Regional income inequality in China and Indonesia: A comparative analysis

This study examines the extent and trends of regional income inequality in China and Indonesia, and performs a comparative analysis between these two countries in terms of factors determining regional income inequality. There are a number of studies that have analyzed the relationship between economic development and regional income inequality in China and Indonesia. However, most previous studies employed provincial income and population data to measure regional income inequality and were thus unable to measure inequality within provinces. In order to rectify this drawback, we will use district-level income and population data, rather than provincial data, to measure regional income inequality, and examine not only between-province inequalities but also within-province inequalities by using the two-stage nested Theil decomposition method developed by Akita (2002). China and Indonesia are still at a relatively early stage of economic development; therefore, income-enhancing economic activities tend to have concentrated in a few districts in each province to enjoy agglomeration economies. We will show that a very large regional income inequality exists among the districts of China and Indonesia. This study will also conduct a regression analysis to explore possible determinants of within-province income inequality, in which the following variables are considered: foreign direct investment, economic dualism, and migration.

Temporal and Spatial Expansion of Urban LOD for Solving Illegally Parked Bicycles in Tokyo

The illegal parking of bicycles is a serious urban problem in Tokyo. The purpose of this study was to sustainably build Linked Open Data (LOD) to assist in solving the problem of illegally parked bicycles (IPBs) by raising social awareness, in cooperation with the Office for Youth Affairs and Public Safety of the Tokyo Metropolitan Government (Tokyo Bureau). We first extracted information on the problem factors and designed LOD schema for IPBs. Then we collected pieces of data from the Social Networking Service (SNS) and the websites of municipalities to build the illegally parked bicycle LOD (IPBLOD) with more than 200,000 triples. We then estimated the temporal missing data in the LOD based on the causal relations from the problem factors and estimated spatial missing data based on geospatial features. As a result, the number of IPBs can be inferred with about 70% accuracy, and places where bicycles might be illegally parked are estimated with about 31% accuracy. Then we published the complemented LOD and a Web application to visualize the distribution of IPBs in the city. Finally, we applied IPBLOD to large social activity in order to raise social awareness of the IPB issues and to remove IPBs, in cooperation with the Tokyo Bureau

A Calculation Method of Deposition Profiles in CVD Reactors Using Genetic Algorithms

AbstractIn this study, we introduced a novel and generalized calculation method to reproduce the deposition profiles in various types of chemical vapor deposition reactors. Robust and accurate calculations along with reduced computing cost were achieved by this method. Both boundary value problems and initial value problems for estimating the mass balance equations of the deposition species by iterations of numerical integrations were changed into problems of finding the linear combinations consisting of a few “basis functions,” which are inherent in the reactors and deposition species. The coefficients of the linear combinations were optimized using genetic algorithms. We could demonstrate the validity of the proposed method using various examples of the reaction mechanisms and conditions