Search results for: regression analysis

Authors: Lei Zhang, Li Ji

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Formal learning and informal learning represent two distinct learning styles: one is systematic and organized, another is causal and unstructured. Although there are many factors influencing online learning satisfaction, including self-regulation, self-efficacy, and interaction, factors influencing online formal learning and informal learning satisfaction may differ from each other. This paper investigated and compared influential factors of online formal and informal learning. Two questionnaires were created based on previous studies to explore factors influencing online formal learning and online informal learning satisfaction, respectively. A sample of 105 college students from different departments in a university located in the eastern part of China was selected to participate in this study. They all had an online learning experience and agreed to fill out questionnaires. Correlation analysis, variance analysis, and regression analysis were employed in this study. In addition, five participants were chosen for interviews. The study found that student-content, interaction, self-regulation, and self-efficacy related positively to both online formal learning and informal learning satisfaction. In addition, compared to online formal learning, student-content interaction in informal learning was the most influential factor for online learning satisfaction, perhaps that online informal learning was more goal-oriented and learners paid attention to the quality of content. In addition, results also revealed that interactions among students or teachers had little impact on online informal learning satisfaction. This study compared influential factors in online formal and informal learning satisfaction helped to add discussions to online learning satisfaction and contributed to further practices of online learning.

Keywords: learning satisfaction, formal learning, informal learning, online learning

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Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

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Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

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Authors: S. Sharma, U. Batra, S. Kapoor, A. Dua

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In this study, the effects and interactions of reaction time and capping agent assistance during sol-gel synthesis of magnesium substituted hydroxyapatite nanopowder (MgHA) on hydroxyapatite (HA) to β-tricalcium phosphate (β-TCP) ratio, Ca/P ratio and mean crystallite size was examined experimentally as well as through statistical analysis. MgHA nanopowders were synthesized by sol-gel technique at room temperature using aqueous solution of calcium nitrate tetrahydrate, magnesium nitrate hexahydrate and potassium dihydrogen phosphate as starting materials. The reaction time for sol-gel synthesis was varied between 15 to 60 minutes. Two process routes were followed with and without addition of triethanolamine (TEA) in the solutions. The elemental compositions of as-synthesized powders were determined using X-ray fluorescence (XRF) spectroscopy. The functional groups present in the as-synthesized MgHA nanopowders were established through Fourier Transform Infrared Spectroscopy (FTIR). The amounts of phases present, Ca/P ratio and mean crystallite sizes of MgHA nanopowders were determined using X-ray diffraction (XRD). The HA content in biphasic mixture of HA and β-TCP and Ca/P ratio in as-synthesized MgHA nanopowders increased effectively with reaction time of sols (p < 0.0001, two way Anova), however, these were independent of TEA addition (p > 0.15, two way Anova). The MgHA nanopowders synthesized with TEA assistance exhibited 14 nm lower crystallite size (p < 0.018, 2 sample t-test) compared to the powder synthesized without TEA assistance.

Keywords: capping agent, hydroxyapatite, regression analysis, sol-gel, 2- sample t-test, two-way analysis of variance (ANOVA)

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Authors: Ayodele Ajayi, John Ajayi

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This paper investigates the effect of corporate governance with a view to determining the relationship between board size and bank performance. Data for the study were obtained from the audited financial statements of five sampled banks listed on the Nigerian Stock Exchange. Panel data technique was adopted and analysis was carried out with the use of multiple regression and pooled ordinary least square. Results from the study show that the larger the board size, the greater the profit implying that corporate governance is positively correlated with bank performance.

Keywords: corporate governance, banks performance, board size, pooled data

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Authors: E. Fredrick Rice

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Over the past three decades, a substantial body of academic literature has asserted that the pressure to maintain household income can negatively affect the personal well-being of breadwinners. Given that scholars have failed to thoroughly explore this phenomenon with breadwinners who are also business owners, theory has been underdeveloped in the entrepreneurial context. To identify the most appropriate theories to apply to entrepreneurs, the current paper utilized two approaches. First, a comprehensive bibliographic analysis was conducted focusing on works at the intersection of breadwinner status and well-being. Co-authorship and journal citation patterns highlighted relative resource theory as a boundary spanning approach with promising applications in the entrepreneurial space. To build upon this theory, regression analysis was performed using data from the Panel Study of Entrepreneurial Dynamics (PSED). Empirical results showed evidence for the effects of breadwinner status and household income on entrepreneurial well-being. Further, the findings suggest that it is not merely income or job status that predicts well-being, but one’s relative financial contribution compared to that of one’s non-breadwinning organizationally employed partner. This paper offers insight into how breadwinner status can be studied in relation to the entrepreneurial personality.

Keywords: breadwinner, entrepreneurship, household income, well-being.

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Authors: Waseem Al Talalwah, Shorok Al Dorazi, Roger Soames

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Persistent sciatic artery is a rare anatomical vascular variation resulting from a lack of regression of the embryonic dorsal axial artery. The axial artery is the main artery supplying the lower limb during development in the first trimester. The current research includes 206 sciatic artery cases in 171 patients between 1864 and 2012. It aims to identify the risk factor of sciatic artery aneurysm in congenital limb anomalies. Sciatic artery aneurysm was diagnosed incidentally in amniotic band syndrome (ABS) existing with no congenital anomaly in 0.7% or with double knee in 0.7%, with the tibia in 0.7% and with hemihypertrophy or soft tissue hypertrophy in 1.4%. Therefore, the current study indicates a relationship the same gene responsible for the congenital limb deformities may be responsible for non-regression of the sciatic artery. Furthermore, pediatricians should refer cases of congenital limb anomalies for vascular evaluation prior to corrective surgical intervention.

Keywords: amniotic band syndrome, congenital limb deformities, double knee, sciatic artery, sciatic artery aneurysm , soft tissue hypertrophy

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Authors: Pisit Potjanajaruwit

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The objectives of the study were to determine the marketing mix factors that influencing tourist’s destination decision making for cultural tourism in the Chonburi province. Both quantitative and qualitative data were applied in this study. The samples of 400 cases for quantitative analysis were tourists (both Thai and foreign) who were interested in cultural tourism in the Chonburi province, and traveled to cultural sites in Chonburi and 14 representatives from provincial tourism committee of Chonburi and local tourism experts. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. The study found that Thai and foreign tourists are influenced by different important marketing mix factors. The important factors for Thai respondents were physical evidence, price, people, and place at high importance level. For foreign respondents, physical evidence, price, people, and process were high importance level, whereas, product, place, and promotion were moderate importance level.

Keywords: Chonburi Province, decision making, cultural tourism, marketing mixed

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Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: Jeeban Amgain

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This paper investigates the impact of the size and composition of government expenditure and tax on GDP per capita growth in 36 Asian economies over the period of 1991-2012. The research employs the technique of panel regression; Fixed Effects and Generalized Method of Moments (GMM) as well as other statistical and descriptive approaches. The finding concludes that the size of government expenditure and tax revenue are generally low in this region. GDP per capita growth is strongly negative in response to Government expenditure, however, no significant relationship can be measured in case of size of taxation although it is positively correlated with economic growth. Panel regression of decomposed fiscal components also shows that the pattern of allocation of expenditure and taxation really matters on growth. Taxes on international trade and property have a significant positive impact on growth. In contrast, a major portion of expenditure, i.e. expenditure on general public services, health and education are found to have significant negative impact on growth, implying that government expenditures are not being productive in the Asian region for some reasons. Comparatively smaller and efficient government size would enhance the growth.

Keywords: government expenditure, tax, GDP per capita growth, composition

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Authors: Tatjana Pekmezovic, Milica Jecmenica-Lukic, Igor Petrovic, Vladimir Kostic

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Background: A group of atypical parkinsonian syndromes (APS) includes a variety of rare neurodegenerative disorders characterized by reduced life expectancy, increasing disability, and considerable impact on health-related quality of life (HRQoL). Aim: In this study we wanted to answer two questions: a) which demographic and clinical factors are main contributors of HRQoL in our cohort of patients with APS, and b) how does quality of life of these patients change over 1-year follow-up period. Patients and Methods: We conducted a prospective cohort study in hospital settings. The initial study comprised all consecutive patients who were referred to the Department of Movement Disorders, Clinic of Neurology, Clinical Centre of Serbia, Faculty of Medicine, University of Belgrade (Serbia), from January 31, 2000 to July 31, 2013, with the initial diagnoses of ‘Parkinson’s disease’, ‘parkinsonism’, ‘atypical parkinsonism’ and ‘parkinsonism plus’ during the first 8 months from the appearance of first symptom(s). The patients were afterwards regularly followed in 4-6 month intervals and eventually the diagnoses were established for 46 patients fulfilling the criteria for clinically probable progressive supranuclear palsy (PSP) and 36 patients for probable multiple system atrophy (MSA). The health-related quality of life was assessed by using the SF-36 questionnaire (Serbian translation). Hierarchical multiple regression analysis was conducted to identify predictors of composite scores of SF-36. The importance of changes in quality of life scores of patients with APS between baseline and follow-up time-point were quantified using Wilcoxon Signed Ranks Test. The magnitude of any differences for the quality of life changes was calculated as an effect size (ES). Results: The final models of hierarchical regression analysis showed that apathy measured by the Apathy evaluation scale (AES) score accounted for 59% of the variance in the Physical Health Composite Score of SF-36 and 14% of the variance in the Mental Health Composite Score of SF-36 (p<0.01). The changes in HRQoL were assessed in 52 patients with APS who completed 1-year follow-up period. The analysis of magnitude for changes in HRQoL during one-year follow-up period have shown sustained medium ES (0.50-0.79) for both Physical and Mental health composite scores, total quality of life as well as for the Physical Health, Vitality, Role Emotional and Social Functioning. Conclusion: This study provides insight into new potential predictors of HRQoL and its changes over time in patients with APS. Additionally, identification of both prognostic markers of a poor HRQoL and magnitude of its changes should be considered when developing comprehensive treatment-related strategies and health care programs aimed at improving HRQoL and well-being in patients with APS.

Keywords: atypical parkinsonian syndromes, follow-up study, quality of life, APS

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Authors: Anudeep Appe, Bhanu Poluparthi, Lakshmi Kasivajjula, Udai Mv, Sobha Bagadi, Punya Modi, Aditya Singh, Hemanth Gunupudi, Spenser Troiano, Jeff Paul, Justin Stovall, Justin Yamamoto

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The necessity of data-driven decisions in healthcare strategy formulation is rapidly increasing. A reliable framework which helps identify factors impacting a healthcare provider facility or a hospital (from here on termed as facility) market share is of key importance. This pilot study aims at developing a data-driven machine learning-regression framework which aids strategists in formulating key decisions to improve the facility’s market share which in turn impacts in improving the quality of healthcare services. The US (United States) healthcare business is chosen for the study, and the data spanning 60 key facilities in Washington State and about 3 years of historical data is considered. In the current analysis, market share is termed as the ratio of the facility’s encounters to the total encounters among the group of potential competitor facilities. The current study proposes a two-pronged approach of competitor identification and regression approach to evaluate and predict market share, respectively. Leveraged model agnostic technique, SHAP, to quantify the relative importance of features impacting the market share. Typical techniques in literature to quantify the degree of competitiveness among facilities use an empirical method to calculate a competitive factor to interpret the severity of competition. The proposed method identifies a pool of competitors, develops Directed Acyclic Graphs (DAGs) and feature level word vectors, and evaluates the key connected components at the facility level. This technique is robust since its data-driven, which minimizes the bias from empirical techniques. The DAGs factor in partial correlations at various segregations and key demographics of facilities along with a placeholder to factor in various business rules (for ex. quantifying the patient exchanges, provider references, and sister facilities). Identified are the multiple groups of competitors among facilities. Leveraging the competitors' identified developed and fine-tuned Random Forest Regression model to predict the market share. To identify key drivers of market share at an overall level, permutation feature importance of the attributes was calculated. For relative quantification of features at a facility level, incorporated SHAP (SHapley Additive exPlanations), a model agnostic explainer. This helped to identify and rank the attributes at each facility which impacts the market share. This approach proposes an amalgamation of the two popular and efficient modeling practices, viz., machine learning with graphs and tree-based regression techniques to reduce the bias. With these, we helped to drive strategic business decisions.

Keywords: competition, DAGs, facility, healthcare, machine learning, market share, random forest, SHAP

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Authors: Davod Ahmadigheidari

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The main objective of this study was to explore prevalence of anthropometric indicators as well the factors associated with the anthropometric indications in Mali. Data on 2015, downloaded from the website of Unicef, were analyzed. A total of 16,467 women (ages 15-49 years) and 16,467 children (ages 0-59 months) were selected for the sample. Different statistical analyses, such as descriptive, crosstabs and binary logistic regression form the basis of this study. Child anthropometric indicators (i.e., wasting, stunting, underweight and BMI for age) were used as the dependent variables. SPSS Syntax from WHO was used to create anthropometric indicators. Different factors, such as child’s sex, child’s age groups, child’s diseases symptoms (i.e., diarrhea, cough and fever), maternal education, household wealth index and area of residence were used as independent variables. Results showed more than forty percent of Malian households were in nutritional crises (stunting (42%) and underweight (34%). Findings from logistic regression analyses indicated that low score of wealth index, low maternal education and experience of diarrhea in last two weeks increase the probability of child malnutrition.

Keywords: Mali, wasting, stunting, underweight, BMI for age and wealth index

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Authors: Arun Dhakal, Geoff Cockfield, Tek Narayan Maraseni

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This paper attempts to fulfil the gap in measuring adoption in agroforestry studies. It explains the derivation of an index of adoption rate in a Nepalese context and examines the factors affecting adoption of agroforestry-based land management practice (AFLMP) in the Dhanusha District of Nepal. Data about the different farm practices and the factors (bio-physical, socio-economic) influencing adoption were collected during focus group discussion and from the randomly selected households using a household survey questionnaire, respectively. A multivariate regression model was used to determine the factors. The factors (variables) found to significantly affect adoption of AFLMP were: farm size, availability of irrigation water, education of household heads, agricultural labour force, frequency of visits by extension workers, expenditure on farm inputs purchase, household’s experience in agroforestry, and distance from home to government forest. The regression model explained about 75% of variation in adoption decision. The model rejected ‘erosion hazard’, ‘flood hazard’ and ‘gender’ as determinants of adoption, which in case of single agroforestry practice were major variables and played positive role. Out of eight variables, farm size played the most powerful role in explaining the variation in adoption, followed by availability of irrigation water and education of household heads. The results of this study suggest that policies to promote the provision of irrigation water, extension services and motivation to obtaining higher education would probably provide the incentive to adopt agroforestry elsewhere in the terai of Nepal.

Keywords: agroforestry, adoption index, determinants of adoption, step-wise linear regression, Nepal

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Authors: Peter Temitope Agboola

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Food insecurity continues to affect a large number of U.S households during this coronavirus COVID-19 pandemic. The pandemic has threatened the livelihoods of people, making them vulnerable to severe hardship and has had an unanticipated impact on the U.S economy. This study attempts to identify the food insecurity status of households and the determinant factors driving household food insecurity. Additionally, it attempts to discover the mitigation measures adopted by households during the pandemic in the city of Huntsville, Texas. A structured online sample survey was used to collect data, with a household expenditures survey used in evaluating the food security status of the household. Most survey respondents disclosed that the COVID-19 pandemic had affected their life and source of income. Furthermore, the main analytical tool used for the study is descriptive statistics and logistic regression modeling. A logistic regression model was used to determine the factors responsible for food insecurity in the study area. The result revealed that most households in the study area are food secure, with the remainder being food insecure.

Keywords: food insecurity, household expenditure survey, COVID-19, coping strategies, food pantry

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Authors: Caren Hilger, Silke Burkert, Friederike Kendel

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Men with localized prostate cancer (PCa) have to choose among different treatment options, such as active surveillance (AS) and radical prostatectomy (RP). All available treatment options may be accompanied by specific psychological or physiological side effects. Depending on the nature and extent of these side effects, patients are more or less likely to be satisfied or to struggle with their treatment decision in the long term. Therefore, the aim of this study was to assess and explain decisional regret in men with localized PCa. The role of erectile functioning as one of the main physiological side effects of invasive PCa treatment, depressive symptoms as a common psychological side effect, and the association of erectile functioning and depressive symptoms with decisional regret were investigated. Men with localized PCa initially managed with AS or RP (N=292) were matched according to length of therapy (mean 47.9±15.4 months). Subjects completed mailed questionnaires assessing decisional regret, changes in erectile functioning, depressive symptoms, and sociodemographic variables. Clinical data were obtained from case report forms. Differences among the two treatment groups (AS and RP) were calculated using t-tests and χ²-tests, relationships of decisional regret with erectile functioning and depressive symptoms were computed using multiple regression. Men were on average 70±7.2 years old. The two treatment groups differed markedly regarding decisional regret (p<.001, d=.50), changes in erectile functioning (p<.001, d=1.2), and depressive symptoms (p=.01, d=.30), with men after RP reporting higher values, respectively. Regression analyses showed that after adjustment for age, tumor risk category, and changes in erectile functioning, depressive symptoms were still significantly associated with decisional regret (B=0.52, p<.001). Additionally, when predicting decisional regret, the interaction of changes in erectile functioning and depressive symptoms reached significance for men after RP (B=0.52, p<.001), but not for men under AS (B=-0.16, p=.14). With increased changes in erectile functioning, the association of depressive symptoms with decisional regret became stronger in men after RP. Decisional regret is a phenomenon more prominent in men after RP than in men under AS. Erectile functioning and depressive symptoms interact in their prediction of decisional regret. Screening and treating depressive symptoms might constitute a starting point for interventions aiming to reduce decisional regret in this target group.

Keywords: active surveillance, decisional regret, depressive symptoms, erectile functioning, prostate cancer, radical prostatectomy

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Authors: Ali Soroush, Mehdi Mirzaei Alavijeh, Touraj Ahmadi Jouybari, Fazel Zinat-Motlagh, Abbas Aghaei, Mari Ataee

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Diabetes is a disease with long cardiovascular, renal, ophthalmic and neural complications. It is prevalent all around the world including Iran, and its prevalence is increasing. The aim of this study was to determine the factors related to self-care behavior based on health belief model among sample of Iranian diabetic patients. This cross-sectional study was conducted among 301 type 2 diabetic patients in Gachsaran, Iran. Data collection was based on an interview and the data were analyzed by SPSS version 20 using ANOVA, t-tests, Pearson correlation, and linear regression statistical tests at 95% significant level. Linear regression analyses showed the health belief model variables accounted for 29% of the variation in self-care behavior; and perceived severity and perceived self-efficacy are more influential predictors on self-care behavior among diabetic patients.

Keywords: diabetes, patients, self-care behaviors, health belief model

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Authors: Rukhsana Kausar, Issam Malki

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The integration and assimilation of ethnic minority immigrants (EMIs) and their subsequent generations remains a serious unsettled issue in most of the host countries. This study conducts the labour market gender analysis to investigate specifically whether second generation of ethnic minority immigrants in the UK is gaining access to professional and managerial employment and advantaged occupational positions on par with their native counterparts. The data used to examine the labour market achievements of EMIs is taken from Labour Force Survey (LFS) for the period 2014-2018. We apply a multivalued treatment under ignorability as proposed by Cattaneo (2010), which refers to treatment effects under the assumptions of (i) selection – on – observables and (ii) common support. We report estimates of Average Treatment Effect (ATE), Average Treatment Effect on the Treated (ATET), and Potential Outcomes Means (POM) using three estimators, including the Regression Adjustment (RA), Augmented Inverse Probability Weighting (AIPW) and Inverse Probability Weighting- Regression Adjustment (IPWRA). We consider two cases: the case with four categories where the first-generation natives are the base category, the second case combine all natives as a base group. Our findings suggest the following. Under Case 1, the estimated probabilities and differences across groups are consistently similar and highly significant. As expected, first generation natives have the highest probability for higher career attainment among both men and women. The findings also suggest that first generation immigrants perform better than the remaining two groups, including the second-generation natives and immigrants. Furthermore, second generation immigrants have higher probability to attain higher professional career, while this is lower for a managerial career. Similar conclusions are reached under Case 2. That is to say that both first – generation and second – generation immigrants have a lower probability for higher career and managerial attainment. First – generation immigrants are found to perform better than second – generation immigrants.

Keywords: immigrnats, second generation, occupational attainment, ethnicity

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Authors: Pitchayanin Sukholthaman

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Gradually accumulated, the enormous amount of waste has caused tremendous adverse impacts to the world. Bangkok, Thailand, is chosen as an urban city of a developing country having coped with serious MSW problems due to the vast amount of waste generated, ineffective and improper waste management problems. Waste generation is the most important factor for successful planning of MSW management system. Thus, the prediction of MSW is a very important role to understand MSW distribution and characteristic; to be used for strategic planning issues. This study aims to find influencing variables that affect the amount of Bangkok MSW generation quantity.

Keywords: MSW generation, MSW quantity prediction, MSW management, multiple regression, Bangkok

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Authors: Mahmoud T. Alwidyan, Ahmad Alrawashdeh, Alaa O. Oteir

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Background: Emergency medical service (EMS) providers, oftentimes, use the lights and sirens (L&S) of their ambulances to warn road users, navigate through traffic, and expedite transport to save lives of ill and injured patients. Despite the contribution of road users in the effectiveness of reducing transport time of EMS ambulances using L&S, there is a lack of empirical assessments exploring the road user’s attitude and behavior in such situations. This study, therefore, aimed to assess the attitude and behavior of road users in response to EMS ambulances with warning L&S in use. Methods: This was a cross-sectional survey developed and distributed to adult road users in Northern Jordan. The questionnaire included 20 items addressing demographics, attitudes, and behavior toward emergency ambulances. We described the participants’ responses and assessed the association between demographics and attitude statements using logistic regression. Results: A total of 1302 questionnaires were complete and appropriate for analysis. The mean age was 34.2 (SD± 11.4) years, and the majority were males (72.6%). About half of road users (47.9%) in our sample would perform inappropriate action in response to EMS ambulances with L&S in use. The multivariate logistic regression model show that being female (OR, 0.63; 95% CI = 0.48-0.81), more educated (OR, 0.68; 95% CI = 0.53-0.86), or public transport driver (OR, 0.55; 95% CI = 0.34-0.90) is significantly associated with inappropriate response to EMS ambulances. Additionally, a significant proportion of road users may perform inappropriate and lawless driving practices such as crossing red traffic lights or following the passing by EMS ambulances, which would, in turn, increase the risk on ambulances and other road users. Conclusions: A large proportion of road users in Jordan may respond inappropriately to the EMS ambulances, and many engage in risky driving behaviors due perhaps to the lack of procedural knowledge. Policy-related interventions and educational programs are crucially needed to increase public awareness of the traffic law concerning EMS ambulances and to enhance appropriate driving behavior, which, in turn, improves the efficiency of ambulance services.

Keywords: EMS ambulances, lights and sirens, road users, attitude and behavior

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Authors: Fuchun Li, Hong Xiao

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We propose a new early warning model for predicting financial stress events for a given future time. In this model, we examine whether credit conditions play an important role as a nonlinear propagator of shocks when predicting the likelihood of occurrence of financial stress events for a given future time. This propagation takes the form of a threshold regression in which a regime change occurs if credit conditions cross a critical threshold. Given the new early warning model for financial stress events, we evaluate the performance of this model and currently available alternatives, such as the model from signal extraction approach, and linear regression model. In-sample forecasting results indicate that the three types of models are useful tools for predicting financial stress events while none of them outperforms others across all criteria considered. The out-of-sample forecasting results suggest that the credit-regime switching model performs better than the two others across all criteria and all forecasting horizons considered.

Keywords: cut-off probability, early warning model, financial crisis, financial stress, regime-switching model, forecasting horizons

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Authors: H. Hotait, X. Chiementin, L. Rasolofondraibe

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This paper presents a continuous work to detect the abnormal state in the rolling bearing by studying the vibration signature analysis and calculation of the remaining useful life. To achieve these aims, two methods; the first method is the classification to detect the degradation state by the AOM-OPTICS (Acousto-Optic Modulator) method. The second one is the prediction of the degradation state using least-squares support vector regression and then compared with the linear degradation model. An experimental investigation on ball-bearing was conducted to see the effectiveness of the used method by applying the acquired vibration signals. The proposed model for predicting the state of bearing gives us accurate results with the experimental and numerical data.

Keywords: bearings, automatization, optimization, prognosis, classification, defect detection

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Authors: Ryan Dale B. Elnar

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This study developed a multidimensional need assessment scale for college students called The University of Mindanao Needs Assessment Scale (UMNAS). Although there are context-specific instruments measuring the needs of clinical and non-clinical samples, literature reveals no standardized scales to measure the needs of the college students thus a four-phase item development process was initiated to support its content validity. Comprising seven broad facets namely spiritual-moral, intrapersonal, socio-personal, psycho-emotional, cognitive, physical and sexual, a pyramid model of college needs was deconstructed through FGD sample to support the literature review. Using various construct validity procedures, the model was further tested using a total of 881 Filipino college samples. The result of the study revealed evidences of the reliability and validity of the UMNAS. The reliability indices range from .929-.933. Exploratory and confirmatory factor analyses revealed a one-factor-six-dimensional instrument to measure the needs of the college students. Using multivariate regression analysis, year level and course are found predictors of students’ needs. Content analysis attested the usefulness of the instrument to diagnose students’ personal and academic issues and concerns in conjunction with other measures. The norming process includes 1728 students from the different colleges of the University of Mindanao. Further validation is recommended to establish a national norm for the instrument.

Keywords: needs assessment scale, validity, factor analysis, college students

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Authors: Ahmad Zulfahmi Mohd Kamaruzaman, Mohd Ismail Ibrahim, Ariffin Marzuki Mokhtar, Maizun Mohd Zain, Saiful Nazri Satiman, Mohd Najib Majdi Yaacob

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Background: Aftermath any patient safety incidents, the involved healthcare providers possibly sustained second victim-related distress (second victim distress and reduced their professional efficacy), with subsequent negative work-related outcomes or vice versa cultivating resilience. This study aimed to investigate the factors affecting negative work-related outcomes and resilience, with the triad of support; colleague, supervisor, and institutional support as the hypothetical mediators. Methods: This was a cross sectional study recruiting a total of 733 healthcare providers from three tertiary care in Kelantan, Malaysia. Three steps of hierarchical linear regression were developed for each outcome; negative work-related outcomes and resilience. Then, four multiple mediator models of support triad were analyzed. Results: Second victim distress, professional efficacy, and the support triad contributed significantly for each regression model. In the pathway of professional efficacy on each negative work-related outcomes and resilience, colleague support partially mediated the relationship. As for second victim distress on negative work related outcomes, colleague and supervisor support were the partial mediator, and on resilience; all support triad also produced a similar effect. Conclusion: Second victim distress, professional efficacy, and the support triad influenced the relationship with the negative work-related outcomes and resilience. Support triad as the mediators ameliorated the effect in between and explained the urgency of having good support for recovery post encountering patient safety incidents.

Keywords: second victims, patient safety incidents, hierarchical linear regression, mediation, support

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Authors: Jasbir Arora, Indu Talwar, Daisy Sahni, Vidya Rattan

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Introduction: Age estimation is a crucial step to build the identity of a person, both in case of deceased and alive. In adults, age can be estimated on the basis of six regressive (Attrition, Secondary dentine, Dentine transparency, Root resorption, Cementum apposition and Periodontal Disease) changes in teeth qualitatively using scoring system and quantitatively by micrometric method. The present research was designed to establish the reliability of qualitative (method 1) and quantitative (method 2) of age estimation among North Indians and to compare the efficacy of these two methods. Method: 250 single-rooted extracted teeth (18-75 yrs.) were collected from Department of Oral Health Sciences, PGIMER, Chandigarh. Before extraction, periodontal score of each tooth was noted. Labiolingual sections were prepared and examined under light microscope for regressive changes. Each parameter was scored using Gustafson’s 0-3 point score system (qualitative), and total score was calculated. For quantitative method, each regressive change was measured quantitatively in form of 18 micrometric parameters under microscope with the help of measuring eyepiece. Age was estimated using linear and multiple regression analysis in Gustafson’s method and Kedici’s method respectively. Estimated age was compared with actual age on the basis of absolute mean error. Results: In pooled data, by Gustafson’s method, significant correlation (r= 0.8) was observed between total score and actual age. Total score generated an absolute mean error of ±7.8 years. Whereas, for Kedici’s method, a value of correlation coefficient of r=0.5 (p<0.01) was observed between all the eighteen micrometric parameters and known age. Using multiple regression equation, age was estimated, and an absolute mean error of age was found to be ±12.18 years. Conclusion: Gustafson’s (qualitative) method was found to be a better predictor for age estimation among North Indians.

Keywords: forensic odontology, age estimation, North India, teeth

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Authors: Areej Al-Khabbaz, Swapna Goerge, Majedah Abdul-Rasoul

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Introduction: The most prevalent periodontal disease among children is gingivitis, and it usually becomes more severe in adolescence. A number of intervention studies suggested that resolution of periodontal inflammation can improve metabolic control in patients diagnosed with diabetes mellitus. Aim: to assess the effect of non-surgical periodontal therapy on glycemic control of children diagnosed with diabetes mellitus. Method: Twenty-eight children diagnosed with diabetes mellitus were recruited with established diagnosis diabetes for at least 1 year. Informed consent and child assent form were obtained from children and parents prior to enrolment. The dental examination for the participants was performed on the same week directly following their annual medical assessment. All patients had their glycosylated hemoglobin (HbA1c%) test one week prior to their annual medical and dental visit and 3 months following non-surgical periodontal therapy. All patients received a comprehensive periodontal examination The periodontal assessment included clinical attachment loss, bleeding on probing, plaque score, plaque index and gingival index. All patients were referred for non-surgical periodontal therapy, which included oral hygiene instruction and motivation followed by supra-gingival and subg-ingival scaling using ultrasonic and hand instruments. Statistical Analysis: Data were entered and analyzed using the Statistical Package for Social Science software (SPSS, Chicago, USA), version 18. Statistical analysis of clinical findings was performed to detect differences between the two groups in term of periodontal findings and HbA1c%. Binary logistic regression analysis was performed in order to examine which factors were significant in multivariate analysis after adjusting for confounding between effects. The regression model used the dependent variable ‘Improved glycemic control’, and the independent variables entered in the model were plaque index, gingival index, bleeding %, plaque Statistical significance was set at p < 0.05. Result: A total of 28 children. The mean age of the participants was 13.3±1.92 years. The study participants were divided into two groups; Compliant group (received dental scaling) and non-complaints group (received oral hygiene instructions only). No statistical difference was found between compliant and non-compliant group in age, gender distribution, oral hygiene practice and the level of diabetes control. There was a significant difference between compliant and non-compliant group in term of improvement of HBa1c before and after periodontal therapy. Mean gingival index was the only significant variable associated with improved glycemic control level. In conclusion, this study has demonstrated that non-surgical mechanical periodontal therapy can improve HbA1c% control. The result of this study confirmed that children with diabetes mellitus who are compliant to dental care and have routine professional scaling may have better metabolic control compared to diabetic children who are erratic with dental care.

Keywords: children, diabetes, metabolic control, periodontal therapy

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Authors: Amornchai Challcharoenwattana, Chanathip Pharino

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Rising amount of MSW every day, maximizing material diversions from landfills via recycling is a prefer method to land dumping. Characteristic of Thai MSW is classified as 40 -60 per cent compostable wastes while potentially recyclable materials in waste streams are composed of plastics, papers, glasses, and metals. However, rate of material recovery from MSW, excluding composting or biogas generation, in Thailand is still low. Thailand’s recycling rate in 2010 was only 20.5 per cent. Central government as well as local governments in Thailand have tried to curb this problem by charging some of MSW management fees at the users. However, the fee is often too low to promote MSW minimization. The objective of this paper is to identify levels of willingness-to-pay (WTP) for MSW recycling in different social structures with expected outcome of sustainable MSW managements for different town settlements to maximize MSW recycling pertaining to each town’s potential. The method of eliciting WTP is a payment card. The questionnaire was deployed using online survey during December 2012. Responses were categorized into respondents living in Bangkok, living in other municipality areas, or outside municipality area. The responses were analysed using descriptive statistics, and multiple linear regression analysis to identify relationships and factors that could influence high or low WTP. During the survey period, there were 168 filled questionnaires from total 689 visits. However, only 96 questionnaires could be usable. Among respondents in the usable questionnaires, 36 respondents lived in within the boundary of Bangkok Metropolitan Administration while 45 respondents lived in the chartered areas that were classified as other municipality but not in BMA. Most of respondents were well-off as 75 respondents reported positive monthly cash flow (77.32%), 15 respondents reported neutral monthly cash flow (15.46%) while 7 respondent reported negative monthly cash flow (7.22%). For WTP data including WTP of 0 baht with valid responses, ranking from the highest means of WTP to the lowest WTP of respondents by geographical locations for good MSW management were Bangkok (196 baht/month), municipalities (154 baht/month), and non-urbanized towns (111 baht/month). In-depth analysis was conducted to analyse whether there are additional room for further increase of MSW management fees from the current payment that each correspondent is currently paying. The result from multiple-regression analysis suggested that the following factors could impacts the increase or decrease of WTP: incomes, age, and gender. Overall, the outcome of this study suggests that survey respondents are likely to support improvement of MSW treatments that are not solely relying on landfilling technique. Recommendations for further studies are to obtain larger sample sizes in order to improve statistical powers and to provide better accuracy of WTP study.

Keywords: MSW, willingness to pay, payment card, waste seperation

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Authors: Suryapeta Harini

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Road surface roughness is one of the essential aspects of the road's functional condition, indicating riding comfort in both the transverse and longitudinal directions. The government of India has made maintaining good surface evenness a prerequisite for all highway projects. Pavement distress data was collected with a Network Survey Vehicle (NSV) on a National Highway. It determines the smoothness and frictional qualities of the pavement surface, which are related to driving safety and ease. Based on the data obtained in the field, a regression equation was created with the IRI value and the visual distresses. The suggested system can use wireless acceleration sensors and GPS to gather vehicle status and location data, as well as calculate the international roughness index (IRI). Potholes, raveling, rut depth, cracked area, and repair work are all affected by pavement roughness, according to the current study. The study was carried out in one location. Data collected through using Bump integrator was used for the validation. The bump integrator (BI) obtained using deflection from the network survey vehicle was correlated with the distress parameter to establish an equation.

Keywords: roughness index, network survey vehicle, regression, correlation

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Authors: Odey Moses Ogah, Felix Terhemba Ikyereve

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The study was carried out to analyzed risks in financing agriculture by agricultural cooperatives in Benue State, Nigeria. The study made use of research questionnaires for data collection. A multistage sampling technique was used to select a sample of 210 respondents from 21 agricultural cooperatives. Both descriptive and inferential statistics were employed in data analysis. Loan defaulting (66.7%) and reduction in savings by members (51.4%) were the major causes of risks faced by agricultural cooperatives in financing agriculture in the study area. Other causes include adverse changes in commodity prices (48.6%), disaster (45.7%), among others. It was found that risks adversely influence the profitability and competition of agricultural cooperatives (82.9%). Multiple regression analysis results showed that the coefficient of multiple determinations was 0.67, implying that the explanatory variables included in the model accounted for 67% of the variation in the level of profitability of agricultural cooperatives. The number of loans, average amount of loan and the interest rate were significant and important determinants of profitability of the cooperatives. The majority of the respondents (88.6%) made use of loan guarantors as a strategy of managing loan default/no repayment. It was found that the majority (70%) of the respondents were faced with the challenge of lack of insurance cover. The study recommends that agricultural cooperative officials should be encouraged to undergo formal training and education to easily acquire administrative skills in the management of agricultural loans; Farmer's loan size should be increased and released on time to enable them to use it effectively. Policies that enhance insuring farm activities should be put in place to discourage farmers from risk aversion.

Keywords: agriculture, analysis, cooperative, finance, risks

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Authors: B. Varaprasad, C. Srinivasa Rao

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Hard turning has been explored as an alternative to the conventional one used for manufacture of Parts using tool steels. In the present study, the effects of cutting speed, feed rate and Depth of Cut (DOC) on cutting forces, specific cutting force, power and surface roughness in the hard turning are experimentally investigated. Experiments are carried out using mixed ceramic(Al2O3+TiC) cutting tool of corner radius 0.8mm, in turning operations on AISI H13 tool steel, heat treated to a hardness of 62 HRC. Based on Design of Experiments (DOE), a total of 20 tests are carried out. The range of each one of the three parameters is set at three different levels, viz, low, medium and high. The validity of the model is checked by Analysis of variance (ANOVA). Predicted models are derived from regression analysis. Comparison of experimental and predicted values of specific cutting force, power and surface roughness shows that good agreement has been achieved between them. Therefore, the developed model may be recommended to be used for predicting specific cutting force, power and surface roughness in hard turning of tool steel that is AISI H13 steel.

Keywords: hard turning, specific cutting force, power, surface roughness, AISI H13, mixed ceramic

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Authors: Raeed Alanazi

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Introduction: Nursing students have a crucial role to play in the inhibition of infectious diseases and, therefore, must be trained in infection control and prevention modules prior to entering clinical settings. Simulations have been found to have a positive impact on infection control skills and the use of standard precautions. Aim: The purpose of this study was to use the four sources of self-efficacy in explaining the level of clinical self-efficacy and adherence to infection control practices in Saudi nursing students during simulation practice. Method: A cross-sectional design with convenience sampling was used. This study was conducted in all Saudi nursing schools, with a total number of 197 students participated in this study. Three scales were used simulation self- efficacy Scale (SSES), the four sources of self-efficacy scale (SSES), and Compliance with Standard Precautions Scale (CSPS). Multiple linear regression was used to test the use of the four sources of self-efficacy (SSES) in explaining level of clinical self-efficacy and adherence to infection control in nursing students. Results: The vicarious experience subscale (p =.044) was statistically significant. The regression model indicated that for every one unit increase in vicarious experience (observation and reflection in simulation), the participants’ adherence to infection control increased by .13 units (β =.22, t = 2.03, p =.044). In addition, the regression model indicated that for every one unit increase in education level, the participants’ adherence to infection control increased by 1.82 units (beta=.34= 3.64, p <.001). Also, the mastery experience subscale (p <.001) and vicarious experience subscale (p = .020) were shared significant associations with clinical self-efficacy. Conclusion: The findings of this research support the idea that simulation-based learning can be a valuable teaching-learning method to help nursing students develop clinical competence, which is essential in providing quality and safe nursing care.

Keywords: simulation-based learning, clinical self-efficacy, infection control, nursing students

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