Search results for: regression discontinuity design

Authors: Gang Wang

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Education is widely believed to be a prerequisite for democracy and civil society, but the causal link between education and outcome variables is usually hardly to be identified. This study applies a fuzzy regression discontinuity design to examine the effects of college education on democratic attitudes in the Chinese context. In the analysis treatment assignment is determined by students’ college entry years and thus naturally selected by subjects’ ages. Using a sample of Chinese college students collected in Beijing in 2009, this study finds that college education actually reduces undergraduates’ motivation for political development in China but promotes political loyalty to the authoritarian government. Further hypotheses tests explain these interesting findings from two perspectives. The first is related to the complexity of politics. As college students progress over time, they increasingly realize the complexity of political reform in China’s authoritarian regime and rather stay away from politics. The second is related to students’ career opportunities. As students are close to graduation, they are immersed with job hunting and have a reduced interest in political freedom.

Keywords: china, college education, democratic attitudes, regression discontinuity

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Authors: Kuixi Du, Thomas J. Lipscomb

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The proficiency in Mathematics skills is fundamental to success in the STEM disciplines. In the US, beginning college students who are placed in remedial/developmental Mathematics courses frequently struggle to achieve academic success. Therefore, Mathematics remediation in college has become an important concern, and providing Mathematics remediation is a prevalent way to help the students who may not be fully prepared for college-level courses. Programs vary, however, and the effectiveness of a particular remedial Mathematics program must be empirically demonstrated. The purpose of this study was to apply the sharp regression discontinuity (RD) technique to determine the effectiveness of the Jack Leaps Summer (JLS) Mathematic remediation program in supporting improved Mathematics learning outcomes among newly admitted Mathematics students in the South Dakota State University. The researchers studied the newly admitted Fall 2019 cohort of Mathematics majors (n=423). The results indicated that students whose pretest score was lower than the cut-off point and who were assigned to the JLS program experienced significantly higher scores on the post-test (Math 101 final score). Based on these results, there is evidence that the JLS program is effective in meeting its primary objective.

Keywords: causal inference, mathematisc remedial program evaluation, quasi-experimental research design, regression discontinuity design, cohort studies

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Authors: Fatma Romeh, Shiferaw Gurmu

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This paper examines the impact of female education on fertility, using the change in length of primary schooling in Egypt in 1988-89 as the source of exogenous variation in schooling. In particular, beginning in 1988, children had to attend primary school for only five years rather than six years. This change was applicable to all individuals born on or after October 1977. Using a nonparametric regression discontinuity approach, we compare education and fertility of women born just before and after October 1977. The results show that female education significantly reduces the number of children born per woman and delays the time until first birth. Applying a robust regression discontinuity approach, however, the impact of education on the number of children is no longer significant. The impact on the timing of first birth remained significant under the robust approach. Each year of female education postponed childbearing by three months, on average.

Keywords: Egypt, female education, fertility, robust regression discontinuity

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Authors: Pushpendra Kumar, Sanjeev Kumar, R. Balasubramanian

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Estimation of optical flow from a sequence of images using variational methods is one of the most successful approach. Discontinuity between different motions is one of the challenging problem in flow estimation. In this paper, we design a new anisotropic diffusion operator, which is able to provide smooth flow over a region and efficiently preserve discontinuity in optical flow. This operator is designed on the basis of intensity differences of the pixels and isotropic operator using exponential function. The combination of these are used to control the propagation of flow. Experimental results on the different datasets verify the robustness and accuracy of the algorithm and also validate the effect of anisotropic operator in the discontinuity preserving.

Keywords: optical flow, variational methods, computer vision, anisotropic operator

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Authors: Sha Fan, Renuka Mahadevan

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In recent years, the subject of how retirement influences consumption behaviours has garnered attention in economic research. However, a significant gap persists in our understanding of how retirement precisely impacts tourism consumption patterns among the elderly demographic. To address this gap, this research conducts an in-depth exploration into the multifaceted relationship between retirement and elderly tourism consumption.To achieve this, the study employs regression discontinuity design, using three waves of panel data from China covering a span of six years. This approach aims to identify the causality between retirement and tourism consumption. Furthermore, the study scrutinizes the pathways through which retirement's impact on tourism consumption unfolds. It adopts a dual-pronged perspective, examining the roles played by economic status and the availability of leisure time. The economic dimension underscores the financial adjustments that retirees make as they transition into a new phase of life, impacting their propensity to allocate resources towards tourism activities. Meanwhile, considering leisure time recognizes that retirement often heralds an era of newfound freedom, allowing retirees the luxury to engage in leisurely pursuits like tourism.

Keywords: tourism consumption, retirement, the elderly, regression discontinuity design

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Authors: Tran Trong Thang, Nguyen Phan Kien, Trinh Quang Duc

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The phased-array ultrasound transducer types are utilities for medical ultrasonography as well as optical imaging. However, their discontinuity characteristic limits the applications due to the artifacts contaminated into the reconstructed images. Because of the effects of the ultrasound pressure field pattern to the echo ultrasonic waves as well as the optical modulated signal, the side lobes of the focused ultrasound beam induced by discontinuity of the phased-array ultrasound transducer might the reason of the artifacts. In this paper, a simple method in approach of numerical simulation was used to investigate the limitation of discontinuity of the elements in phased-array ultrasound transducer and their effects to the ultrasound pressure field. Take into account the change of ultrasound pressure field patterns in the conditions of variation of the pitches between elements of the phased-array ultrasound transducer, the appropriated parameters for phased-array ultrasound transducer design were asserted quantitatively.

Keywords: phased-array ultrasound transducer, sound pressure pattern, discontinuous sound field, numerical visualization

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Authors: Gelacio Juárez-Luna, Gustavo Ayala, Jaime Retama-Velasco

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This paper shows the advantages of the material failure process simulation by improve finite elements with embedded discontinuities, using a new definition of traction vector, dependent on the discontinuity length and the angle. Particularly, two families of this kind of elements are compared: kinematically optimal symmetric and statically and kinematically optimal non-symmetric. The constitutive model to describe the behavior of the material in the symmetric formulation is a traction-displacement jump relationship equipped with softening after reaching the failure surface. To show the validity of this symmetric formulation, representative numerical examples illustrating the performance of the proposed formulation are presented. It is shown that the non-symmetric family may over or underestimate the energy required to create a discontinuity, as this effect is related with the total length of the discontinuity, fact that is not noticed when the discontinuity path is a straight line.

Keywords: variational formulation, strong discontinuity, embedded discontinuities, strain localization

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Authors: Nishit L. Sanil, Raza M. Khan

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Increasing lift effectively at higher angles of attack has always been a daunting challenge in aviation especially on a delta wing. These are used on military jet fighter planes and has some undesirable characteristics, notably flow separation at high angles of attack and high drag at low speeds. In order to solve this problem, a design modification is modeled on a delta wing which would increase the lift so that we can improve maneuverability. To attain an increase in the lift of a 65 degree delta wing at higher angles of attack, a step-wise discontinuity is created at the upper surface of the delta wing. A normal delta wing is validated for comparison which would thereby give us a measure of flow separation and coefficient of lift affected by the modification. The results obtained deliver a significant increase in lift at higher angles of attack thereby delaying stall. Hence the benefits of the modification would aid the potential designs of aircraft’s in the time to come.

Keywords: coefficient of lift, delta wing, flow separation, step-wise discontinuity

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Authors: Qiuying Li

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It is a shared opinion that sustainable development requires a system discontinuity, meaning that radical changes in the way we produce and consume are needed. Within this framework there is an emerging understanding that an important contribution to this change can be directly linked to decisions taken in the design phase of products, services and systems. Design schools have therefore to be able to provide design students with a broad knowledge and effective Design for Sustainability tools, in order to enable a new generation of designers in playing an active role in reorienting our consumption and production patterns.

Keywords: design for sustainability, services, systems, materials, ecomaterials

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Authors: David Dean Hampton, William Morrison, Mary Rizza, Jan Osborn

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This evaluation examined the effects of a supplemental reading intervThis evaluation examined the effects of a supplemental reading intervention for students with specific learning disabilities in reading who were presented with below grade level on fall benchmark scores on DIBELS 6th ed. Revised. Participants consisted of a condition group, those who received supplemental reading instruction in addition to core + special education services and a comparison group of students who were at grade level in their fall benchmark scores. The students in the condition group received 26 weeks of Project MORE instruction delivered multiple times each week from trained volunteer tutors. Using a regression-discontinuity design, condition and comparison groups were compared on reading development growth using DIBELS ORF. Significant findings were reported for grade 2, 3, and 4. ntion for students with specific learning disabilities in reading who presented with below grade level on fall benchmark scores on DIBELS 6th ed. Revised. Participants consisted of a condition group, those who received supplemental reading instruction in addition to core + special education services and a comparison group of students who were at grade level in their fall benchmark scores. The students in the condition group received 26 weeks of Project MORE instruction delivered multiple times each week from trained volunteer tutors. Using a regression-discontinuity design, condition and comparison groups were compared on reading development growth using DIBELS ORF. Significant findings were reported for grade 2, 3, and 4.

Keywords: special education, evidence-based practices, curriculum, tutoring

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Authors: Basma Yassa

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Evidence on cash transfers’ effectiveness in mitigating macro and idiosyncratic shocks’ impacts has been mixed and is mostly concentrated in Latin America, Sub-Saharan Africa, and South Asia with very limited evidence from the MENA region. Yet conditional cash transfers schemes have been continually used, especially in Egypt, as the main social protection tool in response to the recent socioeconomic crises and macro shocks. We use 2 panel datasets and 1 cross-sectional dataset to estimate the effectiveness of cash transfers as a shock-mitigative mechanism in the Egyptian context. In this paper, the results from the different models (Panel Fixed Effects model and the Regression Discontinuity Design (RDD) model) confirm that micro and macro shocks lead to significant decline in several household-level welfare outcomes and that Takaful cash transfers have a significant positive impact in mitigating the negative shock impacts, especially on households’ debt incidence, debt levels, and asset ownership, but not necessarily on food, and non-food expenditure levels. The results indicate large positive significant effects on decreasing household incidence of debt by up to 12.4 percent and lowered the debt size by approximately 18 percent among Takaful beneficiaries compared to non-beneficiaries’. Similar evidence is found on asset ownership levels, as the RDD model shows significant positive effects on total asset ownership and productive asset ownership, but the model failed to detect positive impacts on per capita food and non-food expenditures. Further extensions are still in progress to compare the models’ results with the DID model results when using a nationally representative ELMPS panel data (2018/2024) rounds. Finally, our initial analysis suggests that conditional cash transfers are effective in buffering the negative shock impacts on certain welfare indicators even after successive macro-economic shocks in 2022 and 2023 in the Egyptian Context.

Keywords: cash transfers, fixed effects, household welfare, household debt, micro shocks, regression discontinuity design

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Authors: Bahatti̇n Ki̇mençe, Uğur Ki̇mençe

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In this study, the purpose of obtaining the influence functions of the displacement discontinuity in an anisotropic elastic medium is to produce the boundary element equations. A Displacement Discontinuous Method formulation (DDM) is presented with the aim of modeling two-dimensional elastic fracture problems. This formulation is found by analytical integration of the fundamental solution along a straight-line crack. With this purpose, Kelvin's fundamental solutions for anisotropic media on an infinite plane are used to form dipoles from singular loads, and the various combinations of the said dipoles are used to obtain the influence functions of displacement discontinuity. This study introduces a technique for coupling Fictitious Stress Method (FSM) and DDM; the reason for applying this technique to some examples is to demonstrate the effectiveness of the proposed coupling method. In this study, displacement discontinuity equations are obtained by using dipole solutions calculated with known singular force solutions in an anisotropic medium. The displacement discontinuities method obtained from the solutions of these equations and the fictitious stress methods is combined and compared with various examples. In this study, one or more crack problems with various geometries in rectangular plates in finite and infinite regions, under the effect of tensile stress with coupled FSM and DDM in the anisotropic environment, were examined, and the effectiveness of the coupled method was demonstrated. Since crack problems can be modeled more easily with DDM, it has been observed that the use of DDM has increased recently. In obtaining the displacement discontinuity equations, Papkovitch functions were used in Crouch, and harmonic functions were chosen to satisfy various boundary conditions. A comparison is made between two indirect boundary element formulations, DDM, and an extension of FSM, for solving problems involving cracks. Several numerical examples are presented, and the outcomes are contrasted to existing analytical or reference outs.

Keywords: displacement discontinuity method, fictitious stress method, crack problems, anisotropic material

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Authors: Galal Elkobrosy, Amr M. Abdelrazek, Bassuny M. Elsouhily, Mohamed E. Khidr

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Crank shaft length, connecting rod length, crank angle, engine rpm, cylinder bore, mass of piston and compression ratio are the inputs that can control the performance of the slider crank mechanism and then its efficiency. Several combinations of these seven inputs are used and compared. The throughput engine torque predicted by the simulation is analyzed through two different regression models, with and without interaction terms, developed according to multi-linear regression using LU decomposition to solve system of algebraic equations. These models are validated. A regression model in seven inputs including their interaction terms lowered the polynomial degree from 3^rd degree to 1^st degree and suggested valid predictions and stable explanations.

Keywords: design of experiments, regression analysis, SI engine, statistical modeling

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Authors: Lavinia B. Dulla

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The exploration study of the fuzzy regression approach attempts to present that fuzzy regression can be used as a possible alternative to classical regression. It likewise seeks to assess the differences and characteristics of simple linear regression and fuzzy regression using the width of prediction interval, mean absolute deviation, and variance of residuals. Based on the simple linear regression model, the fuzzy regression approach is worth considering as an alternative to simple linear regression when the sample size is between 10 and 20. As the sample size increases, the fuzzy regression approach is not applicable to use since the assumption regarding large sample size is already operating within the framework of simple linear regression. Nonetheless, it can be suggested for a practical alternative when decisions often have to be made on the basis of small data.

Keywords: fuzzy regression approach, minimum fuzziness criterion, interval regression, prediction interval

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Authors: Ahmed Hosny, Haroon Elshaikh, Gaber Hassib, Yassin Ali

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The Moho discontinuity undulations beneath the southern part of Egypt have been defined using the seismic waves generated by tele earthquakes. These earthquakes have been recorded by the Aswan seismic network, which consists of 10 seismic stations established around the lake of Nasser. An additional seismic station was located towards the east of the Lake of Nasser by about ~ 150 km. Receiver functions and H-k stacking methods were used for obtaining the depths of Moho discontinuity and the Vp/Vs ratios beneath each seismic station. Our results revealed that, the depths of Moho discontinuity beneath the stations located around the Lake of Nasser range from 36 to 39 km, with an average value of 37.5 km. These results are consistent with the previous works done on the same area. The obtained Vp/Vs ratios for the crust of this area were ranged from 1.73 to 1.86, with an average value of 1.79. While beneath the station located towards the east, the Moho discontinuity was detected at a shallowest depth of 27 km and the Vp/Vs ratio was 1.82. The difference in the Moho depths beneath the stations located around the Lake of Nasser and the station located to the east revealed the boundary position between the Saharan Metacraton to the west and the Nubian-Arabian Shield to the east. This structural boundary delineates the position of the old collision of the Oceanic crust of the Nubian-Arabian Shield to the east with the Continental crust of the Saharan Metacraton to the west.

Keywords: Moho undulations, south of Egypt, seismic waves, earthquakes

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Authors: Kiwon Yeom

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Change points are abrupt variations in a data sequence. Detection of change points is useful in modeling, analyzing, and predicting time series in application areas such as robotics and teleoperation. In this paper, a change point is defined to be a discontinuity in one of its derivatives. This paper presents a reliable method for detecting discontinuities within a three-dimensional trajectory data. The problem of determining one or more discontinuities is considered in regular and irregular trajectory data from teleoperation. We examine the geometric detection algorithm and illustrate the use of the method on real data examples.

Keywords: change point, discontinuity, teleoperation, abrupt variation

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Authors: S. Dey, T. Mukhopadhyay, S. Adhikari

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This paper presents an exhaustive comparative investigation on sampling techniques of polynomial regression model based stochastic natural frequency of composite plates. Both individual and combined variations of input parameters are considered to map the computational time and accuracy of each modelling techniques. The finite element formulation of composites is capable to deal with both correlated and uncorrelated random input variables such as fibre parameters and material properties. The results obtained by Polynomial regression (PR) using different sampling techniques are compared. Depending on the suitability of sampling techniques such as 2k Factorial designs, Central composite design, A-Optimal design, I-Optimal, D-Optimal, Taguchi’s orthogonal array design, Box-Behnken design, Latin hypercube sampling, sobol sequence are illustrated. Statistical analysis of the first three natural frequencies is presented to compare the results and its performance.

Keywords: composite plate, natural frequency, polynomial regression model, sampling technique, uncertainty quantification

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Authors: Paola Bordon, Breno Braga

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This paper investigates whether firms use university prestige to statistically discriminate among college graduates. The test is based on the employer learning literature which suggests that if firms use a characteristic for statistical discrimination, this variable should become less important for earnings as a worker gains labor market experience. In this framework, we use a regression discontinuity design to estimate a 19% wage premium for recent graduates of two of the most selective universities in Chile. However, we find that this premium decreases by 3 percentage points per year of labor market experience. These results suggest that employers use college selectivity as a signal of workers' quality when they leave school. However, as workers reveal their productivity throughout their careers, they become rewarded based on their true quality rather than the prestige of their college.

Keywords: employer learning, statistical discrimination, college returns, college selectivity

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Authors: Songul Cinaroglu

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Machine learning regression methods are recommended as an alternative to classical regression methods in the existence of variables which are difficult to model. Data for health expenditure is typically non-normal and have a heavily skewed distribution. This study aims to compare machine learning regression methods by hyperparameter tuning to predict health expenditure per capita. A multiple regression model was conducted and performance results of Lasso Regression, Random Forest Regression and Support Vector Machine Regression recorded when different hyperparameters are assigned. Lambda (λ) value for Lasso Regression, number of trees for Random Forest Regression, epsilon (ε) value for Support Vector Regression was determined as hyperparameters. Study results performed by using 'k' fold cross validation changed from 5 to 50, indicate the difference between machine learning regression results in terms of R², RMSE and MAE values that are statistically significant (p < 0.001). Study results reveal that Random Forest Regression (R² ˃ 0.7500, RMSE ≤ 0.6000 ve MAE ≤ 0.4000) outperforms other machine learning regression methods. It is highly advisable to use machine learning regression methods for modelling health expenditures.

Keywords: machine learning, lasso regression, random forest regression, support vector regression, hyperparameter tuning, health expenditure

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Authors: Frank Kuebler, Rolf Steinhilper

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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

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Authors: S. A. Agbalajobi, W. A. Bello

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The study carried out analysis on slope stability in an excavated gneiss rock using geological strength index (GSI) in Ilorin, Kwara State, Nigeria. A kinematic analysis of planar discontinuity sets in a gneiss deposit was carried out to ascertain the degree of slope stability. Discontinuity orientations in the rock mass were mapped using compass clinometers. The average result of physical and mechanical properties such as specific gravity, unit weight, uniaxial compressive strength, point load index, and Schmidt rebound value are 2.64 g/m3, 25.95 kN/m3, 156 MPa, 6.5 MPa, and 53.12 respectively. Also, a statistical model equation relating the rock strength was developed. The analyses states that the rock face is susceptible to wedge failures having all the geometrical conditions associated with the occurrence of such failures were noticeable. It can be concluded that analyses of discontinuity orientation in relation to cut face direction in rock excavation is essential for mine planning to forestall mine accidents. Assessment of excavated slope methods was evident that one excavation method (blasting and/or use of hydraulic hammer) is applicable for the given rock strength, the ease of excavation decreases as the rock mass quality increases, thus blasting most suitable for such operation.

Keywords: slope stability, wedge failure, geological strength index (GSI), discontinuities and excavated slope

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Authors: Alaa El-Din Rezk

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In Egypt, management of crops still away from what is being used today by utilizing the advances of mechanical design capabilities, sensing and electronics technology. These technologies have been introduced in many places and recorm, for Straight Path, Curved Path, Sine Wave ded high accuracy in different field operations. So, an autonomous robotic platform based on machine vision has been developed and constructed to be implemented in Egyptian conditions as self-propelled mobile vehicle for carrying tools for inter/intra-row crop management based on different control modules. The experiments were carried out at plant protection research institute (PPRI) during 2014-2015 to optimize the accuracy of agricultural robotic platform control using machine vision in term of the autonomous navigation and performance of the robot’s guidance system. Results showed that the robotic platform' guidance system with machine vision was able to adequately distinguish the path and resisted image noise and did better than human operators for getting less lateral offset error. The average error of autonomous was 2.75, 19.33, 21.22, 34.18, and 16.69 mm. while the human operator was 32.70, 4.85, 7.85, 38.35 and 14.75 mm Path, Offset Discontinuity and Angle Discontinuity respectively.

Keywords: autonomous robotic, Hough transform, image processing, machine vision

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Authors: L. Q. Yuan, J. Yang, A. Siddiqui

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A new regression uncertainty analysis methodology was applied to determine the uncertainties of the critical heat flux (CHF) power correlation for an advanced 43-element bundle design, which was developed by Canadian Nuclear Laboratories (CNL) to achieve improved economics, resource utilization and energy sustainability. The new methodology is considered more appropriate than the traditional methodology in the assessment of the experimental uncertainty associated with regressions. The methodology was first assessed using both the Monte Carlo Method (MCM) and the Taylor Series Method (TSM) for a simple linear regression model, and then extended successfully to a non-linear CHF power regression model (CHF power as a function of inlet temperature, outlet pressure and mass flow rate). The regression uncertainty assessed by MCM agrees well with that by TSM. An equation to evaluate the CHF power regression uncertainty was developed and expressed as a function of independent variables that determine the CHF power.

Keywords: CHF experiment, CHF correlation, regression uncertainty, Monte Carlo Method, Taylor Series Method

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Authors: Autcha Araveeporn

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This paper presents a study about a nonparametric regression model consisting of a smoothing spline method and a penalized spline regression method. We also compare the techniques used for estimation and prediction of nonparametric regression model. We tried both methods with crude oil prices in dollars per barrel and the Stock Exchange of Thailand (SET) index. According to the results, it is concluded that smoothing spline method performs better than that of penalized spline regression method.

Keywords: nonparametric regression model, penalized spline regression method, smoothing spline method, Stock Exchange of Thailand (SET)

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Authors: Anastasiia Yu. Timofeeva

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Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.

Keywords: grade point average, orthogonal regression, penalized regression spline, locally weighted regression

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Authors: Yi-Cheng Tian, Miin-Shen Yang

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The mixture likelihood approach to clustering is a popular clustering method where the expectation and maximization (EM) algorithm is the most used mixture likelihood method. In the literature, the EM algorithm had been used for mixture regression models. However, these EM mixture regression algorithms are sensitive to initial values with a priori number of clusters. In this paper, to resolve these drawbacks, we construct a learning-based schema for the EM mixture regression algorithm such that it is free of initializations and can automatically obtain an approximately optimal number of clusters. Some numerical examples and comparisons demonstrate the superiority and usefulness of the proposed learning-based EM mixture regression algorithm.

Keywords: clustering, EM algorithm, Gaussian mixture model, mixture regression model

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Authors: Arun Goel

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Prediction of maximum local scour is necessary for the safety and economical design of the bridges. A number of equations have been developed over the years to predict local scour depth using laboratory data and a few pier equations have also been proposed using field data. Most of these equations are empirical in nature as indicated by the past publications. In this paper, attempts have been made to compute local depth of scour around bridge pier in dimensional and non-dimensional form by using linear regression, simple regression and SVM (Poly and Rbf) techniques along with few conventional empirical equations. The outcome of this study suggests that the SVM (Poly and Rbf) based modeling can be employed as an alternate to linear regression, simple regression and the conventional empirical equations in predicting scour depth of bridge piers. The results of present study on the basis of non-dimensional form of bridge pier scour indicates the improvement in the performance of SVM (Poly and Rbf) in comparison to dimensional form of scour.

Keywords: modeling, pier scour, regression, prediction, SVM (Poly and Rbf kernels)

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Authors: Sina Fatolahzadeh, Sergio A. Sepúlveda

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This paper presents advanced developments in close-range, terrestrial remote sensing techniques to enhance the characterization of rock masses. The study integrates two state-of-the-art laser-scanning technologies, the HandySCAN and GeoSLAM laser scanners, to extract high-resolution geospatial data for rock mass analysis. These instruments offer high accuracy, precision, low acquisition time, and high efficiency in capturing intricate geological features in small to medium size outcrops and slope cuts. Using the HandySCAN and GeoSLAM laser scanners facilitates real-time, three-dimensional mapping of rock surfaces, enabling comprehensive assessments of rock mass characteristics. The collected data provide valuable insights into structural complexities, surface roughness, and discontinuity patterns, which are essential for geological and geotechnical analyses. The synergy of these advanced remote sensing technologies contributes to a more precise and straightforward understanding of rock mass behavior. In this case, the main parameters of RQD, joint spacing, persistence, aperture, roughness, infill, weathering, water condition, and joint orientation in a slope cut along the Sea-to-Sky Highway, BC, were remotely analyzed to calculate and evaluate the Rock Mass Rating (RMR) and Geological Strength Index (GSI) classification systems. Automatic and manual analyses of the acquired data are then compared with field measurements. The results show the usefulness of the proposed remote sensing methods and their appropriate conformity with the actual field data.

Keywords: remote sensing, rock mechanics, rock engineering, slope stability, discontinuity properties

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Authors: Kisan Sarda, Bhavika Shingote

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This paper aims to evaluate regression modelling for prediction of Energy storage of solar photovoltaic (PV) system using Semi parametric regression techniques because there are some parameters which are known while there are some unknown parameters like humidity, dust etc. Here irradiation of solar energy is different for different places on the basis of Latitudes, so by finding out areas which give more storage we can implement PV systems at those places and our need of energy will be fulfilled. This regression modelling is done for daily, monthly and seasonal prediction of solar energy storage. In this, we have used R modules for designing the algorithm. This algorithm will give the best comparative results than other regression models for the solar PV cell energy storage.

Keywords: semi parametric regression, photovoltaic (PV) system, regression modelling, irradiation

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Authors: K. K. Lee, H. W. Han, H. L. Kang, T. A. Kim, S. H. Han

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For the robust optimization of the manufacturing product design, there are design objectives that must be achieved, such as a minimization of the mean and standard deviation in objective functions within the required sensitivity constraints. The authors utilized the sensitivity of objective functions and constraints with respect to the effective design variables to reduce the computational burden associated with the evaluation of the probabilities. The individual mean and sensitivity values could be estimated easily by using the 9 level orthogonal array based response surface models optimized by the stepwise regression. The present study evaluates a proposed procedure from the robust optimization of rubber domes that are commonly used for keyboard switching, by using the 9 level orthogonal array and stepwise regression along with a desirability function. In addition, a new robust optimization process, i.e., the I2GEO (Identify, Integrate, Generate, Explore and Optimize), was proposed on the basis of the robust optimization in rubber domes. The optimized results from the response surface models and the estimated results by using the finite element analysis were consistent within a small margin of error. The standard deviation of objective function is decreasing 54.17% with suggested sensitivity based robust optimization. (Business for Cooperative R&D between Industry, Academy, and Research Institute funded Korea Small and Medium Business Administration in 2017, S2455569)

Keywords: objective function, orthogonal array, response surface model, robust optimization, stepwise regression

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