Curbing Cream-Skimming: Evidence on Enrolment Incentives

Can enrolment incentives reduce the incidence of cream-skimming in the delivery of public sector services (e.g. education, health, job training)? In the context of a large government job training program, we investigate whether the use of enrolment incentives that set different 'shadow prices' for serving different demographic subgroups of clients, influence case workers' choice of intake population. Exploiting exogenous variation in these shadow prices, we show that training agencies change the composition of their enrollee populations in response to changes in the incentives, increasing the relative fraction of subgroups whose shadow prices increase. We also show that the increase is due to training agencies enrolling at the margin weaker members, in terms of performance, of that subgroup.performance measurement, cream-skimming, enrolment incentives, bureaucrat behavior, public organizations

Curbing cream-skimming: Evidence on enrolment incentives

Using data from a large, U.S. federal job training program, we investigate whether enrolment incentives that exogenously vary the ‘shadow prices’ for serving different demographic subgroups of clients influence case workers’ intake decisions. We show that case workers enroll more clients from subgroups whose shadow prices increase but select at the margin weaker-performing members from those subgroups. We conclude that enrolment incentives curb cream-skimming across subgroups leaving a residual potential for cream-skimming within a subgroup.Performance measurement, cream-skimming, enrolment incentives, bureaucrat behavior, public organizations

Capitalist landownership and state policy in 1989-1990 in Korea

In 1989, the Korea government enacted the new land acts to remedy-land speculation. And following that successively in 1990, the government ordered that large capitalists (chaebol) sell their large landholding to others who are end users. Examining changes in the Korean land policy promulgated in those years, this paper argues that land-owning chaebol prevented any substantial social transformation. Referring to these experiences, the author concludes that land-owning chaebol are likely to hinder the implementation of progressive land reforms under the Kim government

Skyrmions and Anomalous Hall Effect in a Dzyloshinskii-Moriya Spiral Magnet

Monte Carlo simulation study of a classical spin model with Dzylosinskii-Moriya interaction and the spin anisotropy under the magnetic field is presented. We found a rich phase diagram containing the multiple spin spiral (or skyrme crystal) phases of square, rectangular, and hexagonal symmetries in addition to the spiral spin state. The Hall conductivity $\sigma_{xy}$ is calculated within the $sd$ model for each of the phases. While $\sigma_{xy}$ is zero in the absence of external magnetic field, applying a field strength $H$ larger than a threshold value $H_c$ leads to the simultaneous onset of nonzero chirality and Hall conductivity. We find $H_c = 0$ for the multiple spin spiral states, but $H_c > 0$ for a single spin spiral state regardless of the field orientation. Relevance of the present results to MnSi is discussed

Development of a burst pressure prediction model for flawless and dented pipelines

Accurate prediction of the burst pressure of a pipeline is critical for pipeline design and safe operation. There are a number of analytical and empirical formulae derived from theoretical, numerical and experimental methods that can be used to predict the burst pressure of plain pipeline. However, there is not an equivalent method available to predict the burst pressure of dented pipeline and consequently the assessment of dents in pipelines is based on the depth or the shape of the dent. Therefore, this thesis presents the development of practical burst pressure prediction models for the flawless pipelines, which is then extended to predict the burst pressure of dented pipeline. Firstly, a study is carried out to develop a new methodology to predict the burst pressure for API 5L X-grade flawless pipelines using Finite Element Analysis (FEA). The FEA is performed using a bilinear material model with the tangent modulus calculated using the strain at Ultimate Tensile Strength (UTS). A new formula has been developed in this work to calculate the strain at UTS based on API 5L X-grade material coupon test data. A comprehensive nonlinear FEA based Parametric Study has then been conducted with this bilinear material model to derive an empirical formula for estimating the burst pressure of API 5L X grade flawless pipelines. Secondly, an empirical formula for the assessment of the structural integrity of a pipeline with an unconstrained, hemispherical, plain dent has been developed, based on the formula derived for the unflawed pipeline. Parametric studies have been conducted using non-linear FEA of the burst pressure for API 5L X52, X65 and X80 grade pipelines with a dent. An empirical formula, that can predict the burst pressure of dented pipelines is proposed, based on the output dataset derived from the FEA based Parametric Study results. Thirdly, a dent produced by a spheroidal indenter on API 5L X52 pipeline has been studied to investigate the effect of the longitudinal and transverse dent lengths on the pipeline structural integrity using FEA. According to the FEA based Parametric Study results, it shows that the burst pressure prediction for the spheroidal dent is comparable with the burst pressure prediction for the hemispherical dent for a given dent depth and longitudinal dent length. Consequently, it is confirmed that the proposed burst pressure prediction formula for the hemispherical dent is applicable to examine the structural integrity of API 5L X52 grade pipelines with an unconstrained, spheroidal, plain dent. Finally, the applicability of machine learning techniques such as Deep Neural Networks (DNN) for the prediction of burst pressure has been investigated for unflawed and dented API 5L X-grade pipelines. The burst pressure derived has been compared with the results of FEA based Parametric Study and the experimental test results and showed good agreement. Therefore, it is concluded that DNN can be another solution for predicting the burst pressure of API 5L X-grade flawless and dented pipelines.Accurate prediction of the burst pressure of a pipeline is critical for pipeline design and safe operation. There are a number of analytical and empirical formulae derived from theoretical, numerical and experimental methods that can be used to predict the burst pressure of plain pipeline. However, there is not an equivalent method available to predict the burst pressure of dented pipeline and consequently the assessment of dents in pipelines is based on the depth or the shape of the dent. Therefore, this thesis presents the development of practical burst pressure prediction models for the flawless pipelines, which is then extended to predict the burst pressure of dented pipeline. Firstly, a study is carried out to develop a new methodology to predict the burst pressure for API 5L X-grade flawless pipelines using Finite Element Analysis (FEA). The FEA is performed using a bilinear material model with the tangent modulus calculated using the strain at Ultimate Tensile Strength (UTS). A new formula has been developed in this work to calculate the strain at UTS based on API 5L X-grade material coupon test data. A comprehensive nonlinear FEA based Parametric Study has then been conducted with this bilinear material model to derive an empirical formula for estimating the burst pressure of API 5L X grade flawless pipelines. Secondly, an empirical formula for the assessment of the structural integrity of a pipeline with an unconstrained, hemispherical, plain dent has been developed, based on the formula derived for the unflawed pipeline. Parametric studies have been conducted using non-linear FEA of the burst pressure for API 5L X52, X65 and X80 grade pipelines with a dent. An empirical formula, that can predict the burst pressure of dented pipelines is proposed, based on the output dataset derived from the FEA based Parametric Study results. Thirdly, a dent produced by a spheroidal indenter on API 5L X52 pipeline has been studied to investigate the effect of the longitudinal and transverse dent lengths on the pipeline structural integrity using FEA. According to the FEA based Parametric Study results, it shows that the burst pressure prediction for the spheroidal dent is comparable with the burst pressure prediction for the hemispherical dent for a given dent depth and longitudinal dent length. Consequently, it is confirmed that the proposed burst pressure prediction formula for the hemispherical dent is applicable to examine the structural integrity of API 5L X52 grade pipelines with an unconstrained, spheroidal, plain dent. Finally, the applicability of machine learning techniques such as Deep Neural Networks (DNN) for the prediction of burst pressure has been investigated for unflawed and dented API 5L X-grade pipelines. The burst pressure derived has been compared with the results of FEA based Parametric Study and the experimental test results and showed good agreement. Therefore, it is concluded that DNN can be another solution for predicting the burst pressure of API 5L X-grade flawless and dented pipelines

Current Trends and New Challenges of Databases and Web Applications for Systems Driven Biological Research

Dynamic and rapidly evolving nature of systems driven research imposes special requirements on the technology, approach, design and architecture of computational infrastructure including database and Web application. Several solutions have been proposed to meet the expectations and novel methods have been developed to address the persisting problems of data integration. It is important for researchers to understand different technologies and approaches. Having familiarized with the pros and cons of the existing technologies, researchers can exploit its capabilities to the maximum potential for integrating data. In this review we discuss the architecture, design and key technologies underlying some of the prominent databases and Web applications. We will mention their roles in integration of biological data and investigate some of the emerging design concepts and computational technologies that are likely to have a key role in the future of systems driven biomedical research