H
Hiroshi Morita
Researcher at Osaka University
Publications - 71
Citations - 1053
Hiroshi Morita is an academic researcher from Osaka University. The author has contributed to research in topics: Data envelopment analysis & Inefficiency. The author has an hindex of 16, co-authored 70 publications receiving 940 citations. Previous affiliations of Hiroshi Morita include Kyocera & Kobe University.
Papers
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Proceedings ArticleDOI
Earthquake disaster management analysis in Dhaka
Sohel Ahmed,Hiroshi Morita +1 more
TL;DR: Statistics-based methodology is used to identify correlations among the occupancy classifications, emergency response, and population density in Bangladesh and indicates that the level of satisfaction regarding disaster management is fairly low with respect to emergency response and medical care.
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Confidence region method for a stochastic programming problem
TL;DR: In this paper, a minirnax model with a "quadratic" recourse is proposed for the case that the parameters of distribution are unknown, where the restrictions on the unknown parameters are imposed from the view point of a confidence region, and then a minimax solution that minimizes the worst case of the parameters is sought.
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Economic Analysis of a High‐volume Flexible Manufacturing System by High‐speed Processing
TL;DR: This paper takes a production system of cylinder heads for automobile engines as a subject, and draws a comparison of the energy-saving effect between HV-FMS and flexible transfer line and gives the permissible level for additional tooling cost.
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A Basic Study on Defect Inspection Method for ASIC Manufacturing Lines
TL;DR: Wang et al. as mentioned in this paper proposed a new manufacturing model which takes account of not only inspection and yield model but also and workflow model, and the numerical experimental results demonstrated that many phenomenon can be calculated only by the model which took account of both yield and workflow.
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Stochastic Approximation Procedure on a Discrete Lattice and its Application to Recursive Time Series Identification
Katsuji Uosaki,Hiroshi Morita +1 more
TL;DR: A stochastic approximation procedure is proposed for finding a point on a discrete lattice which gives the maximum of a regression function defined and observable only at points on the discrete lattices.