Search results for: ordinal regression and life table

Authors: Kajingulu Malandala, Ranganai Edmore

Abstract:

The asymmetric Laplace distribution (ADL) is commonly used as the likelihood function of the Bayesian quantile regression, and it offers different families of likelihood method for quantile regression. Notwithstanding their popularity and practicality, ADL is not smooth and thus making it difficult to maximize its likelihood. Furthermore, Bayesian inference is time consuming and the selection of likelihood may mislead the inference, as the Bayes theorem does not automatically establish the posterior inference. Furthermore, ADL does not account for greater skewness and Kurtosis. This paper develops a new aspect of quantile regression approach for count data based on inverse of the cumulative density function of the Poisson, binomial and Delaporte distributions using the integrated nested Laplace Approximations. Our result validates the benefit of using the integrated nested Laplace Approximations and support the approach for count data.

Keywords: quantile regression, Delaporte distribution, count data, integrated nested Laplace approximation

Procedia PDF Downloads 150

Authors: Ana Paula Camelo, Keila Sanches

Abstract:

The Geographically Weighted Regression (GWR) was proposed in geography literature to allow relationship in a regression model to vary over space. In Brazil, the agricultural exploitation of the Cerrado Biome is the main cause of deforestation. In this study, we propose a methodology using geostatistical methods to characterize the spatial dependence of deforestation in the Cerrado based on agricultural production indicators. Therefore, it was used the set of exploratory spatial data analysis tools (ESDA) and confirmatory analysis using GWR. It was made the calibration a non-spatial model, evaluation the nature of the regression curve, election of the variables by stepwise process and multicollinearity analysis. After the evaluation of the non-spatial model was processed the spatial-regression model, statistic evaluation of the intercept and verification of its effect on calibration. In an analysis of Spearman’s correlation the results between deforestation and livestock was +0.783 and with soybeans +0.405. The model presented R²=0.936 and showed a strong spatial dependence of agricultural activity of soybeans associated to maize and cotton crops. The GWR is a very effective tool presenting results closer to the reality of deforestation in the Cerrado when compared with other analysis.

Keywords: deforestation, geographically weighted regression, land use, spatial analysis

Procedia PDF Downloads 348

Authors: Anucha Taiwong, Nirobol Kanogsunthornrat

Abstract:

This predictive research aimed to investigate the symptom clusters that influence the quality of life among patients with chronic kidney disease, as indicated in the Theory of Unpleasant Symptoms. The purposive sample consisted of 150 patients with stage 3-4 chronic kidney disease who received care at an outpatient chronic kidney disease clinic of a tertiary hospital in Roi-Et province. Data were collected from January to March 2016 by using a patient general information form, unpleasant symptom form, and quality of life (SF-36) and were analyzed by using descriptive statistics, factor analysis, and multiple regression analysis. Findings revealed six core symptom clusters including symptom cluster of the mental and emotional conditions, peripheral nerves abnormality, fatigue, gastro-intestinal tract, pain and, waste congestion. Significant predictors for quality of life were the two symptom clusters of pain (Beta = -.220; p < .05) and the mental and emotional conditions (Beta=-.204; p<.05) which had predictive value of 19.10% (R2=.191, p<.05). This study indicated that the symptom cluster of pain and the mental and emotional conditions would worsen the patients’ quality of life. Nurses should be attentive in managing the two symptom clusters to facilitate the quality of life among patients with chronic kidney disease.

Keywords: chronic kidney disease, symptom clusters, predictors of quality of life, pre-dialysis

Procedia PDF Downloads 305

Authors: Habiba Ben Abdessalem

Abstract:

The emergence of giant set of textual data was the push that has encouraged researchers to invest in this field. The purpose of textual data analysis methods is to facilitate access to such type of data by providing various graphic visualizations. Applying these methods requires a corpus pretreatment step, whose standards are set according to the objective of the problem studied. This step determines the forms list contained in contingency table by keeping only those information carriers. This step may, however, lead to noisy contingency tables, so the use of wavelet denoising function. The validity of the proposed approach is tested on a text database that offers economic and political events in Tunisia for a well definite period.

Keywords: textual data, wavelet, denoising, contingency table

Procedia PDF Downloads 269

Authors: Mardi Falck, André Theron

Abstract:

Traffic congestion on the Northern side of Table Bay is a major problem. In Gauteng, the implementation of the Gautrain between Pretoria and Johannesburg, solved their traffic congestion. In 2002 two entrepreneurs endeavoured to implement a hovercraft ferry service across the bay from Table View to the Port of Cape Town. However, the EIA process proved that disgruntled residents from the area did not agree with their location for a launch site. 17 years later the traffic problem has not gone away, but instead the congestion has increased. While property prices in the City Bowl of Cape Town are ever increasing, people tend to live more on the outskirts of the CBD and commute to work. This means more vehicles on the road every day and the public transport services cannot keep up with the demand. For this reason, the study area of the previous hovercraft plans is being extended further North. The study’s aim is thus to determine the feasibility of a launch site North of Bloubergstrand to launch and receive a public transport ferry across Table Bay. The feasibility is being established by researching ferry services across the world and on what makes them successful. Different types of ferries and their operational capacities in terms of weather and waves are researched and by establishing the offshore and nearshore wind and wave climate for the area, an appropriate protected launch site is determined. It was concluded that travel time could potentially be halved. A hovercraft proved to be the most feasible ferry type, because it does not require a conventional harbour. Other types of vessels require a protected launch site because of the wave climate. This means large breakwaters that influence the cost substantially. The Melkbos Cultural Centre proved to be the most viable option for the location of the launch site, because it already has buildings and infrastructure. It is recommended that, if a harbour is chosen for the proposed ferry service, it could be used for more services like fishing, eco-tourism and leisure. Further studies are recommended to optimise the feasibility of such a harbour.

Keywords: Cape Town, ferry, public, Table Bay

Procedia PDF Downloads 139

Authors: Siqi Fang, Man Cheung Chung

Abstract:

This study examined the inter-relationship between childhood maltreatment, cognitive distortion, alexithymia, eudemonic well-being, and psychological distress. One hundred and eighty-two university students participated in the study and completed an online survey comprising the Childhood Trauma Questionnaire, Cognitive Distortion Scale, Toronto Alexithymia Scale, Psychological Well-Being Scale, and General Health Questionnaire-28. Hierarchical multiple regression analysis showed that child maltreatment, perceptions of hopelessness and helplessness, preoccupation with danger, personal growth, and purpose in life predicted psychological distress. However, alexithymia was not a significant predictor. Further analysis using the regression models with bootstrapping procedure showed that feeling hopeless, helpless and preoccupation with danger mediated the path between child maltreatment and psychological distress. Meanwhile, coping with beliefs in personal growth and life purpose moderated the mediation effects of distorted cognition on psychological distress. To conclude, childhood maltreatment is associated with psychological distress. This relationship is influenced by people’s perceptions of life being hopeless, helpless or dangerous. At the same time, the effect of hopelessness, helplessness, and feelings of danger also depends on the degree of using coping strategies of positive psychological functioning.

Keywords: alexithymia, childhood maltreatment, cognitive distortion, eudemonic well-being, psychological distress

Procedia PDF Downloads 322

Authors: Kaycee Bills

Abstract:

Studies have demonstrated that middle and high school students with disabilities are more likely to experience bullying than other student groups. The high rates of bullying victimization observed among youth with disabilities can result in severe socio-emotional consequences. These socio-emotional consequences often manifest in detrimental impacts on the students’ personal relationships. Past studies have indicated that participating in extracurricular athletic activities can have several socio-emotional benefits for students with disabilities. Given the findings of past studies demonstrating the positive relationship between mental health and participation in sports among students with disabilities, it is possible that participating in athletics could have a moderating relationship on the severity of the impact that bullying has on a student’s relationships with family and friends. Using the National Crime Victimization Survey/School Crime Supplement (NCVS/SCS), this study employs an ordinal logistic regression to determine if participation in extracurricular athletic activities mitigates the damaging impact bullying has on the personal relationships with friends and family among students who have disabilities. This study identified statistically significant results suggesting that students with disabilities who participate in athletics reported reduced levels of negative personal relationships resulting from bullying compared to their peers who did not participate in athletics.

Keywords: disability, inclusion, bullying, relationships

Procedia PDF Downloads 155

Authors: Kang-Mo Jung

Abstract:

The use of regularization for statistical methods has become popular. The least absolute shrinkage and selection operator (LASSO) framework has become the standard tool for sparse regression. However, it is well known that the LASSO is sensitive to outliers or leverage points. We consider a new robust estimation which is composed of the weighted loss function of the pairwise difference of residuals and the adaptive penalty function regulating the tuning parameter for each variable. Rank regression is resistant to regression outliers, but not to leverage points. By adopting a weighted loss function, the proposed method is robust to leverage points of the predictor variable. Furthermore, the adaptive penalty function gives us good statistical properties in variable selection such as oracle property and consistency. We develop an efficient algorithm to compute the proposed estimator using basic functions in program R. We used an optimal tuning parameter based on the Bayesian information criterion (BIC). Numerical simulation shows that the proposed estimator is effective for analyzing real data set and contaminated data.

Keywords: adaptive penalty function, robust penalized regression, variable selection, weighted rank regression

Procedia PDF Downloads 450

Authors: Kaycee Bills

Abstract:

Studies have demonstrated that middle and high school students with disabilities are more likely to experience bullying than other student groups. The high rates of bullying victimization observed among youth with disabilities can result in severe socio-emotional consequences. These socio-emotional consequences often manifest in detrimental impacts on the students’ personal relationships. Past studies have indicated that participating in extracurricular athletic activities can have several socio-emotional benefits for students with disabilities. Given the findings of past studies demonstrating the positive relationship between mental health and participation in sports among students with disabilities, it is possible that participating in athletics could have a moderating relationship on the severity of the impact that bullying has on a student’s relationships with family and friends. Using the National Crime Victimization Survey/School Crime Supplement (NCVS/SCS), this study employs an ordinal logistic regression to determine if participation in extracurricular athletic activities mitigates the damaging impact bullying has on the personal relationships with friends and family among students who have disabilities. This study identified statistically significant results suggesting that students with disabilities who participate in athletics reported reduced levels of negative personal relationships resulting from bullying compared to their peers who did not participate in athletics.

Keywords: disability, inclusion, bullying, relationships

Procedia PDF Downloads 173

Authors: Byung Ho Jung, Dong Hoon Lim

Abstract:

Logistic regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. Logistic regression is used extensively in numerous disciplines, including the medical and social science fields. In this paper, we address the problem of estimating parameters in the logistic regression based on MapReduce framework with RHadoop that integrates R and Hadoop environment applicable to large scale data. There exist three learning algorithms for logistic regression, namely Gradient descent method, Cost minimization method and Newton-Rhapson's method. The Newton-Rhapson's method does not require a learning rate, while gradient descent and cost minimization methods need to manually pick a learning rate. The experimental results demonstrated that our learning algorithms using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also compared the performance of our Newton-Rhapson's method with gradient descent and cost minimization methods. The results showed that our newton's method appeared to be the most robust to all data tested.

Keywords: big data, logistic regression, MapReduce, RHadoop

Procedia PDF Downloads 260

Authors: Filippo Portera

Abstract:

Usually standard algorithms employ a loss where each error is the mere absolute difference between the true value and the prediction, in case of a regression task. In the present, we present several error weighting schemes that are a generalization of the consolidated routine. We study both a binary classification model for Support Vextor Classification and a regression net for Multylayer Perceptron. Results proves that the error is never worse than the standard procedure and several times it is better.

Keywords: loss, binary-classification, MLP, weights, regression

Procedia PDF Downloads 78

Authors: Reza Siyami, Bahram Mirshekari

Abstract:

Seed and oil yield of rapeseed is considerably affected by weeds interference including mustard (Sinapis arvensis L.), lambsquarters (Chenopodium album L.) and redroot pigweed (Amaranthus retroflexus L.) throughout the East Azerbaijan province in Iran. To formulate the relationship between four independent growth variables measured in our experiment with a dependent variable, multiple regression analysis was carried out for the weed leaves number per plant (X1), green cover percentage (X2), LAI (X3) and leaf area per plant (X4) as independent variables and rapeseed oil yield as a dependent variable. The multiple regression equation is shown as follows: Seed essential oil yield (kg/ha) = 0.156 + 0.0325 (X1) + 0.0489 (X2) + 0.0415 (X3) + 0.133 (X4). Furthermore, the stepwise regression analysis was also carried out for the data obtained to test the significance of the independent variables affecting the oil yield as a dependent variable. The resulted stepwise regression equation is shown as follows: Oil yield = 4.42 + 0.0841 (X2) + 0.0801 (X3); R2 = 81.5. The stepwise regression analysis verified that the green cover percentage and LAI of weed had a marked increasing effect on the oil yield of rapeseed.

Keywords: green cover percentage, independent variable, interference, regression

Procedia PDF Downloads 404

Authors: Alam Ali, Ashok Kumar Pathak

Abstract:

Path analysis is a statistical technique used to evaluate the strength of the direct and indirect effects of variables. One or more structural regression equations are used to estimate a series of parameters in order to find the better fit of data. Sometimes, exogenous variables do not show a significant strength of their direct and indirect effect when the assumption of classical regression (ordinary least squares (OLS)) are violated by the nature of the data. The main motive of this article is to investigate the efficacy of the copula-based regression approach over the classical regression approach and calculate the direct and indirect effects of variables when data violates the OLS assumption and variables are linked through an elliptical copula. We perform this study using a well-organized numerical scheme. Finally, a real data application is also presented to demonstrate the performance of the superiority of the copula approach.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

Procedia PDF Downloads 59

Authors: Zarina Zahari, Maria Justine, Kamaria Kamaruddin

Abstract:

Low back pain (LBP) is a major musculoskeletal problem in global population. This study aimed to examine the relationship between pain, disability and quality of life in patients with non-specific low back pain (LBP). One hundred LBP participants were recruited in this cross-sectional study (mean age = 42.23±11.34 years old). Pain was measured using Numerical Rating Scale (11-point). Disability was assessed using the revised Oswestry low back pain disability questionnaire (ODQ) and quality of life (QoL) was evaluated using the SF-36 v2. Majority of participants (58%) presented with moderate pain and 49% experienced severe disability. Thus, the pain and disability were found significant with negative correlation (r= -0.712, p<0.05). The pain and QoL also showed significant and positive correlation with both Physical Health Component Summary (PHCS) (r= .840, p<0.05) and Mental Health Component Summary (MHCS) (r= 0.446, p<0.05). Regression analysis indicated that pain emerged as an indicator of both disability and QoL (PHCS and MHCS) accounting for 51%, 71% and 21% of the variances respectively. This indicates that pain is an important factor in predicting disability and QoL in LBP sufferers.

Keywords: disability, low back pain, pain, quality of life

Procedia PDF Downloads 518

Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

Abstract:

There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

Procedia PDF Downloads 155

Authors: K. Hema Shankari, R. Thirumalaiselvi, N. V. Balasubramanian

Abstract:

The present paper addresses to the research in the area of regression testing with emphasis on automated tools as well as prioritization of test cases. The uniqueness of regression testing and its cyclic nature is pointed out. The difference in approach between industry, with business model as basis, and academia, with focus on data mining, is highlighted. Test Metrics are discussed as a prelude to our formula for prioritization; a case study is further discussed to illustrate this methodology. An industrial case study is also described in the paper, where the number of test cases is so large that they have to be grouped as Test Suites. In such situations, a genetic algorithm proposed by us can be used to reconfigure these Test Suites in each cycle of regression testing. The comparison is made between a proprietary tool and an open source tool using the above-mentioned metrics. Our approach is clarified through several tables.

Keywords: APFD metric, genetic algorithm, regression testing, RFT tool, test case prioritization, selenium tool

Procedia PDF Downloads 416

Authors: Zubana Afzal, Afsheen Massod

Abstract:

This quantitative study was carried out in order to explore the role of coping strategies as an explanatory mechanism in the relationship between self-determination needs and quality of life. A cross-sectional survey research design was conducted using scales such as the Basic Psychological Needs Scale (Deci&Ryan, 2000) to measure self-determination-based needs, Pain Coping Strategies Questionnaire (Harland &Georgieff, 2003), and Quality of Life Brief (The WHOQOL Group, 1998), in translated form in addition to a demographic information sheet. The sample comprised 120 (Women=63, Men=57), taken from different hospitals in Lahore, Multan, and Gojra. Descriptive and Inferential analyses were executed through SPSS version 23.00. All self-determination needs were found in result to be significantly and positively correlated with diversion and cognitive pain coping strategies, physical, psychological, social, and environmental quality of life, and significantly negatively correlated with catastrophizing and reinterpreting pain coping strategies. Cognitive and diversion pain coping strategies were found to be significantly and positively associated with all physical, psychological, social, and environmental quality of life. The regression analyses revealed that the strongest predictors were autonomy, cognitive and diversion pain coping strategies in predicting quality of life. All coping strategies except reinterpreting played a mediating role between self-determination needs and quality of life. The findings can lead to a better understanding of the role of self-determination needs and pain coping strategies in determining the quality of life among chronic non-specific lower back pain patients.

Keywords: quality of life, chronic lower back pain, coping strategies, self determination needs

Procedia PDF Downloads 85

Authors: Dean A. McCorkle, Ed W. Hellman, Rebekka M. Dudensing, Dan D. Hanselka

Abstract:

The motivation for this study centers on the labor- and cost-intensive nature of wine and table grape production in the U.S., and the potential opportunities for precision mechanization using robotics to augment those production tasks that are labor-intensive. The objectives of this study are to evaluate the economic viability of grape production in five U.S. states under current operating conditions, identify common production challenges and tasks that could be augmented with new technology, and quantify a maximum price for new technology that growers would be able to pay. Wine and table grape production is primed for precision mechanization technology as it faces a variety of production and labor issues. Methodology: Using a grower panel process, this project includes the development of a representative wine grape vineyard in five states and a representative table grape vineyard in California. The panels provided production, budget, and financial-related information that are typical for vineyards in their area. Labor costs for various production tasks are of particular interest. Using the data from the representative budget, 10-year projected financial statements have been developed for the representative vineyard and evaluated using a stochastic simulation model approach. Labor costs for selected vineyard production tasks were evaluated for the potential of new precision mechanization technology being developed. These tasks were selected based on a variety of factors, including input from the panel members, and the extent to which the development of new technology was deemed to be feasible. The net present value (NPV) of the labor cost over seven years for each production task was derived. This allowed for the calculation of a maximum price for new technology whereby the NPV of labor costs would equal the NPV of purchasing, owning, and operating new technology. Expected Results: The results from the stochastic model will show the projected financial health of each representative vineyard over the 2015-2024 timeframe. Investigators have developed a preliminary list of production tasks that have the potential for precision mechanization. For each task, the labor requirements, labor costs, and the maximum price for new technology will be presented and discussed. Together, these results will allow technology developers to focus and prioritize their research and development efforts for wine and table grape vineyards, and suggest opportunities to strengthen vineyard profitability and long-term viability using precision mechanization.

Keywords: net present value, robotic technology, stochastic simulation, wine and table grapes

Procedia PDF Downloads 247

Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari

Abstract:

Without a doubt, soil shear strength is the most important property of the soil. The majority of fatal and catastrophic geological accidents are related to shear strength failure of the soil. Therefore, its prediction is a matter of high importance. However, acquiring the shear strength is usually a cumbersome task that might need complicated laboratory testing. Therefore, prediction of it based on common and easy to get soil properties can simplify the projects substantially. In this paper, A hybrid model based on the classification and regression tree algorithm and logistic regression is proposed where each leaf of the tree is an independent regression model. A database of 189 points for clay soil, including Moisture content, liquid limit, plastic limit, clay content, and shear strength, is collected. The performance of the developed model compared to the existing models and equations using root mean squared error and coefficient of correlation.

Keywords: model tree, CART, logistic regression, soil shear strength

Procedia PDF Downloads 179

Authors: Deepak Raj Bhat, Ryuichi Yatabe

Abstract:

In this study, a residual-state creep failure model was developed based on the residual-state creep test results of clayey soils. To develop the proposed model, the regression analyses were done by using the R. The model results of the failure time (tf) and critical displacement (δc) were compared with experimental results and found in close agreements to each others. It is expected that the proposed regression model for residual-state creep failure will be more useful for the prediction of displacement of different clayey soils in the future.

Keywords: regression model, residual-state creep failure, displacement prediction, clayey soils

Procedia PDF Downloads 386

Authors: O. Poleshchuk, E. Komarov

Abstract:

This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions.

Keywords: interval type-2 fuzzy sets, fuzzy regression, weighted interval

Procedia PDF Downloads 357

Authors: T. Mohammed Chikouche, K. Hartani

Abstract:

In order to solve the instantaneous power ripple and achieve better performance of direct power control (DPC) for a three-phase PWM rectifier, a control method is proposed in this paper. This control method is applied to overcome the instantaneous power ripple, to eliminate line current harmonics and therefore reduce the total harmonic distortion and to improve the power factor. A switching table is based on the analysis on the change of instantaneous active and reactive power, to select the optimum switching state of the three-phase PWM rectifier. The simulation result shows feasibility of this control method.

Keywords: power quality, direct power control, power ripple, switching table, unity power factor

Procedia PDF Downloads 307

Authors: Shih-Pin Chen, Shih-Syuan You

Abstract:

This study proposes a regression model with flexible spreads for fuzzy input-output data to cope with the situation that the existing measures cannot reflect the actual estimation error. The main idea is that a dissemblance index (DI) is carefully identified and defined for precisely measuring the actual estimation error. Moreover, the graded mean integration (GMI) representation is adopted for determining more representative numeric regression coefficients. Notably, to comprehensively compare the performance of the proposed model with other ones, three different criteria are adopted. The results from commonly used test numerical examples and an application to Taiwan's business monitoring indicator illustrate that the proposed dissemblance index method not only produces valid fuzzy regression models for fuzzy input-output data, but also has satisfactory and stable performance in terms of the total estimation error based on these three criteria.

Keywords: dissemblance index, forecasting, fuzzy sets, linear regression

Procedia PDF Downloads 343

Authors: Samai'la Abdullahi

Abstract:

A graph is a pair of two set and so that a graph is a pictorial representation of a system using two basic element nodes and edges. A node is represented by a circle (either hallo shade) and edge is represented by a line segment connecting two nodes together. In this paper, we present a circuit network in the concept of graph theory application and also circuit models of graph are represented in logical connection method were we formulate matrix method of adjacency and incidence of matrix and application of truth table.

Keywords: euler circuit and path, graph representation of circuit networks, representation of graph models, representation of circuit network using logical truth table

Procedia PDF Downloads 544

Authors: Omar Qaftan

Abstract:

Earthquakes can cause tremendous loss of human life and can result in severe damage to a several of civil engineering structures especially the tall buildings. The response of a multistory structure subjected to earthquake loading is a complex task, and it requires to be studied by physical and numerical modelling. For many circumstances, the scale models on shaking table may be a more economical option than the similar full-scale tests. A shaking table apparatus is a powerful tool that offers a possibility of understanding the actual behaviour of structural systems under earthquake loading. It is required to use a set of scaling relations to predict the behaviour of the full-scale structure. Selecting the scale factors is the most important steps in the simulation of the prototype into the scaled model. In this paper, the principles of scaling modelling procedure are explained in details, and the simulation of scaled multi-storey concrete structure for dynamic studies is investigated. A procedure for a complete dynamic simulation analysis is investigated experimentally and numerically with a scale factor of 1/50. The frequency domain accounting and lateral displacement for both numerical and experimental scaled models are determined. The procedure allows accounting for the actual dynamic behave of actual size porotype structure and scaled model. The procedure is adapted to determine the effects of the tall multi-storey structure on a raft foundation. Four generated accelerograms were used as inputs for the time history motions which are in complying with EC8. The output results of experimental works expressed regarding displacements and accelerations are compared with those obtained from a conventional fixed-base numerical model. Four-time history was applied in both experimental and numerical models, and they concluded that the experimental has an acceptable output accuracy in compare with the numerical model output. Therefore this modelling methodology is valid and qualified for different shaking table experiments tests.

Keywords: structure, raft, soil, interaction

Procedia PDF Downloads 124

Authors: Vashti Carissa

Abstract:

The main objective of this study is to examine whether the life-cycle theory of dividends could explain the determinant of an optimal dividend policy in Indonesia. The sample that was used consists of 1,420 non-financial and non-trade, services, investment firms listed in Indonesian Stock Exchange during the period of 2005-2014. According to this finding using logistic regression, firm life-cycle measured by retained earnings as a proportion of total equity (RETE) significantly has a positive effect on the propensity of a firm pays dividend. The higher company’s earned surplus portion in its capital structure could reflect firm maturity level which will increase the likelihood of dividend payment in mature firms. This result provides an additional empirical evidence about the existence of life-cycle theory of dividends for dividend payout phenomenon in Indonesia. It can be known that dividends tend to be paid by mature firms while retention is more dominating in growth firms. From the testing results, it can also be known that majority of sample firms are being in the growth phase which proves the fact about infrequent dividend distribution in Indonesia during the ten years observation period.

Keywords: dividend, dividend policy, life-cycle theory of dividends, mix of earned and contributed capital

Procedia PDF Downloads 281

Authors: Zikiou Nadia, Lahdir Mourad, Ameur Soltane

Abstract:

In this paper, we propose an effective method for image compression based on SVM Regression (SVR), with three different kernels, and biorthogonal 2D Discrete Wavelet Transform. SVM regression could learn dependency from training data and compressed using fewer training points (support vectors) to represent the original data and eliminate the redundancy. Biorthogonal wavelet has been used to transform the image and the coefficients acquired are then trained with different kernels SVM (Gaussian, Polynomial, and Linear). Run-length and Arithmetic coders are used to encode the support vectors and its corresponding weights, obtained from the SVM regression. The peak signal noise ratio (PSNR) and their compression ratios of several test images, compressed with our algorithm, with different kernels are presented. Compared with other kernels, Gaussian kernel achieves better image quality. Experimental results show that the compression performance of our method gains much improvement.

Keywords: image compression, 2D discrete wavelet transform (DWT-2D), support vector regression (SVR), SVM Kernels, run-length, arithmetic coding

Procedia PDF Downloads 369

Authors: Milica Lazic, Jovana Jestrovic

Abstract:

The aim of this research is to examine moderating role of positive and negative affect, defined as traits, in relationship between a number of stressful life events to which an individual is exposed and life satisfaction. The tendency to experience positive and negative emotions is considered as relatively independent, and life satisfaction depends on presence and intensity of emotions of different valence. However, the role of positive and negative affect can be much more complex. It can change the direction and/or intensity of correlation between a number of stressful life events and life satisfaction. Thus, this question is important for two reasons, (I) better comprehension of inconsistent result of correlation intensity between stressful events and life satisfaction (II) verification on what conditions positive and negative affect have a protective role, and on what conditions the positive and/or negative affect is vulnerability factor. Longitudinal data were collected in two waves from 660 adolescents. Firstly, participants completed the Positive and Negative Affect Schedule. A year later, Life events questionnaire, which measures the number of stressful events in the past six months and Satisfaction with Life Scale were administered. The data were analyzed using hierarchical regression analyses: three-way interaction. The results show that number of life events, positive and negative effect contribute to the level of life satisfaction. The check of moderation role shows the significant three-way interaction of number of life event, and both, positive and negative affect. Individuals who report high level of positive affect, estimate to be moderate to highly satisfied with their lives, regardless of number of stressors to which they are exposed and also how often they experience negative emotions. Individuals, who often experience negative emotions and rarely positive, report the lowest level of life satisfaction. It doesn't change despite the number of stressors they were exposed to. Individuals who report that rarely experience not only positive than also negative emotions estimate different level of life satisfaction depending on number of stressors they were exposed to. Under the influence of numerous stressors, their level of life satisfaction is low, and it's equal to life satisfaction level of individuals who often experience negative and rarely positive emotions. The result of this research shows that tendency to often experience positive emotions is the protective factor in situation when individuals are exposed to high number of stressors. On the other hand, tendency to rarely experience positive emotions present vulnerability factor. Conclusions and practical implications are further discussed.

Keywords: life events, life satisfaction, subjective well-being, positive and negative affect

Procedia PDF Downloads 284

Authors: Adriano Z. Zambom, Preethi Ravikumar

Abstract:

One of the biggest challenges in nonparametric regression is the curse of dimensionality. Additive models are known to overcome this problem by estimating only the individual additive effects of each covariate. However, if the model is misspecified, the accuracy of the estimator compared to the fully nonparametric one is unknown. In this work the efficiency of completely nonparametric regression estimators such as the Loess is compared to the estimators that assume additivity in several situations, including additive and non-additive regression scenarios. The comparison is done by computing the oracle mean square error of the estimators with regards to the true nonparametric regression function. Then, a backward elimination selection procedure based on the Akaike Information Criteria is proposed, which is computed from either the additive or the nonparametric model. Simulations show that if the additive model is misspecified, the percentage of time it fails to select important variables can be higher than that of the fully nonparametric approach. A dimension reduction step is included when nonparametric estimator cannot be computed due to the curse of dimensionality. Finally, the Boston housing dataset is analyzed using the proposed backward elimination procedure and the selected variables are identified.

Keywords: additive model, nonparametric regression, variable selection, Akaike Information Criteria

Procedia PDF Downloads 255

Authors: Mohamad Saberi, Arash Sohrabi

Abstract:

Tuned liquid damper is one the passive structural control ways which has been used since mid-1980 decade for seismic control in civil engineering. This system is made of one or many tanks filled with fluid, mostly water that installed on top of the high raised structure and used to prevent structure vibration. In this article we will show how to make seismic table contain TLD system and analysis the result of using this system in our structure. Results imply that when frequency ratio approaches 1 this system can perform its best in both dissipate energy and increasing structural damping. And also results of these serial experiments are proved compatible with Hunzer linear theory behaviour.

Keywords: TLD, seismic table, structural system, Hunzer linear behaviour

Procedia PDF Downloads 366