Search results for: panel data regression

Authors: S. J. Yune, S. Y. Lee, S. J. Im, B. S. Kam, S. Y. Baek

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This study explored whether academic emotion, major satisfaction, and learning flow are associated with academic achievement in medical school. We know that emotion and affective factors are important factors in students' learning and performance. Emotion has taken the stage in much of contemporary educational psychology literature, no longer relegated to secondary status behind traditionally studied cognitive constructs. Medical school students (n=164) completed academic emotion, major satisfaction, and learning flow online survey. Academic performance was operationalized as students' average grade on two semester exams. For data analysis, correlation analysis, multiple regression analysis, hierarchical multiple regression analyses and ANOVA were conducted. The results largely confirmed the hypothesized relations among academic emotion, major satisfaction, learning flow and academic achievement. Positive academic emotion had a correlation with academic achievement (β=.191). Positive emotion had 8.5% explanatory power for academic achievement. Especially, sense of accomplishment had a significant impact on learning performance (β=.265). On the other hand, negative emotion, major satisfaction, and learning flow did not affect academic performance. Also, there were differences in sense of great (F=5.446, p=.001) and interest (F=2.78, p=.043) among positive emotion, boredom (F=3.55, p=.016), anger (F=4.346, p=.006), and petulance (F=3.779, p=.012) among negative emotion by grade. This study suggested that medical students' positive emotion was an important contributor to their academic achievement. At the same time, it is important to consider that some negative emotions can act to increase one’s motivation. Of particular importance is the notion that instructors can and should create learning environment that foster positive emotion for students. In doing so, instructors improve their chances of positively impacting students’ achievement emotions, as well as their subsequent motivation, learning, and performance. This result had an implication for medical educators striving to understand the personal emotional factors that influence learning and performance in medical training.

Keywords: academic achievement, learning emotion, learning flow, major satisfaction

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Authors: S. A. Salau, I. F. Ayanda, I. Afe, M. O. Adesina, N. B. Nofiu

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Food insecurity is still a critical challenge among rural and urban households in Nigeria. The country’s food insecurity situation became more pronounced due to frequent conflict between pastoralist and crop farmers. Thus, this study assesses pastoralist-crop farmers’ conflict and food security of farming households in Kwara state, Nigeria. The specific objectives are to measure the food security status of the respondents, quantify pastoralist- crop farmers’ conflict, determine the effect of pastoralist- crop farmers conflict on food security and describe the effective coping strategies adopted by the respondents to reduce the effect of food insecurity. A combination of purposive and simple random sampling techniques will be used to select 250 farming households for the study. The analytical tools include descriptive statistics, Likert-scale, logistic regression, and food security index. Using the food security index approach, the percentage of households that were food secure and insecure will be known. Pastoralist- crop farmers’ conflict will be measured empirically by quantifying loses due to the conflict. The logistic regression will indicate if pastoralist- crop farmers’ conflict is a critical determinant of food security among farming households in the study area. The coping strategies employed by the respondents in cushioning the effects of food insecurity will also be revealed. Empirical studies on the effect of pastoralist- crop farmers’ conflict on food security are rare in the literature. This study will quantify conflict and reveal the direction as well as the extent of the relationship between conflict and food security. It could contribute to the identification and formulation of strategies for the minimization of conflict among pastoralist and crop farmers in an attempt to reduce food insecurity. Moreover, this study could serve as valuable reference material for future researches and open up new areas for further researches.

Keywords: agriculture, conflict, coping strategies, food security, logistic regression

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Data that is high in volume, velocity, veracity and comes from a variety of sources is usually generated in all sectors including the government sector. Globally public administrations are pursuing (big) data as new technology and trying to adopt a data-centric architecture for hosting and sharing data. Properly executed, big data and data analytics in the government (big) data ecosystem can be led to data-driven government and have a direct impact on the way policymakers work and citizens interact with governments. In this research paper, we conduct a systematic literature review. The main aims of this paper are to highlight essential aspects of the government (big) data ecosystem and to explore the most critical socio-technical factors that contribute to the successful implementation of government (big) data ecosystem. The essential aspects of government (big) data ecosystem include definition, data types, data lifecycle models, and actors and their roles. We also discuss the potential impact of (big) data in public administration and gaps in the government data ecosystems literature. As this is a new topic, we did not find specific articles on government (big) data ecosystem and therefore focused our research on various relevant areas like humanitarian data, open government data, scientific research data, industry data, etc.

Keywords: applications of big data, big data, big data types. big data ecosystem, critical success factors, data-driven government, egovernment, gaps in data ecosystems, government (big) data, literature review, public administration, systematic review

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Authors: Anli Du Preez, James Bekker

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Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

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Authors: Yu-Chien Huang, Shu-Chen Yang

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

Keywords: inferiority, nonattachment, parenting style, psychology

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Authors: Farnoush Haghanipour

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Recent research studies relation between coping strategies with stress and mental health situation in flying addicted family of self-introducer and private, Units of Guilan province. For this purpose 251 family (parent, spouse), that referred to private and self-introducer centers to break out of drug are selected in random sampling form. Research method was cross sectional-descriptive and purpose of research was fixing of between kinds of coping strategies with stress and mental health condition with attention to demographic variables. Therefore to collection of information, coping strategies questionnaire (CSQ) and mental health questionnaire (GHQ) was used and finally data analyzed by descriptive statistical methods (average, standard deviation) and inferential statistical correlation coefficient and regression. Study of correlation coefficient between mental healths with problem focused emotional focused and detachment strategies in level more than %99 is confirmed. Also mental health with avoidant focused hasn't correlation in other words relation is between mental health with problem focused strategies (r= 0/34) and emotional focused with mental health (r=0.52) and detachment with mental health (r= 0.18) in meaningful level 0.05. And also relation is between emotional focused strategies and mental health (r= 0.034) that is meaningless in Alpha 0.05. Also relation between problem processed coping strategies and mental health situation with attention to demographic variable is meaningful and relation level verified in confidence level more than 0.99. And result of anticipation equation regression statistical test has most a have in problem focused coping strategy, mental health, but relation of the avoidant emotional, detachment strategy with mental health was meaningless with attention to demographic variables.

Keywords: stress, coping strategy with stress, mental health, self introducer and private

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Authors: Ploychompoo Kittikunchotiwut

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This study examines the relationships between human resource practices, knowledge management capacity, and innovation performance. The data were collected by using a questionnaire from 241 firms in the hotels in Thailand. The hypothesized relationships among variables are examined by using ordinary least square (OLS) regression analysis. The findings show that human resource practices have a positive effect on knowledge management capacity. Besides, knowledge management capacity was found to positively affect innovation performance. Finally, the limitations of the study and directions for future research are discussed.

Keywords: human resource practices, knowledge management capacity, innovation performance

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Authors: Mohammad Azam

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The purpose of this study is to investigate risk and real excess portfolio returns using inflation adjusted risk-free rates, a measuring technique that focuses on the momentum augmented Fama-French six-factor model and use monthly data from 1994 to 2022. With the exception of profitability, the data show that market, size, value, momentum, and investment factors are all strongly associated to excess portfolio stock returns using ordinary lease square regression technique. According to the Gibbons, Ross, and Shanken test, the momentum augmented Fama-French six-factor model outperforms the market. This technique discovery may be utilised by academics and professionals to acquire an in-depth knowledge of the Pakistan Stock Exchange across a broad stock pattern for investing decisions and portfolio construction.

Keywords: real excess portfolio returns, momentum augmented fama & french five-factor model, GRS-test, pakistan stock exchange

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Authors: Arpita Saha, Satish Chandra, Indrajit Ghosh

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Delay implicates the time loss of a traveler while crossing an intersection. Efficiency of traffic operation at signalized intersections is assessed in terms of delay caused to an individual vehicle. Highway Capacity Manual (HCM) method and Webster’s method are the most widely used in India for delay estimation purpose. However, in India, traffic is highly heterogeneous in nature with extremely poor lane discipline. Therefore, to explore best delay estimation technique for Indian condition, a comparison was made. In this study, seven signalized intersections from three different cities where chosen. Data was collected for both during morning and evening peak hours. Only under saturated cycles were considered for this study. Delay was estimated based on the field data. With the help of Simpson’s 1/3 rd rule, delay of under saturated cycles was estimated by measuring the area under the curve of queue length and cycle time. Moreover, the field observed delay was compared with the delay estimated using HCM, Webster, Probabilistic, Taylor’s expansion and Regression methods. The drawbacks of the existing delay estimation methods to be use in Indian heterogeneous traffic conditions were figured out, and best method was proposed. It was observed that direct estimation of delay using field measured data is more accurate than existing conventional and modified methods.

Keywords: delay estimation technique, field delay, heterogeneous traffic, signalised intersection

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Authors: V. Howard, R. Maguire, S. Corrigan

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Background: Type 1 Diabetes (T1D) is a chronic autoimmune disease, typically diagnosed in childhood. T1D puts an enormous strain on families; controlling blood-glucose in children is difficult and the consequences of poor control for patient health are significant. Successful illness management and better health outcomes can be dependent on quality of caregiving. On diagnosis, parent-caregivers face a steep learning curve as T1D care requires a significant level of knowledge to inform complex decision making throughout the day. The majority of illness management is carried out in the home setting, independent of clinical health providers. Parent-caregivers vary in their level of knowledge and their level of engagement in applying this knowledge in the practice of illness management. Enabling researchers to quantify these aspects of the caregiver experience is key to identifying targets for psychosocial support interventions, which are desirable for reducing stress and anxiety in this highly burdened cohort, and supporting better health outcomes in children. Currently, there are limited tools available that are designed to capture this information. Where tools do exist, they are not comprehensive and do not adequately capture the lived experience. Objectives: Development of quantitative tools, informed by lived experience, to enable researchers gather data on parent-caregiver knowledge and engagement, which accurately represents the experience/cohort and enables exploration of questions that are of real-world value to the cohort themselves. Methods: This research employed an engaged approach to address the problem of quantifying two key aspects of caregiver diabetes management: Knowledge and engagement. The research process was multi-staged and iterative. Stage 1: Working from a constructivist standpoint, literature was reviewed to identify relevant questionnaires, scales and single-item measures of T1D caregiver knowledge and engagement, and harvest candidate questionnaire items. Stage 2: Aggregated findings from the review were circulated among a PPI (patient and public involvement) expert panel of caregivers (n=6), for discussion and feedback. Stage 3: In collaboration with the expert panel, data were interpreted through the lens of lived experience to create a long-list of candidate items for novel questionnaires. Items were categorized as either ‘knowledge’ or ‘engagement’. Stage 4: A Delphi-method process (iterative surveys) was used to prioritize question items and generate novel questions that further captured the lived experience. Stage 5: Both questionnaires were piloted to refine wording of text to increase accessibility and limit socially desirable responding. Stage 6: Tools were piloted using an online survey that was deployed using an online peer-support group for caregivers for Juveniles with T1D. Ongoing Research: 123 parent-caregivers completed the survey. Data analysis is ongoing to establish face and content validity qualitatively and through exploratory factor analysis. Reliability will be established using an alternative-form method and Cronbach’s alpha will assess internal consistency. Work will be completed by early 2024. Conclusion: These tools will enable researchers to gain deeper insights into caregiving practices among parents of juveniles with T1D. Development was driven by lived experience, illustrating the value of engaged research at all levels of the research process.

Keywords: caregiving, engaged research, juvenile type 1 diabetes, quantified engagement and knowledge

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Authors: Sara Hasani

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This research focuses on natural sudden onset disasters characterised as ‘occurring with little or no warning and often cause excessive injuries far surpassing the national response capacities’. Based on the panel analysis of the historic record of 4,252 natural onset disasters between 1980 to 2015, a predictive method was developed to predict the human impact of the disaster (fatality, injured, homeless) with less than 3% of errors. The geographical dispersion of the disasters includes every country where the data were available and cross-examined from various humanitarian sources. The records were then filtered into 4252 records of the disasters where the five predictive variables (disaster type, HDI, DRI, population, and population density) were clearly stated. The procedure was designed based on a combination of pattern recognition techniques and rule-based clustering for prediction and discrimination analysis to validate the results further. The result indicates that there is a relationship between the disaster human impact and the five socio-economic characteristics of the affected country mentioned above. As a result, a framework was put forward, which could predict the disaster’s human impact based on their severity rank in the early hours of disaster strike. The predictions in this model were outlined in two worst and best-case scenarios, which respectively inform the lower range and higher range of the prediction. A necessity to develop the predictive framework can be highlighted by noticing that despite the existing research in literature, a framework for predicting the human impact and estimating the needs at the time of the disaster is yet to be developed. This can further be used to allocate the resources at the response phase of the disaster where the data is scarce.

Keywords: disaster management, natural disaster, pattern recognition, prediction

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Authors: Syeda Faiza Gardazi, Syed Ahsan Ali Gardazi, Ajmal Waheed

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The trend of overtime is increasing among workers due to more pressure to perform workloads, job insecurity, and financial issues. Overtime work affects the work-life balance conflict negatively as well positively. Work-life balance conflict has become an important issue as traditional work and family roles have changed. The purpose of the current research was to study the impact of overtime work on work-life balance conflict along with the moderating role of job satisfaction. For this purpose, data is collected from the employees working in different public and private sectors of Pakistan using simple random sampling technique. Descriptive statistics was used for data presentation and analysis. Correlation and regression analysis were used to test four research hypotheses proposed on the basis of research framework. The findings led to the acceptance of four hypotheses. The results show that high working hours and overtime in general lead to high work-life balance conflict. Moreover, job satisfaction moderates the relationship between overtime work and work-life balance conflict.

Keywords: family to work conflict, overtime work, work to family conflict, work-life balance conflict

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Authors: John Paul Q. Tomas, Mark Wilson L. de los Reyes, Kirsten Joyce P. Vasquez

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The most frequent type of fracture is a wrist fracture, which often makes it difficult for medical professionals to find and locate. In this study, fractures in wrist x-ray pictures were located and identified using deep learning and computer vision. The researchers used image filtering, masking, morphological operations, and data augmentation for the image preprocessing and trained the RetinaNet and Faster R-CNN models with ResNet50 backbones and Adam optimizers separately for each image filtering technique and projection. The RetinaNet model with Anisotropic Diffusion Smoothing filter trained with 50 epochs has obtained the greatest accuracy of 99.14%, precision of 100%, sensitivity/recall of 98.41%, specificity of 100%, and an IoU score of 56.44% for the Posteroanterior projection utilizing augmented data. For the Lateral projection using augmented data, the RetinaNet model with an Anisotropic Diffusion filter trained with 50 epochs has produced the highest accuracy of 98.40%, precision of 98.36%, sensitivity/recall of 98.36%, specificity of 98.43%, and an IoU score of 58.69%. When comparing the test results of the different individual projections, models, and image filtering techniques, the Anisotropic Diffusion filter trained with 50 epochs has produced the best classification and regression scores for both projections.

Keywords: Artificial Intelligence, Computer Vision, Wrist Fracture, Deep Learning

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Authors: Somtop Keawchuer

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The purpose of the research is to study the level of social responsibility among the undergraduate students of the faculty of Management Science, Suan Sunandha Rajabhat University. The research also studies the factors affecting social responsibility of the undergraduate students. The research methodology applied a self-administered questionnaire as a quantitative method. A convenience sampling was used to distribute the questionnaire. Finally, 350 questionnaires were received for data analysis. Data were analyzed by using descriptive statistics including percentage, mean, standard deviation, and inferential statistics including regression analysis for hypothesis testing. The results indicated that the level of social responsibility of the students was at a good level. In addition, internal and external factors were related to social responsibility of the undergraduate students with the statistical significance level of 0.05.

Keywords: internal and external factors, social responsibility, Suan Sunandha Rajabhat University, undergraduate students

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Authors: Ahmad A. Kader

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In the principles of Microeconomics course taught during the Fall Semester 2019, 158out of 179 students participated in the completion of two questionnaires and a survey describing their demographic and academic profiles. The two questionnaires include the 29 items of the Rotter Locus of Control Scale and the 52 items of the Schraw andDennisonMetacognitive Awareness Scale. The 52 items consist of 17 items describing knowledge of cognition and 37 items describing the regulation of cognition. The paper is intended to show the combined influence of locus of control, metacognitive knowledge, and metacognitive regulation on student performance. The survey covers variables that have been tested and recognized in economic education literature, which include GPA, gender, age, course level, race, student classification, whether the course was required or elective, employments, whether a high school economic course was taken, and attendance. Regression results show that of the economic education variables, GPA, classification, whether the course was required or elective, and attendance are the only significant variables in their influence on student grade. Of the educational psychology variables, the regression results show that the locus of control variable has a negative and significant effect, while the metacognitive knowledge variable has a positive and significant effect on student grade. Also, the adjusted R square value increased markedly with the addition of the locus of control, metacognitive knowledge, and metacognitive regulation variables to the regression equation. The t test results also show that students who are internally oriented and are high on the metacognitive knowledge scale significantly outperform students who are externally oriented and are low on the metacognitive knowledge scale. The implication of these results for educators is discussed in the paper.

Keywords: locus of control, metacognitive knowledge, metacognitive regulation, student performance, economic education

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Authors: Praniil Nagaraj

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This paper proposes a method to collect homeless data using crowdsourcing and presents an approach to analyze the data, demonstrating its potential to strengthen existing and future policies aimed at promoting socio-economic equilibrium. This paper's contributions can be categorized into three main areas. Firstly, a unique method for collecting homeless data is introduced, utilizing a user-friendly smartphone app (currently available for Android). The app enables the general public to quickly record information about homeless individuals, including the number of people and details about their living conditions. The collected data, including date, time, and location, is anonymized and securely transmitted to the cloud. It is anticipated that an increasing number of users motivated to contribute to society will adopt the app, thus expanding the data collection efforts. Duplicate data is addressed through simple classification methods, and historical data is utilized to fill in missing information. The second contribution of this paper is the description of data analysis techniques applied to the collected data. By combining this new data with existing information, statistical regression analysis is employed to gain insights into various aspects, such as distinguishing between unsheltered and sheltered homeless populations, as well as examining their correlation with factors like unemployment rates, housing affordability, and labor demand. Initial data is collected in San Francisco, while pre-existing information is drawn from three cities: San Francisco, New York City, and Washington D.C., facilitating the conduction of simulations. The third contribution focuses on demonstrating the practical implications of the data processing results. The challenges faced by key stakeholders, including charitable organizations and local city governments, are taken into consideration. Two case studies are presented as examples. The first case study explores improving the efficiency of food and necessities distribution, as well as medical assistance, driven by charitable organizations. The second case study examines the correlation between micro-geographic budget expenditure by local city governments and homeless information to justify budget allocation and expenditures. The ultimate objective of this endeavor is to enable the continuous enhancement of the quality of life for the underprivileged. It is hoped that through increased crowdsourcing of data from the public, the Generosity Curve and the Need Curve will intersect, leading to a better world for all.

Keywords: crowdsourcing, homelessness, socio-economic policies, statistical analysis

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Authors: D. S. Gomes, A. T. Silva

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Analysis of the uncertainty quantification related to nuclear safety margins applied to the nuclear reactor is an important concept to prevent future radioactive accidents. The nuclear fuel performance code may involve the tolerance level determined by traditional deterministic models producing acceptable results at burn cycles under 62 GWd/MTU. The behavior of nuclear fuel can simulate applying a series of material properties under irradiation and physics models to calculate the safety limits. In this study, theoretical predictions of nuclear fuel failure under transient conditions investigate extended radiation cycles at 75 GWd/MTU, considering the behavior of fuel rods in light-water reactors under reactivity accident conditions. The fuel pellet can melt due to the quick increase of reactivity during a transient. Large power excursions in the reactor are the subject of interest bringing to a treatment that is known as the Fuchs-Hansen model. The point kinetic neutron equations show similar characteristics of non-linear differential equations. In this investigation, the multivariate logistic regression is employed to a probabilistic forecast of fuel failure. A comparison of computational simulation and experimental results was acceptable. The experiments carried out use the pre-irradiated fuels rods subjected to a rapid energy pulse which exhibits the same behavior during a nuclear accident. The propagation of uncertainty utilizes the Wilk's formulation. The variables chosen as essential to failure prediction were the fuel burnup, the applied peak power, the pulse width, the oxidation layer thickness, and the cladding type.

Keywords: logistic regression, reactivity-initiated accident, safety margins, uncertainty propagation

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Authors: Vijay Pal Singh, Yogesh Chandra Kotiyal

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Structures are a combination of various load carrying members which transfer the loads to the foundation from the superstructure safely. At the design stage, the loading of the structure is defined and appropriate material choices are made based upon their properties, mainly related to strength. The strength of materials kept on reducing with time because of many factors like environmental exposure and deformation caused by unpredictable external loads. Hence, to predict the strength of materials used in structures, various techniques are used. Among these techniques, Non-Destructive Techniques (NDT) are the one that can be used to predict the strength without damaging the structure. In the present study, the compressive strength of concrete has been predicted using Artificial Neural Network (ANN). The predicted strength was compared with the experimentally obtained actual compressive strength of concrete and equations were developed for different models. A good co-relation has been obtained between the predicted strength by these models and experimental values. Further, the co-relation has been developed using two NDT techniques for prediction of strength by regression analysis. It was found that the percentage error has been reduced between the predicted strength by using combined techniques in place of single techniques.

Keywords: rebound, ultra-sonic pulse, penetration, ANN, NDT, regression

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Authors: Taoufik Benchelha, Toufik Remmal, Rachid El Hamdouni, Hamou Mansouri, Houssein Ejjaouani, Halima Jounaid, Said Benchelha

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During the earthworks for the construction of Marrakech-Agadir highway in southern Morocco, which crosses mountainous areas of the High Western Atlas, the main problem faced is the stability of the slopes. Indeed, the use of explosives as a means of excavation associated with the geological structure of the terrain encountered can trigger major ruptures and cause damage which depends on the intrinsic characteristics of the rock mass. The study consists of a geological and geotechnical analysis of several unstable zones located along the route, mobilizing millions of cubic meters of rock, with deduction of the parameters influencing slope stability. From this analysis, a predictive model for rock mass stability is carried out, based on a statistic method of logistic regression, in order to predict the geomechanical behavior of the rock slopes constrained by earthworks.

Keywords: explosive, logistic regression, rock mass, slope stability

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Authors: M. V. Shivaani, P. K. Jain, Surendra S. Yadav

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Risk management has been gaining extensive focus from international organizations like Committee of Sponsoring Organizations and Financial Stability Board, and, the foundation of such an effective and efficient risk management system lies in a strong risk governance structure. In view of this, an attempt (perhaps a first of its kind) has been made to develop a risk governance index, which could be used as proxy for quality of risk governance structures. The index (normative framework) is based on eleven variables, namely, size of board, board diversity in terms of gender, proportion of executive directors, executive/non-executive status of chairperson, proportion of independent directors, CEO duality, chief risk officer (CRO), risk management committee, mandatory committees, voluntary committees and existence/non-existence of whistle blower policy. These variables are scored on a scale of 1 to 5 with the exception of the variables, namely, status of chairperson and CEO duality (which have been scored on a dichotomous scale with the score of 3 or 5). In case there is a legal/statutory requirement in respect of above-mentioned variables and there is a non-compliance with such requirement a score of one has been envisaged. Though there is no legal requirement, for the larger part of study, in context of CRO, risk management committee and whistle blower policy, still a score of 1 has been assigned in the event of their non-existence. Recognizing the importance of these variables in context of risk governance structure and the fact that the study basically focuses on risk governance, the absence of these variables has been equated to non-compliance with a legal/statutory requirement. Therefore, based on this the minimum score is 15 and the maximum possible is 55. In addition, an attempt has been made to explore the determinants of this index. For this purpose, the sample consists of non-financial companies (429) that constitute S&P CNX500 index. The study covers a 10 years period from April 1, 2005 to March 31, 2015. Given the panel nature of data, Hausman test was applied, and it suggested that fixed effects regression would be appropriate. The results indicate that age and size of firms have significant positive impact on its risk governance structures. Further, post-recession period (2009-2015) has witnessed significant improvement in quality of governance structures. In contrast, profitability (positive relationship), leverage (negative relationship) and growth (negative relationship) do not have significant impact on quality of risk governance structures. The value of rho indicates that about 77.74% variation in risk governance structures is due to firm specific factors. Given the fact that each firm is unique in terms of its risk exposure, risk culture, risk appetite, and risk tolerance levels, it appears reasonable to assume that the specific conditions and circumstances that a company is beset with, could be the biggest determinants of its risk governance structures. Given the recommendations put forth in the paper (particularly for regulators and companies), the study is expected to be of immense utility in an important yet neglected aspect of risk management.

Keywords: corporate governance, ERM, risk governance, risk management

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Authors: Hatim Bastawi

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Three varieties of potatoes, namely Agria, Alpha and Diamant were evaluated for their suitability for industrial production of French fries. The evaluation was under taken after testing quality parameters of specific gravity, dry matter, peeling ratio, and defect after frying and panel test. The variety Agria ranked the best followed by Alpha with regard to the parameters tested. On the other hand, Diamant showed significantly higher defect percentage than the other cultivars. Also, it was significantly judged of low acceptance by panelists.

Keywords: cultivars, crisps, French fries

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Authors: S. M. Gupta, Vanita Aggarwal, Som Nath Sachdeva

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The work reported through this paper is an experimental work conducted on High Performance Concrete (HPC) with super plasticizer with the aim to develop some models suitable for prediction of compressive strength of HPC mixes. In this study, the effect of varying proportions of fly ash (0% to 50% at 10% increment) on compressive strength of high performance concrete has been evaluated. The mix designs studied were M30, M40 and M50 to compare the effect of fly ash addition on the properties of these concrete mixes. In all eighteen concrete mixes have been designed, three as conventional concretes for three grades under discussion and fifteen as HPC with fly ash with varying percentages of fly ash. The concrete mix designing has been done in accordance with Indian standard recommended guidelines i.e. IS: 10262. All the concrete mixes have been studied in terms of compressive strength at 7 days, 28 days, 90 days and 365 days. All the materials used have been kept same throughout the study to get a perfect comparison of values of results. The models for compressive strength prediction have been developed using Linear Regression method (LR), Artificial Neural Network (ANN) and Leave One Out Validation (LOOV) methods.

Keywords: high performance concrete, fly ash, concrete mixes, compressive strength, strength prediction models, linear regression, ANN

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Authors: Annapureddy Srikant Reddy, Atthanti Mahendra, Samala Chinni Krishna, N. Neelima

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In our present world, we are generating a lot of data and we, need a specific device to store all these data. Generally, we store data in pen drives, hard drives, etc. Sometimes we may loss the data due to the corruption of devices. To overcome all these issues, we implemented a cloud space for storing the data, and it provides more security to the data. We can access the data with just using the internet from anywhere in the world. We implemented all these with the java using Net beans IDE. Once user uploads the data, he does not have any rights to change the data. Users uploaded files are stored in the cloud with the file name as system time and the directory will be created with some random words. Cloud accepts the data only if the size of the file is less than 2MB.

Keywords: cloud space, AES, FTP, NetBeans IDE

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Authors: Kaycee L. Bills

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Adolescents and youth who are members of a minority group are more likely to experience higher rates of bullying in comparison to other student demographics. Specifically, adolescents with intellectual disabilities are a minority population that is more susceptible to experience unfair treatment in social settings. This study employs the 2015 Wave of the National Crime Victimization Survey – School Crime Supplement (NCVS/SCS) longitudinal dataset to explore bullying rates experienced among adolescents with intellectual disabilities. This study uses chi-square testing and a logistic regression to analyze if having a disability influences the likelihood of being bullied in comparison to other student demographics. Results of the chi-square testing and the logistic regression indicate that adolescent students who were identified as having a disability were approximately four times more likely to experience higher bullying rates in comparison to all other majority and minority student populations. Thus, it means having a disability resulted in higher bullying rates in comparison to all student groups.

Keywords: disability, bullying, social work, school bullying

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Authors: Younis Jabarzadeh, Rahim Sarvari, Negar Ahmadi Alghalandis

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Entrepreneurship at both individual and organizational level is one of the most driving forces in economic development and leads to growth and competition, job generation and social development. Especially in developing countries, the role of entrepreneurship in economic and social prosperity is more emphasized. But the effect of global economic development on the environment is undeniable, especially in negative ways, and there is a need to rethink current business models and the way entrepreneurs act to introduce new businesses to address and embed environmental issues in order to achieve sustainable development. In this paper, green or sustainable entrepreneurship is addressed in Iran to identify challenges and barriers entrepreneurs in the economic and social sectors face in developing green business solutions. Sustainable or green entrepreneurship has been gaining interest among scholars in recent years and addressing its challenges and barriers need much more attention to fill the gap in the literature and facilitate the way those entrepreneurs are pursuing. This research comprised of two main phases: qualitative and quantitative. At qualitative phase, after a thorough literature review, fuzzy Delphi method is utilized to verify those challenges and barriers by gathering a panel of experts and surveying them. In this phase, several other contextually related factors were added to the list of identified barriers and challenges mentioned in the literature. Then, at the quantitative phase, Interpretive Structural Modeling is applied to construct a network of interactions among those barriers identified at the previous phase. Again, a panel of subject matter experts comprised of academic and industry experts was surveyed. The results of this study can be used by policymakers in both the public and industry sector, to introduce more systematic solutions to eliminate those barriers and help entrepreneurs overcome challenges of sustainable entrepreneurship. It also contributes to the literature as the first research in this type which deals with the barriers of sustainable entrepreneurship and explores their interaction.

Keywords: green entrepreneurship, barriers, fuzzy Delphi method, interpretive structural modeling

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Authors: Mohiuddin Ahsanul Kabir Chowdhury, Ahmed Ehsanur Rahman, Nazia Binte Ali, Abdullah Nurus Salam Khan, Afrin Iqbal, Mohammad Mehedi Hasan, Salma Morium, Afsana Bhuiyan, Shams El Arifeen

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Violence against women has been treated as a global epidemic which is as fatal as any serious disease or accidents. Like many other low-income countries it is also common in Bangladesh. In spite of existence of a few documented evidences in some other countries, in Bangladesh, domestic violence against women (DVAW) is not considered as a factor for malnutrition in children yet. Hence, the aim of the study was to investigate the association between DVAW and the nutritional status of their under-5 children in the context of slum areas of Chittagong, Bangladesh. A Cross-sectional survey was conducted among 87 women of reproductive age having at least one child under-5 years of age and staying with husband for at least last 1 year in selected slums under Chittagong City Corporation area. Data collection tools were structured questionnaire for the study participants and mid-upper arm circumference (MUAC) to measure the nutritional status of the under-5 children. The data underwent descriptive and regression analysis. Out of 87 respondents, 50 (57.5%) reported to suffer from domestic violence by their husband during last one year. Physical violence was found to be significantly associated with age (p=0.02), age at marriage (p=0.043), wealth score (p=0.000), and with knowledge regarding law (p=0.017). According to the measurement of mid-upper arm circumference (MUAC) 21% children were suffering from severe acute malnutrition (SAM) and the same percentage of children were suffering from moderate acute malnutrition (MAM). However, unadjusted odds ratio suggested that there was negative association with domestic violence and nutritional status. But, the logistic regression confounding for other variable showed significant association with total family income (p=0.006), wealth score (p=0.031), age at marriage (p=0.029) and number of child (p=0.006). Domestic violence against women and under nutrition of the children, both are highly prevalent in Bangladesh. More extensive research should be performed to identify the factors contributing to the high prevalence of domestic violence and malnutrition in urban slums of Bangladesh. Household-based intervention is needed to limit this burning problem. In a nutshell, effective community participation, education and counseling are essential to create awareness among the community.

Keywords: Bangladesh, cross sectional survey, domestic violence against women, nutritional status, under-5 children, urban slums

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Authors: Ali Ashraf, Ghazaleh Aghaee, Sedigheh Samimian, Mohaya Farzin

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Objectives: Previous studies have indicated the positive effect of physical activity and sports on different aspects of health, such as muscle endurance and sleep cycle. However, in university students, particularly medical students, who have limited time and a stressful lifestyle, there have been limited studies exploring this matter with proven statistical results. In this regard, this study aims to find out how regular physical activity can influence the academic performance of medical students during their internship period. Methods: This was a descriptive-analytical study. Overall, 160 medical students (including 80 women and 88 men) voluntarily participated in the study. The Baecke Physical Activity Questionnaire was applied to determine the student’s physical activity levels. The student's academic performance was determined based on their total average academic scores. The data were analyzed in SPSS version 16 software using the independent t-test, Pearson correlation, and linear regression. Results: The average age of the students was 26.0±1.5 years. Eighty-eight students (52.4%) were male, and 142 (84.5%) were single. The student's mean total average academic score was 16.2±1.2, and their average physical activity score was 8.3±1.1. The student's average academic score was not associated with their gender (P=0.427), marital status (P=0.645), and age (P=0.320). However, married students had a significantly lower physical activity level compared to single students (P=0.020). The results indicated a significant positive correlation between student's physical activity levels and average academic scores (r=+0.410 and P<0.001). This correlation was independent of the student’s age, gender, and marital status based on the regression analysis. Conclusion: The results of the current study suggested that the physical activity level in medical students was low to moderate in most cases, and there was a significant direct relationship between student’s physical activity level and academic performance, independent of age, gender, and marital status.

Keywords: exercise, education, physical activity, academic performance

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Authors: Thilini Hathurusinghe, Uthpalie Siriwardhana, W. M. Ediri Arachchi, Ranga Thudugala, Indeewari Herath, Gayani Senanayake

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The foramen magnum is more prone to protect than other skeletal remains during high impact and severe disruptive injuries. Therefore, it is worthwhile to explore whether these measurements can be used to determine the human gender which is vital in forensic and anthropological studies. The idea was to find out the ability to use quantitative measurements of foramen magnum as an anatomical indicator for human gender estimation and to evaluate the gender-dependent variations of foramen magnum using quantitative measurements. Randomly selected 113 subjects who underwent CT head scans at Sri Jayawardhanapura General Hospital of Sri Lanka within a period of six months, were included in the study. The sample contained 58 males (48.76 ± 14.7 years old) and 55 females (47.04 ±15.9 years old). Maximum length of the foramen magnum (LFM), maximum width of the foramen magnum (WFM), minimum distance between occipital condyles (MnD) and maximum interior distance between occipital condyles (MxID) were measured. Further, AreaT and AreaR were also calculated. The gender was estimated using binomial logistic regression. The mean values of all explanatory variables (LFM, WFM, MnD, MxID, AreaT, and AreaR) were greater among male than female. All explanatory variables except MnD (p=0.669) were statistically significant (p < 0.05). Significant bivariate correlations were demonstrated by AreaT and AreaR with the explanatory variables. The results evidenced that WFM and MxID were the best measurements in predicting gender according to binomial logistic regression. The estimated model was: log (p/1-p) =10.391-0.136×MxID-0.231×WFM, where p is the probability of being a female. The classification accuracy given by the above model was 65.5%. The quantitative measurements of foramen magnum can be used as a reliable anatomical marker for human gender estimation in the Sri Lankan context.

Keywords: foramen magnum, forensic and anthropological studies, gender estimation, logistic regression

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Authors: Chandra Shekhar Prasad, Ludek Pesek Prasad

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In the present day fan blade of aero engine, turboprop propellers, gas turbine or steam turbine low-pressure blades are getting bigger, lighter and thus, become more flexible. Therefore, flutter, forced blade response and vibration related failure of the high aspect ratio blade are of main concern for the designers, thus need to be address properly in order to achieve successful component design. At the preliminary design stage large number of design iteration is need to achieve the utter free safe design. Most of the numerical method used for aeroelastic analysis is based on field-based methods such as finite difference method, finite element method, finite volume method or coupled. These numerical schemes are used to solve the coupled fluid Flow-Structural equation based on full Naiver-Stokes (NS) along with structural mechanics’ equations. These type of schemes provides very accurate results if modeled properly, however, they are computationally very expensive and need large computing recourse along with good personal expertise. Therefore, it is not the first choice for aeroelastic analysis during preliminary design phase. A reduced order aeroelastic model (ROAM) with acceptable accuracy and fast execution is more demanded at this stage. Similar ROAM are being used by other researchers for aeroelastic and force response analysis of turbomachinery. In the present paper new medium fidelity ROAM is successfully developed and implemented in numerical tool to simulated the aeroelastic stability phenomena in turbomachinery and well as flexible wings. In the present, a hybrid flow solver based on 3D viscous-inviscid coupled 3D panel method (PM) and 3d discrete vortex particle method (DVM) is developed, viscous parameters are estimated using boundary layer(BL) approach. This method can simulate flow separation and is a good compromise between accuracy and speed compared to CFD. In the second phase of the research work, the flow solver (PM) will be coupled with ROM non-linear beam element method (BEM) based FEM structural solver (with multibody capabilities) to perform the complete aeroelastic simulation of a steam turbine bladed disk, propellers, fan blades, aircraft wing etc. The partitioned based coupling approach is used for fluid-structure interaction (FSI). The numerical results are compared with experimental data for different test cases and for the blade cascade test case, experimental data is obtained from in-house lab experiments at IT CAS. Furthermore, the results from the new aeroelastic model will be compared with classical CFD-CSD based aeroelastic models. The proposed methodology for the aeroelastic stability analysis of gas turbine or steam turbine blades, or propellers or fan blades will provide researchers and engineers a fast, cost-effective and efficient tool for aeroelastic (classical flutter) analysis for different design at preliminary design stage where large numbers of design iteration are required in short time frame.

Keywords: aeroelasticity, beam element method (BEM), discrete vortex particle method (DVM), classical flutter, fluid-structure interaction (FSI), panel method, reduce order aeroelastic model (ROAM), turbomachinery, viscous-inviscid coupling

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Authors: Wajeeha Shahid

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The study was designed to assess the impact of transformational and transactional leadership styles on work motivation and organizational commitment among faculty members of universities of Punjab. 713 faculty members were selected as sample through convenient random sampling technique. Three self-constructed questionnaires namely Leadership Styles Questionnaire (LSQ), Work Motivation Questionnaire (WMQ) and Organizational Commitment Questionnaire (OCMQ) were used as research instruments. Major objectives of the study included assessing the effect and impact of transformational and transactional leadership styles on work motivation and organizational commitment. Theoretical frame work of the study included Idealized Influence, Inspirational Motivation, Intellectual Stimulation, Individualized Consideration, Contingent Rewards and Management by Exception as independent variables and Extrinsic motivation, Intrinsic motivation, Affective commitment, Continuance commitment and Normative commitment as dependent variables. SPSS Version 21 was used to analyze and tabulate data. Cronbach's Alpha reliability, Pearson Correlation and Multiple regression analysis were applied as statistical treatments for the analysis. Results revealed that Idealized Influence correlated significantly with intrinsic motivation and Affective commitment whereas Contingent rewards had a strong positive correlation with extrinsic motivation and affective commitment. Multiple regression models revealed a variance of 85% for transformational leadership style over work motivation and organizational commitment. Whereas transactional style as a predictor manifested a variance of 79% for work motivation and 76% for organizational commitment. It was suggested that changing organizational cultures are demanding more from their leadership. All organizations need to consider transformational leadership style as an important part of their equipment in leveraging both soft and hard organizational targets.

Keywords: leadership styles, work motivation, organizational commitment, faculty member

Procedia PDF Downloads 308