Search results for: quantile regression theory
7489 A Monte Carlo Fuzzy Logistic Regression Framework against Imbalance and Separation
Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen
Abstract:
Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning
Procedia PDF Downloads 627488 Prenatal Lead Exposure and Postpartum Depression: An Exploratory Study of Women in Mexico
Authors: Nia McRae, Robert Wright, Ghalib Bello
Abstract:
Introduction: Postpartum depression is a prevalent mood disorder that is detrimental to the mental and physical health of mothers and their newborns. Lead (Pb) is a toxic metal that is associated with hormonal imbalance and mental impairments. The hormone changes that accompany pregnancy and childbirth may be exacerbated by Pb and increase new mothers’ susceptibility to postpartum depression. To the best of the author’s knowledge, this is the only study that investigates the association between prenatal Pb exposure and postpartum depression. Identifying risk factors can contribute to improved prevention and treatment strategies for postpartum depression. Methods: Data was derived from the Programming Research in Obesity, Growth, Environment and Social Stress (PROGRESS) study which is an ongoing longitudinal birth cohort. Postpartum depression was identified by a score of 13 or above on the 10-Item Edinburg Postnatal Depression Scale (EPDS) 6-months and 12-months postpartum. Pb was measured in the blood (BPb) in the second and third trimester and in the tibia and patella 1-month postpartum. Quantile regression models were used to assess the relationship between BPb and postpartum depression. Results: BPb in the second trimester was negatively associated with the 80th percentile of depression 6-months postpartum (β: -0.26; 95% CI: -0.51, -0.01). No significant association was found between BPb in the third trimester and depression 6-months postpartum. BPb in the third trimester exhibited an inverse relationship with the 60th percentile (β: -0.23; 95% CI: -0.41, -0.06), 70th percentile (β: -0.31; 95% CI: -0.52, -0.10), and 90th percentile of depression 12-months postpartum (β: -0.36; 95% CI: -0.69, -0.03). There was no significant association between BPb in the second trimester and depression 12-months postpartum. Bone Pb concentrations were not significantly associated with postpartum depression. Conclusion: The negative association between BPb and postpartum depression may support research which demonstrates lead is a nontherapeutic stimulant. Further research is needed to verify these results and identify effect modifiers.Keywords: depression, lead, postpartum, prenatal
Procedia PDF Downloads 2207487 Value from Environmental and Cultural Perspectives or Two Sides of the Same Coin
Authors: Vilem Paril, Dominika Tothova
Abstract:
This paper discusses the value theory in cultural heritage and the value theory in environmental economics. Two economic views of the value theory are compared within the field of cultural heritage maintenance and within the field of the environment. The main aims are to find common features in these two differently structured theories under the layer of differently defined terms as well as really differing features of these two approaches, to clear the confusion which stems from different terminology as in fact these terms capture the same aspects of reality and to show possible inspiration these two perspectives can offer one another. Another aim is to present these two value systems in one value framework. First, important moments of the value theory from the economic perspective are presented, leading to the marginal revolution of (not only) the Austrian School. Then the theory of value within cultural heritage and environmental economics are explored. Finally, individual approaches are compared and their potential mutual inspiration searched for.Keywords: cultural heritage, environmental economics, existence value, value theory
Procedia PDF Downloads 3157486 The Signaling Power of ESG Accounting in Sub-Sahara Africa: A Dynamic Model Approach
Authors: Haruna Maama
Abstract:
Environmental, social and governance (ESG) reporting is gaining considerable attention despite being voluntary. Meanwhile, it consumes resources to provide ESG reporting, raising a question of its value relevance. The study examined the impact of ESG reporting on the market value of listed firms in SSA. The annual and integrated reports of 276 listed sub-Sahara Africa (SSA) firms. The integrated reporting scores of the firm were analysed using a content analysis method. A multiple regression estimation technique using a GMM approach was employed for the analysis. The results revealed that ESG has a positive relationship with firms’ market value, suggesting that investors are interested in the ESG information disclosure of firms in SSA. This suggests that extensive ESG disclosures are attempts by firms to obtain the approval of powerful social, political and environmental stakeholders, especially institutional investors. Furthermore, the market value analysis evidence is consistent with signalling theory, which postulates that firms provide integrated reports as a signal to influence the behaviour of stakeholders. This finding reflects the value placed on investors' social, environmental and governance disclosures, which affirms the views that conventional investors would care about the social, environmental and governance issues of their potential or existing investee firms. Overall, the evidence is consistent with the prediction of signalling theory. In the context of this theory, integrated reporting is seen as part of firms' overall competitive strategy to influence investors' behaviour. The findings of this study make unique contributions to knowledge and practice in corporate reporting.Keywords: environmental accounting, ESG accounting, signalling theory, sustainability reporting, sub-saharan Africa
Procedia PDF Downloads 677485 Landslide Susceptibility Mapping: A Comparison between Logistic Regression and Multivariate Adaptive Regression Spline Models in the Municipality of Oudka, Northern of Morocco
Authors: S. Benchelha, H. C. Aoudjehane, M. Hakdaoui, R. El Hamdouni, H. Mansouri, T. Benchelha, M. Layelmam, M. Alaoui
Abstract:
The logistic regression (LR) and multivariate adaptive regression spline (MarSpline) are applied and verified for analysis of landslide susceptibility map in Oudka, Morocco, using geographical information system. From spatial database containing data such as landslide mapping, topography, soil, hydrology and lithology, the eight factors related to landslides such as elevation, slope, aspect, distance to streams, distance to road, distance to faults, lithology map and Normalized Difference Vegetation Index (NDVI) were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by the two mentioned methods. Before the calculation, this database was divided into two parts, the first for the formation of the model and the second for the validation. The results of the landslide susceptibility analysis were verified using success and prediction rates to evaluate the quality of these probabilistic models. The result of this verification was that the MarSpline model is the best model with a success rate (AUC = 0.963) and a prediction rate (AUC = 0.951) higher than the LR model (success rate AUC = 0.918, rate prediction AUC = 0.901).Keywords: landslide susceptibility mapping, regression logistic, multivariate adaptive regression spline, Oudka, Taounate
Procedia PDF Downloads 1827484 Robust Variable Selection Based on Schwarz Information Criterion for Linear Regression Models
Authors: Shokrya Saleh A. Alshqaq, Abdullah Ali H. Ahmadini
Abstract:
The Schwarz information criterion (SIC) is a popular tool for selecting the best variables in regression datasets. However, SIC is defined using an unbounded estimator, namely, the least-squares (LS), which is highly sensitive to outlying observations, especially bad leverage points. A method for robust variable selection based on SIC for linear regression models is thus needed. This study investigates the robustness properties of SIC by deriving its influence function and proposes a robust SIC based on the MM-estimation scale. The aim of this study is to produce a criterion that can effectively select accurate models in the presence of vertical outliers and high leverage points. The advantages of the proposed robust SIC is demonstrated through a simulation study and an analysis of a real dataset.Keywords: influence function, robust variable selection, robust regression, Schwarz information criterion
Procedia PDF Downloads 1327483 Generalized Additive Model for Estimating Propensity Score
Authors: Tahmidul Islam
Abstract:
Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching
Procedia PDF Downloads 3627482 A Comparison of Neural Network and DOE-Regression Analysis for Predicting Resource Consumption of Manufacturing Processes
Authors: Frank Kuebler, Rolf Steinhilper
Abstract:
Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.Keywords: artificial neural network, design of experiments, regression analysis, resource efficiency, manufacturing process
Procedia PDF Downloads 5167481 Logistic Regression Model versus Additive Model for Recurrent Event Data
Authors: Entisar A. Elgmati
Abstract:
Recurrent infant diarrhea is studied using daily data collected in Salvador, Brazil over one year and three months. A logistic regression model is fitted instead of Aalen's additive model using the same covariates that were used in the analysis with the additive model. The model gives reasonably similar results to that using additive regression model. In addition, the problem with the estimated conditional probabilities not being constrained between zero and one in additive model is solved here. Also martingale residuals that have been used to judge the goodness of fit for the additive model are shown to be useful for judging the goodness of fit of the logistic model.Keywords: additive model, cumulative probabilities, infant diarrhoea, recurrent event
Procedia PDF Downloads 6287480 An Axiomatic Approach to Constructing an Applied Theory of Possibility
Authors: Oleksii Bychkov
Abstract:
The fundamental difference between randomness and vagueness is that the former requires statistical research. These issues were studied by Zadeh L, Dubois D., Prad A. The theory of possibility works with expert assessments, hypotheses, etc. gives an idea of the characteristics of the problem situation, the nature of the goals and real limitations. Possibility theory examines experiments that are not repeated. The article discusses issues related to the formalization of a fuzzy, uncertain idea of reality. The author proposes to expand the classical model of the theory of possibilities by introducing a measure of necessity. The proposed model of the theory of possibilities allows us to extend the measures of possibility and necessity onto a Boolean while preserving the properties of the measure. Thus, upper and lower estimates are obtained to describe the fact that the event will occur. Knowledge of the patterns that govern mass random, uncertain, fuzzy events allows us to predict how these events will proceed. The article proposed for publication quite fully reveals the essence of the construction and use of the theory of probability and the theory of possibility.Keywords: possibility, artificial, modeling, axiomatics, intellectual approach
Procedia PDF Downloads 197479 Identifying Factors Contributing to the Spread of Lyme Disease: A Regression Analysis of Virginia’s Data
Authors: Fatemeh Valizadeh Gamchi, Edward L. Boone
Abstract:
This research focuses on Lyme disease, a widespread infectious condition in the United States caused by the bacterium Borrelia burgdorferi sensu stricto. It is critical to identify environmental and economic elements that are contributing to the spread of the disease. This study examined data from Virginia to identify a subset of explanatory variables significant for Lyme disease case numbers. To identify relevant variables and avoid overfitting, linear poisson, and regularization regression methods such as a ridge, lasso, and elastic net penalty were employed. Cross-validation was performed to acquire tuning parameters. The methods proposed can automatically identify relevant disease count covariates. The efficacy of the techniques was assessed using four criteria on three simulated datasets. Finally, using the Virginia Department of Health’s Lyme disease data set, the study successfully identified key factors, and the results were consistent with previous studies.Keywords: lyme disease, Poisson generalized linear model, ridge regression, lasso regression, elastic net regression
Procedia PDF Downloads 1267478 An Analysis of the Effect of Sharia Financing and Work Relation Founding towards Non-Performing Financing in Islamic Banks in Indonesia
Authors: Muhammad Bahrul Ilmi
Abstract:
The purpose of this research is to analyze the influence of Islamic financing and work relation founding simultaneously and partially towards non-performing financing in Islamic banks. This research was regression quantitative field research, and had been done in Muammalat Indonesia Bank and Islamic Danamon Bank in 3 months. The populations of this research were 15 account officers of Muammalat Indonesia Bank and Islamic Danamon Bank in Surakarta, Indonesia. The techniques of collecting data used in this research were documentation, questionnaire, literary study and interview. Regression analysis result shows that Islamic financing and work relation founding simultaneously has positive and significant effect towards non performing financing of two Islamic Banks. It is obtained with probability value 0.003 which is less than 0.05 and F value 9.584. The analysis result of Islamic financing regression towards non performing financing shows the significant effect. It is supported by double linear regression analysis with probability value 0.001 which is less than 0.05. The regression analysis of work relation founding effect towards non-performing financing shows insignificant effect. This is shown in the double linear regression analysis with probability value 0.161 which is bigger than 0.05.Keywords: Syariah financing, work relation founding, non-performing financing (NPF), Islamic Bank
Procedia PDF Downloads 4267477 The Impact of Job Meaningfulness on the Relationships between Job Autonomy, Supportive Organizational Climate, and Job Satisfaction
Authors: Sashank Nyapati, Laura Lorente-Prieto, Maria Peiro
Abstract:
The general objective of this study is to analyse the mediating role of meaningfulness in the relationships between job autonomy and job satisfaction and supportive organizational climate and job satisfaction. Theories such as the Job Characteristics Model, Conservation of Resources theory, as well as the Job Demands-Resources theory were used as theoretical framework. Data was obtained from the 5th European Working Conditions Survey (EWCS), and sample was composed of 1005 and 1000 workers from Spain and Portugal respectively. The analysis was conducted using the SOBEL Macro for SPSS (A multiple regression mediation model) developed by Preacher and Hayes in 2003. Results indicated that Meaningfulness partially mediates both the Job Autonomy-Job Satisfaction as well as the Supportive Organizational Climate-Job Satisfaction relationships. However, the percentages are large enough to draw substantial conclusions, especially that Job Meaningfulness plays an essential – if indirect – role in the amount of Satisfaction that one experiences at work. Some theoretical and practical implications are discussed.Keywords: meaningfulness, job autonomy, supportive organizational climate, job satisfaction
Procedia PDF Downloads 5297476 A Kolmogorov-Smirnov Type Goodness-Of-Fit Test of Multinomial Logistic Regression Model in Case-Control Studies
Authors: Chen Li-Ching
Abstract:
The multinomial logistic regression model is used popularly for inferring the relationship of risk factors and disease with multiple categories. This study based on the discrepancy between the nonparametric maximum likelihood estimator and semiparametric maximum likelihood estimator of the cumulative distribution function to propose a Kolmogorov-Smirnov type test statistic to assess adequacy of the multinomial logistic regression model for case-control data. A bootstrap procedure is presented to calculate the critical value of the proposed test statistic. Empirical type I error rates and powers of the test are performed by simulation studies. Some examples will be illustrated the implementation of the test.Keywords: case-control studies, goodness-of-fit test, Kolmogorov-Smirnov test, multinomial logistic regression
Procedia PDF Downloads 4507475 Exploring the Nature and Meaning of Theory in the Field of Neuroeducation Studies
Authors: Ali Nouri
Abstract:
Neuroeducation is one of the most exciting research fields which is continually evolving. However, there is a need to develop its theoretical bases in connection to practice. The present paper is a starting attempt in this regard to provide a space from which to think about neuroeducational theory and invoke more investigation in this area. Accordingly, a comprehensive theory of neuroeducation could be defined as grouping or clustering of concepts and propositions that describe and explain the nature of human learning to provide valid interpretations and implications useful for educational practice in relation to philosophical aspects or values. Whereas it should be originated from the philosophical foundations of the field and explain its normative significance, it needs to be testable in terms of rigorous evidence to fundamentally advance contemporary educational policy and practice. There is thus pragmatically a need to include a course on neuroeducational theory into the curriculum of the field. In addition, there is a need to articulate and disseminate considerable discussion over the subject within professional journals and academic societies.Keywords: neuroeducation studies, neuroeducational theory, theory building, neuroeducation research
Procedia PDF Downloads 4417474 A Study on Inference from Distance Variables in Hedonic Regression
Authors: Yan Wang, Yasushi Asami, Yukio Sadahiro
Abstract:
In urban area, several landmarks may affect housing price and rents, hedonic analysis should employ distance variables corresponding to each landmarks. Unfortunately, the effects of distances to landmarks on housing prices are generally not consistent with the true price. These distance variables may cause magnitude error in regression, pointing a problem of spatial multicollinearity. In this paper, we provided some approaches for getting the samples with less bias and method on locating the specific sampling area to avoid the multicollinerity problem in two specific landmarks case.Keywords: landmarks, hedonic regression, distance variables, collinearity, multicollinerity
Procedia PDF Downloads 4487473 Towards Establishing a Universal Theory of Project Management
Authors: Divine Kwaku Ahadzie
Abstract:
Project management (PM) as a concept has evolved from the early 20th Century into a recognized academic and professional discipline, and indications are that it has come to stay in the 21st Century as a world-wide paradigm shift for managing successful construction projects. However, notwithstanding the strong inroads that PM has made in legitimizing its academic and professional status in construction management practice, the underlining philosophies are still based on cases and conventional practices. An important theoretical issue yet to be addressed is the lack of a universal theory that offers philosophical legitimacy for the PM concept as a uniquely specialized management concept. Here, it is hypothesized that the law of entropy, the theory of uncertainties and the theory of risk management offer plausible explanations for addressing the lacuna of what constitute PM theory. The theoretical bases of these plausible underlying theories are argued and attempts made to establish the functional relationships that exist between these theories and the PM concept. The paper then draws on data related to the success and/or failure of a number of construction projects to validate the theory.Keywords: concepts, construction, project management, universal theory
Procedia PDF Downloads 3257472 Estimation of Coefficients of Ridge and Principal Components Regressions with Multicollinear Data
Authors: Rajeshwar Singh
Abstract:
The presence of multicollinearity is common in handling with several explanatory variables simultaneously due to exhibiting a linear relationship among them. A great problem arises in understanding the impact of explanatory variables on the dependent variable. Thus, the method of least squares estimation gives inexact estimates. In this case, it is advised to detect its presence first before proceeding further. Using the ridge regression degree of its occurrence is reduced but principal components regression gives good estimates in this situation. This paper discusses well-known techniques of the ridge and principal components regressions and applies to get the estimates of coefficients by both techniques. In addition to it, this paper also discusses the conflicting claim on the discovery of the method of ridge regression based on available documents.Keywords: conflicting claim on credit of discovery of ridge regression, multicollinearity, principal components and ridge regressions, variance inflation factor
Procedia PDF Downloads 4107471 Low-Cost Image Processing System for Evaluating Pavement Surface Distress
Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa
Abstract:
Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means
Procedia PDF Downloads 1747470 Financial Risk Tolerance and Its Impact on Terrorism-Tourism Relation in Pakistan
Authors: Sania Sana, Afnan Nasim, Usman Malik, Maroof Tahir
Abstract:
The aim of this research is to scrutinize the interdependent relationship between terrorism and behavioral changes in the tourism activities in Pakistan with the moderating impact of a unique variable titled 'Financial Risk Tolerance'. The article looks at the inter-reliant relationship with the alleged political and economic aspects and behavioral changes in the tourists and the consumers by these variables over time. The researchers used many underlying theories like the catastrophe theory by (Svyantek, Deshon and Siler 1991), information integration theory (Anderson 1981, 1982) and prospect theory (Kahneman and Tversky 1979) to shape the study’s framework as per tourist decision making model. A sample of around 110 locals was used for this purpose and the data was gathered by convenience sampling. The responses were analyzed using regression analysis. The results exhibited how terrorism along with the influence of financial risk tolerance had inclined a behavioral shift in the travelling patterns and vacation destination choice of the local tourists. Lastly, the paper proposes a number of suggestive measures for the tourism industry and the legislative bodies to ensure the safety of travelers and to boost the tourist activities in the vacation industry of Pakistan.Keywords: terrorism, tourism, financial risk tolerance, tourist decision-making, destination choice
Procedia PDF Downloads 2327469 Policy Compliance in Information Security
Authors: R. Manjula, Kaustav Bagchi, Sushant Ramesh, Anush Baskaran
Abstract:
In the past century, the emergence of information technology has had a significant positive impact on human life. While companies tend to be more involved in the completion of projects, the turn of the century has seen importance being given to investment in information security policies. These policies are essential to protect important data from adversaries, and thus following these policies has become one of the most important attributes revolving around information security models. In this research, we have focussed on the factors affecting information security policy compliance in two models : The theory of planned behaviour and the integration of the social bond theory and the involvement theory into a single model. Finally, we have given a proposal of where these theories would be successful.Keywords: information technology, information security, involvement theory, policies, social bond theory
Procedia PDF Downloads 3667468 Estimate of Maximum Expected Intensity of One-Half-Wave Lines Dancing
Authors: A. Bekbaev, M. Dzhamanbaev, R. Abitaeva, A. Karbozova, G. Nabyeva
Abstract:
In this paper, the regression dependence of dancing intensity from wind speed and length of span was established due to the statistic data obtained from multi-year observations on line wires dancing accumulated by power systems of Kazakhstan and the Russian Federation. The lower and upper limitations of the equations parameters were estimated, as well as the adequacy of the regression model. The constructed model will be used in research of dancing phenomena for the development of methods and means of protection against dancing and for zoning plan of the territories of line wire dancing.Keywords: power lines, line wire dancing, dancing intensity, regression equation, dancing area intensity
Procedia PDF Downloads 3067467 A Factor-Analytical Approach on Identities in Environmentally Significant Behavior
Authors: Alina M. Udall, Judith de Groot, Simon de Jong, Avi Shankar
Abstract:
There are many ways in which environmentally significant behavior can be explained. Dominant psychological theories, namely, the theory of planned behavior, the norm-activation theory, its extension, the value-belief-norm theory, and the theory of habit do not explain large parts of environmentally significant behaviors. A new and rapidly growing approach is to focus on how consumer’s identities predict environmentally significant behavior. Identity may be relevant because consumers have many identities that are assumed to guide their behavior. Therefore, we assume that many identities will guide environmentally significant behavior. Many identities can be relevant for environmentally significant behavior. In reviewing the literature, over 200 identities have been studied making it difficult to establish the key identities for explaining environmentally significant behavior. Therefore, this paper first aims to establish the key identities previously used for explaining environmentally significant behavior. Second, the aim is to test which key identities explain environmentally significant behavior. To address the aims, an online survey study (n = 578) is conducted. First, the exploratory factor analysis reveals 15 identity factors. The identity factors are namely, environmentally concerned identity, anti-environmental self-identity, environmental place identity, connectedness with nature identity, green space visitor identity, active ethical identity, carbon off-setter identity, thoughtful self-identity, close community identity, anti-carbon off-setter identity, environmental group member identity, national identity, identification with developed countries, cyclist identity, and thoughtful organisation identity. Furthermore, to help researchers understand and operationalize the identities, the article provides theoretical definitions for each of the identities, in line with identity theory, social identity theory, and place identity theory. Second, the hierarchical regression shows only 10 factors significantly uniquely explain the variance in environmentally significant behavior. In order of predictive power the identities are namely, environmentally concerned identity, anti-environmental self-identity, thoughtful self-identity, environmental group member identity, anti-carbon off-setter identity, carbon off-setter identity, connectedness with nature identity, national identity, and green space visitor identity. The identities explain over 60% of the variance in environmentally significant behavior, a large effect size. Based on this finding, the article reveals a new, theoretical framework showing the key identities explaining environmentally significant behavior, to help improve and align the field.Keywords: environmentally significant behavior, factor analysis, place identity, social identity
Procedia PDF Downloads 4457466 Incorporating Anomaly Detection in a Digital Twin Scenario Using Symbolic Regression
Authors: Manuel Alves, Angelica Reis, Armindo Lobo, Valdemar Leiras
Abstract:
In industry 4.0, it is common to have a lot of sensor data. In this deluge of data, hints of possible problems are difficult to spot. The digital twin concept aims to help answer this problem, but it is mainly used as a monitoring tool to handle the visualisation of data. Failure detection is of paramount importance in any industry, and it consumes a lot of resources. Any improvement in this regard is of tangible value to the organisation. The aim of this paper is to add the ability to forecast test failures, curtailing detection times. To achieve this, several anomaly detection algorithms were compared with a symbolic regression approach. To this end, Isolation Forest, One-Class SVM and an auto-encoder have been explored. For the symbolic regression PySR library was used. The first results show that this approach is valid and can be added to the tools available in this context as a low resource anomaly detection method since, after training, the only requirement is the calculation of a polynomial, a useful feature in the digital twin context.Keywords: anomaly detection, digital twin, industry 4.0, symbolic regression
Procedia PDF Downloads 1127465 Principles of Teaching for Successful Intelligence
Authors: Shabnam
Abstract:
The purpose of this study was to see importance of successful intelligence in education which can enhance achievement. There are a number of researches which have tried to apply psychological theories of education and many researches emphasized the role of thinking and intelligence. While going through the various researches, it was found that many students could learn more effectively than they do, if they were taught in a way that better matched their patterns of abilities. Attempts to apply psychological theories to education can falter on the translation of the theory into educational practice. Often, this translation is not clear. Therefore, when a program does not succeed, it is not clear whether the lack of success was due to the inadequacy of the theory or the inadequacy of the implementation of the theory. A set of basic principles for translating a theory into practice can help clarify just what an educational implementation should (and should not) look like. Sternberg’s theory of successful intelligence; analytical, creative and practical intelligence provides a way to create such a match. The results suggest that theory of successful intelligence provides successful interventions in classrooms and provides a proven model for gifted education. This article presents principles for translating a triarchic theory of successful intelligence into educational practice.Keywords: successful intelligence, analytical, creative and practical intelligence, achievement, success, resilience
Procedia PDF Downloads 5847464 Dividend Payout and Capital Structure: A Family Firm Perspective
Authors: Abhinav Kumar Rajverma, Arun Kumar Misra, Abhijeet Chandra
Abstract:
Family involvement in business is universal across countries, with varying characteristics. Firms of developed economies have diffused ownership structure; however, that of emerging markets have concentrated ownership structure, having resemblance with that of family firms. Optimization of dividend payout and leverage are very crucial for firm’s valuation. This paper studies dividend paying behavior of National Stock Exchange listed Indian firms from financial year 2007 to 2016. The final sample consists of 422 firms and of these more than 49% (207) are family firms. Results reveal that family firms pay lower dividend and are more leveraged compared to non-family firms. This unique data set helps to understand dividend behavior and capital structure of sample firms over a long-time period and across varying family ownership concentration. Using panel regression models, this paper examines factors affecting dividend payout and capital structure and establishes a link between the two using Two-stage Least Squares regression model. Profitability shows a positive impact on dividend and negative impact on leverage, confirming signaling and pecking order theory. Further, findings support bankruptcy theory as firm size has a positive relation with dividend and leverage and volatility shows a negative relation with both dividend and leverage. Findings are also consistent with agency theory, family ownership concentration has negative relation with both dividend payments and leverage. Further, the impact of family ownership control confirms the similar finding. The study further reveals that firms with high family ownership concentration (family control) do have an impact on determining the level of private benefits. Institutional ownership is not significant for dividend payments. However, it shows significant negative relation with leverage for both family and non-family firms. Dividend payout and leverage show mixed association with each other. This paper provides evidence of how varying level of family ownership concentration and ownership control influences the dividend policy and capital structure of firms in an emerging market like India and it can have significant contribution towards understanding and formulating corporate dividend policy decisions and capital structure for emerging economies, where majority of firms exhibit behavior of family firm.Keywords: dividend, family firms, leverage, ownership structure
Procedia PDF Downloads 2747463 Impact of Infrastructural Development on Socio-Economic Growth: An Empirical Investigation in India
Authors: Jonardan Koner
Abstract:
The study attempts to find out the impact of infrastructural investment on state economic growth in India. It further tries to determine the magnitude of the impact of infrastructural investment on economic indicator, i.e., per-capita income (PCI) in Indian States. The study uses panel regression technique to measure the impact of infrastructural investment on per-capita income (PCI) in Indian States. Panel regression technique helps incorporate both the cross-section and time-series aspects of the dataset. In order to analyze the difference in impact of the explanatory variables on the explained variables across states, the study uses Fixed Effect Panel Regression Model. The conclusions of the study are that infrastructural investment has a desirable impact on economic development and that the impact is different for different states in India. We analyze time series data (annual frequency) ranging from 1991 to 2010. The study reveals that the infrastructural investment significantly explains the variation of economic indicators.Keywords: infrastructural investment, multiple regression, panel regression techniques, economic development, fixed effect dummy variable model
Procedia PDF Downloads 3627462 Applied Theory Building to Achieve Success in Iran Municipalities
Authors: Morteza Rahiminejad
Abstract:
There are over 1200 cities and municipalities all around Iran, including 30 mega cities, which municipal organizations, Interior ministries, and city councils supervise. Even so, there has been neither any research about the process of success nor performance assessment in municipalities. In this research an attempt is made to build a comprehensive theory (or model) to show the reasons or success process among the local governments. The present research is based on the contingency approach in which the relevant circumstances are important, and both environment and situations call for their own management methods. The methodology of research is grounded theory, which uses Atlas.ti software as a tool.Keywords: success, municipality, Iran, theory building
Procedia PDF Downloads 307461 A Quadratic Model to Early Predict the Blastocyst Stage with a Time Lapse Incubator
Authors: Cecile Edel, Sandrine Giscard D'Estaing, Elsa Labrune, Jacqueline Lornage, Mehdi Benchaib
Abstract:
Introduction: The use of incubator equipped with time-lapse technology in Artificial Reproductive Technology (ART) allows a continuous surveillance. With morphocinetic parameters, algorithms are available to predict the potential outcome of an embryo. However, the different proposed time-lapse algorithms do not take account the missing data, and then some embryos could not be classified. The aim of this work is to construct a predictive model even in the case of missing data. Materials and methods: Patients: A retrospective study was performed, in biology laboratory of reproduction at the hospital ‘Femme Mère Enfant’ (Lyon, France) between 1 May 2013 and 30 April 2015. Embryos (n= 557) obtained from couples (n=108) were cultured in a time-lapse incubator (Embryoscope®, Vitrolife, Goteborg, Sweden). Time-lapse incubator: The morphocinetic parameters obtained during the three first days of embryo life were used to build the predictive model. Predictive model: A quadratic regression was performed between the number of cells and time. N = a. T² + b. T + c. N: number of cells at T time (T in hours). The regression coefficients were calculated with Excel software (Microsoft, Redmond, WA, USA), a program with Visual Basic for Application (VBA) (Microsoft) was written for this purpose. The quadratic equation was used to find a value that allows to predict the blastocyst formation: the synthetize value. The area under the curve (AUC) obtained from the ROC curve was used to appreciate the performance of the regression coefficients and the synthetize value. A cut-off value has been calculated for each regression coefficient and for the synthetize value to obtain two groups where the difference of blastocyst formation rate according to the cut-off values was maximal. The data were analyzed with SPSS (IBM, Il, Chicago, USA). Results: Among the 557 embryos, 79.7% had reached the blastocyst stage. The synthetize value corresponds to the value calculated with time value equal to 99, the highest AUC was then obtained. The AUC for regression coefficient ‘a’ was 0.648 (p < 0.001), 0.363 (p < 0.001) for the regression coefficient ‘b’, 0.633 (p < 0.001) for the regression coefficient ‘c’, and 0.659 (p < 0.001) for the synthetize value. The results are presented as follow: blastocyst formation rate under cut-off value versus blastocyst rate formation above cut-off value. For the regression coefficient ‘a’ the optimum cut-off value was -1.14.10-3 (61.3% versus 84.3%, p < 0.001), 0.26 for the regression coefficient ‘b’ (83.9% versus 63.1%, p < 0.001), -4.4 for the regression coefficient ‘c’ (62.2% versus 83.1%, p < 0.001) and 8.89 for the synthetize value (58.6% versus 85.0%, p < 0.001). Conclusion: This quadratic regression allows to predict the outcome of an embryo even in case of missing data. Three regression coefficients and a synthetize value could represent the identity card of an embryo. ‘a’ regression coefficient represents the acceleration of cells division, ‘b’ regression coefficient represents the speed of cell division. We could hypothesize that ‘c’ regression coefficient could represent the intrinsic potential of an embryo. This intrinsic potential could be dependent from oocyte originating the embryo. These hypotheses should be confirmed by studies analyzing relationship between regression coefficients and ART parameters.Keywords: ART procedure, blastocyst formation, time-lapse incubator, quadratic model
Procedia PDF Downloads 3047460 The Relationship between Iranian EFL Learners' Multiple Intelligences and Their Performance on Grammar Tests
Authors: Rose Shayeghi, Pejman Hosseinioun
Abstract:
The Multiple Intelligences theory characterizes human intelligence as a multifaceted entity that exists in all human beings with varying degrees. The most important contribution of this theory to the field of English Language Teaching (ELT) is its role in identifying individual differences and designing more learner-centered programs. The present study aims at investigating the relationship between different elements of multiple intelligence and grammar scores. To this end, 63 female Iranian EFL learner selected from among intermediate students participated in the study. The instruments employed were a Nelson English language test, Michigan Grammar Test, and Teele Inventory for Multiple Intelligences (TIMI). The results of Pearson Product-Moment Correlation revealed a significant positive correlation between grammatical accuracy and linguistic as well as interpersonal intelligence. The results of Stepwise Multiple Regression indicated that linguistic intelligence contributed to the prediction of grammatical accuracy.Keywords: multiple intelligence, grammar, ELT, EFL, TIMI
Procedia PDF Downloads 483