Education and Income Inequality Reconsidered: A Cross-Country Analysis of Data from 1960-2000

Recent comparative inequality studies have addressed not only income but also other dimensions such as education and health inequality. Education has been believed to play a critical role in the nexus of inequality and growth. This study examines whether education distribution has an effect on income inequality. It empirically analyzes the relationship between education inequality and income inequality using quinquennial panel data from 100 countries for 1960-2000. The results show that education inequality and income inequality have a nonlinear, inverted-U-shaped relationship. This relationship appeared more consistently in developing countries. These findings suggest that educational opportunities should be more equally provided for better income distribution, especially in developing countries

k-Space Deep Learning for Parallel MRI: Application to Time-Resolved MR Angiography

Time-resolved angiography with interleaved stochastic trajectories (TWIST) has been widely used for dynamic contrast enhanced MRI (DCE-MRI). To achieve highly accelerated acquisitions, TWIST combines the periphery of the k-space data from several adjacent frames to reconstruct one temporal frame. However, this view-sharing scheme limits the true temporal resolution of TWIST. Moreover, the k-space sampling patterns have been specially designed for a specific generalized autocalibrating partial parallel acquisition (GRAPPA) factor so that it is not possible to reduce the number of view-sharing once the k-data is acquired. To address these issues, this paper proposes a novel k-space deep learning approach for parallel MRI. In particular, we have designed our neural network so that accurate k-space interpolations are performed simultaneously for multiple coils by exploiting the redundancies along the coils and images. Reconstruction results using in vivo TWIST data set confirm that the proposed method can immediately generate high-quality reconstruction results with various choices of view- sharing, allowing us to exploit the trade-off between spatial and temporal resolution in time-resolved MR angiography

Modeling and monitoring of the dynamic response of railroad bridges using wireless smart sensors

Railroad bridges form an integral part of railway infrastructure in the USA carrying approximately 40 % of the ton-miles of freight. The US Department of Transportation (DOT) forecasts current rail tonnage to increase up to 88 % by 2035. Within the railway network, a bridge occurs every 1.4 miles of track, on average, making them critical elements. In an effort to accommodate safely the need for increased load carrying capacity, the Federal Railroad Association (FRA) announced a regulation in 2010 that the bridge owners must report annual inspection of all the bridges. Until now, visual inspection has been the most prevalent practice in monitoring this infrastructure, while high-cost and unreliability can limit the efficiency and accuracy of such assessments. With recent advances in sensing technology, structural health monitoring can be a promising solution for providing a reliable and inexpensive ways for assessing the bridges. Nonetheless, because damage is a local phenomenon, to be able to detect/ monitor existing/potential damage, densely deployed sensors are required, which is inefficient and still expensive. Alternatively, model-based monitoring strategies can be adopted to identify a critical element from a numerical model that has been calibrated with measured field data. However, this approach has been widely adopted and applied for highway bridges, while railroad bridges have received comparably less attention. The main reason for the limited number of studies is due, in part, to fundamental differences between the loading being applied to highway bridges and railroad bridges. Usually, the mass of the vehicles crossing highway bridges is assumed to be relatively small compared to the mass of the bridge itself; as a result, the mass of the vehicles are often neglecting in the problem. In contrast, the mass of a train crossing a railroad bridge can be as large as the mass of the bridge itself. Moreover, trains are typically composed of an engine, followed by multiple cars resulting in a nearly deterministic moving mass/load being applied to the bridge that varies with speed. As a consequence, numerous models have been developed to understand the dynamic response of bridges under in-service train loads, but most fail to provide a simple, yet flexible, representation of the salient features of the responses of the bridge. The objective of this research is to develop appropriate modeling and monitoring techniques for railroad bridges toward understanding the dynamic responses under a moving train. To achieve the research objective, the following issues are considered specifically. For modeling, a simple, yet effective, model is developed to capture salient features of the bridge responses under a moving train. A new hybrid model is then proposed, which is a flexible and efficient tool for estimating bridge responses for arbitrary train configurations and speeds. For monitoring, measured field data is used to validate the performance of the numerical model. Further, interpretation of the proposed models showed that those models are efficient tools for predicting response of the bridge under undesirable and local phenomena, such as fatigue and resonance. Finally, fundamental software, hardware, and algorithm components are developed for providing synchronized sensing for geographically distributed networks, as can be found in railroad bridges. The results of this research successfully demonstrate the potentials of using wirelessly measured data to perform model development and calibration that will lead to better understanding the dynamic responses of railroad bridges and to provide an effective tool for prediction of bridge response for arbitrary train configurations and speeds.Ope

Multidimensional child poverty in Korea: developing child-specific indicators for the sustainable development goals

This paper aims to examine child poverty in Korea by constructing a multidimensional child poverty index. The Sustainable Development Goals (hereafter SDGs) recommends producing children-specific poverty statistics based on the concept of multidimensional poverty. Responding to such global norms and trends, in Korea, there is an increasing need to define and measure multidimensional poverty among children, focusing on the individual rather than the household as a whole. Drawing on the Poverty and Social Exclusion methodology, we established a Child Deprivation Index and combined it with household income to estimate multidimensional child poverty, using data from the 2013 Korean National Child Survey. The findings show that the number of children in poverty are in fact around 10% of the child population, as measured by material deprivation and income combined, which is two times higher than the official Korean child poverty rate. This indicates that conventional measurements, based only on household income, not only insufficiently identifies poor children, but also excludes more than half of the potential recipients from the social assistance system. In addition, our logit analysis offers strong evidence that deprived children are mostly living in working-poor and single-parent households. These findings lead to the conclusion that various support for the working poor should be considered as important child policy agenda. In this respect, the child-focused poverty measurement produced in this study has more significant implications for practical policy objectives than the income-based approach, as well as a higher theoretical and methodological accuracy

Transition from the Developmental State: The Deliberative Policy Process of Civil Service Pension Reform in Korea

This paper examines three recent efforts to reform Koreas Civil Service Pension Program, in order to trace the changing policy process in Korea, where the policy regime of the developmental state used to be predominant. It has been argued that the government no longer has overwhelming influence over the policy-making process, while social actors are not able to compromise on social issues. This paper aims to test the hypotheses of the decline of government influence and the inability to reach social compromise, focusing on stakeholders interactions at the micro level. It argues that a new deliberative policy process has emerged that engages a range of stakeholders, such as trade unions and policy experts, and in which different government ministries compete against each other. The paradox of the new policy process is that despite its deliberative nature, the governments strategic influence continues to be strong

現代語の連体修飾節における助詞「の」

名古屋大学・グローバルCOEプログラムNagoya University, Global COE Program本稿では,「髪の長い人」のような主格助詞「の」が用いられる連体節の用例を分析し,次のような傾向を観察した。「の」は連体節の述語連体形が語彙概念として無行為・無変化・無時間の性質(状態性)をもち,その形態が脱テンス・アスペクト化するにつれ使用頻度が高くなる。また,連体形特有の用法を表す形態と親和する傾向を示す。連体節内の主語と述語の間の介在要素がほとんど見られず,主語・述語から成る非対格構造との親和性を見せる。文としての自立性をもつ連体節には表れにくく,被修飾名詞の意味実質性が強い構造で用いられる。このようなことから「の」は,述語が「状態性述語」であることを示し,連体修飾部と被修飾名詞が状態・属性とその帰属対象の関係にあることを示すものと論じた。さらに,状態性述語の特徴は名詞述語の性質と捉えられ,その意味において「の」は述語連体形の名詞性に係るものであると論じた。「の」は述定の構造で表れるが,その内実は述語連体形と装定の関係を成している。The present study 1) investigates the semantic and syntactic functions of the genitive subject marker no in contemporary Japanese and 2) accounts for the syntactic reason why the genitive subject marker no appears in subordinate clauses. Through examination of contemporary novels data, this paper reveals that, comparing it with the subjective marker ga, the genitive subject marker no has marked tendencies to appear in predicates and head nouns of subordinate clauses. Specifically, it turns out that predicates in subordinate clauses show parallel characteristics to noun predicates in copular sentences. This paper argues that the genitive subject marker no serves as a marker which indicates the stativity of predicates, and that the predicate was derived as a stative structure. It is also argued that the genitive subject marker no modified the nouniness of a predicate, the standard usage of no as a modifier of nouns influences and thus restricts its usage as a modifier of predicates

Persim - Simulator for Human Activities in Pervasive Spaces

Activity recognition research relies heavily on test data to verify the modeling technique and the performance of the activity recognition algorithm. But data from real deployments are expensive and time consuming to obtain. And even if cost is not an issue, regulatory limitations on the use of human subjects prohibit the collection of extensive datasets that can test all scenarios, under all circumstances. A powerful and verifiable simulation tool is needed to accelerate research on human activity recognition. We present Persim, an event driven simulator of human activities in pervasive spaces. Persim is capable of capturing elements of space, sensors, behaviors (activities), and their inter-relationships. We focus on presenting the five main use cases for Persim addressing dataset synthesis, reuse and extension of existing datasets, sharing of data and simulation projects, as well as data validation. © 2011 IEEE

RS485 Image Sensor for Digital Cinema System

To activate various devices using RS485, a repeater is generally used. In current digital cinema systems, each device is controlled with RS485 by mixing RS485 and DMX512. However, as today’s cinema equips hundreds of 4D chairs and the environmental directors, it is nearly infeasible for the legacy system to control. To this end, this paper designs and implements a new system which makes hundreds of 4D chairs and the environmental directors be controlled simultaneously exploiting RS485 network topology and its repeaters. The proposed approach is tested in a real-time system for assessing the performance by Paessler Router Traffic Grapher (PRTG) in Windows environment. Simulation results show that the tested system supports 4D chairs and their motions are well operated simultaneously with RS485