutting combinations (NBCC) with the aid of the known surface roughness readings of the boundary cutting combinations (BCC). The following simulation involved the use of the predicted outputs from the NBCC to recover the surface roughness readings for the boundary cutting combinations (BCC). The simulation trial for the NBCC attained a state of total stability in the 7th iteration i.e. a point where the actual and desired roughness readings are equal such that error is minimized to zero by using a set of dynamic weights generated in every following simulation trial. A comparative study among the three methods showed that the proposed difference analysis technique with adaptive weight from feedback control, produced a much accurate output as against the abductive and regression analysis techniques presented in this.

Keywords: Difference Analysis, Surface Roughness; Mesh- Analysis, Feedback control, Adaptive weight, Boundary Element

Procedia PDF Downloads 625
28697 An Analysis of Fertility Decline in India: Evidences from Tamil Nadu and Uttar Pradesh

Authors: Ajay Kumar

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Using data from census of India, sample registration system and national family health survey (NFHS-3), this paper traces spatial pattern, trends and the factors which have played their role differently in fertility transition in Uttar Pradesh and Tamil Nadu. For the purpose spatial variation analysis, trend line and binary logistic regression analysis has been carried out. There exist considerable regional disparities in terms of fertility decline in northern and southern states. The pace of fertility decline has been faster in southern and coastal regions, and at a slow pace in backward northern state. In Tamil Nadu fertility declined substantially among the women of lower and higher age groups in comparison to Uttar Pradesh characterized by low literacy, low female age at marriage, poor health infrastructure and low status of women. The Study shows that Fertility rates have been higher among the most vulnerable and deprived sections of the society like Illiterate women, women belong to scheduled caste, scheduled tribe and women residing in rural areas.

Keywords: age specific fertility rate, fertility transition, replacement level, total fertility rate

Procedia PDF Downloads 290
28696 Evaluation of the Effect of IMS on the Social Responsibility in the Oil and Gas Production Companies of National Iranian South Oil Fields Company (NISOC)

Authors: Kamran Taghizadeh

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This study was aimed at evaluating the effect of IMS including occupational health system, environmental management system, and safety and health system on the social responsibility (case study of NISOC`s oil and gas production companies). This study`s objectives include evaluating the IMS situation and its effect on social responsibility in addition of providing appropriate solutions based on the study`s hypotheses as a basis for future. Data collection was carried out by library and field studies as well as a questionnaire. The stratified random method was the sampling method and a sample of 285 employees in addition to the collected data (from the questionnaire) were analyzed by inferential statistics methods using SPSS software. Finally, results of regression and fitted model at a significance level of 5% confirmed all hypotheses meaning that IMS and its items have a significant effect on social responsibility.

Keywords: social responsibility, integrated management, oil and gas production companies, regression

Procedia PDF Downloads 260
28695 An Integrated GIS Approach to Sustainable Non-Motorized Transport Analysis in Gondar City Administration, Northwestern Ethiopia

Authors: Yosef Kassa

Abstract:

Gondar City, a city in Ethiopia, is going through growth and increased use of motor vehicles, causing issues of traffic congestion, pollution, and limited mobility options. Despite the growing number of cars on the road, walking still accounts for 54% of all journeys. However, the city’s transportation planning has mainly focused on accommodating vehicles, leading to a lack of infrastructure for non-motorized transportation (nmt). This study utilized GIS analysis and surveys involving residents to examine how aspects of the city impact motorized transport. The GIS analysis objectively evaluated built environment factors influencing nmt, such as infrastructure quality, land usage patterns, topography features, and environmental factors using a multi-criteria analysis method (mca). The survey gathered feedback from residents on these factors and analyzed them statistically. The GIS analysis pinpointed areas with potential for nmt, slopes (<10.03°), mixed-use developments with 15% coverage, and high intersection densities (> 4.2/100m). On the hand, steep slopes (>23.77°) and low intersection areas require interventions. The MCA analysis indicated that 66% of areas in Gondar City had limited nmt accessibility levels, while only 7% were considered accessible. According to survey findings, environmental characteristics such as building density differed throughout sub-cities and demographics, with 1-3 story townhouses dominating Azezo Teda compared to connected kebele housing in Arada, while agreeing topography has obstructed walking. Correlation analysis shows significant relationships like topographies' negative associations with connectivity (-0.373**) and infrastructure (-0.391**). Although, regression analysis found housing type (1.036), safety (-0.688), land use (0.933), connectedness (0.585), and infrastructure (0.889) with p<0.05 were among the determinants of transportation frequency. The integrated analysis uncovered disparities between survey analysis and GIS analysis. In Azezo Teda, the GIS score is 2.27, while the survey score is 2.89. However, there is a correlation (rho=0.56, p<0.01) indicating the reliability of gis in assessing walkability. This research offers insights for enhancing nmt accessibility in Gondar City by promoting transportation planning that focuses on (nmt) and the needs of residents.

Keywords: non-motorized transportation, accessibility, built environment, infrastructure

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28694 The Positive Impact of COVID-19 on the Level of Investments of U.S. Retail Investors: Evidence from a Quantitative Online Survey and Ordered Probit Analysis

Authors: Corina E. Niculaescu, Ivan Sangiorgi, Adrian R. Bell

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The COVID-19 pandemic has been life-changing in many aspects of people’s daily and social lives, but has it also changed attitudes towards investments? This paper explores the effect of the COVID-19 pandemic on retail investors’ levels of investments in the U.S. during the first COVID-19 wave in summer 2020. This is an unprecedented health crisis, which could lead to changes in investment behavior, including irrational behavior in retail investors. As such, this study aims to inform policymakers of what happened to investment decisions during the COVID-19 pandemic so that they can protect retail investors during extreme events like a global health crisis. The study aims to answer two research questions. First, was the level of investments affected by the COVID-19 pandemic, and if so, why? Second, how were investments affected by retail investors’ personal experience with COVID-19? The research analysis is based on primary survey data collected on the Amazon Mechanical Turk platform from a representative sample of U.S. respondents. Responses were collected between the 15th of July and 28th of August 2020 from 1,148 U.S. retail investors who hold mutual fund investments and a savings account. The research explores whether being affected by COVID-19, change in the level of savings, and risk capacity can explain the change in the level of investments by using regression analysis. The dependent variable is changed in investments measured as decrease, no change, and increase. For this reason, the methodology used is ordered probit regression models. The results show that retail investors in the U.S. increased their investments during the first wave of COVID-19, which is unexpected as investors are usually more cautious in crisis times. Moreover, the study finds that those who were affected personally by COVID-19 (e.g., tested positive) were more likely to increase their investments, which is irrational behavior and contradicts expectations. An increase in the level of savings and risk capacity was also associated with increased investments. Overall, the findings show that having personal experience with a health crisis can have an impact on one’s investment decisions as well. Those findings are important for both retail investors and policymakers, especially now that online trading platforms have made trading easily accessible to everyone. There are risks and potential irrational behaviors associated with investment decisions during times of crisis, and it is important that retail investors are aware of them before making financial decisions.

Keywords: COVID-19, financial decision-making, health crisis retail investors, survey

Procedia PDF Downloads 195
28693 The Mediation Role of Loneliness in the Relationship between Interpersonal Trust and Empathy

Authors: Ghazal Doostmohammadi, Susan Rahimzadeh

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

Keywords: empathy, loneliness, interpersonal trust, gender

Procedia PDF Downloads 88
28692 Personal Characteristics and Personality Traits as Predictors of Compassion Fatigue among Counselors from Dominican Schools in the Philippines

Authors: Neil Jordan M. Uy, Fe Pelilia V. Hernandez

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A counselor is always regarded as a professional who embodies the willingness to help others through the process of counseling. He is knowledgeable and skillful of the different theories, tools, and techniques that are useful in aiding the client to cope with their dilemmas. The negative experiences of the clients that are shared during the counseling session can affect the professional counselor. Compassion fatigue, a professional impairment, is characterized by the decline of one’s productivity and the feeling of anxiety and stress brought about as the counselor empathizes, listens, and cares for others. This descriptive type of research aimed to explore variables that are predictors of compassion fatigue utilizing three research instruments; Demographic Profile Sheet, Professional Quality of Life Scale, and Neo-Pi-R. The 52 respondents of this study were counselors from the different Dominican schools in the Philippines. Generally, the counselors have low level of compassion fatigue across personal characteristics (age, gender, years of service, highest educational attainment, and professional status) and personality traits (extraversion, agreeableness, conscientiousness, openness, and neuroticism). ANOVA validated the findings of this that among the personal characteristics and personality traits, extraversion with f-value of 3.944 and p-value of 0.026, and conscientiousness, with f-value of 4.125 and p-value of 0.022 were found to have significant difference in the level of compassion fatigue. A very significant difference was observed with neuroticism with f-value of 6.878 and p-value 0.002. Among the personal characteristics and personal characteristics, only neuroticism was found to predict compassion fatigue. The computed r2 value of 0.204 using multiple regression analysis suggests that 20.4 percent of compassion fatigue can be predicted by neuroticism. The predicting power of neuroticism can be computed from the regression model Y=0.156x+26.464; where x is the number of neuroticism.

Keywords: big five personality traits, compassion fatigue, counselors, professional quality of life scale

Procedia PDF Downloads 382
28691 Evaluation of Environmental Disclosures on Financial Performance of Quoted Industrial Goods Manufacturing Sectors in Nigeria (2011 – 2020)

Authors: C. C. Chima, C. J. M. Anumaka

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This study evaluates environmental disclosures on the financial performance of quoted industrial goods manufacturing sectors in Nigeria. The study employed a quasi-experimental research design to establish the relationship that exists between the environmental disclosure index and financial performance indices (return on assets - ROA, return on equity - ROE, and earnings per share - EPS). A purposeful sampling technique was employed to select five (5) industrial goods manufacturing sectors quoted on the Nigerian Stock Exchange. Secondary data covering 2011 to 2020 financial years were extracted from annual reports of the study sectors using a content analysis method. The data were analyzed using SPSS, Version 23. Panel Ordinary Least Squares (OLS) regression method was employed in estimating the unknown parameters in the study’s regression model after conducting diagnostic and preliminary tests to ascertain that the data set are reliable and not misleading. Empirical results show that there is an insignificant negative relationship between the environmental disclosure index (EDI) and the performance indices (ROA, ROE, and EPS) of the industrial goods manufacturing sectors in Nigeria. The study recommends that: only relevant information which increases the performance indices should appear on the disclosure checklist; environmental disclosure practices should be country-specific; and company executives in Nigeria should increase and monitor the level of investment (resources, time, and energy) in order to ensure that environmental disclosure has a significant impact on financial performance.

Keywords: earnings per share, environmental disclosures, return on assets, return on equity

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28690 The Prevalence and Impact of Anxiety Among Medical Students in the MENA Region: A Systematic Review, Meta-Analysis, and Meta-Regression

Authors: Kawthar F. Albasri, Abdullah M. AlHudaithi, Dana B. AlTurairi, Abdullaziz S. AlQuraini, Adoub Y. AlDerazi, Reem A. Hubail, Haitham A. Jahrami

Abstract:

Several studies have found that medical students have a significant prevalence of anxiety. The purpose of this review paper is to carefully evaluate the current research on anxiety among medical students in the MENA region and, as a result, estimate the prevalence of these disturbances. Multiple databases, including the CINAHL (Cumulative Index to Nursing and Allied Health Literature), Cochrane Library, Embase, MEDLINE (Medical Literature Analysis and Retrieval System Online), PubMed, PsycINFO (Psychological Information Database), Scopus, Web of Science, UpToDate, ClinicalTrials.gov, WHO Global Health Library, EbscoHost, ProQuest, JAMA Network, and ScienceDirect, were searched. The retrieved article reference lists were rigorously searched and rated for quality. A random effects meta-analysis was performed to compute estimates. The current meta-analysis revealed an alarming estimated pooled prevalence of anxiety (K = 46, N = 27023) of 52.5% [95%CI: 43.3%–61.6%]. A total of 62.0% [95% CI 42.9%; 78.0%] of the students (K = 18, N = 16466) suffered from anxiety during the COVID-19 pandemic, while 52.5% [95% CI 43.3%; 61.6%] had anxiety before COVID-19. Based on the GAD-7 measure, a total of 55.7% [95%CI 30.5%; 78.3%] of the students (K = 10, N = 5830) had anxiety, and a total of 54.7% of the students (K = 18, N = 12154) [95%CI 42.8%; 66.0%] had anxiety using the DASS-21 or 42 measure. Anxiety is a common issue among medical students, making it a genuine problem. Further research should be conducted post-COVD 19, with a focus on anxiety prevention and intervention initiatives for medical students.

Keywords: anxiety, medical students, MENA, meta-analysis, prevalence

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28689 How to Use E-Learning to Increase Job Satisfaction in Large Commercial Bank in Bangkok

Authors: Teerada Apibunyopas, Nithinant Thammakoranonta

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Many organizations bring e-Learning to use as a tool in their training and human development department. It is getting more popular because it is easy to access to get knowledge all the time and also it provides a rich content, which can develop the employees skill efficiently. This study focused on the factors that affect using e-Learning efficiently, so it will make job satisfaction increased. The questionnaires were sent to employees in large commercial banks, which use e-Learning located in Bangkok, the results from multiple linear regression analysis showed that employee’s characteristics, characteristics of e-Learning, learning and growth have influence on job satisfaction.

Keywords: e-Learning, job satisfaction, learning and growth, Bangkok

Procedia PDF Downloads 497
28688 Agroforestry Systems and Practices and Its Adoption in Kilombero Cluster of Sagcot, Tanzania

Authors: Lazaro E. Nnko, Japhet J. Kashaigili, Gerald C. Monela, Pantaleo K. T. Munishi

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Agroforestry systems and practices are perceived to improve livelihood and sustainable management of natural resources. However, their adoption in various regions differs with the biophysical conditions and societal characteristics. This study was conducted in Kilombero District to investigate the factors influencing the adoption of different agroforestry systems and practices in agro-ecosystems and farming systems. A household survey, key informant interviews, and focus group discussion was used for data collection in three villages. Descriptive statistics and multinomial logistic regression in SPSS were applied for analysis. Results show that Igima and Ngajengwa villages had home garden practices dominated, as revealed by 63.3% and 66.7%, respectively, while Mbingu village had mixed intercropping practice with 56.67%. Agrosilvopasture systems were dominant in Igima and Ngajengwa villages with 56.7% and 66.7%, respectively, while in Mbingu village, the dominant system was agrosilviculture with 66.7%. The results from multinomial logistic regression show that different explanatory variable was statistical significance as predictors of the adoption of agroforestry systems and practices. Residence type and sex were the most dominant factor influencing the adoption of agroforestry systems. Duration of stay in the village, availability of extension education, residence, and sex were the dominant factor influencing the adoption of agroforestry practices. The most important and statistically significant factors among these were residence type and sex. The study concludes that agroforestry will be more successful if the local priorities, which include social-economic need characteristics of the society, will be considered in designing systems and practices. The socio-economic need of the community should be addressed in the process of expanding the adoption of agroforestry systems and practices.

Keywords: agroforestry adoption, agroforestry systems, agroforestry practices, agroforestry, Kilombero

Procedia PDF Downloads 120
28687 Using Simulation Modeling Approach to Predict USMLE Steps 1 and 2 Performances

Authors: Chau-Kuang Chen, John Hughes, Jr., A. Dexter Samuels

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The prediction models for the United States Medical Licensure Examination (USMLE) Steps 1 and 2 performances were constructed by the Monte Carlo simulation modeling approach via linear regression. The purpose of this study was to build robust simulation models to accurately identify the most important predictors and yield the valid range estimations of the Steps 1 and 2 scores. The application of simulation modeling approach was deemed an effective way in predicting student performances on licensure examinations. Also, sensitivity analysis (a/k/a what-if analysis) in the simulation models was used to predict the magnitudes of Steps 1 and 2 affected by changes in the National Board of Medical Examiners (NBME) Basic Science Subject Board scores. In addition, the study results indicated that the Medical College Admission Test (MCAT) Verbal Reasoning score and Step 1 score were significant predictors of the Step 2 performance. Hence, institutions could screen qualified student applicants for interviews and document the effectiveness of basic science education program based on the simulation results.

Keywords: prediction model, sensitivity analysis, simulation method, USMLE

Procedia PDF Downloads 342
28686 Job Satisfaction and Commitment among Academic Staff of Selected Colleges of Education in Kano and Kaduna States of Nigeria

Authors: Mary Okonkwo Ekwy

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The problem of the growing disillusionment of College of Education teachers with academic life vis-à-vis their job satisfaction and commitment was investigated in this study with a view to finding out if both their job satisfaction and commitment have suffered, and to find out if there was a relationship between job satisfaction and commitment among these College of Education teachers. Due consideration was also given in the study to the possible effects of demographic variables on attitudes to their job. To carry out a study of job satisfaction and commitment among the College of Education teachers and to explore the relationship between them, research instruments were used for measuring the levels of job satisfaction and commitment among them. A sample of 200 Colleges of Education teachers, comprising 15 Professors, 9 Principal Lecturers, 70 Senior Lecturer and 106 Lecturers was used for the study. Five major hypothesis were tested with regard to the relationship between job satisfaction and commitment among the teachers. The Pearson correlation, the F-ratio, and regression analysis were used for data analysis and hypothesis testing. The result of this investigation suggests that, perhaps the best way to secure the commitment of teachers is to ensure their job satisfaction. Future investigations will further enrich our knowledge about these very important themes.

Keywords: job satisfaction, commitment, academic staff, college of education

Procedia PDF Downloads 556